EXL_R1_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('whitegrid')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "File = pd.ExcelFile(\"C:\\Users\\welcome\\Desktop\\EXL CASES\\CASE 1\\Data.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'Demographics',\n",
       " u'Store Mapping',\n",
       " u'Category Mapping',\n",
       " u'Ping_Information',\n",
       " u'Variable Descriptions']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "File.sheet_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "demographics= pd.read_excel(File, \"Demographics\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "demographics.drop(['Unnamed: 0'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_Id</th>\n",
       "      <th>ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Marital_Status</th>\n",
       "      <th>Owns_Home</th>\n",
       "      <th>Number_of_Children_under_18_years_of_age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>831b9564-99d7-3b57-a9c0-3ac1f31560d5</td>\n",
       "      <td>23</td>\n",
       "      <td>F</td>\n",
       "      <td>D</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Shopper_2</td>\n",
       "      <td>1bd5093b-5a76-3ccc-b0d2-37695a858a95</td>\n",
       "      <td>42</td>\n",
       "      <td>F</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shopper_3</td>\n",
       "      <td>d08139f8-c50d-3472-adf8-6dcc4724164c</td>\n",
       "      <td>51</td>\n",
       "      <td>F</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shopper_4</td>\n",
       "      <td>29b285af-f631-3100-9a4e-5de09df7f974</td>\n",
       "      <td>35</td>\n",
       "      <td>F</td>\n",
       "      <td>D</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shopper_5</td>\n",
       "      <td>63fc3248-9900-3074-b887-c6ed6d73d0e3</td>\n",
       "      <td>42</td>\n",
       "      <td>M</td>\n",
       "      <td>S</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Shopper_Id                                    ID  Age Gender Marital_Status  \\\n",
       "0  Shopper_1  831b9564-99d7-3b57-a9c0-3ac1f31560d5   23      F              D   \n",
       "1  Shopper_2  1bd5093b-5a76-3ccc-b0d2-37695a858a95   42      F              M   \n",
       "2  Shopper_3  d08139f8-c50d-3472-adf8-6dcc4724164c   51      F              M   \n",
       "3  Shopper_4  29b285af-f631-3100-9a4e-5de09df7f974   35      F              D   \n",
       "4  Shopper_5  63fc3248-9900-3074-b887-c6ed6d73d0e3   42      M              S   \n",
       "\n",
       "  Owns_Home  Number_of_Children_under_18_years_of_age  \n",
       "0         N                                         1  \n",
       "1         N                                         1  \n",
       "2         N                                         1  \n",
       "3         N                                         2  \n",
       "4         N                                         0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demographics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "storemapping = pd.read_excel(File, \"Store Mapping\")\n",
    "storemapping.drop(['Unnamed: 0'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>Concourse Level</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>Concourse Level</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>Concourse Level</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>Concourse Level</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>Concourse Level</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name       Floor_name  Floor_Index  \\\n",
       "0                         Jamba Juice  Concourse Level            0   \n",
       "1              Coriander Gourmet Thai  Concourse Level            0   \n",
       "2                      NYS Collection  Concourse Level            0   \n",
       "3                            Hallmark  Concourse Level            0   \n",
       "4  Sorabol Korean BBQ & Asian Noodles  Concourse Level            0   \n",
       "\n",
       "    latitude   longitude  \n",
       "0  37.784091 -122.406813  \n",
       "1  37.784596 -122.406210  \n",
       "2  37.784396 -122.406587  \n",
       "3  37.783771 -122.407377  \n",
       "4  37.784601 -122.406328  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemapping.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Broad_Category</th>\n",
       "      <th>Fine_Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Amazon Pop-Up</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bespoke Events</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bespoke Coworking</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Specialty Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Dyson</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Penhaligonï¿½Ûªs</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Store_Name Broad_Category    Fine_Category\n",
       "0      Amazon Pop-Up         Retail            Misc.\n",
       "1     Bespoke Events         Retail            Misc.\n",
       "2  Bespoke Coworking         Retail  Specialty Store\n",
       "3              Dyson         Retail            Misc.\n",
       "4   Penhaligonï¿½Ûªs         Retail            Misc."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorymapping = pd.read_excel(File, \"Category Mapping\")\n",
    "categorymapping.drop(['Unnamed: 0'], axis=1, inplace=True)\n",
    "categorymapping.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>floor</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>seenTimestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 4</td>\n",
       "      <td>37.661463</td>\n",
       "      <td>-122.298673</td>\n",
       "      <td>-2934.558251</td>\n",
       "      <td>-16169.722290</td>\n",
       "      <td>2016-11-22T02:16:06.000Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 1</td>\n",
       "      <td>37.784062</td>\n",
       "      <td>-122.406943</td>\n",
       "      <td>117.262475</td>\n",
       "      <td>151.823812</td>\n",
       "      <td>2016-12-23T22:01:25.000Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 4</td>\n",
       "      <td>37.784361</td>\n",
       "      <td>-122.406710</td>\n",
       "      <td>156.125087</td>\n",
       "      <td>171.357200</td>\n",
       "      <td>2016-11-22T01:42:28.000Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>Concourse</td>\n",
       "      <td>37.784341</td>\n",
       "      <td>-122.406891</td>\n",
       "      <td>134.499673</td>\n",
       "      <td>167.674401</td>\n",
       "      <td>2016-10-13T18:27:38.000Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>Floor 2</td>\n",
       "      <td>37.784017</td>\n",
       "      <td>-122.407307</td>\n",
       "      <td>94.981693</td>\n",
       "      <td>172.269243</td>\n",
       "      <td>2016-10-12T21:36:18.000Z</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shopper_ID      floor        lat         lng            x             y  \\\n",
       "0  Shopper_556    Floor 4  37.661463 -122.298673 -2934.558251 -16169.722290   \n",
       "1  Shopper_556    Floor 1  37.784062 -122.406943   117.262475    151.823812   \n",
       "2  Shopper_556    Floor 4  37.784361 -122.406710   156.125087    171.357200   \n",
       "3  Shopper_360  Concourse  37.784341 -122.406891   134.499673    167.674401   \n",
       "4  Shopper_360    Floor 2  37.784017 -122.407307    94.981693    172.269243   \n",
       "\n",
       "              seenTimestamp  \n",
       "0  2016-11-22T02:16:06.000Z  \n",
       "1  2016-12-23T22:01:25.000Z  \n",
       "2  2016-11-22T01:42:28.000Z  \n",
       "3  2016-10-13T18:27:38.000Z  \n",
       "4  2016-10-12T21:36:18.000Z  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginformation = pd.read_excel(File, \"Ping_Information\")\n",
    "pinginformation.drop(['Unnamed: 0'], axis=1, inplace=True)\n",
    "pinginformation.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 567 entries, 0 to 566\n",
      "Data columns (total 7 columns):\n",
      "Shopper_Id                                  567 non-null object\n",
      "ID                                          567 non-null object\n",
      "Age                                         567 non-null int64\n",
      "Gender                                      567 non-null object\n",
      "Marital_Status                              567 non-null object\n",
      "Owns_Home                                   567 non-null object\n",
      "Number_of_Children_under_18_years_of_age    567 non-null int64\n",
      "dtypes: int64(2), object(5)\n",
      "memory usage: 31.1+ KB\n"
     ]
    }
   ],
   "source": [
    "demographics.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 166 entries, 0 to 165\n",
      "Data columns (total 5 columns):\n",
      "Store_Name     166 non-null object\n",
      "Floor_name     166 non-null object\n",
      "Floor_Index    166 non-null int64\n",
      "latitude       166 non-null float64\n",
      "longitude      166 non-null float64\n",
      "dtypes: float64(2), int64(1), object(2)\n",
      "memory usage: 6.6+ KB\n"
     ]
    }
   ],
   "source": [
    "storemapping.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 154 entries, 0 to 153\n",
      "Data columns (total 3 columns):\n",
      "Store_Name        154 non-null object\n",
      "Broad_Category    154 non-null object\n",
      "Fine_Category     154 non-null object\n",
      "dtypes: object(3)\n",
      "memory usage: 3.7+ KB\n"
     ]
    }
   ],
   "source": [
    "categorymapping.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 107635 entries, 0 to 107634\n",
      "Data columns (total 7 columns):\n",
      "Shopper_ID       107635 non-null object\n",
      "floor            107635 non-null object\n",
      "lat              107635 non-null float64\n",
      "lng              107635 non-null float64\n",
      "x                107635 non-null float64\n",
      "y                107635 non-null float64\n",
      "seenTimestamp    107635 non-null object\n",
      "dtypes: float64(4), object(3)\n",
      "memory usage: 5.7+ MB\n"
     ]
    }
   ],
   "source": [
    "pinginformation.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfo=pinginformation.drop(['x', 'y', 'seenTimestamp'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>floor</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 4</td>\n",
       "      <td>37.661463</td>\n",
       "      <td>-122.298673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 1</td>\n",
       "      <td>37.784062</td>\n",
       "      <td>-122.406943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 4</td>\n",
       "      <td>37.784361</td>\n",
       "      <td>-122.406710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>Concourse</td>\n",
       "      <td>37.784341</td>\n",
       "      <td>-122.406891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>Floor 2</td>\n",
       "      <td>37.784017</td>\n",
       "      <td>-122.407307</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shopper_ID      floor        lat         lng\n",
       "0  Shopper_556    Floor 4  37.661463 -122.298673\n",
       "1  Shopper_556    Floor 1  37.784062 -122.406943\n",
       "2  Shopper_556    Floor 4  37.784361 -122.406710\n",
       "3  Shopper_360  Concourse  37.784341 -122.406891\n",
       "4  Shopper_360    Floor 2  37.784017 -122.407307"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name  Floor_Index   latitude   longitude\n",
       "0                         Jamba Juice            0  37.784091 -122.406813\n",
       "1              Coriander Gourmet Thai            0  37.784596 -122.406210\n",
       "2                      NYS Collection            0  37.784396 -122.406587\n",
       "3                            Hallmark            0  37.783771 -122.407377\n",
       "4  Sorabol Korean BBQ & Asian Noodles            0  37.784601 -122.406328"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemap = storemapping.drop(['Floor_name'], axis=1)\n",
    "storemap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'Concourse', u'Floor 1', u'Floor 2', u'Floor 3', u'Floor 4']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#converting floor in pinginfo into int type:\n",
    "floors= sorted(pinginfo['floor'].unique())\n",
    "floors\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'Concourse': 0, u'Floor 1': 1, u'Floor 2': 2, u'Floor 3': 3, u'Floor 4': 4}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "floor_mapping = dict(zip(floors, range(0, len(floors) + 1)))\n",
    "floor_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>floor</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>Floor_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 4</td>\n",
       "      <td>37.661463</td>\n",
       "      <td>-122.298673</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 1</td>\n",
       "      <td>37.784062</td>\n",
       "      <td>-122.406943</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>Floor 4</td>\n",
       "      <td>37.784361</td>\n",
       "      <td>-122.406710</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>Concourse</td>\n",
       "      <td>37.784341</td>\n",
       "      <td>-122.406891</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>Floor 2</td>\n",
       "      <td>37.784017</td>\n",
       "      <td>-122.407307</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shopper_ID      floor        lat         lng  Floor_Index\n",
       "0  Shopper_556    Floor 4  37.661463 -122.298673            4\n",
       "1  Shopper_556    Floor 1  37.784062 -122.406943            1\n",
       "2  Shopper_556    Floor 4  37.784361 -122.406710            4\n",
       "3  Shopper_360  Concourse  37.784341 -122.406891            0\n",
       "4  Shopper_360    Floor 2  37.784017 -122.407307            2"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo['Floor_Index'] = pinginfo['floor'].map(floor_mapping).astype(int)\n",
    "pinginfo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>Floor_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>37.661463</td>\n",
       "      <td>-122.298673</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>37.784062</td>\n",
       "      <td>-122.406943</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>37.784361</td>\n",
       "      <td>-122.406710</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>37.784341</td>\n",
       "      <td>-122.406891</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>37.784017</td>\n",
       "      <td>-122.407307</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shopper_ID        lat         lng  Floor_Index\n",
       "0  Shopper_556  37.661463 -122.298673            4\n",
       "1  Shopper_556  37.784062 -122.406943            1\n",
       "2  Shopper_556  37.784361 -122.406710            4\n",
       "3  Shopper_360  37.784341 -122.406891            0\n",
       "4  Shopper_360  37.784017 -122.407307            2"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.drop(['floor'], axis=1, inplace=True)\n",
    "pinginfo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfo['latitude'] = pinginfo['lat']\n",
    "pinginfo['longitude'] = pinginfo['lng']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>Shopper_556</td>\n",
       "      <td>4</td>\n",
       "      <td>37.661463</td>\n",
       "      <td>-122.298673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>1</td>\n",
       "      <td>37.784062</td>\n",
       "      <td>-122.406943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shopper_556</td>\n",
       "      <td>4</td>\n",
       "      <td>37.784361</td>\n",
       "      <td>-122.406710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784341</td>\n",
       "      <td>-122.406891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shopper_360</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784017</td>\n",
       "      <td>-122.407307</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shopper_ID  Floor_Index   latitude   longitude\n",
       "0  Shopper_556            4  37.661463 -122.298673\n",
       "1  Shopper_556            1  37.784062 -122.406943\n",
       "2  Shopper_556            4  37.784361 -122.406710\n",
       "3  Shopper_360            0  37.784341 -122.406891\n",
       "4  Shopper_360            2  37.784017 -122.407307"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.drop(['lat', 'lng'], axis=1, inplace=True)\n",
    "pinginfo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name  Floor_Index   latitude   longitude\n",
       "0                         Jamba Juice            0  37.784091 -122.406813\n",
       "1              Coriander Gourmet Thai            0  37.784596 -122.406210\n",
       "2                      NYS Collection            0  37.784396 -122.406587\n",
       "3                            Hallmark            0  37.783771 -122.407377\n",
       "4  Sorabol Korean BBQ & Asian Noodles            0  37.784601 -122.406328"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   0.      ,   37.784091, -122.406813],\n",
       "       [   0.      ,   37.784596, -122.40621 ],\n",
       "       [   0.      ,   37.784396, -122.406587],\n",
       "       [   0.      ,   37.783771, -122.407377],\n",
       "       [   0.      ,   37.784601, -122.406328],\n",
       "       [   0.      ,   37.784534, -122.406025],\n",
       "       [   0.      ,   37.783944, -122.407537],\n",
       "       [   0.      ,   37.784447, -122.406224],\n",
       "       [   0.      ,   37.784161, -122.4069  ],\n",
       "       [   0.      ,   37.784808, -122.406501],\n",
       "       [   0.      ,   37.784569, -122.406141],\n",
       "       [   0.      ,   37.78467 , -122.406679],\n",
       "       [   0.      ,   37.784126, -122.407061],\n",
       "       [   0.      ,   37.784159, -122.40635 ],\n",
       "       [   0.      ,   37.783959, -122.40691 ],\n",
       "       [   0.      ,   37.784411, -122.406709],\n",
       "       [   0.      ,   37.784511, -122.405956],\n",
       "       [   0.      ,   37.784071, -122.406885],\n",
       "       [   0.      ,   37.784591, -122.406782],\n",
       "       [   0.      ,   37.783778, -122.407161],\n",
       "       [   0.      ,   37.784053, -122.407307],\n",
       "       [   0.      ,   37.783893, -122.407389],\n",
       "       [   0.      ,   37.784222, -122.406978],\n",
       "       [   0.      ,   37.783953, -122.407318],\n",
       "       [   0.      ,   37.784505, -122.406555],\n",
       "       [   0.      ,   37.783767, -122.40707 ],\n",
       "       [   0.      ,   37.784106, -122.407189],\n",
       "       [   0.      ,   37.784292, -122.40601 ],\n",
       "       [   0.      ,   37.784449, -122.406665],\n",
       "       [   0.      ,   37.784353, -122.406773],\n",
       "       [   0.      ,   37.784294, -122.406164],\n",
       "       [   0.      ,   37.78432 , -122.406195],\n",
       "       [   0.      ,   37.783944, -122.407175],\n",
       "       [   0.      ,   37.783831, -122.406941],\n",
       "       [   0.      ,   37.784312, -122.405822],\n",
       "       [   0.      ,   37.783887, -122.405783],\n",
       "       [   0.      ,   37.784208, -122.40743 ],\n",
       "       [   0.      ,   37.784505, -122.406399],\n",
       "       [   0.      ,   37.784625, -122.406417],\n",
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       "       [   1.      ,   37.783909, -122.407393],\n",
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       "       [   2.      ,   37.784252, -122.406942],\n",
       "       [   2.      ,   37.784387, -122.406732],\n",
       "       [   2.      ,   37.783739, -122.407271],\n",
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       "       [   2.      ,   37.784385, -122.406276],\n",
       "       [   2.      ,   37.784195, -122.407081],\n",
       "       [   2.      ,   37.784433, -122.40608 ],\n",
       "       [   2.      ,   37.784031, -122.406181],\n",
       "       [   2.      ,   37.783852, -122.405805],\n",
       "       [   2.      ,   37.783931, -122.406086],\n",
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       "       [   3.      ,   37.783986, -122.406922],\n",
       "       [   3.      ,   37.783839, -122.406836],\n",
       "       [   3.      ,   37.783812, -122.406021],\n",
       "       [   3.      ,   37.784133, -122.407419],\n",
       "       [   3.      ,   37.783752, -122.407371],\n",
       "       [   3.      ,   37.78429 , -122.406561],\n",
       "       [   3.      ,   37.783737, -122.407253],\n",
       "       [   3.      ,   37.78424 , -122.406455],\n",
       "       [   3.      ,   37.784101, -122.406854],\n",
       "       [   3.      ,   37.783871, -122.407073],\n",
       "       [   3.      ,   37.784153, -122.405871],\n",
       "       [   3.      ,   37.783745, -122.405601],\n",
       "       [   3.      ,   37.784191, -122.407111],\n",
       "       [   3.      ,   37.784267, -122.405933],\n",
       "       [   3.      ,   37.784386, -122.406589],\n",
       "       [   3.      ,   37.78454 , -122.406132],\n",
       "       [   3.      ,   37.783912, -122.407474],\n",
       "       [   3.      ,   37.784663, -122.406313],\n",
       "       [   3.      ,   37.784135, -122.406406],\n",
       "       [   3.      ,   37.783957, -122.406249],\n",
       "       [   3.      ,   37.783814, -122.407399],\n",
       "       [   3.      ,   37.784197, -122.40698 ],\n",
       "       [   3.      ,   37.784701, -122.406758],\n",
       "       [   3.      ,   37.78436 , -122.406786],\n",
       "       [   4.      ,   37.78442 , -122.406832],\n",
       "       [   4.      ,   37.784702, -122.406248],\n",
       "       [   4.      ,   37.784206, -122.406528],\n",
       "       [   4.      ,   37.784178, -122.405776],\n",
       "       [   4.      ,   37.783859, -122.40635 ],\n",
       "       [   4.      ,   37.784539, -122.406081],\n",
       "       [   4.      ,   37.78382 , -122.407311],\n",
       "       [   4.      ,   37.783802, -122.405736],\n",
       "       [   5.      ,   37.784076, -122.407307],\n",
       "       [   5.      ,   37.78389 , -122.405736],\n",
       "       [   5.      ,   37.784204, -122.406574],\n",
       "       [   6.      ,   37.78409 , -122.407309],\n",
       "       [   7.      ,   37.784073, -122.407289],\n",
       "       [   8.      ,   37.784087, -122.407307]])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = storemap.drop(['Store_Name'],axis=1).as_matrix().astype(np.float)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [-4.24108586e-01,  1.44998271e+00, -3.75112964e-01],\n",
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       "       [-4.24108586e-01, -1.12886573e+00, -2.70191564e-01],\n",
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       "       [-4.24108586e-01, -4.96252772e-01, -6.87778733e-01],\n",
       "       [-4.24108586e-01,  7.13662715e-01,  1.17352689e+00],\n",
       "       [-4.24108586e-01, -1.92003800e-02,  6.88790024e-01],\n",
       "       [-4.24108586e-01,  7.10205813e-01, -3.93644864e-02],\n",
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       "       [ 2.40061464e-01,  1.12157708e+00,  1.02663693e+00],\n",
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       "       [ 2.40061464e-01, -1.54023699e+00, -9.26999523e-01],\n",
       "       [ 2.40061464e-01,  6.72179898e-01,  9.04928106e-01],\n",
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       "       [ 2.40061464e-01,  1.01441314e+00,  4.30683382e-01],\n",
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       "       [ 2.40061464e-01,  1.25985313e+00, -2.24026149e-01],\n",
       "       [ 2.40061464e-01, -1.23948657e+00, -6.58400741e-01],\n",
       "       [ 2.40061464e-01, -8.17744601e-01, -1.67823674e+00],\n",
       "       [ 2.40061464e-01, -1.92003800e-02,  5.77573341e-01],\n",
       "       [ 2.40061464e-01, -1.12886573e+00, -4.54853227e-01],\n",
       "       [ 2.40061464e-01, -8.45399812e-01, -1.86254445e-01],\n",
       "       [ 2.40061464e-01,  4.33653702e-01,  3.08974559e-01],\n",
       "       [ 2.40061464e-01, -6.41400981e-02, -5.40534823e-02],\n",
       "       [ 2.40061464e-01,  2.78093139e-01,  1.85167308e-01],\n",
       "       [ 2.40061464e-01,  3.29946660e-01,  1.48199580e+00],\n",
       "       [ 9.04231513e-01, -5.13537279e-01, -4.06589383e-01],\n",
       "       [ 9.04231513e-01, -1.94123755e+00, -9.37491663e-01],\n",
       "       [ 9.04231513e-01, -1.55406460e+00, -4.08687811e-01],\n",
       "       [ 9.04231513e-01,  1.51220694e+00,  1.09168820e+00],\n",
       "       [ 9.04231513e-01,  5.51188349e-01,  1.34979484e+00],\n",
       "       [ 9.04231513e-01, -2.95752491e-01,  8.00006707e-01],\n",
       "       [ 9.04231513e-01,  1.46726722e+00, -3.24750692e-01],\n",
       "       [ 9.04231513e-01,  8.20826658e-01,  1.34805036e-01],\n",
       "       [ 9.04231513e-01,  8.86507784e-01, -2.13534009e-01],\n",
       "       [ 9.04231513e-01, -7.07123756e-01, -4.50656371e-01],\n",
       "       [ 9.04231513e-01, -1.21528826e+00, -2.70191564e-01],\n",
       "       [ 9.04231513e-01, -1.30862460e+00,  1.44002724e+00],\n",
       "       [ 9.04231513e-01, -1.98959252e-01, -1.49357508e+00],\n",
       "       [ 9.04231513e-01, -1.51603868e+00, -1.39285054e+00],\n",
       "       [ 9.04231513e-01,  3.43774266e-01,  3.06876131e-01],\n",
       "       [ 9.04231513e-01, -1.56789220e+00, -1.14523603e+00],\n",
       "       [ 9.04231513e-01,  1.70929196e-01,  5.29309497e-01],\n",
       "       [ 9.04231513e-01, -3.09580097e-01, -3.07963268e-01],\n",
       "       [ 9.04231513e-01, -1.10466742e+00, -7.67518996e-01],\n",
       "       [ 9.04231513e-01, -1.29821224e-01,  1.75479144e+00],\n",
       "       [ 9.04231513e-01, -1.54023699e+00,  2.32136699e+00],\n",
       "       [ 9.04231513e-01,  1.54102834e-03, -8.47259260e-01],\n",
       "       [ 9.04231513e-01,  2.64265534e-01,  1.62468890e+00],\n",
       "       [ 9.04231513e-01,  6.75636799e-01,  2.48120147e-01],\n",
       "       [ 9.04231513e-01,  1.20799961e+00,  1.20710174e+00],\n",
       "       [ 9.04231513e-01, -9.62934459e-01, -1.60898862e+00],\n",
       "       [ 9.04231513e-01,  1.63319848e+00,  8.27286270e-01],\n",
       "       [ 9.04231513e-01, -1.92045449e-01,  6.32132468e-01],\n",
       "       [ 9.04231513e-01, -8.07373897e-01,  9.61585661e-01],\n",
       "       [ 9.04231513e-01, -1.30171080e+00, -1.45160652e+00],\n",
       "       [ 9.04231513e-01,  2.22824367e-02, -5.72365194e-01],\n",
       "       [ 9.04231513e-01,  1.76456074e+00, -1.06514182e-01],\n",
       "       [ 9.04231513e-01,  5.85757363e-01, -1.65270165e-01],\n",
       "       [ 1.56840156e+00,  7.93171447e-01, -2.61797853e-01],\n",
       "       [ 1.56840156e+00,  1.76801764e+00,  9.63684089e-01],\n",
       "       [ 1.56840156e+00,  5.33945492e-02,  3.76124254e-01],\n",
       "       [ 1.56840156e+00, -4.33986897e-02,  1.95414210e+00],\n",
       "       [ 1.56840156e+00, -1.14615023e+00,  7.49644435e-01],\n",
       "       [ 1.56840156e+00,  1.20454271e+00,  1.31412156e+00],\n",
       "       [ 1.56840156e+00, -1.28096939e+00, -1.26694486e+00],\n",
       "       [ 1.56840156e+00, -1.34319361e+00,  2.03807922e+00],\n",
       "       [ 2.23257161e+00, -3.96002631e-01, -1.25855114e+00],\n",
       "       [ 2.23257161e+00, -1.03898629e+00,  2.03807922e+00],\n",
       "       [ 2.23257161e+00,  4.64807464e-02,  2.79596567e-01],\n",
       "       [ 2.89674166e+00, -3.47606012e-01, -1.26274800e+00],\n",
       "       [ 3.56091171e+00, -4.06373336e-01, -1.22077944e+00],\n",
       "       [ 4.22508176e+00, -3.57976716e-01, -1.25855114e+00]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#convert into matrix having mean= 0 and std dev= 1\n",
    "from sklearn import preprocessing\n",
    "scaler = preprocessing.StandardScaler()\n",
    "X = scaler.fit_transform(X)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'49ers Team Store',\n",
       " u'Abercrombie & Fitch',\n",
       " u'Adidas',\n",
       " u'Ajisen Ramen',\n",
       " u'Aldo',\n",
       " u'Amazon Pop-Up',\n",
       " u'American Eagle Outfitters',\n",
       " u'Amiri Salon',\n",
       " u'Amoura Cafe Fresh Mediterranean',\n",
       " u'Andale Mexican Restaurant',\n",
       " u'Aritzia',\n",
       " u\"Auntie Anne's Pretzels\",\n",
       " u'Aveda',\n",
       " u'BCBGMAXAZRIA',\n",
       " u'BOSS',\n",
       " u'Banana Republic',\n",
       " u'Bath & Body Works',\n",
       " u\"Beard Papa's Cream Puffs\",\n",
       " u'Bespoke Coworking',\n",
       " u'Bespoke Events',\n",
       " u\"Bloomingdale's\",\n",
       " u'Bose',\n",
       " u'Brighton Collectibles',\n",
       " u'Bristol Farms',\n",
       " u'Brookstone',\n",
       " u'Buckhorn Grill',\n",
       " u'Burberry',\n",
       " u'Burke Williams Day Spa',\n",
       " u'Cafe Bellini',\n",
       " u'Caffe Central',\n",
       " u'Cako Bakery',\n",
       " u'Camper',\n",
       " u'Century San Francisco Centre 9',\n",
       " u'Champs Sports',\n",
       " u\"Charley's Grilled Subs\",\n",
       " u'Chipotle',\n",
       " u\"Claire's Boutique\",\n",
       " u'Clarks',\n",
       " u'Club Monaco Men',\n",
       " u'Club Monaco Women',\n",
       " u'Coach',\n",
       " u'Coriander Gourmet Thai',\n",
       " u'Corner W',\n",
       " u'Cotton On',\n",
       " u'Currency Exchange International ',\n",
       " u'DAVIDsTEA',\n",
       " u'Dyson',\n",
       " u'ECCO',\n",
       " u'Eddie Bauer',\n",
       " u'Express',\n",
       " u'Eyebrow Plus',\n",
       " u'Finish Line',\n",
       " u'Fire of Brazil',\n",
       " u'Forever Flawless',\n",
       " u'Forever Flawless ',\n",
       " u'Fossil',\n",
       " u\"Francesca's Collection \",\n",
       " u'GNC',\n",
       " u'GUESS ',\n",
       " u'Ghirardelli Ice Cream and Chocolate Shop ',\n",
       " u'Go! Toys and Games',\n",
       " u'Godiva Chocolatier',\n",
       " u'H&M',\n",
       " u'H&M Man',\n",
       " u'Haagen Dazs',\n",
       " u'Hallmark',\n",
       " u'Hollister Co.',\n",
       " u'House of Hoops by Foot Locker',\n",
       " u'J.Crew',\n",
       " u'Jamba Juice',\n",
       " u'Janie And Jack',\n",
       " u'Karen Millen',\n",
       " u'Kate Spade New York',\n",
       " u'Kay Jewelers',\n",
       " u'Kichi Grill',\n",
       " u\"Kiehl's\",\n",
       " u\"L'Occitane en Provence\",\n",
       " u'LEGO',\n",
       " u'Lady Foot Locker',\n",
       " u'Lids',\n",
       " u'Lobster Me',\n",
       " u'Loving Hut Vegan Cuisine ',\n",
       " u'Lucky Brand Jeans',\n",
       " u'M.Y. China',\n",
       " u'Madewell',\n",
       " u'Marbles: The Brain Store',\n",
       " u'Max & Co.',\n",
       " u'Michael Kors',\n",
       " u'Michael Kors Men',\n",
       " u'Microsoft',\n",
       " u'Mrs. Fields',\n",
       " u'NYS Collection',\n",
       " u'New Era',\n",
       " u'Nordstrom',\n",
       " u'Nordstrom E-Bar',\n",
       " u'OAK+FORT',\n",
       " u'Onassis',\n",
       " u'Optica',\n",
       " u'Origins',\n",
       " u'PacSun',\n",
       " u'Panda Express',\n",
       " u'Pandora',\n",
       " u'Papyrus',\n",
       " u'Pasta Moto',\n",
       " u\"Peet's Coffee & Tea\",\n",
       " u'Penhaligon\\xef\\xbf\\xbd\\xdb\\xaas',\n",
       " u'Perfumania',\n",
       " u'Pressed Juicery',\n",
       " u'ProActiv Solutions ',\n",
       " u'RED Valentino',\n",
       " u'Razer',\n",
       " u'Rolex',\n",
       " u'SF Sports',\n",
       " u'Samsonite',\n",
       " u'San Francisco Luggage Co.',\n",
       " u'San Francisco Soup Company',\n",
       " u'Sarku Japan',\n",
       " u'Shoe Palace ',\n",
       " u'Shoe Wiz',\n",
       " u'Solstice',\n",
       " u'Sorabol Korean BBQ & Asian Noodles',\n",
       " u'Starbucks',\n",
       " u'Steve Madden',\n",
       " u'Studio Manhattan',\n",
       " u'Sunglass Hut',\n",
       " u'Sunglass Hut ',\n",
       " u'Superdry ',\n",
       " u'Sur La Table',\n",
       " u'Swarovski',\n",
       " u'Swatch',\n",
       " u'T-Mobile',\n",
       " u'TAP 415',\n",
       " u'Teavana',\n",
       " u'The Art of Shaving',\n",
       " u'The Body Shop',\n",
       " u'The Walking Company',\n",
       " u'Tiffany & Co.',\n",
       " u'Timberland',\n",
       " u'Tory Burch ',\n",
       " u'Tourneau',\n",
       " u'True Religion Jeans',\n",
       " u'Tumi',\n",
       " u'Vans',\n",
       " u'Vera Bradley',\n",
       " u\"Victoria's Secret\",\n",
       " u'Warriors Team Store',\n",
       " u\"Wetzel's Pretzels\",\n",
       " u'Yoppi Frozen Yogurt ',\n",
       " u'Zara',\n",
       " u'abercrombie kids',\n",
       " u'bareMinerals',\n",
       " u'bebe',\n",
       " u'iPlay n Talk',\n",
       " u'lululemon athletica']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stores= sorted(storemap['Store_Name'].unique())\n",
    "stores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'49ers Team Store': 0,\n",
       " u'Abercrombie & Fitch': 1,\n",
       " u'Adidas': 2,\n",
       " u'Ajisen Ramen': 3,\n",
       " u'Aldo': 4,\n",
       " u'Amazon Pop-Up': 5,\n",
       " u'American Eagle Outfitters': 6,\n",
       " u'Amiri Salon': 7,\n",
       " u'Amoura Cafe Fresh Mediterranean': 8,\n",
       " u'Andale Mexican Restaurant': 9,\n",
       " u'Aritzia': 10,\n",
       " u\"Auntie Anne's Pretzels\": 11,\n",
       " u'Aveda': 12,\n",
       " u'BCBGMAXAZRIA': 13,\n",
       " u'BOSS': 14,\n",
       " u'Banana Republic': 15,\n",
       " u'Bath & Body Works': 16,\n",
       " u\"Beard Papa's Cream Puffs\": 17,\n",
       " u'Bespoke Coworking': 18,\n",
       " u'Bespoke Events': 19,\n",
       " u\"Bloomingdale's\": 20,\n",
       " u'Bose': 21,\n",
       " u'Brighton Collectibles': 22,\n",
       " u'Bristol Farms': 23,\n",
       " u'Brookstone': 24,\n",
       " u'Buckhorn Grill': 25,\n",
       " u'Burberry': 26,\n",
       " u'Burke Williams Day Spa': 27,\n",
       " u'Cafe Bellini': 28,\n",
       " u'Caffe Central': 29,\n",
       " u'Cako Bakery': 30,\n",
       " u'Camper': 31,\n",
       " u'Century San Francisco Centre 9': 32,\n",
       " u'Champs Sports': 33,\n",
       " u\"Charley's Grilled Subs\": 34,\n",
       " u'Chipotle': 35,\n",
       " u\"Claire's Boutique\": 36,\n",
       " u'Clarks': 37,\n",
       " u'Club Monaco Men': 38,\n",
       " u'Club Monaco Women': 39,\n",
       " u'Coach': 40,\n",
       " u'Coriander Gourmet Thai': 41,\n",
       " u'Corner W': 42,\n",
       " u'Cotton On': 43,\n",
       " u'Currency Exchange International ': 44,\n",
       " u'DAVIDsTEA': 45,\n",
       " u'Dyson': 46,\n",
       " u'ECCO': 47,\n",
       " u'Eddie Bauer': 48,\n",
       " u'Express': 49,\n",
       " u'Eyebrow Plus': 50,\n",
       " u'Finish Line': 51,\n",
       " u'Fire of Brazil': 52,\n",
       " u'Forever Flawless': 53,\n",
       " u'Forever Flawless ': 54,\n",
       " u'Fossil': 55,\n",
       " u\"Francesca's Collection \": 56,\n",
       " u'GNC': 57,\n",
       " u'GUESS ': 58,\n",
       " u'Ghirardelli Ice Cream and Chocolate Shop ': 59,\n",
       " u'Go! Toys and Games': 60,\n",
       " u'Godiva Chocolatier': 61,\n",
       " u'H&M': 62,\n",
       " u'H&M Man': 63,\n",
       " u'Haagen Dazs': 64,\n",
       " u'Hallmark': 65,\n",
       " u'Hollister Co.': 66,\n",
       " u'House of Hoops by Foot Locker': 67,\n",
       " u'J.Crew': 68,\n",
       " u'Jamba Juice': 69,\n",
       " u'Janie And Jack': 70,\n",
       " u'Karen Millen': 71,\n",
       " u'Kate Spade New York': 72,\n",
       " u'Kay Jewelers': 73,\n",
       " u'Kichi Grill': 74,\n",
       " u\"Kiehl's\": 75,\n",
       " u\"L'Occitane en Provence\": 76,\n",
       " u'LEGO': 77,\n",
       " u'Lady Foot Locker': 78,\n",
       " u'Lids': 79,\n",
       " u'Lobster Me': 80,\n",
       " u'Loving Hut Vegan Cuisine ': 81,\n",
       " u'Lucky Brand Jeans': 82,\n",
       " u'M.Y. China': 83,\n",
       " u'Madewell': 84,\n",
       " u'Marbles: The Brain Store': 85,\n",
       " u'Max & Co.': 86,\n",
       " u'Michael Kors': 87,\n",
       " u'Michael Kors Men': 88,\n",
       " u'Microsoft': 89,\n",
       " u'Mrs. Fields': 90,\n",
       " u'NYS Collection': 91,\n",
       " u'New Era': 92,\n",
       " u'Nordstrom': 93,\n",
       " u'Nordstrom E-Bar': 94,\n",
       " u'OAK+FORT': 95,\n",
       " u'Onassis': 96,\n",
       " u'Optica': 97,\n",
       " u'Origins': 98,\n",
       " u'PacSun': 99,\n",
       " u'Panda Express': 100,\n",
       " u'Pandora': 101,\n",
       " u'Papyrus': 102,\n",
       " u'Pasta Moto': 103,\n",
       " u\"Peet's Coffee & Tea\": 104,\n",
       " u'Penhaligon\\xef\\xbf\\xbd\\xdb\\xaas': 105,\n",
       " u'Perfumania': 106,\n",
       " u'Pressed Juicery': 107,\n",
       " u'ProActiv Solutions ': 108,\n",
       " u'RED Valentino': 109,\n",
       " u'Razer': 110,\n",
       " u'Rolex': 111,\n",
       " u'SF Sports': 112,\n",
       " u'Samsonite': 113,\n",
       " u'San Francisco Luggage Co.': 114,\n",
       " u'San Francisco Soup Company': 115,\n",
       " u'Sarku Japan': 116,\n",
       " u'Shoe Palace ': 117,\n",
       " u'Shoe Wiz': 118,\n",
       " u'Solstice': 119,\n",
       " u'Sorabol Korean BBQ & Asian Noodles': 120,\n",
       " u'Starbucks': 121,\n",
       " u'Steve Madden': 122,\n",
       " u'Studio Manhattan': 123,\n",
       " u'Sunglass Hut': 124,\n",
       " u'Sunglass Hut ': 125,\n",
       " u'Superdry ': 126,\n",
       " u'Sur La Table': 127,\n",
       " u'Swarovski': 128,\n",
       " u'Swatch': 129,\n",
       " u'T-Mobile': 130,\n",
       " u'TAP 415': 131,\n",
       " u'Teavana': 132,\n",
       " u'The Art of Shaving': 133,\n",
       " u'The Body Shop': 134,\n",
       " u'The Walking Company': 135,\n",
       " u'Tiffany & Co.': 136,\n",
       " u'Timberland': 137,\n",
       " u'Tory Burch ': 138,\n",
       " u'Tourneau': 139,\n",
       " u'True Religion Jeans': 140,\n",
       " u'Tumi': 141,\n",
       " u'Vans': 142,\n",
       " u'Vera Bradley': 143,\n",
       " u\"Victoria's Secret\": 144,\n",
       " u'Warriors Team Store': 145,\n",
       " u\"Wetzel's Pretzels\": 146,\n",
       " u'Yoppi Frozen Yogurt ': 147,\n",
       " u'Zara': 148,\n",
       " u'abercrombie kids': 149,\n",
       " u'bareMinerals': 150,\n",
       " u'bebe': 151,\n",
       " u'iPlay n Talk': 152,\n",
       " u'lululemon athletica': 153}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "store_mapping = dict(zip(stores, range(0, len(stores) + 1)))\n",
    "store_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name  Floor_Index   latitude   longitude  \\\n",
       "0                         Jamba Juice            0  37.784091 -122.406813   \n",
       "1              Coriander Gourmet Thai            0  37.784596 -122.406210   \n",
       "2                      NYS Collection            0  37.784396 -122.406587   \n",
       "3                            Hallmark            0  37.783771 -122.407377   \n",
       "4  Sorabol Korean BBQ & Asian Noodles            0  37.784601 -122.406328   \n",
       "\n",
       "   Store_Index  \n",
       "0           69  \n",
       "1           41  \n",
       "2           91  \n",
       "3           65  \n",
       "4          120  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemap['Store_Index'] = storemap['Store_Name'].map(store_mapping).astype(int)\n",
    "storemap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 69,  41,  91,  65, 120, 103,   1,  52, 108,  42,  25,  30,  36,\n",
       "        23,  99,  45,   9, 125, 104, 100,  57,  92,  77,  90,  17,   3,\n",
       "       117,  81,  59,  85,  29, 107,  28, 116,  74,  20, 145,  80,   8,\n",
       "       146, 118,  64, 127,  34,  33, 115, 121,  35, 110,  84,  20, 129,\n",
       "        75,   5,  70, 133, 109,  26, 128,  22,  87,  71,  10, 141,  72,\n",
       "       105,   1, 138,  76, 111, 124, 137, 139,   2, 126,  98,  38,  44,\n",
       "        39,   6,  94,  75, 136,  14,  88, 153,  40, 150,  54,  95,  11,\n",
       "        86,  96, 148, 151,  47,  78,  43, 101, 134,  49, 130,  24,  13,\n",
       "        63,  20,   0, 123,  56,   2,  46,  66,  89, 113,  58,  12,  31,\n",
       "       147,  68, 135,  49, 102, 114,  15, 143,  48,  61, 112,   4,  67,\n",
       "       149, 144, 106,  73,   7,  37,  79, 152,  60,  20,  55, 142,  50,\n",
       "       140,  51,  82,  16,  62, 132, 122,  53, 119, 131,  97,  83,  18,\n",
       "        19,  21,  93,  20,  93,  32,  27,  93,  93,  93])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = storemap['Store_Index'].as_matrix().astype(np.int)\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'CROSS VALIDATION and checking the accuracy of our classifiers'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''CROSS VALIDATION and checking the accuracy of our classifiers'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\welcome\\Anaconda2\\lib\\site-packages\\sklearn\\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn import cross_validation\n",
    "from sklearn import tree\n",
    "from sklearn import svm\n",
    "from sklearn import ensemble\n",
    "from sklearn import neighbors\n",
    "from sklearn import linear_model\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stratified_cv(X, y, clf_class, shuffle=True, n_folds=2, **kwargs):\n",
    "    stratified_k_fold = cross_validation.StratifiedKFold(y, n_folds=n_folds, shuffle=shuffle)\n",
    "    y_pred = y.copy()\n",
    "    for ii, jj in stratified_k_fold:\n",
    "        X_train, X_test = X[ii], X[jj]\n",
    "        y_train = y[ii]\n",
    "        clf = clf_class(**kwargs)\n",
    "        clf.fit(X_train,y_train)\n",
    "        y_pred[jj] = clf.predict(X_test)\n",
    "    return y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\welcome\\Anaconda2\\lib\\site-packages\\sklearn\\cross_validation.py:553: Warning: The least populated class in y has only 1 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=2.\n",
      "  % (min_labels, self.n_folds)), Warning)\n",
      "C:\\Users\\welcome\\Anaconda2\\lib\\site-packages\\sklearn\\linear_model\\stochastic_gradient.py:128: FutureWarning: max_iter and tol parameters have been added in <class 'sklearn.linear_model.passive_aggressive.PassiveAggressiveClassifier'> in 0.19. If both are left unset, they default to max_iter=5 and tol=None. If tol is not None, max_iter defaults to max_iter=1000. From 0.21, default max_iter will be 1000, and default tol will be 1e-3.\n",
      "  \"and default tol will be 1e-3.\" % type(self), FutureWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Passive Aggressive Classifier: 0.01\n",
      "Gradient Boosting Classifier:  0.05\n",
      "Support vector machine(SVM):   0.05\n",
      "Random Forest Classifier:      0.05\n",
      "K Nearest Neighbor Classifier: 0.05\n",
      "Logistic Regression:           0.07\n"
     ]
    }
   ],
   "source": [
    "print('Passive Aggressive Classifier: {:.2f}'.format(metrics.accuracy_score(y, stratified_cv(X, y, linear_model.PassiveAggressiveClassifier))))\n",
    "print('Gradient Boosting Classifier:  {:.2f}'.format(metrics.accuracy_score(y, stratified_cv(X, y, ensemble.GradientBoostingClassifier))))\n",
    "print('Support vector machine(SVM):   {:.2f}'.format(metrics.accuracy_score(y, stratified_cv(X, y, svm.SVC))))\n",
    "print('Random Forest Classifier:      {:.2f}'.format(metrics.accuracy_score(y, stratified_cv(X, y, ensemble.RandomForestClassifier))))\n",
    "print('K Nearest Neighbor Classifier: {:.2f}'.format(metrics.accuracy_score(y, stratified_cv(X, y, neighbors.KNeighborsClassifier))))\n",
    "print('Logistic Regression:           {:.2f}'.format(metrics.accuracy_score(y, stratified_cv(X, y, linear_model.LogisticRegression))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"print('Misclassified samples: %d' % (y != y_pred).sum())\""
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''print('Misclassified samples: %d' % (y != y_pred).sum())'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#OR:\\nfrom sklearn.model_selection import StratifiedKFold\\nskf = StratifiedKFold(n_splits=2)\\nskf.get_n_splits(X, y)\\n\\nprint(skf)  \\n\\nfor train_index, test_index in skf.split(X, y):\\n   print(\"TRAIN:\", train_index, \"TEST:\", test_index)\\n   X_train, X_test = X[train_index], X[test_index]\\n   y_train, y_test = y[train_index], y[test_index]\\n'"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''#OR:\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "skf = StratifiedKFold(n_splits=2)\n",
    "skf.get_n_splits(X, y)\n",
    "\n",
    "print(skf)  \n",
    "\n",
    "for train_index, test_index in skf.split(X, y):\n",
    "   print(\"TRAIN:\", train_index, \"TEST:\", test_index)\n",
    "   X_train, X_test = X[train_index], X[test_index]\n",
    "   y_train, y_test = y[train_index], y[test_index]\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mean accuracy of Random Forest: 1.0'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#RANDOM FOREST TRAINING: SKIPPING CROSS VALIDATION:\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "clf = RandomForestClassifier(n_estimators=100)\n",
    "#Fit the training data and create the decision trees:\n",
    "\n",
    "train_features = X\n",
    "\n",
    "#labels\n",
    "train_target = y\n",
    "\n",
    "# Fit the model to our training data\n",
    "clf = clf.fit(train_features, train_target)\n",
    "score = clf.score(train_features, train_target)\n",
    "\"Mean accuracy of Random Forest: {0}\".format(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   4.        ,   37.66146302, -122.2986728 ],\n",
       "       [   1.        ,   37.78406211, -122.4069432 ],\n",
       "       [   4.        ,   37.78436125, -122.4067095 ],\n",
       "       ...,\n",
       "       [   2.        ,   36.0179502 , -116.704627  ],\n",
       "       [   1.        ,   37.78404745, -122.4069997 ],\n",
       "       [   0.        ,   37.78407819, -122.4070869 ]])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test = pinginfo.drop(['Shopper_ID'], axis=1).as_matrix().astype(np.float)\n",
    "X_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.83464372,  0.36209925, -0.40275272],\n",
       "       [-0.32798594,  0.42248019, -0.41922354],\n",
       "       [ 1.83464372,  0.42262752, -0.41918799],\n",
       "       ...,\n",
       "       [ 0.39289061, -0.44734271,  0.44825139],\n",
       "       [-0.32798594,  0.42247297, -0.41923214],\n",
       "       [-1.04886249,  0.42248811, -0.4192454 ]])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler = preprocessing.StandardScaler()\n",
    "test_data = scaler.fit_transform(X_test)\n",
    "test_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_y = clf.predict(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfo['Store_Index'] = test_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfo.sort_values(['Shopper_ID'], axis=0, ascending=True, inplace=True, kind='quicksort', na_position='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "    </tr>\n",
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       "      <td>0</td>\n",
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       "      <th>52049</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>31.486702</td>\n",
       "      <td>-102.005952</td>\n",
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       "      <td>20</td>\n",
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       "      <td>-122.407172</td>\n",
       "      <td>108</td>\n",
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       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
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       "      <td>-111.278963</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.085205</td>\n",
       "      <td>-113.663751</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>20</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>30.227255</td>\n",
       "      <td>-97.925648</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37372</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407009</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21770</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.968828</td>\n",
       "      <td>-110.133960</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28495</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>35.561458</td>\n",
       "      <td>-115.206698</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28513</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.349118</td>\n",
       "      <td>-111.279163</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93921</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784079</td>\n",
       "      <td>-122.407114</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50871</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.565384</td>\n",
       "      <td>-108.788102</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61183</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>31.971140</td>\n",
       "      <td>-103.575216</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50835</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>34.877596</td>\n",
       "      <td>-112.991172</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21547</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784064</td>\n",
       "      <td>-122.407207</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61182</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>4</td>\n",
       "      <td>35.756717</td>\n",
       "      <td>-115.930223</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74866</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.757750</td>\n",
       "      <td>-122.383892</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74855</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55291</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.783956</td>\n",
       "      <td>-122.407213</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74843</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74806</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784168</td>\n",
       "      <td>-122.406034</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74805</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.635384</td>\n",
       "      <td>-112.206523</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.539867</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50625</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.644070</td>\n",
       "      <td>-115.570418</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50624</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784065</td>\n",
       "      <td>-122.407157</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93848</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.746176</td>\n",
       "      <td>-106.086128</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11819</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85044</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.338040</td>\n",
       "      <td>-91.805298</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85045</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.539812</td>\n",
       "      <td>-115.187564</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11637</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784120</td>\n",
       "      <td>-122.406620</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60944</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784048</td>\n",
       "      <td>-122.407212</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.635388</td>\n",
       "      <td>-112.206498</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85080</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.386344</td>\n",
       "      <td>-104.920316</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74419</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.585855</td>\n",
       "      <td>-108.806241</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.784032</td>\n",
       "      <td>-122.407175</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Shopper_ID  Floor_Index   latitude   longitude  Store_Index\n",
       "35181   Shopper_1            3  37.762391 -122.388008          119\n",
       "70238   Shopper_1            0  33.585825 -108.806374           20\n",
       "70264   Shopper_1            0  37.784023 -122.406786          108\n",
       "40491   Shopper_1            2  37.761052 -122.386801           43\n",
       "4777    Shopper_1            3  35.664542 -115.588398           16\n",
       "4776    Shopper_1            0  32.386375 -104.920369           20\n",
       "101158  Shopper_1            1  34.005662 -110.166421           20\n",
       "49054   Shopper_1            0  35.399517 -114.736228           99\n",
       "22621   Shopper_1            1  32.721647 -106.064451           20\n",
       "22620   Shopper_1            0  17.523494  -56.901809           20\n",
       "22619   Shopper_1            2  34.349167 -111.279150            0\n",
       "52049   Shopper_1            3  31.486702 -102.005952           20\n",
       "95887   Shopper_1            1  33.061045 -107.106172           20\n",
       "98815   Shopper_1            0  37.784038 -122.406711          108\n",
       "78061   Shopper_1            1  31.971133 -103.575228           20\n",
       "106999  Shopper_1            0  33.061063 -107.106165           20\n",
       "78035   Shopper_1            0  37.784263 -122.405984          108\n",
       "77973   Shopper_1            3  37.784085 -122.407135          119\n",
       "100499  Shopper_1            3  37.784018 -122.407150          119\n",
       "35762   Shopper_1            3  37.784052 -122.407079          119\n",
       "71239   Shopper_1            3  37.784055 -122.407086          119\n",
       "97924   Shopper_1            0  37.784075 -122.407065          108\n",
       "102120  Shopper_1            0  37.784055 -122.407176          108\n",
       "97101   Shopper_1            2  33.787407 -109.504903           20\n",
       "47032   Shopper_1            0  37.784077 -122.407172          108\n",
       "25665   Shopper_1            0  34.349141 -111.278963          116\n",
       "25664   Shopper_1            3  35.085205 -113.663751           62\n",
       "77426   Shopper_1            2  37.784041 -122.407108           43\n",
       "97946   Shopper_1            1  35.265121 -114.246687           20\n",
       "32914   Shopper_1            0  37.784059 -122.406598          108\n",
       "...           ...          ...        ...         ...          ...\n",
       "418     Shopper_1            1  30.227255  -97.925648           20\n",
       "37372   Shopper_1            0  37.784085 -122.407009          108\n",
       "21770   Shopper_1            0  33.968828 -110.133960           20\n",
       "28495   Shopper_1            2  35.561458 -115.206698           63\n",
       "28513   Shopper_1            1  34.349118 -111.279163           39\n",
       "93921   Shopper_1            2  37.784079 -122.407114           43\n",
       "50871   Shopper_1            1  33.565384 -108.788102           20\n",
       "61183   Shopper_1            0  31.971140 -103.575216           20\n",
       "50835   Shopper_1            3  34.877596 -112.991172           62\n",
       "21547   Shopper_1            3  37.784064 -122.407207          119\n",
       "61182   Shopper_1            4  35.756717 -115.930223           19\n",
       "74866   Shopper_1            1  37.757750 -122.383892          128\n",
       "74855   Shopper_1            2  37.762391 -122.388008           43\n",
       "55291   Shopper_1            2  37.783956 -122.407213           43\n",
       "74843   Shopper_1            3  37.784077 -122.407058          119\n",
       "74806   Shopper_1            0  37.784168 -122.406034          108\n",
       "74805   Shopper_1            1  34.635384 -112.206523           39\n",
       "41665   Shopper_1            1  35.539867 -115.187304           14\n",
       "50625   Shopper_1            0  35.644070 -115.570418           64\n",
       "50624   Shopper_1            3  37.784065 -122.407157          119\n",
       "93848   Shopper_1            1  32.746176 -106.086128           20\n",
       "11819   Shopper_1            2  37.784077 -122.407058           43\n",
       "85044   Shopper_1            0  28.338040  -91.805298           20\n",
       "85045   Shopper_1            3  35.539812 -115.187564           62\n",
       "11637   Shopper_1            0  37.784120 -122.406620          108\n",
       "60944   Shopper_1            0  37.784048 -122.407212          108\n",
       "85061   Shopper_1            2  34.635388 -112.206498            0\n",
       "85080   Shopper_1            1  32.386344 -104.920316           20\n",
       "74419   Shopper_1            1  33.585855 -108.806241           20\n",
       "61181   Shopper_1            1  37.784032 -122.407175          128\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "#now convert these store_index back into store_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'49ers Team Store': 0,\n",
       " u'Abercrombie & Fitch': 1,\n",
       " u'Adidas': 2,\n",
       " u'Ajisen Ramen': 3,\n",
       " u'Aldo': 4,\n",
       " u'Amazon Pop-Up': 5,\n",
       " u'American Eagle Outfitters': 6,\n",
       " u'Amiri Salon': 7,\n",
       " u'Amoura Cafe Fresh Mediterranean': 8,\n",
       " u'Andale Mexican Restaurant': 9,\n",
       " u'Aritzia': 10,\n",
       " u\"Auntie Anne's Pretzels\": 11,\n",
       " u'Aveda': 12,\n",
       " u'BCBGMAXAZRIA': 13,\n",
       " u'BOSS': 14,\n",
       " u'Banana Republic': 15,\n",
       " u'Bath & Body Works': 16,\n",
       " u\"Beard Papa's Cream Puffs\": 17,\n",
       " u'Bespoke Coworking': 18,\n",
       " u'Bespoke Events': 19,\n",
       " u\"Bloomingdale's\": 20,\n",
       " u'Bose': 21,\n",
       " u'Brighton Collectibles': 22,\n",
       " u'Bristol Farms': 23,\n",
       " u'Brookstone': 24,\n",
       " u'Buckhorn Grill': 25,\n",
       " u'Burberry': 26,\n",
       " u'Burke Williams Day Spa': 27,\n",
       " u'Cafe Bellini': 28,\n",
       " u'Caffe Central': 29,\n",
       " u'Cako Bakery': 30,\n",
       " u'Camper': 31,\n",
       " u'Century San Francisco Centre 9': 32,\n",
       " u'Champs Sports': 33,\n",
       " u\"Charley's Grilled Subs\": 34,\n",
       " u'Chipotle': 35,\n",
       " u\"Claire's Boutique\": 36,\n",
       " u'Clarks': 37,\n",
       " u'Club Monaco Men': 38,\n",
       " u'Club Monaco Women': 39,\n",
       " u'Coach': 40,\n",
       " u'Coriander Gourmet Thai': 41,\n",
       " u'Corner W': 42,\n",
       " u'Cotton On': 43,\n",
       " u'Currency Exchange International ': 44,\n",
       " u'DAVIDsTEA': 45,\n",
       " u'Dyson': 46,\n",
       " u'ECCO': 47,\n",
       " u'Eddie Bauer': 48,\n",
       " u'Express': 49,\n",
       " u'Eyebrow Plus': 50,\n",
       " u'Finish Line': 51,\n",
       " u'Fire of Brazil': 52,\n",
       " u'Forever Flawless': 53,\n",
       " u'Forever Flawless ': 54,\n",
       " u'Fossil': 55,\n",
       " u\"Francesca's Collection \": 56,\n",
       " u'GNC': 57,\n",
       " u'GUESS ': 58,\n",
       " u'Ghirardelli Ice Cream and Chocolate Shop ': 59,\n",
       " u'Go! Toys and Games': 60,\n",
       " u'Godiva Chocolatier': 61,\n",
       " u'H&M': 62,\n",
       " u'H&M Man': 63,\n",
       " u'Haagen Dazs': 64,\n",
       " u'Hallmark': 65,\n",
       " u'Hollister Co.': 66,\n",
       " u'House of Hoops by Foot Locker': 67,\n",
       " u'J.Crew': 68,\n",
       " u'Jamba Juice': 69,\n",
       " u'Janie And Jack': 70,\n",
       " u'Karen Millen': 71,\n",
       " u'Kate Spade New York': 72,\n",
       " u'Kay Jewelers': 73,\n",
       " u'Kichi Grill': 74,\n",
       " u\"Kiehl's\": 75,\n",
       " u\"L'Occitane en Provence\": 76,\n",
       " u'LEGO': 77,\n",
       " u'Lady Foot Locker': 78,\n",
       " u'Lids': 79,\n",
       " u'Lobster Me': 80,\n",
       " u'Loving Hut Vegan Cuisine ': 81,\n",
       " u'Lucky Brand Jeans': 82,\n",
       " u'M.Y. China': 83,\n",
       " u'Madewell': 84,\n",
       " u'Marbles: The Brain Store': 85,\n",
       " u'Max & Co.': 86,\n",
       " u'Michael Kors': 87,\n",
       " u'Michael Kors Men': 88,\n",
       " u'Microsoft': 89,\n",
       " u'Mrs. Fields': 90,\n",
       " u'NYS Collection': 91,\n",
       " u'New Era': 92,\n",
       " u'Nordstrom': 93,\n",
       " u'Nordstrom E-Bar': 94,\n",
       " u'OAK+FORT': 95,\n",
       " u'Onassis': 96,\n",
       " u'Optica': 97,\n",
       " u'Origins': 98,\n",
       " u'PacSun': 99,\n",
       " u'Panda Express': 100,\n",
       " u'Pandora': 101,\n",
       " u'Papyrus': 102,\n",
       " u'Pasta Moto': 103,\n",
       " u\"Peet's Coffee & Tea\": 104,\n",
       " u'Penhaligon\\xef\\xbf\\xbd\\xdb\\xaas': 105,\n",
       " u'Perfumania': 106,\n",
       " u'Pressed Juicery': 107,\n",
       " u'ProActiv Solutions ': 108,\n",
       " u'RED Valentino': 109,\n",
       " u'Razer': 110,\n",
       " u'Rolex': 111,\n",
       " u'SF Sports': 112,\n",
       " u'Samsonite': 113,\n",
       " u'San Francisco Luggage Co.': 114,\n",
       " u'San Francisco Soup Company': 115,\n",
       " u'Sarku Japan': 116,\n",
       " u'Shoe Palace ': 117,\n",
       " u'Shoe Wiz': 118,\n",
       " u'Solstice': 119,\n",
       " u'Sorabol Korean BBQ & Asian Noodles': 120,\n",
       " u'Starbucks': 121,\n",
       " u'Steve Madden': 122,\n",
       " u'Studio Manhattan': 123,\n",
       " u'Sunglass Hut': 124,\n",
       " u'Sunglass Hut ': 125,\n",
       " u'Superdry ': 126,\n",
       " u'Sur La Table': 127,\n",
       " u'Swarovski': 128,\n",
       " u'Swatch': 129,\n",
       " u'T-Mobile': 130,\n",
       " u'TAP 415': 131,\n",
       " u'Teavana': 132,\n",
       " u'The Art of Shaving': 133,\n",
       " u'The Body Shop': 134,\n",
       " u'The Walking Company': 135,\n",
       " u'Tiffany & Co.': 136,\n",
       " u'Timberland': 137,\n",
       " u'Tory Burch ': 138,\n",
       " u'Tourneau': 139,\n",
       " u'True Religion Jeans': 140,\n",
       " u'Tumi': 141,\n",
       " u'Vans': 142,\n",
       " u'Vera Bradley': 143,\n",
       " u\"Victoria's Secret\": 144,\n",
       " u'Warriors Team Store': 145,\n",
       " u\"Wetzel's Pretzels\": 146,\n",
       " u'Yoppi Frozen Yogurt ': 147,\n",
       " u'Zara': 148,\n",
       " u'abercrombie kids': 149,\n",
       " u'bareMinerals': 150,\n",
       " u'bebe': 151,\n",
       " u'iPlay n Talk': 152,\n",
       " u'lululemon athletica': 153}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "store_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "inv_class_mapping = {v: k for k, v in store_mapping.items()}\n",
    "pinginfo['Store_Name'] = pinginfo['Store_Index'].map(inv_class_mapping)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Floor_Index</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Store_Index</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">latitude</th>\n",
       "      <th colspan=\"8\" halign=\"left\">longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Store_Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"22\" valign=\"top\">Shopper_1</th>\n",
       "      <th>49ers Team Store</th>\n",
       "      <td>7.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.981382</td>\n",
       "      <td>35.399507</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-112.735348</td>\n",
       "      <td>1.259467</td>\n",
       "      <td>-114.736382</td>\n",
       "      <td>-113.327500</td>\n",
       "      <td>-112.991175</td>\n",
       "      <td>-111.742864</td>\n",
       "      <td>-111.279150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOSS</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.539867</td>\n",
       "      <td>35.539867</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>-115.187304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bath &amp; Body Works</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>-115.588398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bespoke Events</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.733657</td>\n",
       "      <td>35.756717</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-115.759376</td>\n",
       "      <td>0.241615</td>\n",
       "      <td>-115.930223</td>\n",
       "      <td>-115.844800</td>\n",
       "      <td>-115.759376</td>\n",
       "      <td>-115.673952</td>\n",
       "      <td>-115.588529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bloomingdale's</th>\n",
       "      <td>64.0</td>\n",
       "      <td>1.140625</td>\n",
       "      <td>1.125000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33.585830</td>\n",
       "      <td>35.664494</td>\n",
       "      <td>64.0</td>\n",
       "      <td>-100.041579</td>\n",
       "      <td>16.522958</td>\n",
       "      <td>-115.588692</td>\n",
       "      <td>-108.806248</td>\n",
       "      <td>-104.920363</td>\n",
       "      <td>-101.542209</td>\n",
       "      <td>-51.038836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bristol Farms</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.240591</td>\n",
       "      <td>35.240591</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-114.224934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-114.224934</td>\n",
       "      <td>-114.224934</td>\n",
       "      <td>-114.224934</td>\n",
       "      <td>-114.224934</td>\n",
       "      <td>-114.224934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Club Monaco Women</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.756492</td>\n",
       "      <td>34.877600</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-112.158942</td>\n",
       "      <td>0.856980</td>\n",
       "      <td>-112.991140</td>\n",
       "      <td>-112.598832</td>\n",
       "      <td>-112.206523</td>\n",
       "      <td>-111.742843</td>\n",
       "      <td>-111.279163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cotton On</th>\n",
       "      <td>14.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784076</td>\n",
       "      <td>37.784150</td>\n",
       "      <td>14.0</td>\n",
       "      <td>-122.404261</td>\n",
       "      <td>0.007147</td>\n",
       "      <td>-122.407213</td>\n",
       "      <td>-122.407141</td>\n",
       "      <td>-122.407099</td>\n",
       "      <td>-122.406918</td>\n",
       "      <td>-122.386801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H&amp;M</th>\n",
       "      <td>9.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.399525</td>\n",
       "      <td>35.539812</td>\n",
       "      <td>9.0</td>\n",
       "      <td>-114.049064</td>\n",
       "      <td>0.778325</td>\n",
       "      <td>-115.187564</td>\n",
       "      <td>-114.736331</td>\n",
       "      <td>-114.224980</td>\n",
       "      <td>-113.663578</td>\n",
       "      <td>-112.991140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H&amp;M Man</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.692423</td>\n",
       "      <td>35.776100</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-115.482491</td>\n",
       "      <td>0.360678</td>\n",
       "      <td>-115.947265</td>\n",
       "      <td>-115.678128</td>\n",
       "      <td>-115.397557</td>\n",
       "      <td>-115.201920</td>\n",
       "      <td>-115.187586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Haagen Dazs</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.659368</td>\n",
       "      <td>35.664467</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-115.579555</td>\n",
       "      <td>0.012921</td>\n",
       "      <td>-115.588692</td>\n",
       "      <td>-115.584123</td>\n",
       "      <td>-115.579555</td>\n",
       "      <td>-115.574987</td>\n",
       "      <td>-115.570418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>House of Hoops by Foot Locker</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.635392</td>\n",
       "      <td>34.635392</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-112.206476</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-112.206476</td>\n",
       "      <td>-112.206476</td>\n",
       "      <td>-112.206476</td>\n",
       "      <td>-112.206476</td>\n",
       "      <td>-112.206476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kay Jewelers</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.716263</td>\n",
       "      <td>37.716263</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-122.187249</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-122.187249</td>\n",
       "      <td>-122.187249</td>\n",
       "      <td>-122.187249</td>\n",
       "      <td>-122.187249</td>\n",
       "      <td>-122.187249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PacSun</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.481179</td>\n",
       "      <td>35.539799</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-114.893503</td>\n",
       "      <td>0.254887</td>\n",
       "      <td>-115.187584</td>\n",
       "      <td>-114.972141</td>\n",
       "      <td>-114.756697</td>\n",
       "      <td>-114.746463</td>\n",
       "      <td>-114.736228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProActiv Solutions</th>\n",
       "      <td>30.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784109</td>\n",
       "      <td>37.784263</td>\n",
       "      <td>30.0</td>\n",
       "      <td>-122.402133</td>\n",
       "      <td>0.015500</td>\n",
       "      <td>-122.407302</td>\n",
       "      <td>-122.407162</td>\n",
       "      <td>-122.406884</td>\n",
       "      <td>-122.406457</td>\n",
       "      <td>-122.341798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RED Valentino</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.716259</td>\n",
       "      <td>37.716259</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-122.187237</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-122.187237</td>\n",
       "      <td>-122.187237</td>\n",
       "      <td>-122.187237</td>\n",
       "      <td>-122.187237</td>\n",
       "      <td>-122.187237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sarku Japan</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.349156</td>\n",
       "      <td>34.349161</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-111.279068</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>-111.279173</td>\n",
       "      <td>-111.279120</td>\n",
       "      <td>-111.279068</td>\n",
       "      <td>-111.279016</td>\n",
       "      <td>-111.278963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Solstice</th>\n",
       "      <td>17.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>37.784121</td>\n",
       "      <td>17.0</td>\n",
       "      <td>-122.404881</td>\n",
       "      <td>0.006154</td>\n",
       "      <td>-122.407207</td>\n",
       "      <td>-122.407150</td>\n",
       "      <td>-122.407085</td>\n",
       "      <td>-122.407039</td>\n",
       "      <td>-122.388008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swarovski</th>\n",
       "      <td>14.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784095</td>\n",
       "      <td>37.784128</td>\n",
       "      <td>14.0</td>\n",
       "      <td>-122.403778</td>\n",
       "      <td>0.008425</td>\n",
       "      <td>-122.407198</td>\n",
       "      <td>-122.407127</td>\n",
       "      <td>-122.407086</td>\n",
       "      <td>-122.406999</td>\n",
       "      <td>-122.383891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAP 415</th>\n",
       "      <td>8.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784114</td>\n",
       "      <td>37.784158</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-122.393541</td>\n",
       "      <td>0.028797</td>\n",
       "      <td>-122.407049</td>\n",
       "      <td>-122.406821</td>\n",
       "      <td>-122.406719</td>\n",
       "      <td>-122.400416</td>\n",
       "      <td>-122.325626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Walking Company</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.851335</td>\n",
       "      <td>35.876436</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-116.109035</td>\n",
       "      <td>0.228386</td>\n",
       "      <td>-116.270529</td>\n",
       "      <td>-116.189782</td>\n",
       "      <td>-116.109035</td>\n",
       "      <td>-116.028289</td>\n",
       "      <td>-115.947542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abercrombie kids</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.349175</td>\n",
       "      <td>34.349176</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-111.279110</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>-111.279129</td>\n",
       "      <td>-111.279120</td>\n",
       "      <td>-111.279110</td>\n",
       "      <td>-111.279101</td>\n",
       "      <td>-111.279091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">Shopper_10</th>\n",
       "      <th>49ers Team Store</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.153643</td>\n",
       "      <td>35.375902</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-113.165187</td>\n",
       "      <td>2.036779</td>\n",
       "      <td>-114.605407</td>\n",
       "      <td>-113.885297</td>\n",
       "      <td>-113.165187</td>\n",
       "      <td>-112.445077</td>\n",
       "      <td>-111.724967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auntie Anne's Pretzels</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.239922</td>\n",
       "      <td>37.239922</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-120.642571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-120.642571</td>\n",
       "      <td>-120.642571</td>\n",
       "      <td>-120.642571</td>\n",
       "      <td>-120.642571</td>\n",
       "      <td>-120.642571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bespoke Events</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.127255</td>\n",
       "      <td>35.135766</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-113.271800</td>\n",
       "      <td>0.972777</td>\n",
       "      <td>-113.827394</td>\n",
       "      <td>-113.799833</td>\n",
       "      <td>-113.721387</td>\n",
       "      <td>-113.193354</td>\n",
       "      <td>-111.817032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bloomingdale's</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.75</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.184860</td>\n",
       "      <td>35.203609</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-112.314990</td>\n",
       "      <td>3.151391</td>\n",
       "      <td>-114.047399</td>\n",
       "      <td>-113.986064</td>\n",
       "      <td>-113.808873</td>\n",
       "      <td>-112.137800</td>\n",
       "      <td>-107.594816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brighton Collectibles</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.031481</td>\n",
       "      <td>37.039586</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-119.646636</td>\n",
       "      <td>0.323971</td>\n",
       "      <td>-119.993700</td>\n",
       "      <td>-119.967906</td>\n",
       "      <td>-119.599567</td>\n",
       "      <td>-119.357911</td>\n",
       "      <td>-119.314095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bristol Farms</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.665839</td>\n",
       "      <td>36.665839</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-118.782953</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-118.782953</td>\n",
       "      <td>-118.782953</td>\n",
       "      <td>-118.782953</td>\n",
       "      <td>-118.782953</td>\n",
       "      <td>-118.782953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Camper</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.874803</td>\n",
       "      <td>37.067269</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-118.836670</td>\n",
       "      <td>1.763762</td>\n",
       "      <td>-120.083838</td>\n",
       "      <td>-119.460254</td>\n",
       "      <td>-118.836670</td>\n",
       "      <td>-118.213086</td>\n",
       "      <td>-117.589502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chipotle</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.100234</td>\n",
       "      <td>34.100234</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-110.472823</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-110.472823</td>\n",
       "      <td>-110.472823</td>\n",
       "      <td>-110.472823</td>\n",
       "      <td>-110.472823</td>\n",
       "      <td>-110.472823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Shopper_98</th>\n",
       "      <th>Swarovski</th>\n",
       "      <td>49.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784067</td>\n",
       "      <td>37.784564</td>\n",
       "      <td>49.0</td>\n",
       "      <td>-122.407030</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>-122.407262</td>\n",
       "      <td>-122.407113</td>\n",
       "      <td>-122.407053</td>\n",
       "      <td>-122.407008</td>\n",
       "      <td>-122.406374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAP 415</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784223</td>\n",
       "      <td>37.784223</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-122.406595</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-122.406595</td>\n",
       "      <td>-122.406595</td>\n",
       "      <td>-122.406595</td>\n",
       "      <td>-122.406595</td>\n",
       "      <td>-122.406595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"28\" valign=\"top\">Shopper_99</th>\n",
       "      <th>49ers Team Store</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.331742</td>\n",
       "      <td>35.422896</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-113.455975</td>\n",
       "      <td>1.811458</td>\n",
       "      <td>-114.756099</td>\n",
       "      <td>-114.490520</td>\n",
       "      <td>-114.224940</td>\n",
       "      <td>-112.805913</td>\n",
       "      <td>-111.386886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOSS</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.399781</td>\n",
       "      <td>35.399860</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-114.736085</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>-114.736313</td>\n",
       "      <td>-114.736226</td>\n",
       "      <td>-114.736139</td>\n",
       "      <td>-114.735970</td>\n",
       "      <td>-114.735801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bath &amp; Body Works</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.550032</td>\n",
       "      <td>36.550032</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-118.408601</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-118.408601</td>\n",
       "      <td>-118.408601</td>\n",
       "      <td>-118.408601</td>\n",
       "      <td>-118.408601</td>\n",
       "      <td>-118.408601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bespoke Events</th>\n",
       "      <td>9.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.153084</td>\n",
       "      <td>35.540035</td>\n",
       "      <td>9.0</td>\n",
       "      <td>-113.225671</td>\n",
       "      <td>1.222782</td>\n",
       "      <td>-115.187127</td>\n",
       "      <td>-113.942530</td>\n",
       "      <td>-112.966029</td>\n",
       "      <td>-112.965748</td>\n",
       "      <td>-110.960084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bloomingdale's</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33.987472</td>\n",
       "      <td>35.664664</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-110.750704</td>\n",
       "      <td>2.750469</td>\n",
       "      <td>-115.588414</td>\n",
       "      <td>-110.149677</td>\n",
       "      <td>-109.740750</td>\n",
       "      <td>-109.504599</td>\n",
       "      <td>-108.770082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brighton Collectibles</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.656019</td>\n",
       "      <td>36.711757</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-118.634512</td>\n",
       "      <td>0.272048</td>\n",
       "      <td>-118.932571</td>\n",
       "      <td>-118.751982</td>\n",
       "      <td>-118.571393</td>\n",
       "      <td>-118.485483</td>\n",
       "      <td>-118.399573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bristol Farms</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.706976</td>\n",
       "      <td>36.711092</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-118.903739</td>\n",
       "      <td>0.037729</td>\n",
       "      <td>-118.930418</td>\n",
       "      <td>-118.917079</td>\n",
       "      <td>-118.903739</td>\n",
       "      <td>-118.890400</td>\n",
       "      <td>-118.877061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Camper</th>\n",
       "      <td>5.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.716910</td>\n",
       "      <td>36.731214</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-118.872381</td>\n",
       "      <td>0.106339</td>\n",
       "      <td>-118.996073</td>\n",
       "      <td>-118.949556</td>\n",
       "      <td>-118.870026</td>\n",
       "      <td>-118.819317</td>\n",
       "      <td>-118.726933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Club Monaco Women</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.759970</td>\n",
       "      <td>34.878280</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-112.330853</td>\n",
       "      <td>0.632001</td>\n",
       "      <td>-112.992201</td>\n",
       "      <td>-112.629783</td>\n",
       "      <td>-112.267364</td>\n",
       "      <td>-112.000178</td>\n",
       "      <td>-111.732993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cotton On</th>\n",
       "      <td>26.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784017</td>\n",
       "      <td>37.784615</td>\n",
       "      <td>26.0</td>\n",
       "      <td>-122.319116</td>\n",
       "      <td>0.208842</td>\n",
       "      <td>-122.407265</td>\n",
       "      <td>-122.407103</td>\n",
       "      <td>-122.407086</td>\n",
       "      <td>-122.406403</td>\n",
       "      <td>-121.798387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H&amp;M</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.539964</td>\n",
       "      <td>35.539964</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-115.187357</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-115.187357</td>\n",
       "      <td>-115.187357</td>\n",
       "      <td>-115.187357</td>\n",
       "      <td>-115.187357</td>\n",
       "      <td>-115.187357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H&amp;M Man</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.776313</td>\n",
       "      <td>35.776410</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-115.827529</td>\n",
       "      <td>0.207177</td>\n",
       "      <td>-115.947290</td>\n",
       "      <td>-115.947143</td>\n",
       "      <td>-115.946996</td>\n",
       "      <td>-115.767649</td>\n",
       "      <td>-115.588303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Haagen Dazs</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.876756</td>\n",
       "      <td>35.876831</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-116.042914</td>\n",
       "      <td>0.393422</td>\n",
       "      <td>-116.270122</td>\n",
       "      <td>-116.270056</td>\n",
       "      <td>-116.269989</td>\n",
       "      <td>-115.929309</td>\n",
       "      <td>-115.588629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Janie And Jack</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35.919820</td>\n",
       "      <td>35.967674</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-116.254680</td>\n",
       "      <td>0.434915</td>\n",
       "      <td>-116.562212</td>\n",
       "      <td>-116.408446</td>\n",
       "      <td>-116.254680</td>\n",
       "      <td>-116.100914</td>\n",
       "      <td>-115.947148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kay Jewelers</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.596348</td>\n",
       "      <td>37.596348</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-121.799024</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-121.799024</td>\n",
       "      <td>-121.799024</td>\n",
       "      <td>-121.799024</td>\n",
       "      <td>-121.799024</td>\n",
       "      <td>-121.799024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L'Occitane en Provence</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.226282</td>\n",
       "      <td>36.257929</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-117.200727</td>\n",
       "      <td>0.350654</td>\n",
       "      <td>-117.496074</td>\n",
       "      <td>-117.394497</td>\n",
       "      <td>-117.292919</td>\n",
       "      <td>-117.053053</td>\n",
       "      <td>-116.813187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lady Foot Locker</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.006933</td>\n",
       "      <td>36.125315</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-116.543429</td>\n",
       "      <td>0.377590</td>\n",
       "      <td>-117.070787</td>\n",
       "      <td>-116.689521</td>\n",
       "      <td>-116.416444</td>\n",
       "      <td>-116.270353</td>\n",
       "      <td>-116.270043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lids</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.194433</td>\n",
       "      <td>36.194433</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-117.293123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-117.293123</td>\n",
       "      <td>-117.293123</td>\n",
       "      <td>-117.293123</td>\n",
       "      <td>-117.293123</td>\n",
       "      <td>-117.293123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M.Y. China</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.049928</td>\n",
       "      <td>36.049928</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-116.828233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-116.828233</td>\n",
       "      <td>-116.828233</td>\n",
       "      <td>-116.828233</td>\n",
       "      <td>-116.828233</td>\n",
       "      <td>-116.828233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProActiv Solutions</th>\n",
       "      <td>51.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784212</td>\n",
       "      <td>37.785072</td>\n",
       "      <td>51.0</td>\n",
       "      <td>-122.381705</td>\n",
       "      <td>0.100355</td>\n",
       "      <td>-122.409203</td>\n",
       "      <td>-122.407054</td>\n",
       "      <td>-122.407016</td>\n",
       "      <td>-122.406637</td>\n",
       "      <td>-121.799954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sarku Japan</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.401416</td>\n",
       "      <td>34.401416</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-111.466124</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-111.466124</td>\n",
       "      <td>-111.466124</td>\n",
       "      <td>-111.466124</td>\n",
       "      <td>-111.466124</td>\n",
       "      <td>-111.466124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Solstice</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784019</td>\n",
       "      <td>37.784026</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-122.400953</td>\n",
       "      <td>0.011070</td>\n",
       "      <td>-122.407110</td>\n",
       "      <td>-122.407097</td>\n",
       "      <td>-122.407072</td>\n",
       "      <td>-122.399447</td>\n",
       "      <td>-122.379400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sunglass Hut</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.125510</td>\n",
       "      <td>36.125510</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-117.070583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-117.070583</td>\n",
       "      <td>-117.070583</td>\n",
       "      <td>-117.070583</td>\n",
       "      <td>-117.070583</td>\n",
       "      <td>-117.070583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swarovski</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784346</td>\n",
       "      <td>37.785318</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-122.401428</td>\n",
       "      <td>0.007984</td>\n",
       "      <td>-122.409686</td>\n",
       "      <td>-122.406787</td>\n",
       "      <td>-122.406541</td>\n",
       "      <td>-122.395289</td>\n",
       "      <td>-122.379390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swatch</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.582725</td>\n",
       "      <td>37.583199</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-121.753377</td>\n",
       "      <td>0.004345</td>\n",
       "      <td>-121.756450</td>\n",
       "      <td>-121.754913</td>\n",
       "      <td>-121.753377</td>\n",
       "      <td>-121.751841</td>\n",
       "      <td>-121.750305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAP 415</th>\n",
       "      <td>18.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37.784389</td>\n",
       "      <td>37.784623</td>\n",
       "      <td>18.0</td>\n",
       "      <td>-122.307073</td>\n",
       "      <td>0.360206</td>\n",
       "      <td>-122.406745</td>\n",
       "      <td>-122.406516</td>\n",
       "      <td>-122.391547</td>\n",
       "      <td>-122.380519</td>\n",
       "      <td>-120.865104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Art of Shaving</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36.336388</td>\n",
       "      <td>36.336577</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-117.715760</td>\n",
       "      <td>0.001732</td>\n",
       "      <td>-117.716985</td>\n",
       "      <td>-117.716373</td>\n",
       "      <td>-117.715760</td>\n",
       "      <td>-117.715148</td>\n",
       "      <td>-117.714535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abercrombie kids</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34.218488</td>\n",
       "      <td>34.218488</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-110.902210</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-110.902210</td>\n",
       "      <td>-110.902210</td>\n",
       "      <td>-110.902210</td>\n",
       "      <td>-110.902210</td>\n",
       "      <td>-110.902210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10121 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Floor_Index                           \\\n",
       "                                               count      mean       std  min   \n",
       "Shopper_ID Store_Name                                                           \n",
       "Shopper_1  49ers Team Store                      7.0  2.000000  0.000000  2.0   \n",
       "           BOSS                                  1.0  1.000000       NaN  1.0   \n",
       "           Bath & Body Works                     1.0  3.000000       NaN  3.0   \n",
       "           Bespoke Events                        2.0  4.000000  0.000000  4.0   \n",
       "           Bloomingdale's                       64.0  1.140625  1.125000  0.0   \n",
       "           Bristol Farms                         1.0  0.000000       NaN  0.0   \n",
       "           Club Monaco Women                     3.0  1.000000  0.000000  1.0   \n",
       "           Cotton On                            14.0  2.000000  0.000000  2.0   \n",
       "           H&M                                   9.0  3.000000  0.000000  3.0   \n",
       "           H&M Man                               4.0  2.000000  0.000000  2.0   \n",
       "           Haagen Dazs                           2.0  0.000000  0.000000  0.0   \n",
       "           House of Hoops by Foot Locker         1.0  3.000000       NaN  3.0   \n",
       "           Kay Jewelers                          1.0  3.000000       NaN  3.0   \n",
       "           PacSun                                3.0  0.000000  0.000000  0.0   \n",
       "           ProActiv Solutions                   30.0  0.000000  0.000000  0.0   \n",
       "           RED Valentino                         1.0  1.000000       NaN  1.0   \n",
       "           Sarku Japan                           2.0  0.000000  0.000000  0.0   \n",
       "           Solstice                             17.0  3.000000  0.000000  3.0   \n",
       "           Swarovski                            14.0  1.000000  0.000000  1.0   \n",
       "           TAP 415                               8.0  4.000000  0.000000  4.0   \n",
       "           The Walking Company                   2.0  3.000000  0.000000  3.0   \n",
       "           abercrombie kids                      2.0  3.000000  0.000000  3.0   \n",
       "Shopper_10 49ers Team Store                      2.0  2.000000  0.000000  2.0   \n",
       "           Auntie Anne's Pretzels                1.0  2.000000       NaN  2.0   \n",
       "           Bespoke Events                        4.0  4.000000  0.000000  4.0   \n",
       "           Bloomingdale's                        4.0  1.750000  1.500000  1.0   \n",
       "           Brighton Collectibles                 5.0  1.000000  0.000000  1.0   \n",
       "           Bristol Farms                         1.0  0.000000       NaN  0.0   \n",
       "           Camper                                2.0  2.000000  0.000000  2.0   \n",
       "           Chipotle                              1.0  0.000000       NaN  0.0   \n",
       "...                                              ...       ...       ...  ...   \n",
       "Shopper_98 Swarovski                            49.0  1.000000  0.000000  1.0   \n",
       "           TAP 415                               1.0  4.000000       NaN  4.0   \n",
       "Shopper_99 49ers Team Store                      3.0  2.000000  0.000000  2.0   \n",
       "           BOSS                                  3.0  1.000000  0.000000  1.0   \n",
       "           Bath & Body Works                     1.0  3.000000       NaN  3.0   \n",
       "           Bespoke Events                        9.0  4.000000  0.000000  4.0   \n",
       "           Bloomingdale's                        5.0  3.000000  1.414214  1.0   \n",
       "           Brighton Collectibles                 3.0  1.000000  0.000000  1.0   \n",
       "           Bristol Farms                         2.0  0.000000  0.000000  0.0   \n",
       "           Camper                                5.0  2.000000  0.000000  2.0   \n",
       "           Club Monaco Women                     3.0  1.000000  0.000000  1.0   \n",
       "           Cotton On                            26.0  2.000000  0.000000  2.0   \n",
       "           H&M                                   1.0  3.000000       NaN  3.0   \n",
       "           H&M Man                               3.0  2.000000  0.000000  2.0   \n",
       "           Haagen Dazs                           3.0  0.000000  0.000000  0.0   \n",
       "           Janie And Jack                        2.0  1.000000  0.000000  1.0   \n",
       "           Kay Jewelers                          1.0  3.000000       NaN  3.0   \n",
       "           L'Occitane en Provence                3.0  1.000000  0.000000  1.0   \n",
       "           Lady Foot Locker                      4.0  2.000000  0.000000  2.0   \n",
       "           Lids                                  1.0  3.000000       NaN  3.0   \n",
       "           M.Y. China                            1.0  4.000000       NaN  4.0   \n",
       "           ProActiv Solutions                   51.0  0.000000  0.000000  0.0   \n",
       "           Sarku Japan                           1.0  0.000000       NaN  0.0   \n",
       "           Solstice                              7.0  3.000000  0.000000  3.0   \n",
       "           Sunglass Hut                          1.0  0.000000       NaN  0.0   \n",
       "           Swarovski                            28.0  1.000000  0.000000  1.0   \n",
       "           Swatch                                2.0  1.000000  0.000000  1.0   \n",
       "           TAP 415                              18.0  4.000000  0.000000  4.0   \n",
       "           The Art of Shaving                    2.0  1.000000  0.000000  1.0   \n",
       "           abercrombie kids                      1.0  3.000000       NaN  3.0   \n",
       "\n",
       "                                                              Store_Index  \\\n",
       "                                          25%  50%   75%  max       count   \n",
       "Shopper_ID Store_Name                                                       \n",
       "Shopper_1  49ers Team Store               2.0  2.0  2.00  2.0         7.0   \n",
       "           BOSS                           1.0  1.0  1.00  1.0         1.0   \n",
       "           Bath & Body Works              3.0  3.0  3.00  3.0         1.0   \n",
       "           Bespoke Events                 4.0  4.0  4.00  4.0         2.0   \n",
       "           Bloomingdale's                 0.0  1.0  2.00  4.0        64.0   \n",
       "           Bristol Farms                  0.0  0.0  0.00  0.0         1.0   \n",
       "           Club Monaco Women              1.0  1.0  1.00  1.0         3.0   \n",
       "           Cotton On                      2.0  2.0  2.00  2.0        14.0   \n",
       "           H&M                            3.0  3.0  3.00  3.0         9.0   \n",
       "           H&M Man                        2.0  2.0  2.00  2.0         4.0   \n",
       "           Haagen Dazs                    0.0  0.0  0.00  0.0         2.0   \n",
       "           House of Hoops by Foot Locker  3.0  3.0  3.00  3.0         1.0   \n",
       "           Kay Jewelers                   3.0  3.0  3.00  3.0         1.0   \n",
       "           PacSun                         0.0  0.0  0.00  0.0         3.0   \n",
       "           ProActiv Solutions             0.0  0.0  0.00  0.0        30.0   \n",
       "           RED Valentino                  1.0  1.0  1.00  1.0         1.0   \n",
       "           Sarku Japan                    0.0  0.0  0.00  0.0         2.0   \n",
       "           Solstice                       3.0  3.0  3.00  3.0        17.0   \n",
       "           Swarovski                      1.0  1.0  1.00  1.0        14.0   \n",
       "           TAP 415                        4.0  4.0  4.00  4.0         8.0   \n",
       "           The Walking Company            3.0  3.0  3.00  3.0         2.0   \n",
       "           abercrombie kids               3.0  3.0  3.00  3.0         2.0   \n",
       "Shopper_10 49ers Team Store               2.0  2.0  2.00  2.0         2.0   \n",
       "           Auntie Anne's Pretzels         2.0  2.0  2.00  2.0         1.0   \n",
       "           Bespoke Events                 4.0  4.0  4.00  4.0         4.0   \n",
       "           Bloomingdale's                 1.0  1.0  1.75  4.0         4.0   \n",
       "           Brighton Collectibles          1.0  1.0  1.00  1.0         5.0   \n",
       "           Bristol Farms                  0.0  0.0  0.00  0.0         1.0   \n",
       "           Camper                         2.0  2.0  2.00  2.0         2.0   \n",
       "           Chipotle                       0.0  0.0  0.00  0.0         1.0   \n",
       "...                                       ...  ...   ...  ...         ...   \n",
       "Shopper_98 Swarovski                      1.0  1.0  1.00  1.0        49.0   \n",
       "           TAP 415                        4.0  4.0  4.00  4.0         1.0   \n",
       "Shopper_99 49ers Team Store               2.0  2.0  2.00  2.0         3.0   \n",
       "           BOSS                           1.0  1.0  1.00  1.0         3.0   \n",
       "           Bath & Body Works              3.0  3.0  3.00  3.0         1.0   \n",
       "           Bespoke Events                 4.0  4.0  4.00  4.0         9.0   \n",
       "           Bloomingdale's                 2.0  4.0  4.00  4.0         5.0   \n",
       "           Brighton Collectibles          1.0  1.0  1.00  1.0         3.0   \n",
       "           Bristol Farms                  0.0  0.0  0.00  0.0         2.0   \n",
       "           Camper                         2.0  2.0  2.00  2.0         5.0   \n",
       "           Club Monaco Women              1.0  1.0  1.00  1.0         3.0   \n",
       "           Cotton On                      2.0  2.0  2.00  2.0        26.0   \n",
       "           H&M                            3.0  3.0  3.00  3.0         1.0   \n",
       "           H&M Man                        2.0  2.0  2.00  2.0         3.0   \n",
       "           Haagen Dazs                    0.0  0.0  0.00  0.0         3.0   \n",
       "           Janie And Jack                 1.0  1.0  1.00  1.0         2.0   \n",
       "           Kay Jewelers                   3.0  3.0  3.00  3.0         1.0   \n",
       "           L'Occitane en Provence         1.0  1.0  1.00  1.0         3.0   \n",
       "           Lady Foot Locker               2.0  2.0  2.00  2.0         4.0   \n",
       "           Lids                           3.0  3.0  3.00  3.0         1.0   \n",
       "           M.Y. China                     4.0  4.0  4.00  4.0         1.0   \n",
       "           ProActiv Solutions             0.0  0.0  0.00  0.0        51.0   \n",
       "           Sarku Japan                    0.0  0.0  0.00  0.0         1.0   \n",
       "           Solstice                       3.0  3.0  3.00  3.0         7.0   \n",
       "           Sunglass Hut                   0.0  0.0  0.00  0.0         1.0   \n",
       "           Swarovski                      1.0  1.0  1.00  1.0        28.0   \n",
       "           Swatch                         1.0  1.0  1.00  1.0         2.0   \n",
       "           TAP 415                        4.0  4.0  4.00  4.0        18.0   \n",
       "           The Art of Shaving             1.0  1.0  1.00  1.0         2.0   \n",
       "           abercrombie kids               3.0  3.0  3.00  3.0         1.0   \n",
       "\n",
       "                                                    ...       latitude  \\\n",
       "                                           mean     ...            75%   \n",
       "Shopper_ID Store_Name                               ...                  \n",
       "Shopper_1  49ers Team Store                 0.0     ...      34.981382   \n",
       "           BOSS                            14.0     ...      35.539867   \n",
       "           Bath & Body Works               16.0     ...      35.664542   \n",
       "           Bespoke Events                  19.0     ...      35.733657   \n",
       "           Bloomingdale's                  20.0     ...      33.585830   \n",
       "           Bristol Farms                   23.0     ...      35.240591   \n",
       "           Club Monaco Women               39.0     ...      34.756492   \n",
       "           Cotton On                       43.0     ...      37.784076   \n",
       "           H&M                             62.0     ...      35.399525   \n",
       "           H&M Man                         63.0     ...      35.692423   \n",
       "           Haagen Dazs                     64.0     ...      35.659368   \n",
       "           House of Hoops by Foot Locker   67.0     ...      34.635392   \n",
       "           Kay Jewelers                    73.0     ...      37.716263   \n",
       "           PacSun                          99.0     ...      35.481179   \n",
       "           ProActiv Solutions             108.0     ...      37.784109   \n",
       "           RED Valentino                  109.0     ...      37.716259   \n",
       "           Sarku Japan                    116.0     ...      34.349156   \n",
       "           Solstice                       119.0     ...      37.784077   \n",
       "           Swarovski                      128.0     ...      37.784095   \n",
       "           TAP 415                        131.0     ...      37.784114   \n",
       "           The Walking Company            135.0     ...      35.851335   \n",
       "           abercrombie kids               149.0     ...      34.349175   \n",
       "Shopper_10 49ers Team Store                 0.0     ...      35.153643   \n",
       "           Auntie Anne's Pretzels          11.0     ...      37.239922   \n",
       "           Bespoke Events                  19.0     ...      35.127255   \n",
       "           Bloomingdale's                  20.0     ...      35.184860   \n",
       "           Brighton Collectibles           22.0     ...      37.031481   \n",
       "           Bristol Farms                   23.0     ...      36.665839   \n",
       "           Camper                          31.0     ...      36.874803   \n",
       "           Chipotle                        35.0     ...      34.100234   \n",
       "...                                         ...     ...            ...   \n",
       "Shopper_98 Swarovski                      128.0     ...      37.784067   \n",
       "           TAP 415                        131.0     ...      37.784223   \n",
       "Shopper_99 49ers Team Store                 0.0     ...      35.331742   \n",
       "           BOSS                            14.0     ...      35.399781   \n",
       "           Bath & Body Works               16.0     ...      36.550032   \n",
       "           Bespoke Events                  19.0     ...      35.153084   \n",
       "           Bloomingdale's                  20.0     ...      33.987472   \n",
       "           Brighton Collectibles           22.0     ...      36.656019   \n",
       "           Bristol Farms                   23.0     ...      36.706976   \n",
       "           Camper                          31.0     ...      36.716910   \n",
       "           Club Monaco Women               39.0     ...      34.759970   \n",
       "           Cotton On                       43.0     ...      37.784017   \n",
       "           H&M                             62.0     ...      35.539964   \n",
       "           H&M Man                         63.0     ...      35.776313   \n",
       "           Haagen Dazs                     64.0     ...      35.876756   \n",
       "           Janie And Jack                  70.0     ...      35.919820   \n",
       "           Kay Jewelers                    73.0     ...      37.596348   \n",
       "           L'Occitane en Provence          76.0     ...      36.226282   \n",
       "           Lady Foot Locker                78.0     ...      36.006933   \n",
       "           Lids                            79.0     ...      36.194433   \n",
       "           M.Y. China                      83.0     ...      36.049928   \n",
       "           ProActiv Solutions             108.0     ...      37.784212   \n",
       "           Sarku Japan                    116.0     ...      34.401416   \n",
       "           Solstice                       119.0     ...      37.784019   \n",
       "           Sunglass Hut                   125.0     ...      36.125510   \n",
       "           Swarovski                      128.0     ...      37.784346   \n",
       "           Swatch                         129.0     ...      37.582725   \n",
       "           TAP 415                        131.0     ...      37.784389   \n",
       "           The Art of Shaving             133.0     ...      36.336388   \n",
       "           abercrombie kids               149.0     ...      34.218488   \n",
       "\n",
       "                                                    longitude              \\\n",
       "                                                max     count        mean   \n",
       "Shopper_ID Store_Name                                                       \n",
       "Shopper_1  49ers Team Store               35.399507       7.0 -112.735348   \n",
       "           BOSS                           35.539867       1.0 -115.187304   \n",
       "           Bath & Body Works              35.664542       1.0 -115.588398   \n",
       "           Bespoke Events                 35.756717       2.0 -115.759376   \n",
       "           Bloomingdale's                 35.664494      64.0 -100.041579   \n",
       "           Bristol Farms                  35.240591       1.0 -114.224934   \n",
       "           Club Monaco Women              34.877600       3.0 -112.158942   \n",
       "           Cotton On                      37.784150      14.0 -122.404261   \n",
       "           H&M                            35.539812       9.0 -114.049064   \n",
       "           H&M Man                        35.776100       4.0 -115.482491   \n",
       "           Haagen Dazs                    35.664467       2.0 -115.579555   \n",
       "           House of Hoops by Foot Locker  34.635392       1.0 -112.206476   \n",
       "           Kay Jewelers                   37.716263       1.0 -122.187249   \n",
       "           PacSun                         35.539799       3.0 -114.893503   \n",
       "           ProActiv Solutions             37.784263      30.0 -122.402133   \n",
       "           RED Valentino                  37.716259       1.0 -122.187237   \n",
       "           Sarku Japan                    34.349161       2.0 -111.279068   \n",
       "           Solstice                       37.784121      17.0 -122.404881   \n",
       "           Swarovski                      37.784128      14.0 -122.403778   \n",
       "           TAP 415                        37.784158       8.0 -122.393541   \n",
       "           The Walking Company            35.876436       2.0 -116.109035   \n",
       "           abercrombie kids               34.349176       2.0 -111.279110   \n",
       "Shopper_10 49ers Team Store               35.375902       2.0 -113.165187   \n",
       "           Auntie Anne's Pretzels         37.239922       1.0 -120.642571   \n",
       "           Bespoke Events                 35.135766       4.0 -113.271800   \n",
       "           Bloomingdale's                 35.203609       4.0 -112.314990   \n",
       "           Brighton Collectibles          37.039586       5.0 -119.646636   \n",
       "           Bristol Farms                  36.665839       1.0 -118.782953   \n",
       "           Camper                         37.067269       2.0 -118.836670   \n",
       "           Chipotle                       34.100234       1.0 -110.472823   \n",
       "...                                             ...       ...         ...   \n",
       "Shopper_98 Swarovski                      37.784564      49.0 -122.407030   \n",
       "           TAP 415                        37.784223       1.0 -122.406595   \n",
       "Shopper_99 49ers Team Store               35.422896       3.0 -113.455975   \n",
       "           BOSS                           35.399860       3.0 -114.736085   \n",
       "           Bath & Body Works              36.550032       1.0 -118.408601   \n",
       "           Bespoke Events                 35.540035       9.0 -113.225671   \n",
       "           Bloomingdale's                 35.664664       5.0 -110.750704   \n",
       "           Brighton Collectibles          36.711757       3.0 -118.634512   \n",
       "           Bristol Farms                  36.711092       2.0 -118.903739   \n",
       "           Camper                         36.731214       5.0 -118.872381   \n",
       "           Club Monaco Women              34.878280       3.0 -112.330853   \n",
       "           Cotton On                      37.784615      26.0 -122.319116   \n",
       "           H&M                            35.539964       1.0 -115.187357   \n",
       "           H&M Man                        35.776410       3.0 -115.827529   \n",
       "           Haagen Dazs                    35.876831       3.0 -116.042914   \n",
       "           Janie And Jack                 35.967674       2.0 -116.254680   \n",
       "           Kay Jewelers                   37.596348       1.0 -121.799024   \n",
       "           L'Occitane en Provence         36.257929       3.0 -117.200727   \n",
       "           Lady Foot Locker               36.125315       4.0 -116.543429   \n",
       "           Lids                           36.194433       1.0 -117.293123   \n",
       "           M.Y. China                     36.049928       1.0 -116.828233   \n",
       "           ProActiv Solutions             37.785072      51.0 -122.381705   \n",
       "           Sarku Japan                    34.401416       1.0 -111.466124   \n",
       "           Solstice                       37.784026       7.0 -122.400953   \n",
       "           Sunglass Hut                   36.125510       1.0 -117.070583   \n",
       "           Swarovski                      37.785318      28.0 -122.401428   \n",
       "           Swatch                         37.583199       2.0 -121.753377   \n",
       "           TAP 415                        37.784623      18.0 -122.307073   \n",
       "           The Art of Shaving             36.336577       2.0 -117.715760   \n",
       "           abercrombie kids               34.218488       1.0 -110.902210   \n",
       "\n",
       "                                                                             \\\n",
       "                                                std         min         25%   \n",
       "Shopper_ID Store_Name                                                         \n",
       "Shopper_1  49ers Team Store                1.259467 -114.736382 -113.327500   \n",
       "           BOSS                                 NaN -115.187304 -115.187304   \n",
       "           Bath & Body Works                    NaN -115.588398 -115.588398   \n",
       "           Bespoke Events                  0.241615 -115.930223 -115.844800   \n",
       "           Bloomingdale's                 16.522958 -115.588692 -108.806248   \n",
       "           Bristol Farms                        NaN -114.224934 -114.224934   \n",
       "           Club Monaco Women               0.856980 -112.991140 -112.598832   \n",
       "           Cotton On                       0.007147 -122.407213 -122.407141   \n",
       "           H&M                             0.778325 -115.187564 -114.736331   \n",
       "           H&M Man                         0.360678 -115.947265 -115.678128   \n",
       "           Haagen Dazs                     0.012921 -115.588692 -115.584123   \n",
       "           House of Hoops by Foot Locker        NaN -112.206476 -112.206476   \n",
       "           Kay Jewelers                         NaN -122.187249 -122.187249   \n",
       "           PacSun                          0.254887 -115.187584 -114.972141   \n",
       "           ProActiv Solutions              0.015500 -122.407302 -122.407162   \n",
       "           RED Valentino                        NaN -122.187237 -122.187237   \n",
       "           Sarku Japan                     0.000148 -111.279173 -111.279120   \n",
       "           Solstice                        0.006154 -122.407207 -122.407150   \n",
       "           Swarovski                       0.008425 -122.407198 -122.407127   \n",
       "           TAP 415                         0.028797 -122.407049 -122.406821   \n",
       "           The Walking Company             0.228386 -116.270529 -116.189782   \n",
       "           abercrombie kids                0.000027 -111.279129 -111.279120   \n",
       "Shopper_10 49ers Team Store                2.036779 -114.605407 -113.885297   \n",
       "           Auntie Anne's Pretzels               NaN -120.642571 -120.642571   \n",
       "           Bespoke Events                  0.972777 -113.827394 -113.799833   \n",
       "           Bloomingdale's                  3.151391 -114.047399 -113.986064   \n",
       "           Brighton Collectibles           0.323971 -119.993700 -119.967906   \n",
       "           Bristol Farms                        NaN -118.782953 -118.782953   \n",
       "           Camper                          1.763762 -120.083838 -119.460254   \n",
       "           Chipotle                             NaN -110.472823 -110.472823   \n",
       "...                                             ...         ...         ...   \n",
       "Shopper_98 Swarovski                       0.000146 -122.407262 -122.407113   \n",
       "           TAP 415                              NaN -122.406595 -122.406595   \n",
       "Shopper_99 49ers Team Store                1.811458 -114.756099 -114.490520   \n",
       "           BOSS                            0.000260 -114.736313 -114.736226   \n",
       "           Bath & Body Works                    NaN -118.408601 -118.408601   \n",
       "           Bespoke Events                  1.222782 -115.187127 -113.942530   \n",
       "           Bloomingdale's                  2.750469 -115.588414 -110.149677   \n",
       "           Brighton Collectibles           0.272048 -118.932571 -118.751982   \n",
       "           Bristol Farms                   0.037729 -118.930418 -118.917079   \n",
       "           Camper                          0.106339 -118.996073 -118.949556   \n",
       "           Club Monaco Women               0.632001 -112.992201 -112.629783   \n",
       "           Cotton On                       0.208842 -122.407265 -122.407103   \n",
       "           H&M                                  NaN -115.187357 -115.187357   \n",
       "           H&M Man                         0.207177 -115.947290 -115.947143   \n",
       "           Haagen Dazs                     0.393422 -116.270122 -116.270056   \n",
       "           Janie And Jack                  0.434915 -116.562212 -116.408446   \n",
       "           Kay Jewelers                         NaN -121.799024 -121.799024   \n",
       "           L'Occitane en Provence          0.350654 -117.496074 -117.394497   \n",
       "           Lady Foot Locker                0.377590 -117.070787 -116.689521   \n",
       "           Lids                                 NaN -117.293123 -117.293123   \n",
       "           M.Y. China                           NaN -116.828233 -116.828233   \n",
       "           ProActiv Solutions              0.100355 -122.409203 -122.407054   \n",
       "           Sarku Japan                          NaN -111.466124 -111.466124   \n",
       "           Solstice                        0.011070 -122.407110 -122.407097   \n",
       "           Sunglass Hut                         NaN -117.070583 -117.070583   \n",
       "           Swarovski                       0.007984 -122.409686 -122.406787   \n",
       "           Swatch                          0.004345 -121.756450 -121.754913   \n",
       "           TAP 415                         0.360206 -122.406745 -122.406516   \n",
       "           The Art of Shaving              0.001732 -117.716985 -117.716373   \n",
       "           abercrombie kids                     NaN -110.902210 -110.902210   \n",
       "\n",
       "                                                                              \n",
       "                                                 50%         75%         max  \n",
       "Shopper_ID Store_Name                                                         \n",
       "Shopper_1  49ers Team Store              -112.991175 -111.742864 -111.279150  \n",
       "           BOSS                          -115.187304 -115.187304 -115.187304  \n",
       "           Bath & Body Works             -115.588398 -115.588398 -115.588398  \n",
       "           Bespoke Events                -115.759376 -115.673952 -115.588529  \n",
       "           Bloomingdale's                -104.920363 -101.542209  -51.038836  \n",
       "           Bristol Farms                 -114.224934 -114.224934 -114.224934  \n",
       "           Club Monaco Women             -112.206523 -111.742843 -111.279163  \n",
       "           Cotton On                     -122.407099 -122.406918 -122.386801  \n",
       "           H&M                           -114.224980 -113.663578 -112.991140  \n",
       "           H&M Man                       -115.397557 -115.201920 -115.187586  \n",
       "           Haagen Dazs                   -115.579555 -115.574987 -115.570418  \n",
       "           House of Hoops by Foot Locker -112.206476 -112.206476 -112.206476  \n",
       "           Kay Jewelers                  -122.187249 -122.187249 -122.187249  \n",
       "           PacSun                        -114.756697 -114.746463 -114.736228  \n",
       "           ProActiv Solutions            -122.406884 -122.406457 -122.341798  \n",
       "           RED Valentino                 -122.187237 -122.187237 -122.187237  \n",
       "           Sarku Japan                   -111.279068 -111.279016 -111.278963  \n",
       "           Solstice                      -122.407085 -122.407039 -122.388008  \n",
       "           Swarovski                     -122.407086 -122.406999 -122.383891  \n",
       "           TAP 415                       -122.406719 -122.400416 -122.325626  \n",
       "           The Walking Company           -116.109035 -116.028289 -115.947542  \n",
       "           abercrombie kids              -111.279110 -111.279101 -111.279091  \n",
       "Shopper_10 49ers Team Store              -113.165187 -112.445077 -111.724967  \n",
       "           Auntie Anne's Pretzels        -120.642571 -120.642571 -120.642571  \n",
       "           Bespoke Events                -113.721387 -113.193354 -111.817032  \n",
       "           Bloomingdale's                -113.808873 -112.137800 -107.594816  \n",
       "           Brighton Collectibles         -119.599567 -119.357911 -119.314095  \n",
       "           Bristol Farms                 -118.782953 -118.782953 -118.782953  \n",
       "           Camper                        -118.836670 -118.213086 -117.589502  \n",
       "           Chipotle                      -110.472823 -110.472823 -110.472823  \n",
       "...                                              ...         ...         ...  \n",
       "Shopper_98 Swarovski                     -122.407053 -122.407008 -122.406374  \n",
       "           TAP 415                       -122.406595 -122.406595 -122.406595  \n",
       "Shopper_99 49ers Team Store              -114.224940 -112.805913 -111.386886  \n",
       "           BOSS                          -114.736139 -114.735970 -114.735801  \n",
       "           Bath & Body Works             -118.408601 -118.408601 -118.408601  \n",
       "           Bespoke Events                -112.966029 -112.965748 -110.960084  \n",
       "           Bloomingdale's                -109.740750 -109.504599 -108.770082  \n",
       "           Brighton Collectibles         -118.571393 -118.485483 -118.399573  \n",
       "           Bristol Farms                 -118.903739 -118.890400 -118.877061  \n",
       "           Camper                        -118.870026 -118.819317 -118.726933  \n",
       "           Club Monaco Women             -112.267364 -112.000178 -111.732993  \n",
       "           Cotton On                     -122.407086 -122.406403 -121.798387  \n",
       "           H&M                           -115.187357 -115.187357 -115.187357  \n",
       "           H&M Man                       -115.946996 -115.767649 -115.588303  \n",
       "           Haagen Dazs                   -116.269989 -115.929309 -115.588629  \n",
       "           Janie And Jack                -116.254680 -116.100914 -115.947148  \n",
       "           Kay Jewelers                  -121.799024 -121.799024 -121.799024  \n",
       "           L'Occitane en Provence        -117.292919 -117.053053 -116.813187  \n",
       "           Lady Foot Locker              -116.416444 -116.270353 -116.270043  \n",
       "           Lids                          -117.293123 -117.293123 -117.293123  \n",
       "           M.Y. China                    -116.828233 -116.828233 -116.828233  \n",
       "           ProActiv Solutions            -122.407016 -122.406637 -121.799954  \n",
       "           Sarku Japan                   -111.466124 -111.466124 -111.466124  \n",
       "           Solstice                      -122.407072 -122.399447 -122.379400  \n",
       "           Sunglass Hut                  -117.070583 -117.070583 -117.070583  \n",
       "           Swarovski                     -122.406541 -122.395289 -122.379390  \n",
       "           Swatch                        -121.753377 -121.751841 -121.750305  \n",
       "           TAP 415                       -122.391547 -122.380519 -120.865104  \n",
       "           The Art of Shaving            -117.715760 -117.715148 -117.714535  \n",
       "           abercrombie kids              -110.902210 -110.902210 -110.902210  \n",
       "\n",
       "[10121 rows x 32 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.groupby(['Shopper_ID', 'Store_Name']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\welcome\\Anaconda2\\lib\\site-packages\\scipy\\stats\\stats.py:253: RuntimeWarning: The input array could not be properly checked for nan values. nan values will be ignored.\n",
      "  \"values. nan values will be ignored.\", RuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "df_freq = pinginfo.groupby(by='Shopper_ID').Store_Name.apply(stats.mode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Shopper_ID\n",
       "Shopper_1            ([Bloomingdale's], [64])\n",
       "Shopper_10                  ([TAP 415], [80])\n",
       "Shopper_100     ([ProActiv Solutions ], [58])\n",
       "Shopper_101               ([Swarovski], [53])\n",
       "Shopper_102                ([TAP 415], [125])\n",
       "Shopper_103               ([Cotton On], [52])\n",
       "Shopper_104     ([ProActiv Solutions ], [71])\n",
       "Shopper_105     ([ProActiv Solutions ], [61])\n",
       "Shopper_106     ([ProActiv Solutions ], [63])\n",
       "Shopper_107     ([ProActiv Solutions ], [61])\n",
       "Shopper_108    ([ProActiv Solutions ], [105])\n",
       "Shopper_109          ([Bloomingdale's], [56])\n",
       "Shopper_11      ([ProActiv Solutions ], [72])\n",
       "Shopper_110     ([ProActiv Solutions ], [51])\n",
       "Shopper_111               ([Swarovski], [56])\n",
       "Shopper_112     ([ProActiv Solutions ], [77])\n",
       "Shopper_113     ([ProActiv Solutions ], [97])\n",
       "Shopper_114                 ([TAP 415], [90])\n",
       "Shopper_115               ([Cotton On], [55])\n",
       "Shopper_116                ([TAP 415], [167])\n",
       "Shopper_117    ([ProActiv Solutions ], [133])\n",
       "Shopper_118               ([Cotton On], [45])\n",
       "Shopper_119              ([Swarovski], [119])\n",
       "Shopper_12      ([ProActiv Solutions ], [32])\n",
       "Shopper_120               ([Swarovski], [59])\n",
       "Shopper_121     ([ProActiv Solutions ], [44])\n",
       "Shopper_122                 ([TAP 415], [49])\n",
       "Shopper_123               ([Swarovski], [72])\n",
       "Shopper_124     ([ProActiv Solutions ], [75])\n",
       "Shopper_125               ([Cotton On], [41])\n",
       "                            ...              \n",
       "Shopper_72                  ([TAP 415], [59])\n",
       "Shopper_73      ([ProActiv Solutions ], [51])\n",
       "Shopper_74      ([ProActiv Solutions ], [60])\n",
       "Shopper_75                ([Swarovski], [56])\n",
       "Shopper_76     ([ProActiv Solutions ], [116])\n",
       "Shopper_77                  ([TAP 415], [41])\n",
       "Shopper_78                ([Cotton On], [54])\n",
       "Shopper_79                ([Cotton On], [55])\n",
       "Shopper_8                 ([Swarovski], [57])\n",
       "Shopper_80      ([ProActiv Solutions ], [71])\n",
       "Shopper_81      ([ProActiv Solutions ], [46])\n",
       "Shopper_82                  ([TAP 415], [56])\n",
       "Shopper_83      ([ProActiv Solutions ], [58])\n",
       "Shopper_84                  ([TAP 415], [86])\n",
       "Shopper_85     ([ProActiv Solutions ], [107])\n",
       "Shopper_86      ([ProActiv Solutions ], [57])\n",
       "Shopper_87                  ([TAP 415], [38])\n",
       "Shopper_88                ([Swarovski], [45])\n",
       "Shopper_89      ([ProActiv Solutions ], [76])\n",
       "Shopper_9       ([ProActiv Solutions ], [73])\n",
       "Shopper_90                ([Swarovski], [67])\n",
       "Shopper_91      ([ProActiv Solutions ], [77])\n",
       "Shopper_92      ([ProActiv Solutions ], [71])\n",
       "Shopper_93                  ([TAP 415], [51])\n",
       "Shopper_94                ([Cotton On], [57])\n",
       "Shopper_95                ([Swarovski], [86])\n",
       "Shopper_96                 ([Solstice], [38])\n",
       "Shopper_97           ([Bloomingdale's], [42])\n",
       "Shopper_98      ([ProActiv Solutions ], [66])\n",
       "Shopper_99      ([ProActiv Solutions ], [51])\n",
       "Name: Store_Name, Length: 567, dtype: object"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_freq= df_freq.to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Store_Name    ([TAP 415], [80])\n",
       "Name: Shopper_10, dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq.iloc[1,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "mostvisitedshoplist= []\n",
    "for shop in df_freq['Store_Name']:\n",
    "    mostvisitedshoplist.append(shop[0][0])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([u\"Bloomingdale's\", u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'TAP 415', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'Cotton On', u'TAP 415', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u\"Bloomingdale's\",\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'Cotton On', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'TAP 415', u'Cotton On', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'Swarovski',\n",
       "       u\"Bloomingdale's\", u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Solstice', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'TAP 415', u'Swarovski',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Swarovski', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u\"Bloomingdale's\", u\"Bloomingdale's\",\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'Swarovski', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'TAP 415',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'Swarovski', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'TAP 415', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Cotton On', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'Cotton On', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Swarovski', u'Solstice',\n",
       "       u\"Bloomingdale's\", u'Cotton On', u'Cotton On', u'TAP 415',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Cotton On', u'TAP 415', u'Swarovski', u'Swarovski',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Solstice', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On', u'Cotton On',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'Swarovski', u'Solstice', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Swarovski', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'Swarovski', u'Swarovski',\n",
       "       u'Swarovski', u'Cotton On', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Marbles: The Brain Store',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'Solstice', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'Swarovski', u'Swarovski', u'Solstice', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Solstice', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Swarovski', u'TAP 415',\n",
       "       u'TAP 415', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Solstice', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'TAP 415', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'Swarovski', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'TAP 415', u'Cotton On',\n",
       "       u\"Bloomingdale's\", u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'Cotton On', u'Cotton On', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'Swarovski', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'TAP 415', u'Cotton On',\n",
       "       u'Cotton On', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Cotton On', u'Swarovski',\n",
       "       u'Solstice', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions '], dtype='<U24')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mostvisitedshop_array= np.array(mostvisitedshoplist)\n",
    "mostvisitedshop_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([u\"Bloomingdale's\", u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'TAP 415', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'Cotton On', u'TAP 415', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u\"Bloomingdale's\",\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'Cotton On', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'TAP 415', u'Cotton On', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'Swarovski',\n",
       "       u\"Bloomingdale's\", u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Solstice', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'TAP 415', u'Swarovski',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Swarovski', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u\"Bloomingdale's\", u\"Bloomingdale's\",\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'Swarovski', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'TAP 415',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'Swarovski', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'TAP 415', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Cotton On', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'Cotton On', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Swarovski', u'Solstice',\n",
       "       u\"Bloomingdale's\", u'Cotton On', u'Cotton On', u'TAP 415',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Cotton On', u'TAP 415', u'Swarovski', u'Swarovski',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Solstice', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On', u'Cotton On',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'Swarovski', u'Solstice', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'Swarovski', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'Swarovski', u\"Bloomingdale's\", u'Swarovski', u'Swarovski',\n",
       "       u'Swarovski', u'Cotton On', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Marbles: The Brain Store',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'Solstice', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'TAP 415',\n",
       "       u'Swarovski', u'Swarovski', u'Solstice', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Solstice', u'Cotton On', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Swarovski', u'TAP 415',\n",
       "       u'TAP 415', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Solstice', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'TAP 415', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u'Cotton On',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'Swarovski', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'TAP 415', u'Cotton On',\n",
       "       u\"Bloomingdale's\", u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'Cotton On', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Solstice', u'ProActiv Solutions ', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ', u\"Bloomingdale's\",\n",
       "       u'Cotton On', u'Cotton On', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'Swarovski', u'ProActiv Solutions ',\n",
       "       u\"Bloomingdale's\", u'ProActiv Solutions ', u'Solstice',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Cotton On', u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'TAP 415',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u\"Bloomingdale's\", u'Swarovski',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Cotton On', u\"Bloomingdale's\",\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'Swarovski', u'ProActiv Solutions ', u'TAP 415', u'Cotton On',\n",
       "       u'Cotton On', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'ProActiv Solutions ', u'ProActiv Solutions ',\n",
       "       u'TAP 415', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'Swarovski', u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions ', u'TAP 415', u'Cotton On', u'Swarovski',\n",
       "       u'Solstice', u\"Bloomingdale's\", u'ProActiv Solutions ',\n",
       "       u'ProActiv Solutions '], dtype=object)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mostvisitedshop_array.astype(object)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_freq = df_freq.to_frame().reset_index()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>New_Store</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Shopper_1</th>\n",
       "      <td>([Bloomingdale's], [64])</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_10</th>\n",
       "      <td>([TAP 415], [80])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_100</th>\n",
       "      <td>([ProActiv Solutions ], [58])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_101</th>\n",
       "      <td>([Swarovski], [53])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_102</th>\n",
       "      <td>([TAP 415], [125])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Store_Name            New_Store\n",
       "Shopper_ID                                                     \n",
       "Shopper_1         ([Bloomingdale's], [64])       Bloomingdale's\n",
       "Shopper_10               ([TAP 415], [80])              TAP 415\n",
       "Shopper_100  ([ProActiv Solutions ], [58])  ProActiv Solutions \n",
       "Shopper_101            ([Swarovski], [53])            Swarovski\n",
       "Shopper_102             ([TAP 415], [125])              TAP 415"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq['New_Store']= mostvisitedshop_array\n",
    "df_freq.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_freq.to_csv(r\"C:\\Users\\welcome\\Desktop\\exl__rf.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>New_Store</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Shopper_1</th>\n",
       "      <td>([Bloomingdale's], [64])</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_10</th>\n",
       "      <td>([TAP 415], [80])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_100</th>\n",
       "      <td>([ProActiv Solutions ], [58])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_101</th>\n",
       "      <td>([Swarovski], [53])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_102</th>\n",
       "      <td>([TAP 415], [125])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_103</th>\n",
       "      <td>([Cotton On], [52])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_104</th>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_105</th>\n",
       "      <td>([ProActiv Solutions ], [61])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_106</th>\n",
       "      <td>([ProActiv Solutions ], [63])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_107</th>\n",
       "      <td>([ProActiv Solutions ], [61])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_108</th>\n",
       "      <td>([ProActiv Solutions ], [105])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_109</th>\n",
       "      <td>([Bloomingdale's], [56])</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_11</th>\n",
       "      <td>([ProActiv Solutions ], [72])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_110</th>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_111</th>\n",
       "      <td>([Swarovski], [56])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_112</th>\n",
       "      <td>([ProActiv Solutions ], [77])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_113</th>\n",
       "      <td>([ProActiv Solutions ], [97])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_114</th>\n",
       "      <td>([TAP 415], [90])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_115</th>\n",
       "      <td>([Cotton On], [55])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_116</th>\n",
       "      <td>([TAP 415], [167])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_117</th>\n",
       "      <td>([ProActiv Solutions ], [133])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_118</th>\n",
       "      <td>([Cotton On], [45])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_119</th>\n",
       "      <td>([Swarovski], [119])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_12</th>\n",
       "      <td>([ProActiv Solutions ], [32])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_120</th>\n",
       "      <td>([Swarovski], [59])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_121</th>\n",
       "      <td>([ProActiv Solutions ], [44])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_122</th>\n",
       "      <td>([TAP 415], [49])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_123</th>\n",
       "      <td>([Swarovski], [72])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_124</th>\n",
       "      <td>([ProActiv Solutions ], [75])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_125</th>\n",
       "      <td>([Cotton On], [41])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_72</th>\n",
       "      <td>([TAP 415], [59])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_73</th>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_74</th>\n",
       "      <td>([ProActiv Solutions ], [60])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_75</th>\n",
       "      <td>([Swarovski], [56])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_76</th>\n",
       "      <td>([ProActiv Solutions ], [116])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_77</th>\n",
       "      <td>([TAP 415], [41])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_78</th>\n",
       "      <td>([Cotton On], [54])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_79</th>\n",
       "      <td>([Cotton On], [55])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_8</th>\n",
       "      <td>([Swarovski], [57])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_80</th>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_81</th>\n",
       "      <td>([ProActiv Solutions ], [46])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_82</th>\n",
       "      <td>([TAP 415], [56])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_83</th>\n",
       "      <td>([ProActiv Solutions ], [58])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_84</th>\n",
       "      <td>([TAP 415], [86])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_85</th>\n",
       "      <td>([ProActiv Solutions ], [107])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_86</th>\n",
       "      <td>([ProActiv Solutions ], [57])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_87</th>\n",
       "      <td>([TAP 415], [38])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_88</th>\n",
       "      <td>([Swarovski], [45])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_89</th>\n",
       "      <td>([ProActiv Solutions ], [76])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_9</th>\n",
       "      <td>([ProActiv Solutions ], [73])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_90</th>\n",
       "      <td>([Swarovski], [67])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_91</th>\n",
       "      <td>([ProActiv Solutions ], [77])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_92</th>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_93</th>\n",
       "      <td>([TAP 415], [51])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_94</th>\n",
       "      <td>([Cotton On], [57])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_95</th>\n",
       "      <td>([Swarovski], [86])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_96</th>\n",
       "      <td>([Solstice], [38])</td>\n",
       "      <td>Solstice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_97</th>\n",
       "      <td>([Bloomingdale's], [42])</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_98</th>\n",
       "      <td>([ProActiv Solutions ], [66])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_99</th>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>567 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Store_Name            New_Store\n",
       "Shopper_ID                                                      \n",
       "Shopper_1          ([Bloomingdale's], [64])       Bloomingdale's\n",
       "Shopper_10                ([TAP 415], [80])              TAP 415\n",
       "Shopper_100   ([ProActiv Solutions ], [58])  ProActiv Solutions \n",
       "Shopper_101             ([Swarovski], [53])            Swarovski\n",
       "Shopper_102              ([TAP 415], [125])              TAP 415\n",
       "Shopper_103             ([Cotton On], [52])            Cotton On\n",
       "Shopper_104   ([ProActiv Solutions ], [71])  ProActiv Solutions \n",
       "Shopper_105   ([ProActiv Solutions ], [61])  ProActiv Solutions \n",
       "Shopper_106   ([ProActiv Solutions ], [63])  ProActiv Solutions \n",
       "Shopper_107   ([ProActiv Solutions ], [61])  ProActiv Solutions \n",
       "Shopper_108  ([ProActiv Solutions ], [105])  ProActiv Solutions \n",
       "Shopper_109        ([Bloomingdale's], [56])       Bloomingdale's\n",
       "Shopper_11    ([ProActiv Solutions ], [72])  ProActiv Solutions \n",
       "Shopper_110   ([ProActiv Solutions ], [51])  ProActiv Solutions \n",
       "Shopper_111             ([Swarovski], [56])            Swarovski\n",
       "Shopper_112   ([ProActiv Solutions ], [77])  ProActiv Solutions \n",
       "Shopper_113   ([ProActiv Solutions ], [97])  ProActiv Solutions \n",
       "Shopper_114               ([TAP 415], [90])              TAP 415\n",
       "Shopper_115             ([Cotton On], [55])            Cotton On\n",
       "Shopper_116              ([TAP 415], [167])              TAP 415\n",
       "Shopper_117  ([ProActiv Solutions ], [133])  ProActiv Solutions \n",
       "Shopper_118             ([Cotton On], [45])            Cotton On\n",
       "Shopper_119            ([Swarovski], [119])            Swarovski\n",
       "Shopper_12    ([ProActiv Solutions ], [32])  ProActiv Solutions \n",
       "Shopper_120             ([Swarovski], [59])            Swarovski\n",
       "Shopper_121   ([ProActiv Solutions ], [44])  ProActiv Solutions \n",
       "Shopper_122               ([TAP 415], [49])              TAP 415\n",
       "Shopper_123             ([Swarovski], [72])            Swarovski\n",
       "Shopper_124   ([ProActiv Solutions ], [75])  ProActiv Solutions \n",
       "Shopper_125             ([Cotton On], [41])            Cotton On\n",
       "...                                     ...                  ...\n",
       "Shopper_72                ([TAP 415], [59])              TAP 415\n",
       "Shopper_73    ([ProActiv Solutions ], [51])  ProActiv Solutions \n",
       "Shopper_74    ([ProActiv Solutions ], [60])  ProActiv Solutions \n",
       "Shopper_75              ([Swarovski], [56])            Swarovski\n",
       "Shopper_76   ([ProActiv Solutions ], [116])  ProActiv Solutions \n",
       "Shopper_77                ([TAP 415], [41])              TAP 415\n",
       "Shopper_78              ([Cotton On], [54])            Cotton On\n",
       "Shopper_79              ([Cotton On], [55])            Cotton On\n",
       "Shopper_8               ([Swarovski], [57])            Swarovski\n",
       "Shopper_80    ([ProActiv Solutions ], [71])  ProActiv Solutions \n",
       "Shopper_81    ([ProActiv Solutions ], [46])  ProActiv Solutions \n",
       "Shopper_82                ([TAP 415], [56])              TAP 415\n",
       "Shopper_83    ([ProActiv Solutions ], [58])  ProActiv Solutions \n",
       "Shopper_84                ([TAP 415], [86])              TAP 415\n",
       "Shopper_85   ([ProActiv Solutions ], [107])  ProActiv Solutions \n",
       "Shopper_86    ([ProActiv Solutions ], [57])  ProActiv Solutions \n",
       "Shopper_87                ([TAP 415], [38])              TAP 415\n",
       "Shopper_88              ([Swarovski], [45])            Swarovski\n",
       "Shopper_89    ([ProActiv Solutions ], [76])  ProActiv Solutions \n",
       "Shopper_9     ([ProActiv Solutions ], [73])  ProActiv Solutions \n",
       "Shopper_90              ([Swarovski], [67])            Swarovski\n",
       "Shopper_91    ([ProActiv Solutions ], [77])  ProActiv Solutions \n",
       "Shopper_92    ([ProActiv Solutions ], [71])  ProActiv Solutions \n",
       "Shopper_93                ([TAP 415], [51])              TAP 415\n",
       "Shopper_94              ([Cotton On], [57])            Cotton On\n",
       "Shopper_95              ([Swarovski], [86])            Swarovski\n",
       "Shopper_96               ([Solstice], [38])             Solstice\n",
       "Shopper_97         ([Bloomingdale's], [42])       Bloomingdale's\n",
       "Shopper_98    ([ProActiv Solutions ], [66])  ProActiv Solutions \n",
       "Shopper_99    ([ProActiv Solutions ], [51])  ProActiv Solutions \n",
       "\n",
       "[567 rows x 2 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 567 entries, Shopper_1 to Shopper_99\n",
      "Data columns (total 2 columns):\n",
      "Store_Name    567 non-null object\n",
      "New_Store     567 non-null object\n",
      "dtypes: object(2)\n",
      "memory usage: 33.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_freq.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_freq.sort_values(['Shopper_ID'], axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_freq.to_csv(r\"C:\\Users\\welcome\\Desktop\\exl__rf.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_freq2=pinginfo.pivot_table(values='Store_Name', columns='Shopper_ID', aggfunc=stats.mode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Shopper_1</th>\n",
       "      <th>Shopper_10</th>\n",
       "      <th>Shopper_100</th>\n",
       "      <th>Shopper_101</th>\n",
       "      <th>Shopper_102</th>\n",
       "      <th>Shopper_103</th>\n",
       "      <th>Shopper_104</th>\n",
       "      <th>Shopper_105</th>\n",
       "      <th>Shopper_106</th>\n",
       "      <th>Shopper_107</th>\n",
       "      <th>...</th>\n",
       "      <th>Shopper_90</th>\n",
       "      <th>Shopper_91</th>\n",
       "      <th>Shopper_92</th>\n",
       "      <th>Shopper_93</th>\n",
       "      <th>Shopper_94</th>\n",
       "      <th>Shopper_95</th>\n",
       "      <th>Shopper_96</th>\n",
       "      <th>Shopper_97</th>\n",
       "      <th>Shopper_98</th>\n",
       "      <th>Shopper_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Store_Name</th>\n",
       "      <td>([Bloomingdale's], [64])</td>\n",
       "      <td>([TAP 415], [80])</td>\n",
       "      <td>([ProActiv Solutions ], [58])</td>\n",
       "      <td>([Swarovski], [53])</td>\n",
       "      <td>([TAP 415], [125])</td>\n",
       "      <td>([Cotton On], [52])</td>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>([ProActiv Solutions ], [61])</td>\n",
       "      <td>([ProActiv Solutions ], [63])</td>\n",
       "      <td>([ProActiv Solutions ], [61])</td>\n",
       "      <td>...</td>\n",
       "      <td>([Swarovski], [67])</td>\n",
       "      <td>([ProActiv Solutions ], [77])</td>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>([TAP 415], [51])</td>\n",
       "      <td>([Cotton On], [57])</td>\n",
       "      <td>([Swarovski], [86])</td>\n",
       "      <td>([Solstice], [38])</td>\n",
       "      <td>([Bloomingdale's], [42])</td>\n",
       "      <td>([ProActiv Solutions ], [66])</td>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 567 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Shopper_ID                 Shopper_1         Shopper_10  \\\n",
       "Store_Name  ([Bloomingdale's], [64])  ([TAP 415], [80])   \n",
       "\n",
       "Shopper_ID                    Shopper_100          Shopper_101  \\\n",
       "Store_Name  ([ProActiv Solutions ], [58])  ([Swarovski], [53])   \n",
       "\n",
       "Shopper_ID         Shopper_102          Shopper_103  \\\n",
       "Store_Name  ([TAP 415], [125])  ([Cotton On], [52])   \n",
       "\n",
       "Shopper_ID                    Shopper_104                    Shopper_105  \\\n",
       "Store_Name  ([ProActiv Solutions ], [71])  ([ProActiv Solutions ], [61])   \n",
       "\n",
       "Shopper_ID                    Shopper_106                    Shopper_107  \\\n",
       "Store_Name  ([ProActiv Solutions ], [63])  ([ProActiv Solutions ], [61])   \n",
       "\n",
       "Shopper_ID              ...                         Shopper_90  \\\n",
       "Store_Name              ...                ([Swarovski], [67])   \n",
       "\n",
       "Shopper_ID                     Shopper_91                     Shopper_92  \\\n",
       "Store_Name  ([ProActiv Solutions ], [77])  ([ProActiv Solutions ], [71])   \n",
       "\n",
       "Shopper_ID         Shopper_93           Shopper_94           Shopper_95  \\\n",
       "Store_Name  ([TAP 415], [51])  ([Cotton On], [57])  ([Swarovski], [86])   \n",
       "\n",
       "Shopper_ID          Shopper_96                Shopper_97  \\\n",
       "Store_Name  ([Solstice], [38])  ([Bloomingdale's], [42])   \n",
       "\n",
       "Shopper_ID                     Shopper_98                     Shopper_99  \n",
       "Store_Name  ([ProActiv Solutions ], [66])  ([ProActiv Solutions ], [51])  \n",
       "\n",
       "[1 rows x 567 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_freq2.to_csv(r\"C:\\Users\\welcome\\Desktop\\exl_final2.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mean accuracy of SVM: 0.83734939759'"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SVM TRAINING AND FITTING:\n",
    "from sklearn.svm import SVC\n",
    "for kernel in ('linear', 'poly', 'rbf'):\n",
    "    clf = svm.SVC(kernel=kernel, gamma=2)\n",
    "    clf.fit(X, y)\n",
    "\n",
    "\n",
    "# Training data features, skip the first column 'Survived'\n",
    "train_features = X\n",
    "\n",
    "# 'Survived' column values\n",
    "train_target = y\n",
    "\n",
    "# Fit the model to our training data\n",
    "clf = clf.fit(train_features, train_target)\n",
    "score = clf.score(train_features, train_target)\n",
    "\"Mean accuracy of SVM: {0}\".format(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_y2 = clf.predict(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfo['Store_Index2'] = test_y2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Store_Index2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70238</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.585825</td>\n",
       "      <td>-108.806374</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70264</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784023</td>\n",
       "      <td>-122.406786</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40491</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.761052</td>\n",
       "      <td>-122.386801</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4777</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4776</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>32.386375</td>\n",
       "      <td>-104.920369</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101158</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.005662</td>\n",
       "      <td>-110.166421</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49054</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.399517</td>\n",
       "      <td>-114.736228</td>\n",
       "      <td>99</td>\n",
       "      <td>PacSun</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22621</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.721647</td>\n",
       "      <td>-106.064451</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22620</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>17.523494</td>\n",
       "      <td>-56.901809</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22619</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.349167</td>\n",
       "      <td>-111.279150</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52049</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>31.486702</td>\n",
       "      <td>-102.005952</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95887</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.061045</td>\n",
       "      <td>-107.106172</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98815</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784038</td>\n",
       "      <td>-122.406711</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>31.971133</td>\n",
       "      <td>-103.575228</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106999</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.061063</td>\n",
       "      <td>-107.106165</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78035</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784263</td>\n",
       "      <td>-122.405984</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77973</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407135</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100499</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784018</td>\n",
       "      <td>-122.407150</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35762</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784052</td>\n",
       "      <td>-122.407079</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71239</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784055</td>\n",
       "      <td>-122.407086</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97924</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784075</td>\n",
       "      <td>-122.407065</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102120</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784055</td>\n",
       "      <td>-122.407176</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97101</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>33.787407</td>\n",
       "      <td>-109.504903</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47032</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407172</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>34.349141</td>\n",
       "      <td>-111.278963</td>\n",
       "      <td>116</td>\n",
       "      <td>Sarku Japan</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25664</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.085205</td>\n",
       "      <td>-113.663751</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77426</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784041</td>\n",
       "      <td>-122.407108</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97946</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.265121</td>\n",
       "      <td>-114.246687</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32914</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784059</td>\n",
       "      <td>-122.406598</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>30.227255</td>\n",
       "      <td>-97.925648</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37372</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407009</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21770</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.968828</td>\n",
       "      <td>-110.133960</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28495</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>35.561458</td>\n",
       "      <td>-115.206698</td>\n",
       "      <td>63</td>\n",
       "      <td>H&amp;M Man</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28513</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.349118</td>\n",
       "      <td>-111.279163</td>\n",
       "      <td>39</td>\n",
       "      <td>Club Monaco Women</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93921</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784079</td>\n",
       "      <td>-122.407114</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50871</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.565384</td>\n",
       "      <td>-108.788102</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61183</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>31.971140</td>\n",
       "      <td>-103.575216</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50835</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>34.877596</td>\n",
       "      <td>-112.991172</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21547</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784064</td>\n",
       "      <td>-122.407207</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61182</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>4</td>\n",
       "      <td>35.756717</td>\n",
       "      <td>-115.930223</td>\n",
       "      <td>19</td>\n",
       "      <td>Bespoke Events</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74866</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.757750</td>\n",
       "      <td>-122.383892</td>\n",
       "      <td>128</td>\n",
       "      <td>Swarovski</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74855</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55291</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.783956</td>\n",
       "      <td>-122.407213</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74843</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74806</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784168</td>\n",
       "      <td>-122.406034</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74805</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.635384</td>\n",
       "      <td>-112.206523</td>\n",
       "      <td>39</td>\n",
       "      <td>Club Monaco Women</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.539867</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>14</td>\n",
       "      <td>BOSS</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50625</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.644070</td>\n",
       "      <td>-115.570418</td>\n",
       "      <td>64</td>\n",
       "      <td>Haagen Dazs</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50624</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784065</td>\n",
       "      <td>-122.407157</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93848</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.746176</td>\n",
       "      <td>-106.086128</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11819</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85044</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.338040</td>\n",
       "      <td>-91.805298</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85045</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.539812</td>\n",
       "      <td>-115.187564</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11637</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784120</td>\n",
       "      <td>-122.406620</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60944</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784048</td>\n",
       "      <td>-122.407212</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.635388</td>\n",
       "      <td>-112.206498</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85080</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.386344</td>\n",
       "      <td>-104.920316</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74419</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.585855</td>\n",
       "      <td>-108.806241</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.784032</td>\n",
       "      <td>-122.407175</td>\n",
       "      <td>128</td>\n",
       "      <td>Swarovski</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Shopper_ID  Floor_Index   latitude   longitude  Store_Index  \\\n",
       "35181   Shopper_1            3  37.762391 -122.388008          119   \n",
       "70238   Shopper_1            0  33.585825 -108.806374           20   \n",
       "70264   Shopper_1            0  37.784023 -122.406786          108   \n",
       "40491   Shopper_1            2  37.761052 -122.386801           43   \n",
       "4777    Shopper_1            3  35.664542 -115.588398           16   \n",
       "4776    Shopper_1            0  32.386375 -104.920369           20   \n",
       "101158  Shopper_1            1  34.005662 -110.166421           20   \n",
       "49054   Shopper_1            0  35.399517 -114.736228           99   \n",
       "22621   Shopper_1            1  32.721647 -106.064451           20   \n",
       "22620   Shopper_1            0  17.523494  -56.901809           20   \n",
       "22619   Shopper_1            2  34.349167 -111.279150            0   \n",
       "52049   Shopper_1            3  31.486702 -102.005952           20   \n",
       "95887   Shopper_1            1  33.061045 -107.106172           20   \n",
       "98815   Shopper_1            0  37.784038 -122.406711          108   \n",
       "78061   Shopper_1            1  31.971133 -103.575228           20   \n",
       "106999  Shopper_1            0  33.061063 -107.106165           20   \n",
       "78035   Shopper_1            0  37.784263 -122.405984          108   \n",
       "77973   Shopper_1            3  37.784085 -122.407135          119   \n",
       "100499  Shopper_1            3  37.784018 -122.407150          119   \n",
       "35762   Shopper_1            3  37.784052 -122.407079          119   \n",
       "71239   Shopper_1            3  37.784055 -122.407086          119   \n",
       "97924   Shopper_1            0  37.784075 -122.407065          108   \n",
       "102120  Shopper_1            0  37.784055 -122.407176          108   \n",
       "97101   Shopper_1            2  33.787407 -109.504903           20   \n",
       "47032   Shopper_1            0  37.784077 -122.407172          108   \n",
       "25665   Shopper_1            0  34.349141 -111.278963          116   \n",
       "25664   Shopper_1            3  35.085205 -113.663751           62   \n",
       "77426   Shopper_1            2  37.784041 -122.407108           43   \n",
       "97946   Shopper_1            1  35.265121 -114.246687           20   \n",
       "32914   Shopper_1            0  37.784059 -122.406598          108   \n",
       "...           ...          ...        ...         ...          ...   \n",
       "418     Shopper_1            1  30.227255  -97.925648           20   \n",
       "37372   Shopper_1            0  37.784085 -122.407009          108   \n",
       "21770   Shopper_1            0  33.968828 -110.133960           20   \n",
       "28495   Shopper_1            2  35.561458 -115.206698           63   \n",
       "28513   Shopper_1            1  34.349118 -111.279163           39   \n",
       "93921   Shopper_1            2  37.784079 -122.407114           43   \n",
       "50871   Shopper_1            1  33.565384 -108.788102           20   \n",
       "61183   Shopper_1            0  31.971140 -103.575216           20   \n",
       "50835   Shopper_1            3  34.877596 -112.991172           62   \n",
       "21547   Shopper_1            3  37.784064 -122.407207          119   \n",
       "61182   Shopper_1            4  35.756717 -115.930223           19   \n",
       "74866   Shopper_1            1  37.757750 -122.383892          128   \n",
       "74855   Shopper_1            2  37.762391 -122.388008           43   \n",
       "55291   Shopper_1            2  37.783956 -122.407213           43   \n",
       "74843   Shopper_1            3  37.784077 -122.407058          119   \n",
       "74806   Shopper_1            0  37.784168 -122.406034          108   \n",
       "74805   Shopper_1            1  34.635384 -112.206523           39   \n",
       "41665   Shopper_1            1  35.539867 -115.187304           14   \n",
       "50625   Shopper_1            0  35.644070 -115.570418           64   \n",
       "50624   Shopper_1            3  37.784065 -122.407157          119   \n",
       "93848   Shopper_1            1  32.746176 -106.086128           20   \n",
       "11819   Shopper_1            2  37.784077 -122.407058           43   \n",
       "85044   Shopper_1            0  28.338040  -91.805298           20   \n",
       "85045   Shopper_1            3  35.539812 -115.187564           62   \n",
       "11637   Shopper_1            0  37.784120 -122.406620          108   \n",
       "60944   Shopper_1            0  37.784048 -122.407212          108   \n",
       "85061   Shopper_1            2  34.635388 -112.206498            0   \n",
       "85080   Shopper_1            1  32.386344 -104.920316           20   \n",
       "74419   Shopper_1            1  33.585855 -108.806241           20   \n",
       "61181   Shopper_1            1  37.784032 -122.407175          128   \n",
       "\n",
       "                 Store_Name  Store_Index2  \n",
       "35181              Solstice            93  \n",
       "70238        Bloomingdale's             2  \n",
       "70264   ProActiv Solutions             93  \n",
       "40491             Cotton On            85  \n",
       "4777      Bath & Body Works            43  \n",
       "4776         Bloomingdale's            93  \n",
       "101158       Bloomingdale's             2  \n",
       "49054                PacSun            43  \n",
       "22621        Bloomingdale's            43  \n",
       "22620        Bloomingdale's             2  \n",
       "22619      49ers Team Store            85  \n",
       "52049        Bloomingdale's            20  \n",
       "95887        Bloomingdale's            20  \n",
       "98815   ProActiv Solutions             85  \n",
       "78061        Bloomingdale's            20  \n",
       "106999       Bloomingdale's            85  \n",
       "78035   ProActiv Solutions             85  \n",
       "77973              Solstice            20  \n",
       "100499             Solstice            93  \n",
       "35762              Solstice            22  \n",
       "71239              Solstice            93  \n",
       "97924   ProActiv Solutions             85  \n",
       "102120  ProActiv Solutions             20  \n",
       "97101        Bloomingdale's            43  \n",
       "47032   ProActiv Solutions             20  \n",
       "25665           Sarku Japan           119  \n",
       "25664                   H&M            20  \n",
       "77426             Cotton On            85  \n",
       "97946        Bloomingdale's            20  \n",
       "32914   ProActiv Solutions              2  \n",
       "...                     ...           ...  \n",
       "418          Bloomingdale's            31  \n",
       "37372   ProActiv Solutions              2  \n",
       "21770        Bloomingdale's            93  \n",
       "28495               H&M Man            22  \n",
       "28513     Club Monaco Women           119  \n",
       "93921             Cotton On             2  \n",
       "50871        Bloomingdale's             2  \n",
       "61183        Bloomingdale's            85  \n",
       "50835                   H&M           119  \n",
       "21547              Solstice           119  \n",
       "61182        Bespoke Events            20  \n",
       "74866             Swarovski            85  \n",
       "74855             Cotton On             2  \n",
       "55291             Cotton On            85  \n",
       "74843              Solstice            77  \n",
       "74806   ProActiv Solutions             85  \n",
       "74805     Club Monaco Women            20  \n",
       "41665                  BOSS            20  \n",
       "50625           Haagen Dazs            20  \n",
       "50624              Solstice            85  \n",
       "93848        Bloomingdale's            43  \n",
       "11819             Cotton On            20  \n",
       "85044        Bloomingdale's            93  \n",
       "85045                   H&M             2  \n",
       "11637   ProActiv Solutions              2  \n",
       "60944   ProActiv Solutions             85  \n",
       "85061      49ers Team Store             2  \n",
       "85080        Bloomingdale's            43  \n",
       "74419        Bloomingdale's             2  \n",
       "61181             Swarovski             2  \n",
       "\n",
       "[100 rows x 7 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mean accuracy: 0.0903614457831'"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#LOGISTIC REFGRESSION AND PREDICTING:\n",
    "from sklearn import linear_model\n",
    "clf= linear_model.LogisticRegression()\n",
    "train_features = X\n",
    "\n",
    "train_target = y\n",
    "\n",
    "# Fit the model to our training data\n",
    "clf = clf.fit(train_features, train_target)\n",
    "score = clf.score(train_features, train_target)\n",
    "\"Mean accuracy: {0}\".format(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf= neighbors.KNeighborsClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mean accuracy: 0.246987951807'"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_features = X\n",
    "\n",
    "train_target = y\n",
    "\n",
    "# Fit the model to our training data\n",
    "clf = clf.fit(train_features, train_target)\n",
    "score = clf.score(train_features, train_target)\n",
    "\"Mean accuracy: {0}\".format(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_y3 = clf.predict(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfo['Store_Index3'] = test_y3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Store_Index2</th>\n",
       "      <th>Store_Index3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70238</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.585825</td>\n",
       "      <td>-108.806374</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70264</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784023</td>\n",
       "      <td>-122.406786</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40491</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.761052</td>\n",
       "      <td>-122.386801</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4777</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4776</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>32.386375</td>\n",
       "      <td>-104.920369</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101158</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.005662</td>\n",
       "      <td>-110.166421</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49054</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.399517</td>\n",
       "      <td>-114.736228</td>\n",
       "      <td>99</td>\n",
       "      <td>PacSun</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22621</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.721647</td>\n",
       "      <td>-106.064451</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22620</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>17.523494</td>\n",
       "      <td>-56.901809</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22619</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.349167</td>\n",
       "      <td>-111.279150</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52049</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>31.486702</td>\n",
       "      <td>-102.005952</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95887</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.061045</td>\n",
       "      <td>-107.106172</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98815</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784038</td>\n",
       "      <td>-122.406711</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>31.971133</td>\n",
       "      <td>-103.575228</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106999</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.061063</td>\n",
       "      <td>-107.106165</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78035</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784263</td>\n",
       "      <td>-122.405984</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77973</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407135</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100499</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784018</td>\n",
       "      <td>-122.407150</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35762</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784052</td>\n",
       "      <td>-122.407079</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71239</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784055</td>\n",
       "      <td>-122.407086</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97924</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784075</td>\n",
       "      <td>-122.407065</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102120</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784055</td>\n",
       "      <td>-122.407176</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97101</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>33.787407</td>\n",
       "      <td>-109.504903</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47032</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407172</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>34.349141</td>\n",
       "      <td>-111.278963</td>\n",
       "      <td>116</td>\n",
       "      <td>Sarku Japan</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25664</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.085205</td>\n",
       "      <td>-113.663751</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77426</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784041</td>\n",
       "      <td>-122.407108</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97946</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.265121</td>\n",
       "      <td>-114.246687</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32914</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784059</td>\n",
       "      <td>-122.406598</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>30.227255</td>\n",
       "      <td>-97.925648</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>31</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37372</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407009</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21770</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.968828</td>\n",
       "      <td>-110.133960</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28495</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>35.561458</td>\n",
       "      <td>-115.206698</td>\n",
       "      <td>63</td>\n",
       "      <td>H&amp;M Man</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28513</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.349118</td>\n",
       "      <td>-111.279163</td>\n",
       "      <td>39</td>\n",
       "      <td>Club Monaco Women</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93921</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784079</td>\n",
       "      <td>-122.407114</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50871</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.565384</td>\n",
       "      <td>-108.788102</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61183</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>31.971140</td>\n",
       "      <td>-103.575216</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50835</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>34.877596</td>\n",
       "      <td>-112.991172</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21547</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784064</td>\n",
       "      <td>-122.407207</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61182</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>4</td>\n",
       "      <td>35.756717</td>\n",
       "      <td>-115.930223</td>\n",
       "      <td>19</td>\n",
       "      <td>Bespoke Events</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74866</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.757750</td>\n",
       "      <td>-122.383892</td>\n",
       "      <td>128</td>\n",
       "      <td>Swarovski</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74855</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55291</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.783956</td>\n",
       "      <td>-122.407213</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74843</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>77</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74806</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784168</td>\n",
       "      <td>-122.406034</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74805</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.635384</td>\n",
       "      <td>-112.206523</td>\n",
       "      <td>39</td>\n",
       "      <td>Club Monaco Women</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.539867</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>14</td>\n",
       "      <td>BOSS</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50625</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.644070</td>\n",
       "      <td>-115.570418</td>\n",
       "      <td>64</td>\n",
       "      <td>Haagen Dazs</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50624</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784065</td>\n",
       "      <td>-122.407157</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93848</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.746176</td>\n",
       "      <td>-106.086128</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11819</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85044</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.338040</td>\n",
       "      <td>-91.805298</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85045</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.539812</td>\n",
       "      <td>-115.187564</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11637</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784120</td>\n",
       "      <td>-122.406620</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60944</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784048</td>\n",
       "      <td>-122.407212</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.635388</td>\n",
       "      <td>-112.206498</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85080</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.386344</td>\n",
       "      <td>-104.920316</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74419</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.585855</td>\n",
       "      <td>-108.806241</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.784032</td>\n",
       "      <td>-122.407175</td>\n",
       "      <td>128</td>\n",
       "      <td>Swarovski</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Shopper_ID  Floor_Index   latitude   longitude  Store_Index  \\\n",
       "35181   Shopper_1            3  37.762391 -122.388008          119   \n",
       "70238   Shopper_1            0  33.585825 -108.806374           20   \n",
       "70264   Shopper_1            0  37.784023 -122.406786          108   \n",
       "40491   Shopper_1            2  37.761052 -122.386801           43   \n",
       "4777    Shopper_1            3  35.664542 -115.588398           16   \n",
       "4776    Shopper_1            0  32.386375 -104.920369           20   \n",
       "101158  Shopper_1            1  34.005662 -110.166421           20   \n",
       "49054   Shopper_1            0  35.399517 -114.736228           99   \n",
       "22621   Shopper_1            1  32.721647 -106.064451           20   \n",
       "22620   Shopper_1            0  17.523494  -56.901809           20   \n",
       "22619   Shopper_1            2  34.349167 -111.279150            0   \n",
       "52049   Shopper_1            3  31.486702 -102.005952           20   \n",
       "95887   Shopper_1            1  33.061045 -107.106172           20   \n",
       "98815   Shopper_1            0  37.784038 -122.406711          108   \n",
       "78061   Shopper_1            1  31.971133 -103.575228           20   \n",
       "106999  Shopper_1            0  33.061063 -107.106165           20   \n",
       "78035   Shopper_1            0  37.784263 -122.405984          108   \n",
       "77973   Shopper_1            3  37.784085 -122.407135          119   \n",
       "100499  Shopper_1            3  37.784018 -122.407150          119   \n",
       "35762   Shopper_1            3  37.784052 -122.407079          119   \n",
       "71239   Shopper_1            3  37.784055 -122.407086          119   \n",
       "97924   Shopper_1            0  37.784075 -122.407065          108   \n",
       "102120  Shopper_1            0  37.784055 -122.407176          108   \n",
       "97101   Shopper_1            2  33.787407 -109.504903           20   \n",
       "47032   Shopper_1            0  37.784077 -122.407172          108   \n",
       "25665   Shopper_1            0  34.349141 -111.278963          116   \n",
       "25664   Shopper_1            3  35.085205 -113.663751           62   \n",
       "77426   Shopper_1            2  37.784041 -122.407108           43   \n",
       "97946   Shopper_1            1  35.265121 -114.246687           20   \n",
       "32914   Shopper_1            0  37.784059 -122.406598          108   \n",
       "...           ...          ...        ...         ...          ...   \n",
       "418     Shopper_1            1  30.227255  -97.925648           20   \n",
       "37372   Shopper_1            0  37.784085 -122.407009          108   \n",
       "21770   Shopper_1            0  33.968828 -110.133960           20   \n",
       "28495   Shopper_1            2  35.561458 -115.206698           63   \n",
       "28513   Shopper_1            1  34.349118 -111.279163           39   \n",
       "93921   Shopper_1            2  37.784079 -122.407114           43   \n",
       "50871   Shopper_1            1  33.565384 -108.788102           20   \n",
       "61183   Shopper_1            0  31.971140 -103.575216           20   \n",
       "50835   Shopper_1            3  34.877596 -112.991172           62   \n",
       "21547   Shopper_1            3  37.784064 -122.407207          119   \n",
       "61182   Shopper_1            4  35.756717 -115.930223           19   \n",
       "74866   Shopper_1            1  37.757750 -122.383892          128   \n",
       "74855   Shopper_1            2  37.762391 -122.388008           43   \n",
       "55291   Shopper_1            2  37.783956 -122.407213           43   \n",
       "74843   Shopper_1            3  37.784077 -122.407058          119   \n",
       "74806   Shopper_1            0  37.784168 -122.406034          108   \n",
       "74805   Shopper_1            1  34.635384 -112.206523           39   \n",
       "41665   Shopper_1            1  35.539867 -115.187304           14   \n",
       "50625   Shopper_1            0  35.644070 -115.570418           64   \n",
       "50624   Shopper_1            3  37.784065 -122.407157          119   \n",
       "93848   Shopper_1            1  32.746176 -106.086128           20   \n",
       "11819   Shopper_1            2  37.784077 -122.407058           43   \n",
       "85044   Shopper_1            0  28.338040  -91.805298           20   \n",
       "85045   Shopper_1            3  35.539812 -115.187564           62   \n",
       "11637   Shopper_1            0  37.784120 -122.406620          108   \n",
       "60944   Shopper_1            0  37.784048 -122.407212          108   \n",
       "85061   Shopper_1            2  34.635388 -112.206498            0   \n",
       "85080   Shopper_1            1  32.386344 -104.920316           20   \n",
       "74419   Shopper_1            1  33.585855 -108.806241           20   \n",
       "61181   Shopper_1            1  37.784032 -122.407175          128   \n",
       "\n",
       "                 Store_Name  Store_Index2  Store_Index3  \n",
       "35181              Solstice            93            27  \n",
       "70238        Bloomingdale's             2             2  \n",
       "70264   ProActiv Solutions             93            27  \n",
       "40491             Cotton On            85            45  \n",
       "4777      Bath & Body Works            43            11  \n",
       "4776         Bloomingdale's            93            27  \n",
       "101158       Bloomingdale's             2             2  \n",
       "49054                PacSun            43            11  \n",
       "22621        Bloomingdale's            43            11  \n",
       "22620        Bloomingdale's             2             2  \n",
       "22619      49ers Team Store            85            45  \n",
       "52049        Bloomingdale's            20             0  \n",
       "95887        Bloomingdale's            20            22  \n",
       "98815   ProActiv Solutions             85            45  \n",
       "78061        Bloomingdale's            20            20  \n",
       "106999       Bloomingdale's            85            45  \n",
       "78035   ProActiv Solutions             85            45  \n",
       "77973              Solstice            20             0  \n",
       "100499             Solstice            93            27  \n",
       "35762              Solstice            22            22  \n",
       "71239              Solstice            93            27  \n",
       "97924   ProActiv Solutions             85            45  \n",
       "102120  ProActiv Solutions             20             0  \n",
       "97101        Bloomingdale's            43            11  \n",
       "47032   ProActiv Solutions             20            20  \n",
       "25665           Sarku Japan           119            55  \n",
       "25664                   H&M            20            16  \n",
       "77426             Cotton On            85            45  \n",
       "97946        Bloomingdale's            20             0  \n",
       "32914   ProActiv Solutions              2             2  \n",
       "...                     ...           ...           ...  \n",
       "418          Bloomingdale's            31            16  \n",
       "37372   ProActiv Solutions              2             2  \n",
       "21770        Bloomingdale's            93            27  \n",
       "28495               H&M Man            22            22  \n",
       "28513     Club Monaco Women           119            55  \n",
       "93921             Cotton On             2             2  \n",
       "50871        Bloomingdale's             2             2  \n",
       "61183        Bloomingdale's            85            45  \n",
       "50835                   H&M           119            55  \n",
       "21547              Solstice           119            55  \n",
       "61182        Bespoke Events            20            20  \n",
       "74866             Swarovski            85            45  \n",
       "74855             Cotton On             2             2  \n",
       "55291             Cotton On            85            45  \n",
       "74843              Solstice            77            45  \n",
       "74806   ProActiv Solutions             85            45  \n",
       "74805     Club Monaco Women            20            20  \n",
       "41665                  BOSS            20            20  \n",
       "50625           Haagen Dazs            20            20  \n",
       "50624              Solstice            85            45  \n",
       "93848        Bloomingdale's            43            11  \n",
       "11819             Cotton On            20            16  \n",
       "85044        Bloomingdale's            93            27  \n",
       "85045                   H&M             2             2  \n",
       "11637   ProActiv Solutions              2             2  \n",
       "60944   ProActiv Solutions             85            45  \n",
       "85061      49ers Team Store             2             2  \n",
       "85080        Bloomingdale's            43            11  \n",
       "74419        Bloomingdale's             2             2  \n",
       "61181             Swarovski             2             2  \n",
       "\n",
       "[100 rows x 8 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "inv_class_mapping = {v: k for k, v in store_mapping.items()}\n",
    "pinginfo['Store_Name3'] = pinginfo['Store_Index3'].map(inv_class_mapping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Store_Index2</th>\n",
       "      <th>Store_Index3</th>\n",
       "      <th>Store_Name3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70238</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.585825</td>\n",
       "      <td>-108.806374</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70264</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784023</td>\n",
       "      <td>-122.406786</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40491</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.761052</td>\n",
       "      <td>-122.386801</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4777</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>Auntie Anne's Pretzels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4776</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>32.386375</td>\n",
       "      <td>-104.920369</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101158</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.005662</td>\n",
       "      <td>-110.166421</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49054</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.399517</td>\n",
       "      <td>-114.736228</td>\n",
       "      <td>99</td>\n",
       "      <td>PacSun</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>Auntie Anne's Pretzels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22621</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.721647</td>\n",
       "      <td>-106.064451</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>Auntie Anne's Pretzels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22620</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>17.523494</td>\n",
       "      <td>-56.901809</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22619</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.349167</td>\n",
       "      <td>-111.279150</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52049</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>31.486702</td>\n",
       "      <td>-102.005952</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95887</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.061045</td>\n",
       "      <td>-107.106172</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>22</td>\n",
       "      <td>Brighton Collectibles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98815</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784038</td>\n",
       "      <td>-122.406711</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>31.971133</td>\n",
       "      <td>-103.575228</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106999</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.061063</td>\n",
       "      <td>-107.106165</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78035</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784263</td>\n",
       "      <td>-122.405984</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77973</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407135</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100499</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784018</td>\n",
       "      <td>-122.407150</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35762</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784052</td>\n",
       "      <td>-122.407079</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>Brighton Collectibles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71239</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784055</td>\n",
       "      <td>-122.407086</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97924</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784075</td>\n",
       "      <td>-122.407065</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102120</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784055</td>\n",
       "      <td>-122.407176</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97101</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>33.787407</td>\n",
       "      <td>-109.504903</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>Auntie Anne's Pretzels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47032</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407172</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>34.349141</td>\n",
       "      <td>-111.278963</td>\n",
       "      <td>116</td>\n",
       "      <td>Sarku Japan</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "      <td>Fossil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25664</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.085205</td>\n",
       "      <td>-113.663751</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77426</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784041</td>\n",
       "      <td>-122.407108</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97946</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.265121</td>\n",
       "      <td>-114.246687</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32914</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784059</td>\n",
       "      <td>-122.406598</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>30.227255</td>\n",
       "      <td>-97.925648</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>31</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37372</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784085</td>\n",
       "      <td>-122.407009</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21770</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.968828</td>\n",
       "      <td>-110.133960</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28495</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>35.561458</td>\n",
       "      <td>-115.206698</td>\n",
       "      <td>63</td>\n",
       "      <td>H&amp;M Man</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>Brighton Collectibles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28513</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.349118</td>\n",
       "      <td>-111.279163</td>\n",
       "      <td>39</td>\n",
       "      <td>Club Monaco Women</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "      <td>Fossil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93921</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784079</td>\n",
       "      <td>-122.407114</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50871</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.565384</td>\n",
       "      <td>-108.788102</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61183</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>31.971140</td>\n",
       "      <td>-103.575216</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50835</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>34.877596</td>\n",
       "      <td>-112.991172</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "      <td>Fossil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21547</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784064</td>\n",
       "      <td>-122.407207</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "      <td>Fossil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61182</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>4</td>\n",
       "      <td>35.756717</td>\n",
       "      <td>-115.930223</td>\n",
       "      <td>19</td>\n",
       "      <td>Bespoke Events</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74866</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.757750</td>\n",
       "      <td>-122.383892</td>\n",
       "      <td>128</td>\n",
       "      <td>Swarovski</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74855</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55291</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.783956</td>\n",
       "      <td>-122.407213</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74843</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>77</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74806</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784168</td>\n",
       "      <td>-122.406034</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74805</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>34.635384</td>\n",
       "      <td>-112.206523</td>\n",
       "      <td>39</td>\n",
       "      <td>Club Monaco Women</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41665</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.539867</td>\n",
       "      <td>-115.187304</td>\n",
       "      <td>14</td>\n",
       "      <td>BOSS</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50625</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.644070</td>\n",
       "      <td>-115.570418</td>\n",
       "      <td>64</td>\n",
       "      <td>Haagen Dazs</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50624</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.784065</td>\n",
       "      <td>-122.407157</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93848</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.746176</td>\n",
       "      <td>-106.086128</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>Auntie Anne's Pretzels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11819</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.784077</td>\n",
       "      <td>-122.407058</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85044</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>28.338040</td>\n",
       "      <td>-91.805298</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>93</td>\n",
       "      <td>27</td>\n",
       "      <td>Burke Williams Day Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85045</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.539812</td>\n",
       "      <td>-115.187564</td>\n",
       "      <td>62</td>\n",
       "      <td>H&amp;M</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11637</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784120</td>\n",
       "      <td>-122.406620</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60944</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784048</td>\n",
       "      <td>-122.407212</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>85</td>\n",
       "      <td>45</td>\n",
       "      <td>DAVIDsTEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85061</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>34.635388</td>\n",
       "      <td>-112.206498</td>\n",
       "      <td>0</td>\n",
       "      <td>49ers Team Store</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85080</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.386344</td>\n",
       "      <td>-104.920316</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>Auntie Anne's Pretzels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74419</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>33.585855</td>\n",
       "      <td>-108.806241</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>1</td>\n",
       "      <td>37.784032</td>\n",
       "      <td>-122.407175</td>\n",
       "      <td>128</td>\n",
       "      <td>Swarovski</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Adidas</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Shopper_ID  Floor_Index   latitude   longitude  Store_Index  \\\n",
       "35181   Shopper_1            3  37.762391 -122.388008          119   \n",
       "70238   Shopper_1            0  33.585825 -108.806374           20   \n",
       "70264   Shopper_1            0  37.784023 -122.406786          108   \n",
       "40491   Shopper_1            2  37.761052 -122.386801           43   \n",
       "4777    Shopper_1            3  35.664542 -115.588398           16   \n",
       "4776    Shopper_1            0  32.386375 -104.920369           20   \n",
       "101158  Shopper_1            1  34.005662 -110.166421           20   \n",
       "49054   Shopper_1            0  35.399517 -114.736228           99   \n",
       "22621   Shopper_1            1  32.721647 -106.064451           20   \n",
       "22620   Shopper_1            0  17.523494  -56.901809           20   \n",
       "22619   Shopper_1            2  34.349167 -111.279150            0   \n",
       "52049   Shopper_1            3  31.486702 -102.005952           20   \n",
       "95887   Shopper_1            1  33.061045 -107.106172           20   \n",
       "98815   Shopper_1            0  37.784038 -122.406711          108   \n",
       "78061   Shopper_1            1  31.971133 -103.575228           20   \n",
       "106999  Shopper_1            0  33.061063 -107.106165           20   \n",
       "78035   Shopper_1            0  37.784263 -122.405984          108   \n",
       "77973   Shopper_1            3  37.784085 -122.407135          119   \n",
       "100499  Shopper_1            3  37.784018 -122.407150          119   \n",
       "35762   Shopper_1            3  37.784052 -122.407079          119   \n",
       "71239   Shopper_1            3  37.784055 -122.407086          119   \n",
       "97924   Shopper_1            0  37.784075 -122.407065          108   \n",
       "102120  Shopper_1            0  37.784055 -122.407176          108   \n",
       "97101   Shopper_1            2  33.787407 -109.504903           20   \n",
       "47032   Shopper_1            0  37.784077 -122.407172          108   \n",
       "25665   Shopper_1            0  34.349141 -111.278963          116   \n",
       "25664   Shopper_1            3  35.085205 -113.663751           62   \n",
       "77426   Shopper_1            2  37.784041 -122.407108           43   \n",
       "97946   Shopper_1            1  35.265121 -114.246687           20   \n",
       "32914   Shopper_1            0  37.784059 -122.406598          108   \n",
       "...           ...          ...        ...         ...          ...   \n",
       "418     Shopper_1            1  30.227255  -97.925648           20   \n",
       "37372   Shopper_1            0  37.784085 -122.407009          108   \n",
       "21770   Shopper_1            0  33.968828 -110.133960           20   \n",
       "28495   Shopper_1            2  35.561458 -115.206698           63   \n",
       "28513   Shopper_1            1  34.349118 -111.279163           39   \n",
       "93921   Shopper_1            2  37.784079 -122.407114           43   \n",
       "50871   Shopper_1            1  33.565384 -108.788102           20   \n",
       "61183   Shopper_1            0  31.971140 -103.575216           20   \n",
       "50835   Shopper_1            3  34.877596 -112.991172           62   \n",
       "21547   Shopper_1            3  37.784064 -122.407207          119   \n",
       "61182   Shopper_1            4  35.756717 -115.930223           19   \n",
       "74866   Shopper_1            1  37.757750 -122.383892          128   \n",
       "74855   Shopper_1            2  37.762391 -122.388008           43   \n",
       "55291   Shopper_1            2  37.783956 -122.407213           43   \n",
       "74843   Shopper_1            3  37.784077 -122.407058          119   \n",
       "74806   Shopper_1            0  37.784168 -122.406034          108   \n",
       "74805   Shopper_1            1  34.635384 -112.206523           39   \n",
       "41665   Shopper_1            1  35.539867 -115.187304           14   \n",
       "50625   Shopper_1            0  35.644070 -115.570418           64   \n",
       "50624   Shopper_1            3  37.784065 -122.407157          119   \n",
       "93848   Shopper_1            1  32.746176 -106.086128           20   \n",
       "11819   Shopper_1            2  37.784077 -122.407058           43   \n",
       "85044   Shopper_1            0  28.338040  -91.805298           20   \n",
       "85045   Shopper_1            3  35.539812 -115.187564           62   \n",
       "11637   Shopper_1            0  37.784120 -122.406620          108   \n",
       "60944   Shopper_1            0  37.784048 -122.407212          108   \n",
       "85061   Shopper_1            2  34.635388 -112.206498            0   \n",
       "85080   Shopper_1            1  32.386344 -104.920316           20   \n",
       "74419   Shopper_1            1  33.585855 -108.806241           20   \n",
       "61181   Shopper_1            1  37.784032 -122.407175          128   \n",
       "\n",
       "                 Store_Name  Store_Index2  Store_Index3  \\\n",
       "35181              Solstice            93            27   \n",
       "70238        Bloomingdale's             2             2   \n",
       "70264   ProActiv Solutions             93            27   \n",
       "40491             Cotton On            85            45   \n",
       "4777      Bath & Body Works            43            11   \n",
       "4776         Bloomingdale's            93            27   \n",
       "101158       Bloomingdale's             2             2   \n",
       "49054                PacSun            43            11   \n",
       "22621        Bloomingdale's            43            11   \n",
       "22620        Bloomingdale's             2             2   \n",
       "22619      49ers Team Store            85            45   \n",
       "52049        Bloomingdale's            20             0   \n",
       "95887        Bloomingdale's            20            22   \n",
       "98815   ProActiv Solutions             85            45   \n",
       "78061        Bloomingdale's            20            20   \n",
       "106999       Bloomingdale's            85            45   \n",
       "78035   ProActiv Solutions             85            45   \n",
       "77973              Solstice            20             0   \n",
       "100499             Solstice            93            27   \n",
       "35762              Solstice            22            22   \n",
       "71239              Solstice            93            27   \n",
       "97924   ProActiv Solutions             85            45   \n",
       "102120  ProActiv Solutions             20             0   \n",
       "97101        Bloomingdale's            43            11   \n",
       "47032   ProActiv Solutions             20            20   \n",
       "25665           Sarku Japan           119            55   \n",
       "25664                   H&M            20            16   \n",
       "77426             Cotton On            85            45   \n",
       "97946        Bloomingdale's            20             0   \n",
       "32914   ProActiv Solutions              2             2   \n",
       "...                     ...           ...           ...   \n",
       "418          Bloomingdale's            31            16   \n",
       "37372   ProActiv Solutions              2             2   \n",
       "21770        Bloomingdale's            93            27   \n",
       "28495               H&M Man            22            22   \n",
       "28513     Club Monaco Women           119            55   \n",
       "93921             Cotton On             2             2   \n",
       "50871        Bloomingdale's             2             2   \n",
       "61183        Bloomingdale's            85            45   \n",
       "50835                   H&M           119            55   \n",
       "21547              Solstice           119            55   \n",
       "61182        Bespoke Events            20            20   \n",
       "74866             Swarovski            85            45   \n",
       "74855             Cotton On             2             2   \n",
       "55291             Cotton On            85            45   \n",
       "74843              Solstice            77            45   \n",
       "74806   ProActiv Solutions             85            45   \n",
       "74805     Club Monaco Women            20            20   \n",
       "41665                  BOSS            20            20   \n",
       "50625           Haagen Dazs            20            20   \n",
       "50624              Solstice            85            45   \n",
       "93848        Bloomingdale's            43            11   \n",
       "11819             Cotton On            20            16   \n",
       "85044        Bloomingdale's            93            27   \n",
       "85045                   H&M             2             2   \n",
       "11637   ProActiv Solutions              2             2   \n",
       "60944   ProActiv Solutions             85            45   \n",
       "85061      49ers Team Store             2             2   \n",
       "85080        Bloomingdale's            43            11   \n",
       "74419        Bloomingdale's             2             2   \n",
       "61181             Swarovski             2             2   \n",
       "\n",
       "                   Store_Name3  \n",
       "35181   Burke Williams Day Spa  \n",
       "70238                   Adidas  \n",
       "70264   Burke Williams Day Spa  \n",
       "40491                DAVIDsTEA  \n",
       "4777    Auntie Anne's Pretzels  \n",
       "4776    Burke Williams Day Spa  \n",
       "101158                  Adidas  \n",
       "49054   Auntie Anne's Pretzels  \n",
       "22621   Auntie Anne's Pretzels  \n",
       "22620                   Adidas  \n",
       "22619                DAVIDsTEA  \n",
       "52049         49ers Team Store  \n",
       "95887    Brighton Collectibles  \n",
       "98815                DAVIDsTEA  \n",
       "78061           Bloomingdale's  \n",
       "106999               DAVIDsTEA  \n",
       "78035                DAVIDsTEA  \n",
       "77973         49ers Team Store  \n",
       "100499  Burke Williams Day Spa  \n",
       "35762    Brighton Collectibles  \n",
       "71239   Burke Williams Day Spa  \n",
       "97924                DAVIDsTEA  \n",
       "102120        49ers Team Store  \n",
       "97101   Auntie Anne's Pretzels  \n",
       "47032           Bloomingdale's  \n",
       "25665                   Fossil  \n",
       "25664        Bath & Body Works  \n",
       "77426                DAVIDsTEA  \n",
       "97946         49ers Team Store  \n",
       "32914                   Adidas  \n",
       "...                        ...  \n",
       "418          Bath & Body Works  \n",
       "37372                   Adidas  \n",
       "21770   Burke Williams Day Spa  \n",
       "28495    Brighton Collectibles  \n",
       "28513                   Fossil  \n",
       "93921                   Adidas  \n",
       "50871                   Adidas  \n",
       "61183                DAVIDsTEA  \n",
       "50835                   Fossil  \n",
       "21547                   Fossil  \n",
       "61182           Bloomingdale's  \n",
       "74866                DAVIDsTEA  \n",
       "74855                   Adidas  \n",
       "55291                DAVIDsTEA  \n",
       "74843                DAVIDsTEA  \n",
       "74806                DAVIDsTEA  \n",
       "74805           Bloomingdale's  \n",
       "41665           Bloomingdale's  \n",
       "50625           Bloomingdale's  \n",
       "50624                DAVIDsTEA  \n",
       "93848   Auntie Anne's Pretzels  \n",
       "11819        Bath & Body Works  \n",
       "85044   Burke Williams Day Spa  \n",
       "85045                   Adidas  \n",
       "11637                   Adidas  \n",
       "60944                DAVIDsTEA  \n",
       "85061                   Adidas  \n",
       "85080   Auntie Anne's Pretzels  \n",
       "74419                   Adidas  \n",
       "61181                   Adidas  \n",
       "\n",
       "[100 rows x 9 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfo.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pinginfo.groupby(['Shopper_ID', 'Store_Name3']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "df_freq3 = pinginfo.groupby(by='Shopper_ID').Store_Name3.apply(stats.mode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Shopper_ID\n",
       "Shopper_1         ([Adidas], [41])\n",
       "Shopper_10     ([DAVIDsTEA], [46])\n",
       "Shopper_100    ([DAVIDsTEA], [48])\n",
       "Shopper_101    ([DAVIDsTEA], [46])\n",
       "Shopper_102    ([DAVIDsTEA], [55])\n",
       "Shopper_103    ([DAVIDsTEA], [44])\n",
       "Shopper_104    ([DAVIDsTEA], [45])\n",
       "Shopper_105    ([DAVIDsTEA], [48])\n",
       "Shopper_106    ([DAVIDsTEA], [41])\n",
       "Shopper_107    ([DAVIDsTEA], [53])\n",
       "Shopper_108    ([DAVIDsTEA], [61])\n",
       "Shopper_109    ([DAVIDsTEA], [40])\n",
       "Shopper_11        ([Adidas], [39])\n",
       "Shopper_110    ([DAVIDsTEA], [53])\n",
       "Shopper_111    ([DAVIDsTEA], [63])\n",
       "Shopper_112    ([DAVIDsTEA], [42])\n",
       "Shopper_113    ([DAVIDsTEA], [53])\n",
       "Shopper_114    ([DAVIDsTEA], [49])\n",
       "Shopper_115    ([DAVIDsTEA], [51])\n",
       "Shopper_116    ([DAVIDsTEA], [44])\n",
       "Shopper_117    ([DAVIDsTEA], [41])\n",
       "Shopper_118    ([DAVIDsTEA], [42])\n",
       "Shopper_119    ([DAVIDsTEA], [47])\n",
       "Shopper_12     ([DAVIDsTEA], [45])\n",
       "Shopper_120    ([DAVIDsTEA], [54])\n",
       "Shopper_121    ([DAVIDsTEA], [40])\n",
       "Shopper_122    ([DAVIDsTEA], [46])\n",
       "Shopper_123    ([DAVIDsTEA], [50])\n",
       "Shopper_124       ([Adidas], [43])\n",
       "Shopper_125    ([DAVIDsTEA], [48])\n",
       "                      ...         \n",
       "Shopper_72     ([DAVIDsTEA], [50])\n",
       "Shopper_73     ([DAVIDsTEA], [45])\n",
       "Shopper_74        ([Adidas], [48])\n",
       "Shopper_75     ([DAVIDsTEA], [52])\n",
       "Shopper_76     ([DAVIDsTEA], [58])\n",
       "Shopper_77     ([DAVIDsTEA], [52])\n",
       "Shopper_78     ([DAVIDsTEA], [42])\n",
       "Shopper_79     ([DAVIDsTEA], [43])\n",
       "Shopper_8      ([DAVIDsTEA], [55])\n",
       "Shopper_80     ([DAVIDsTEA], [54])\n",
       "Shopper_81     ([DAVIDsTEA], [49])\n",
       "Shopper_82     ([DAVIDsTEA], [51])\n",
       "Shopper_83     ([DAVIDsTEA], [57])\n",
       "Shopper_84     ([DAVIDsTEA], [57])\n",
       "Shopper_85     ([DAVIDsTEA], [44])\n",
       "Shopper_86     ([DAVIDsTEA], [50])\n",
       "Shopper_87     ([DAVIDsTEA], [56])\n",
       "Shopper_88     ([DAVIDsTEA], [54])\n",
       "Shopper_89     ([DAVIDsTEA], [57])\n",
       "Shopper_9      ([DAVIDsTEA], [51])\n",
       "Shopper_90     ([DAVIDsTEA], [51])\n",
       "Shopper_91     ([DAVIDsTEA], [60])\n",
       "Shopper_92     ([DAVIDsTEA], [50])\n",
       "Shopper_93     ([DAVIDsTEA], [46])\n",
       "Shopper_94     ([DAVIDsTEA], [43])\n",
       "Shopper_95     ([DAVIDsTEA], [47])\n",
       "Shopper_96     ([DAVIDsTEA], [43])\n",
       "Shopper_97     ([DAVIDsTEA], [42])\n",
       "Shopper_98     ([DAVIDsTEA], [48])\n",
       "Shopper_99     ([DAVIDsTEA], [44])\n",
       "Name: Store_Name3, Length: 567, dtype: object"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "#NOW FIND MOST STORE VISITED:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name  Floor_Index   latitude   longitude  \\\n",
       "0                         Jamba Juice            0  37.784091 -122.406813   \n",
       "1              Coriander Gourmet Thai            0  37.784596 -122.406210   \n",
       "2                      NYS Collection            0  37.784396 -122.406587   \n",
       "3                            Hallmark            0  37.783771 -122.407377   \n",
       "4  Sorabol Korean BBQ & Asian Noodles            0  37.784601 -122.406328   \n",
       "\n",
       "   Store_Index  \n",
       "0           69  \n",
       "1           41  \n",
       "2           91  \n",
       "3           65  \n",
       "4          120  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70238</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.585825</td>\n",
       "      <td>-108.806374</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70264</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784023</td>\n",
       "      <td>-122.406786</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40491</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.761052</td>\n",
       "      <td>-122.386801</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4777</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Shopper_ID  Floor_Index   latitude   longitude  Store_Index  \\\n",
       "35181  Shopper_1            3  37.762391 -122.388008          119   \n",
       "70238  Shopper_1            0  33.585825 -108.806374           20   \n",
       "70264  Shopper_1            0  37.784023 -122.406786          108   \n",
       "40491  Shopper_1            2  37.761052 -122.386801           43   \n",
       "4777   Shopper_1            3  35.664542 -115.588398           16   \n",
       "\n",
       "                Store_Name  \n",
       "35181             Solstice  \n",
       "70238       Bloomingdale's  \n",
       "70264  ProActiv Solutions   \n",
       "40491            Cotton On  \n",
       "4777     Bath & Body Works  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfonew=pinginfo.drop(['Store_Index2', 'Store_Index3','Store_Name3'], axis=1)\n",
    "pinginfonew.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Broad_Category</th>\n",
       "      <th>Fine_Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Amazon Pop-Up</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bespoke Events</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bespoke Coworking</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Specialty Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Dyson</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Penhaligonï¿½Ûªs</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Store_Name Broad_Category    Fine_Category\n",
       "0      Amazon Pop-Up         Retail            Misc.\n",
       "1     Bespoke Events         Retail            Misc.\n",
       "2  Bespoke Coworking         Retail  Specialty Store\n",
       "3              Dyson         Retail            Misc.\n",
       "4   Penhaligonï¿½Ûªs         Retail            Misc."
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorymapping.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>New_Store</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Shopper_1</th>\n",
       "      <td>([Bloomingdale's], [64])</td>\n",
       "      <td>Bloomingdale's</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_10</th>\n",
       "      <td>([TAP 415], [80])</td>\n",
       "      <td>TAP 415</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_100</th>\n",
       "      <td>([ProActiv Solutions ], [58])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_101</th>\n",
       "      <td>([Swarovski], [53])</td>\n",
       "      <td>Swarovski</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_102</th>\n",
       "      <td>([TAP 415], [125])</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_103</th>\n",
       "      <td>([Cotton On], [52])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_104</th>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_105</th>\n",
       "      <td>([ProActiv Solutions ], [61])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_106</th>\n",
       "      <td>([ProActiv Solutions ], [63])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_107</th>\n",
       "      <td>([ProActiv Solutions ], [61])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_108</th>\n",
       "      <td>([ProActiv Solutions ], [105])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_109</th>\n",
       "      <td>([Bloomingdale's], [56])</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_11</th>\n",
       "      <td>([ProActiv Solutions ], [72])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_110</th>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
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       "    <tr>\n",
       "      <th>Shopper_111</th>\n",
       "      <td>([Swarovski], [56])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_112</th>\n",
       "      <td>([ProActiv Solutions ], [77])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_113</th>\n",
       "      <td>([ProActiv Solutions ], [97])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_114</th>\n",
       "      <td>([TAP 415], [90])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_115</th>\n",
       "      <td>([Cotton On], [55])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_116</th>\n",
       "      <td>([TAP 415], [167])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_117</th>\n",
       "      <td>([ProActiv Solutions ], [133])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_118</th>\n",
       "      <td>([Cotton On], [45])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_119</th>\n",
       "      <td>([Swarovski], [119])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_12</th>\n",
       "      <td>([ProActiv Solutions ], [32])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_120</th>\n",
       "      <td>([Swarovski], [59])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_121</th>\n",
       "      <td>([ProActiv Solutions ], [44])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_122</th>\n",
       "      <td>([TAP 415], [49])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_123</th>\n",
       "      <td>([Swarovski], [72])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_124</th>\n",
       "      <td>([ProActiv Solutions ], [75])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_125</th>\n",
       "      <td>([Cotton On], [41])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_72</th>\n",
       "      <td>([TAP 415], [59])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_73</th>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_74</th>\n",
       "      <td>([ProActiv Solutions ], [60])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_75</th>\n",
       "      <td>([Swarovski], [56])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_76</th>\n",
       "      <td>([ProActiv Solutions ], [116])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_77</th>\n",
       "      <td>([TAP 415], [41])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_78</th>\n",
       "      <td>([Cotton On], [54])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_79</th>\n",
       "      <td>([Cotton On], [55])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_8</th>\n",
       "      <td>([Swarovski], [57])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_80</th>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_81</th>\n",
       "      <td>([ProActiv Solutions ], [46])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_82</th>\n",
       "      <td>([TAP 415], [56])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_83</th>\n",
       "      <td>([ProActiv Solutions ], [58])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_84</th>\n",
       "      <td>([TAP 415], [86])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_85</th>\n",
       "      <td>([ProActiv Solutions ], [107])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_86</th>\n",
       "      <td>([ProActiv Solutions ], [57])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_87</th>\n",
       "      <td>([TAP 415], [38])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_88</th>\n",
       "      <td>([Swarovski], [45])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_89</th>\n",
       "      <td>([ProActiv Solutions ], [76])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_9</th>\n",
       "      <td>([ProActiv Solutions ], [73])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_90</th>\n",
       "      <td>([Swarovski], [67])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_91</th>\n",
       "      <td>([ProActiv Solutions ], [77])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_92</th>\n",
       "      <td>([ProActiv Solutions ], [71])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_93</th>\n",
       "      <td>([TAP 415], [51])</td>\n",
       "      <td>TAP 415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_94</th>\n",
       "      <td>([Cotton On], [57])</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_95</th>\n",
       "      <td>([Swarovski], [86])</td>\n",
       "      <td>Swarovski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_96</th>\n",
       "      <td>([Solstice], [38])</td>\n",
       "      <td>Solstice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_97</th>\n",
       "      <td>([Bloomingdale's], [42])</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_98</th>\n",
       "      <td>([ProActiv Solutions ], [66])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_99</th>\n",
       "      <td>([ProActiv Solutions ], [51])</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>567 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Store_Name            New_Store\n",
       "Shopper_ID                                                      \n",
       "Shopper_1          ([Bloomingdale's], [64])       Bloomingdale's\n",
       "Shopper_10                ([TAP 415], [80])              TAP 415\n",
       "Shopper_100   ([ProActiv Solutions ], [58])  ProActiv Solutions \n",
       "Shopper_101             ([Swarovski], [53])            Swarovski\n",
       "Shopper_102              ([TAP 415], [125])              TAP 415\n",
       "Shopper_103             ([Cotton On], [52])            Cotton On\n",
       "Shopper_104   ([ProActiv Solutions ], [71])  ProActiv Solutions \n",
       "Shopper_105   ([ProActiv Solutions ], [61])  ProActiv Solutions \n",
       "Shopper_106   ([ProActiv Solutions ], [63])  ProActiv Solutions \n",
       "Shopper_107   ([ProActiv Solutions ], [61])  ProActiv Solutions \n",
       "Shopper_108  ([ProActiv Solutions ], [105])  ProActiv Solutions \n",
       "Shopper_109        ([Bloomingdale's], [56])       Bloomingdale's\n",
       "Shopper_11    ([ProActiv Solutions ], [72])  ProActiv Solutions \n",
       "Shopper_110   ([ProActiv Solutions ], [51])  ProActiv Solutions \n",
       "Shopper_111             ([Swarovski], [56])            Swarovski\n",
       "Shopper_112   ([ProActiv Solutions ], [77])  ProActiv Solutions \n",
       "Shopper_113   ([ProActiv Solutions ], [97])  ProActiv Solutions \n",
       "Shopper_114               ([TAP 415], [90])              TAP 415\n",
       "Shopper_115             ([Cotton On], [55])            Cotton On\n",
       "Shopper_116              ([TAP 415], [167])              TAP 415\n",
       "Shopper_117  ([ProActiv Solutions ], [133])  ProActiv Solutions \n",
       "Shopper_118             ([Cotton On], [45])            Cotton On\n",
       "Shopper_119            ([Swarovski], [119])            Swarovski\n",
       "Shopper_12    ([ProActiv Solutions ], [32])  ProActiv Solutions \n",
       "Shopper_120             ([Swarovski], [59])            Swarovski\n",
       "Shopper_121   ([ProActiv Solutions ], [44])  ProActiv Solutions \n",
       "Shopper_122               ([TAP 415], [49])              TAP 415\n",
       "Shopper_123             ([Swarovski], [72])            Swarovski\n",
       "Shopper_124   ([ProActiv Solutions ], [75])  ProActiv Solutions \n",
       "Shopper_125             ([Cotton On], [41])            Cotton On\n",
       "...                                     ...                  ...\n",
       "Shopper_72                ([TAP 415], [59])              TAP 415\n",
       "Shopper_73    ([ProActiv Solutions ], [51])  ProActiv Solutions \n",
       "Shopper_74    ([ProActiv Solutions ], [60])  ProActiv Solutions \n",
       "Shopper_75              ([Swarovski], [56])            Swarovski\n",
       "Shopper_76   ([ProActiv Solutions ], [116])  ProActiv Solutions \n",
       "Shopper_77                ([TAP 415], [41])              TAP 415\n",
       "Shopper_78              ([Cotton On], [54])            Cotton On\n",
       "Shopper_79              ([Cotton On], [55])            Cotton On\n",
       "Shopper_8               ([Swarovski], [57])            Swarovski\n",
       "Shopper_80    ([ProActiv Solutions ], [71])  ProActiv Solutions \n",
       "Shopper_81    ([ProActiv Solutions ], [46])  ProActiv Solutions \n",
       "Shopper_82                ([TAP 415], [56])              TAP 415\n",
       "Shopper_83    ([ProActiv Solutions ], [58])  ProActiv Solutions \n",
       "Shopper_84                ([TAP 415], [86])              TAP 415\n",
       "Shopper_85   ([ProActiv Solutions ], [107])  ProActiv Solutions \n",
       "Shopper_86    ([ProActiv Solutions ], [57])  ProActiv Solutions \n",
       "Shopper_87                ([TAP 415], [38])              TAP 415\n",
       "Shopper_88              ([Swarovski], [45])            Swarovski\n",
       "Shopper_89    ([ProActiv Solutions ], [76])  ProActiv Solutions \n",
       "Shopper_9     ([ProActiv Solutions ], [73])  ProActiv Solutions \n",
       "Shopper_90              ([Swarovski], [67])            Swarovski\n",
       "Shopper_91    ([ProActiv Solutions ], [77])  ProActiv Solutions \n",
       "Shopper_92    ([ProActiv Solutions ], [71])  ProActiv Solutions \n",
       "Shopper_93                ([TAP 415], [51])              TAP 415\n",
       "Shopper_94              ([Cotton On], [57])            Cotton On\n",
       "Shopper_95              ([Swarovski], [86])            Swarovski\n",
       "Shopper_96               ([Solstice], [38])             Solstice\n",
       "Shopper_97         ([Bloomingdale's], [42])       Bloomingdale's\n",
       "Shopper_98    ([ProActiv Solutions ], [66])  ProActiv Solutions \n",
       "Shopper_99    ([ProActiv Solutions ], [51])  ProActiv Solutions \n",
       "\n",
       "[567 rows x 2 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Pick up category of stores from categorymapping and add it to the storemap and then train with storemap and predict on pinginfo'"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''Pick up category of stores from categorymapping and add it to the storemap and then train with storemap and predict on pinginfo'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 154 entries, 0 to 153\n",
      "Data columns (total 3 columns):\n",
      "Store_Name        154 non-null object\n",
      "Broad_Category    154 non-null object\n",
      "Fine_Category     154 non-null object\n",
      "dtypes: object(3)\n",
      "memory usage: 3.7+ KB\n"
     ]
    }
   ],
   "source": [
    "categorymapping.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Broad_Category</th>\n",
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       "      <th>0</th>\n",
       "      <td>Amazon Pop-Up</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Misc.</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bespoke Events</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bespoke Coworking</td>\n",
       "      <td>Retail</td>\n",
       "      <td>Specialty Store</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Dyson</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Penhaligonï¿½Ûªs</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "          Store_Name Broad_Category    Fine_Category\n",
       "0      Amazon Pop-Up         Retail            Misc.\n",
       "1     Bespoke Events         Retail            Misc.\n",
       "2  Bespoke Coworking         Retail  Specialty Store\n",
       "3              Dyson         Retail            Misc.\n",
       "4   Penhaligonï¿½Ûªs         Retail            Misc."
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorymapping.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "for stores, category in zip(categorymapping['Store_Name'], categorymapping['Fine_Category']):\n",
    "    store_and_category_mapping = dict(zip(categorymapping['Store_Name'], categorymapping['Fine_Category']))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'49ers Team Store': u'Sports Stores',\n",
       " u'Abercrombie & Fitch': u'Apparel And Accessories',\n",
       " u'Adidas': u'Apparel And Accessories',\n",
       " u'Ajisen Ramen': u'Qsr Restaurants',\n",
       " u'Aldo': u'Shoe Stores',\n",
       " u'Amazon Pop-Up': u'Misc.',\n",
       " u'American Eagle Outfitters': u'Apparel And Accessories',\n",
       " u'Amiri Salon': u'Furniture And Decor',\n",
       " u'Amoura Cafe Fresh Mediterranean': u'Qsr Restaurants',\n",
       " u'Andale Mexican Restaurant': u'Qsr Restaurants',\n",
       " u'Aritzia': u'Apparel And Accessories',\n",
       " u\"Auntie Anne's Pretzels\": u'Qsr Restaurants',\n",
       " u'Aveda': u'Furniture And Decor',\n",
       " u'BCBGMAXAZRIA': u'Apparel And Accessories',\n",
       " u'BOSS': u'Apparel And Accessories',\n",
       " u'Banana Republic': u'Apparel And Accessories',\n",
       " u'Bath & Body Works': u'Furniture And Decor',\n",
       " u\"Beard Papa's Cream Puffs\": u'Qsr Restaurants',\n",
       " u'Bespoke Coworking': u'Specialty Store',\n",
       " u'Bespoke Events': u'Misc.',\n",
       " u\"Bloomingdale's\": u'Department Stores',\n",
       " u'Bose': u'Electronics Stores',\n",
       " u'Brighton Collectibles': u'Apparel And Accessories',\n",
       " u'Bristol Farms': u'Casual Restaurants',\n",
       " u'Brookstone': u'Department Stores',\n",
       " u'Buckhorn Grill': u'Qsr Restaurants',\n",
       " u'Burberry': u'Apparel And Accessories',\n",
       " u'Burke Williams Day Spa': u'Misc.',\n",
       " u'Cafe Bellini': u'Qsr Restaurants',\n",
       " u'Caffe Central': u'Qsr Restaurants',\n",
       " u'Cako Bakery': u'Qsr Restaurants',\n",
       " u'Camper': u'Shoe Stores',\n",
       " u'Century San Francisco Centre 9': u'Misc.',\n",
       " u'Champs Sports': u'Sports Stores',\n",
       " u\"Charley's Grilled Subs\": u'Qsr Restaurants',\n",
       " u'Chipotle': u'Qsr Restaurants',\n",
       " u\"Claire's Boutique\": u'Apparel And Accessories',\n",
       " u'Clarks': u'Shoe Stores',\n",
       " u'Club Monaco Men': u'Apparel And Accessories',\n",
       " u'Club Monaco Women': u'Apparel And Accessories',\n",
       " u'Coach': u'Apparel And Accessories',\n",
       " u'Coriander Gourmet Thai': u'Qsr Restaurants',\n",
       " u'Corner W': u'Shoe Stores',\n",
       " u'Cotton On': u'Apparel And Accessories',\n",
       " u'Currency Exchange International ': u'Misc.',\n",
       " u'DAVIDsTEA': u'Qsr Restaurants',\n",
       " u'Dyson': u'Misc.',\n",
       " u'ECCO': u'Shoe Stores',\n",
       " u'Eddie Bauer': u'Apparel And Accessories',\n",
       " u'Express': u'Apparel And Accessories',\n",
       " u'Eyebrow Plus': u'Furniture And Decor',\n",
       " u'Finish Line': u'Apparel And Accessories',\n",
       " u'Fire of Brazil': u'Qsr Restaurants',\n",
       " u'Forever Flawless': u'Furniture And Decor',\n",
       " u'Forever Flawless ': u'Furniture And Decor',\n",
       " u'Fossil': u'Apparel And Accessories',\n",
       " u\"Francesca's Collection \": u'Apparel And Accessories',\n",
       " u'GNC': u'Furniture And Decor',\n",
       " u'GUESS ': u'Apparel And Accessories',\n",
       " u'Ghirardelli Ice Cream and Chocolate Shop ': u'Qsr Restaurants',\n",
       " u'Go! Toys and Games': u'Toy Stores',\n",
       " u'Godiva Chocolatier': u'Qsr Restaurants',\n",
       " u'H&M': u'Apparel And Accessories',\n",
       " u'H&M Man': u'Apparel And Accessories',\n",
       " u'Haagen Dazs': u'Qsr Restaurants',\n",
       " u'Hallmark': u'Office Supply Stores',\n",
       " u'Hollister Co.': u'Apparel And Accessories',\n",
       " u'House of Hoops by Foot Locker': u'Sports Stores',\n",
       " u'J.Crew': u'Apparel And Accessories',\n",
       " u'Jamba Juice': u'Qsr Restaurants',\n",
       " u'Janie And Jack': u'Apparel And Accessories',\n",
       " u'Karen Millen': u'Apparel And Accessories',\n",
       " u'Kate Spade New York': u'Apparel And Accessories',\n",
       " u'Kay Jewelers': u'Misc.',\n",
       " u'Kichi Grill': u'Qsr Restaurants',\n",
       " u\"Kiehl's\": u'Furniture And Decor',\n",
       " u\"L'Occitane en Provence\": u'Furniture And Decor',\n",
       " u'LEGO': u'Toy Stores',\n",
       " u'Lady Foot Locker': u'Sports Stores',\n",
       " u'Lids': u'Apparel and Accessories',\n",
       " u'Lobster Me': u'Qsr Restaurants',\n",
       " u'Loving Hut Vegan Cuisine ': u'Qsr Restaurants',\n",
       " u'Lucky Brand Jeans': u'Apparel And Accessories',\n",
       " u'M.Y. China': u'Qsr Restaurants',\n",
       " u'Madewell': u'Apparel And Accessories',\n",
       " u'Marbles: The Brain Store': u'Toy Stores',\n",
       " u'Max & Co.': u'Apparel And Accessories',\n",
       " u'Michael Kors': u'Apparel And Accessories',\n",
       " u'Michael Kors Men': u'Apparel And Accessories',\n",
       " u'Microsoft': u'Electronics Stores',\n",
       " u'Mrs. Fields': u'Qsr Restaurants',\n",
       " u'NYS Collection': u'Apparel And Accessories',\n",
       " u'New Era': u'Sports Stores',\n",
       " u'Nordstrom': u'Department Stores',\n",
       " u'Nordstrom E-Bar': u'Qsr Restaurants',\n",
       " u'OAK+FORT': u'Apparel And Accessories',\n",
       " u'Onassis': u'Furniture And Decor',\n",
       " u'Optica': u'Furniture And Decor',\n",
       " u'Origins': u'Furniture And Decor',\n",
       " u'PacSun': u'Apparel And Accessories',\n",
       " u'Panda Express': u'Qsr Restaurants',\n",
       " u'Pandora': u'Misc.',\n",
       " u'Papyrus': u'Office Supply Stores',\n",
       " u'Pasta Moto': u'Qsr Restaurants',\n",
       " u\"Peet's Coffee & Tea\": u'Qsr Restaurants',\n",
       " u'Penhaligon\\xef\\xbf\\xbd\\xdb\\xaas': u'Misc.',\n",
       " u'Perfumania': u'Furniture And Decor',\n",
       " u'Pressed Juicery': u'Qsr Restaurants',\n",
       " u'ProActiv Solutions ': u'Misc.',\n",
       " u'RED Valentino': u'Apparel And Accessories',\n",
       " u'Razer': u'Specialty Store',\n",
       " u'Rolex': u'Misc.',\n",
       " u'SF Sports': u'Apparel And Accessories',\n",
       " u'Samsonite': u'Apparel and Accessories',\n",
       " u'San Francisco Luggage Co.': u'Apparel and Accessories',\n",
       " u'San Francisco Soup Company': u'Qsr Restaurants',\n",
       " u'Sarku Japan': u'Qsr Restaurants',\n",
       " u'Shoe Palace ': u'Shoe Stores',\n",
       " u'Shoe Wiz': u'Misc.',\n",
       " u'Solstice': u'Apparel And Accessories',\n",
       " u'Sorabol Korean BBQ & Asian Noodles': u'Qsr Restaurants',\n",
       " u'Starbucks': u'Qsr Restaurants',\n",
       " u'Steve Madden': u'Shoe Stores',\n",
       " u'Studio Manhattan': u'Apparel and Accessories',\n",
       " u'Sunglass Hut': u'Apparel And Accessories',\n",
       " u'Sunglass Hut ': u'Apparel And Accessories',\n",
       " u'Superdry ': u'Apparel And Accessories',\n",
       " u'Sur La Table': u'Furniture And Decor',\n",
       " u'Swarovski': u'Apparel and Accessories',\n",
       " u'Swatch': u'Misc.',\n",
       " u'T-Mobile': u'Cellular Phone Stores',\n",
       " u'TAP 415': u'Qsr Restaurants',\n",
       " u'Teavana': u'Qsr Restaurants',\n",
       " u'The Art of Shaving': u'Furniture And Decor',\n",
       " u'The Body Shop': u'Furniture And Decor',\n",
       " u'The Walking Company': u'Shoe Stores',\n",
       " u'Tiffany & Co.': u'Misc.',\n",
       " u'Timberland': u'Apparel And Accessories',\n",
       " u'Tory Burch ': u'Apparel And Accessories',\n",
       " u'Tourneau': u'Misc.',\n",
       " u'True Religion Jeans': u'Apparel And Accessories',\n",
       " u'Tumi': u'Apparel and Accessories',\n",
       " u'Vans': u'Shoe Stores',\n",
       " u'Vera Bradley': u'Apparel And Accessories',\n",
       " u\"Victoria's Secret\": u'Apparel And Accessories',\n",
       " u'Warriors Team Store': u'Sports Stores',\n",
       " u\"Wetzel's Pretzels\": u'Qsr Restaurants',\n",
       " u'Yoppi Frozen Yogurt ': u'Qsr Restaurants',\n",
       " u'Zara': u'Apparel And Accessories',\n",
       " u'abercrombie kids': u'Apparel And Accessories',\n",
       " u'bareMinerals': u'Furniture And Decor',\n",
       " u'bebe': u'Apparel And Accessories',\n",
       " u'iPlay n Talk': u'Electronics Stores',\n",
       " u'lululemon athletica': u'Apparel and Accessories'}"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "store_and_category_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "      <td>69</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "      <td>41</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "      <td>91</td>\n",
       "      <td>Apparel And Accessories</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "      <td>65</td>\n",
       "      <td>Office Supply Stores</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "      <td>120</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name  Floor_Index   latitude   longitude  \\\n",
       "0                         Jamba Juice            0  37.784091 -122.406813   \n",
       "1              Coriander Gourmet Thai            0  37.784596 -122.406210   \n",
       "2                      NYS Collection            0  37.784396 -122.406587   \n",
       "3                            Hallmark            0  37.783771 -122.407377   \n",
       "4  Sorabol Korean BBQ & Asian Noodles            0  37.784601 -122.406328   \n",
       "\n",
       "   Store_Index           Store_Category  \n",
       "0           69          Qsr Restaurants  \n",
       "1           41          Qsr Restaurants  \n",
       "2           91  Apparel And Accessories  \n",
       "3           65     Office Supply Stores  \n",
       "4          120          Qsr Restaurants  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemap['Store_Category'] = storemap['Store_Name'].map(store_and_category_mapping).astype(object)\n",
    "storemap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'Apparel And Accessories',\n",
       " u'Apparel and Accessories',\n",
       " u'Casual Restaurants',\n",
       " u'Cellular Phone Stores',\n",
       " u'Department Stores',\n",
       " u'Electronics Stores',\n",
       " u'Furniture And Decor',\n",
       " u'Misc.',\n",
       " u'Office Supply Stores',\n",
       " u'Qsr Restaurants',\n",
       " u'Shoe Stores',\n",
       " u'Specialty Store',\n",
       " u'Sports Stores',\n",
       " u'Toy Stores']"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Store_Categories= sorted(storemap['Store_Category'].unique())\n",
    "Store_Categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'Apparel And Accessories': 0,\n",
       " u'Apparel and Accessories': 1,\n",
       " u'Casual Restaurants': 2,\n",
       " u'Cellular Phone Stores': 3,\n",
       " u'Department Stores': 4,\n",
       " u'Electronics Stores': 5,\n",
       " u'Furniture And Decor': 6,\n",
       " u'Misc.': 7,\n",
       " u'Office Supply Stores': 8,\n",
       " u'Qsr Restaurants': 9,\n",
       " u'Shoe Stores': 10,\n",
       " u'Specialty Store': 11,\n",
       " u'Sports Stores': 12,\n",
       " u'Toy Stores': 13}"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Store_Categories_mapping = dict(zip(Store_Categories, range(0, len(Store_Categories) + 1)))\n",
    "Store_Categories_mapping\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Category</th>\n",
       "      <th>Category_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jamba Juice</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784091</td>\n",
       "      <td>-122.406813</td>\n",
       "      <td>69</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coriander Gourmet Thai</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784596</td>\n",
       "      <td>-122.406210</td>\n",
       "      <td>41</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NYS Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784396</td>\n",
       "      <td>-122.406587</td>\n",
       "      <td>91</td>\n",
       "      <td>Apparel And Accessories</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hallmark</td>\n",
       "      <td>0</td>\n",
       "      <td>37.783771</td>\n",
       "      <td>-122.407377</td>\n",
       "      <td>65</td>\n",
       "      <td>Office Supply Stores</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sorabol Korean BBQ &amp; Asian Noodles</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784601</td>\n",
       "      <td>-122.406328</td>\n",
       "      <td>120</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Store_Name  Floor_Index   latitude   longitude  \\\n",
       "0                         Jamba Juice            0  37.784091 -122.406813   \n",
       "1              Coriander Gourmet Thai            0  37.784596 -122.406210   \n",
       "2                      NYS Collection            0  37.784396 -122.406587   \n",
       "3                            Hallmark            0  37.783771 -122.407377   \n",
       "4  Sorabol Korean BBQ & Asian Noodles            0  37.784601 -122.406328   \n",
       "\n",
       "   Store_Index           Store_Category  Category_Index  \n",
       "0           69          Qsr Restaurants               9  \n",
       "1           41          Qsr Restaurants               9  \n",
       "2           91  Apparel And Accessories               0  \n",
       "3           65     Office Supply Stores               8  \n",
       "4          120          Qsr Restaurants               9  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "storemap['Category_Index'] = storemap['Store_Category'].map(Store_Categories_mapping).astype(int)\n",
    "storemap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   0.      ,   37.784091, -122.406813],\n",
       "       [   0.      ,   37.784596, -122.40621 ],\n",
       "       [   0.      ,   37.784396, -122.406587],\n",
       "       [   0.      ,   37.783771, -122.407377],\n",
       "       [   0.      ,   37.784601, -122.406328],\n",
       "       [   0.      ,   37.784534, -122.406025],\n",
       "       [   0.      ,   37.783944, -122.407537],\n",
       "       [   0.      ,   37.784447, -122.406224],\n",
       "       [   0.      ,   37.784161, -122.4069  ],\n",
       "       [   0.      ,   37.784808, -122.406501],\n",
       "       [   0.      ,   37.784569, -122.406141],\n",
       "       [   0.      ,   37.78467 , -122.406679],\n",
       "       [   0.      ,   37.784126, -122.407061],\n",
       "       [   0.      ,   37.784159, -122.40635 ],\n",
       "       [   0.      ,   37.783959, -122.40691 ],\n",
       "       [   0.      ,   37.784411, -122.406709],\n",
       "       [   0.      ,   37.784511, -122.405956],\n",
       "       [   0.      ,   37.784071, -122.406885],\n",
       "       [   0.      ,   37.784591, -122.406782],\n",
       "       [   0.      ,   37.783778, -122.407161],\n",
       "       [   0.      ,   37.784053, -122.407307],\n",
       "       [   0.      ,   37.783893, -122.407389],\n",
       "       [   0.      ,   37.784222, -122.406978],\n",
       "       [   0.      ,   37.783953, -122.407318],\n",
       "       [   0.      ,   37.784505, -122.406555],\n",
       "       [   0.      ,   37.783767, -122.40707 ],\n",
       "       [   0.      ,   37.784106, -122.407189],\n",
       "       [   0.      ,   37.784292, -122.40601 ],\n",
       "       [   0.      ,   37.784449, -122.406665],\n",
       "       [   0.      ,   37.784353, -122.406773],\n",
       "       [   0.      ,   37.784294, -122.406164],\n",
       "       [   0.      ,   37.78432 , -122.406195],\n",
       "       [   0.      ,   37.783944, -122.407175],\n",
       "       [   0.      ,   37.783831, -122.406941],\n",
       "       [   0.      ,   37.784312, -122.405822],\n",
       "       [   0.      ,   37.783887, -122.405783],\n",
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       "       [   0.      ,   37.784094, -122.407625],\n",
       "       [   0.      ,   37.783791, -122.406984],\n",
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       "       [   1.      ,   37.784221, -122.406652],\n",
       "       [   1.      ,   37.784776, -122.406643],\n",
       "       [   1.      ,   37.784527, -122.406296],\n",
       "       [   1.      ,   37.78367 , -122.407313],\n",
       "       [   1.      ,   37.783731, -122.407122],\n",
       "       [   1.      ,   37.783976, -122.406906],\n",
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       "       [   1.      ,   37.78398 , -122.407454],\n",
       "       [   1.      ,   37.784714, -122.406476],\n",
       "       [   1.      ,   37.78409 , -122.406835],\n",
       "       [   1.      ,   37.784503, -122.406813],\n",
       "       [   1.      ,   37.784112, -122.406949],\n",
       "       [   1.      ,   37.784884, -122.406486],\n",
       "       [   1.      ,   37.78461 , -122.406886],\n",
       "       [   1.      ,   37.784466, -122.406961],\n",
       "       [   1.      ,   37.78447 , -122.40676 ],\n",
       "       [   1.      ,   37.78373 , -122.407061],\n",
       "       [   1.      ,   37.783909, -122.407393],\n",
       "       [   1.      ,   37.78381 , -122.407336],\n",
       "       [   1.      ,   37.783864, -122.406836],\n",
       "       [   1.      ,   37.784188, -122.407159],\n",
       "       [   1.      ,   37.783827, -122.407024],\n",
       "       [   1.      ,   37.784047, -122.407035],\n",
       "       [   1.      ,   37.784397, -122.406148],\n",
       "       [   1.      ,   37.784185, -122.406379],\n",
       "       [   1.      ,   37.784396, -122.406726],\n",
       "       [   2.      ,   37.784579, -122.406476],\n",
       "       [   2.      ,   37.783744, -122.407323],\n",
       "       [   2.      ,   37.784515, -122.406218],\n",
       "       [   2.      ,   37.784024, -122.407272],\n",
       "       [   2.      ,   37.784139, -122.407183],\n",
       "       [   2.      ,   37.784341, -122.406785],\n",
       "       [   2.      ,   37.784559, -122.40627 ],\n",
       "       [   2.      ,   37.784136, -122.405805],\n",
       "       [   2.      ,   37.784705, -122.406568],\n",
       "       [   2.      ,   37.784142, -122.40742 ],\n",
       "       [   2.      ,   37.784267, -122.406528],\n",
       "       [   2.      ,   37.784046, -122.406884],\n",
       "       [   2.      ,   37.784252, -122.406942],\n",
       "       [   2.      ,   37.784387, -122.406732],\n",
       "       [   2.      ,   37.783739, -122.407271],\n",
       "       [   2.      ,   37.783745, -122.407149],\n",
       "       [   2.      ,   37.784385, -122.406276],\n",
       "       [   2.      ,   37.784195, -122.407081],\n",
       "       [   2.      ,   37.784433, -122.40608 ],\n",
       "       [   2.      ,   37.784031, -122.406181],\n",
       "       [   2.      ,   37.783852, -122.405805],\n",
       "       [   2.      ,   37.783931, -122.406086],\n",
       "       [   2.      ,   37.784484, -122.406502],\n",
       "       [   2.      ,   37.783724, -122.406893],\n",
       "       [   2.      ,   37.784555, -122.406814],\n",
       "       [   2.      ,   37.783832, -122.407021],\n",
       "       [   2.      ,   37.783954, -122.407507],\n",
       "       [   2.      ,   37.784185, -122.406432],\n",
       "       [   2.      ,   37.783864, -122.406924],\n",
       "       [   2.      ,   37.783946, -122.406796],\n",
       "       [   2.      ,   37.784316, -122.40656 ],\n",
       "       [   2.      ,   37.784172, -122.406733],\n",
       "       [   2.      ,   37.784271, -122.406619],\n",
       "       [   2.      ,   37.784286, -122.406001],\n",
       "       [   3.      ,   37.784042, -122.406901],\n",
       "       [   3.      ,   37.783629, -122.407154],\n",
       "       [   3.      ,   37.783741, -122.406902],\n",
       "       [   3.      ,   37.784628, -122.406187],\n",
       "       [   3.      ,   37.78435 , -122.406064],\n",
       "       [   3.      ,   37.784105, -122.406326],\n",
       "       [   3.      ,   37.784615, -122.406862],\n",
       "       [   3.      ,   37.784428, -122.406643],\n",
       "       [   3.      ,   37.784447, -122.406809],\n",
       "       [   3.      ,   37.783986, -122.406922],\n",
       "       [   3.      ,   37.783839, -122.406836],\n",
       "       [   3.      ,   37.783812, -122.406021],\n",
       "       [   3.      ,   37.784133, -122.407419],\n",
       "       [   3.      ,   37.783752, -122.407371],\n",
       "       [   3.      ,   37.78429 , -122.406561],\n",
       "       [   3.      ,   37.783737, -122.407253],\n",
       "       [   3.      ,   37.78424 , -122.406455],\n",
       "       [   3.      ,   37.784101, -122.406854],\n",
       "       [   3.      ,   37.783871, -122.407073],\n",
       "       [   3.      ,   37.784153, -122.405871],\n",
       "       [   3.      ,   37.783745, -122.405601],\n",
       "       [   3.      ,   37.784191, -122.407111],\n",
       "       [   3.      ,   37.784267, -122.405933],\n",
       "       [   3.      ,   37.784386, -122.406589],\n",
       "       [   3.      ,   37.78454 , -122.406132],\n",
       "       [   3.      ,   37.783912, -122.407474],\n",
       "       [   3.      ,   37.784663, -122.406313],\n",
       "       [   3.      ,   37.784135, -122.406406],\n",
       "       [   3.      ,   37.783957, -122.406249],\n",
       "       [   3.      ,   37.783814, -122.407399],\n",
       "       [   3.      ,   37.784197, -122.40698 ],\n",
       "       [   3.      ,   37.784701, -122.406758],\n",
       "       [   3.      ,   37.78436 , -122.406786],\n",
       "       [   4.      ,   37.78442 , -122.406832],\n",
       "       [   4.      ,   37.784702, -122.406248],\n",
       "       [   4.      ,   37.784206, -122.406528],\n",
       "       [   4.      ,   37.784178, -122.405776],\n",
       "       [   4.      ,   37.783859, -122.40635 ],\n",
       "       [   4.      ,   37.784539, -122.406081],\n",
       "       [   4.      ,   37.78382 , -122.407311],\n",
       "       [   4.      ,   37.783802, -122.405736],\n",
       "       [   5.      ,   37.784076, -122.407307],\n",
       "       [   5.      ,   37.78389 , -122.405736],\n",
       "       [   5.      ,   37.784204, -122.406574],\n",
       "       [   6.      ,   37.78409 , -122.407309],\n",
       "       [   7.      ,   37.784073, -122.407289],\n",
       "       [   8.      ,   37.784087, -122.407307]])"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X2 = storemap.drop(['Store_Name','Store_Index', 'Store_Category','Category_Index'],axis=1).as_matrix().astype(np.float)\n",
    "X2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([u'Qsr Restaurants', u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Office Supply Stores', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Misc.',\n",
       "       u'Shoe Stores', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Casual Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Furniture And Decor', u'Sports Stores', u'Toy Stores',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Shoe Stores', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Toy Stores', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Sports Stores', u'Qsr Restaurants',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Misc.',\n",
       "       u'Qsr Restaurants', u'Furniture And Decor', u'Qsr Restaurants',\n",
       "       u'Sports Stores', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Qsr Restaurants', u'Specialty Store', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Misc.', u'Furniture And Decor', u'Misc.',\n",
       "       u'Apparel And Accessories', u'Furniture And Decor',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel and Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel and Accessories',\n",
       "       u'Apparel And Accessories', u'Misc.', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Furniture And Decor', u'Misc.',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories', u'Misc.',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Furniture And Decor', u'Apparel And Accessories', u'Misc.',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Furniture And Decor', u'Misc.',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel and Accessories', u'Apparel And Accessories',\n",
       "       u'Furniture And Decor', u'Furniture And Decor',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Furniture And Decor',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Shoe Stores', u'Sports Stores', u'Apparel And Accessories',\n",
       "       u'Misc.', u'Furniture And Decor', u'Apparel And Accessories',\n",
       "       u'Cellular Phone Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Sports Stores', u'Apparel and Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories', u'Misc.',\n",
       "       u'Apparel And Accessories', u'Electronics Stores',\n",
       "       u'Apparel and Accessories', u'Apparel And Accessories',\n",
       "       u'Furniture And Decor', u'Shoe Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Shoe Stores',\n",
       "       u'Apparel And Accessories', u'Office Supply Stores',\n",
       "       u'Apparel and Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories', u'Shoe Stores',\n",
       "       u'Sports Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Furniture And Decor', u'Misc.',\n",
       "       u'Furniture And Decor', u'Shoe Stores', u'Apparel and Accessories',\n",
       "       u'Electronics Stores', u'Toy Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Shoe Stores', u'Furniture And Decor',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Furniture And Decor',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Shoe Stores',\n",
       "       u'Furniture And Decor', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Furniture And Decor', u'Qsr Restaurants',\n",
       "       u'Specialty Store', u'Misc.', u'Electronics Stores',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Misc.', u'Misc.', u'Department Stores', u'Department Stores',\n",
       "       u'Department Stores'], dtype=object)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y2 = storemap['Store_Category'].as_matrix().astype(object)\n",
    "y2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stratified_cv(X, y, clf_class, shuffle=True, n_folds=2, **kwargs):\n",
    "    stratified_k_fold = cross_validation.StratifiedKFold(y, n_folds=n_folds, shuffle=shuffle)\n",
    "    y_pred = y.copy()\n",
    "    for ii, jj in stratified_k_fold:\n",
    "        X_train, X_test = X[ii], X[jj]\n",
    "        y_train = y[ii]\n",
    "        clf = clf_class(**kwargs)\n",
    "        clf.fit(X_train,y_train)\n",
    "        y_pred[jj] = clf.predict(X_test)\n",
    "    return y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Passive Aggressive Classifier: 0.16\n",
      "Gradient Boosting Classifier:  0.32\n",
      "Support vector machine(SVM):   0.46\n",
      "Random Forest Classifier:      0.40\n",
      "K Nearest Neighbor Classifier: 0.43\n",
      "Logistic Regression:           0.48\n"
     ]
    }
   ],
   "source": [
    "print('Passive Aggressive Classifier: {:.2f}'.format(metrics.accuracy_score(y2, stratified_cv(X2, y2, linear_model.PassiveAggressiveClassifier))))\n",
    "print('Gradient Boosting Classifier:  {:.2f}'.format(metrics.accuracy_score(y2, stratified_cv(X2, y2, ensemble.GradientBoostingClassifier))))\n",
    "print('Support vector machine(SVM):   {:.2f}'.format(metrics.accuracy_score(y2, stratified_cv(X2, y2, svm.SVC))))\n",
    "print('Random Forest Classifier:      {:.2f}'.format(metrics.accuracy_score(y2, stratified_cv(X2, y2, ensemble.RandomForestClassifier))))\n",
    "print('K Nearest Neighbor Classifier: {:.2f}'.format(metrics.accuracy_score(y2, stratified_cv(X2, y2, neighbors.KNeighborsClassifier))))\n",
    "print('Logistic Regression:           {:.2f}'.format(metrics.accuracy_score(y2, stratified_cv(X2, y2, linear_model.LogisticRegression))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn import cross_validation\n",
    "from sklearn import tree\n",
    "from sklearn import svm\n",
    "from sklearn import ensemble\n",
    "from sklearn import neighbors\n",
    "from sklearn import linear_model\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mean accuracy of SVM: 0.5'"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SVM TRAINING AND FITTING:\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "clf = svm.SVC(kernel='rbf', gamma=2)\n",
    "clf.fit(X2, y2)\n",
    "\n",
    "\n",
    "# Training data features, skip the first column 'Survived'\n",
    "train_features = X2\n",
    "\n",
    "# 'Survived' column values\n",
    "train_target = y2\n",
    "\n",
    "# Fit the model to our training data\n",
    "clf = clf.fit(train_features, train_target)\n",
    "score = clf.score(train_features, train_target)\n",
    "\"Mean accuracy of SVM: {0}\".format(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   3.        ,   37.76239083, -122.3880078 ],\n",
       "       [   0.        ,   33.58582518, -108.806374  ],\n",
       "       [   0.        ,   37.78402307, -122.4067857 ],\n",
       "       ...,\n",
       "       [   1.        ,   37.78531785, -122.4096861 ],\n",
       "       [   4.        ,   34.23642783, -110.9600836 ],\n",
       "       [   1.        ,   36.25792852, -117.496074  ]])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test2 = pinginfonew.drop(['Shopper_ID', 'Store_Index','Store_Name'], axis=1).as_matrix().astype(np.float)\n",
    "X_test2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_y2 = clf.predict(X_test2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70238</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.585825</td>\n",
       "      <td>-108.806374</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70264</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784023</td>\n",
       "      <td>-122.406786</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40491</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.761052</td>\n",
       "      <td>-122.386801</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4777</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Shopper_ID  Floor_Index   latitude   longitude  Store_Index  \\\n",
       "35181  Shopper_1            3  37.762391 -122.388008          119   \n",
       "70238  Shopper_1            0  33.585825 -108.806374           20   \n",
       "70264  Shopper_1            0  37.784023 -122.406786          108   \n",
       "40491  Shopper_1            2  37.761052 -122.386801           43   \n",
       "4777   Shopper_1            3  35.664542 -115.588398           16   \n",
       "\n",
       "                Store_Name  \n",
       "35181             Solstice  \n",
       "70238       Bloomingdale's  \n",
       "70264  ProActiv Solutions   \n",
       "40491            Cotton On  \n",
       "4777     Bath & Body Works  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfonew.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "pinginfonew['Store_Category_visited'] = pred_y2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th>Floor_Index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Store_Index</th>\n",
       "      <th>Store_Name</th>\n",
       "      <th>Store_Category_visited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35181</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>37.762391</td>\n",
       "      <td>-122.388008</td>\n",
       "      <td>119</td>\n",
       "      <td>Solstice</td>\n",
       "      <td>Apparel And Accessories</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70238</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>33.585825</td>\n",
       "      <td>-108.806374</td>\n",
       "      <td>20</td>\n",
       "      <td>Bloomingdale's</td>\n",
       "      <td>Department Stores</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70264</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>0</td>\n",
       "      <td>37.784023</td>\n",
       "      <td>-122.406786</td>\n",
       "      <td>108</td>\n",
       "      <td>ProActiv Solutions</td>\n",
       "      <td>Qsr Restaurants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40491</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>2</td>\n",
       "      <td>37.761052</td>\n",
       "      <td>-122.386801</td>\n",
       "      <td>43</td>\n",
       "      <td>Cotton On</td>\n",
       "      <td>Apparel And Accessories</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4777</th>\n",
       "      <td>Shopper_1</td>\n",
       "      <td>3</td>\n",
       "      <td>35.664542</td>\n",
       "      <td>-115.588398</td>\n",
       "      <td>16</td>\n",
       "      <td>Bath &amp; Body Works</td>\n",
       "      <td>Department Stores</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Shopper_ID  Floor_Index   latitude   longitude  Store_Index  \\\n",
       "35181  Shopper_1            3  37.762391 -122.388008          119   \n",
       "70238  Shopper_1            0  33.585825 -108.806374           20   \n",
       "70264  Shopper_1            0  37.784023 -122.406786          108   \n",
       "40491  Shopper_1            2  37.761052 -122.386801           43   \n",
       "4777   Shopper_1            3  35.664542 -115.588398           16   \n",
       "\n",
       "                Store_Name   Store_Category_visited  \n",
       "35181             Solstice  Apparel And Accessories  \n",
       "70238       Bloomingdale's        Department Stores  \n",
       "70264  ProActiv Solutions           Qsr Restaurants  \n",
       "40491            Cotton On  Apparel And Accessories  \n",
       "4777     Bath & Body Works        Department Stores  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pinginfonew.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "df_freq_category = pinginfonew.groupby(by='Shopper_ID').Store_Category_visited.apply(stats.mode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Shopper_ID\n",
       "Shopper_1            ([Department Stores], [112])\n",
       "Shopper_10           ([Department Stores], [130])\n",
       "Shopper_100           ([Department Stores], [96])\n",
       "Shopper_101    ([Apparel And Accessories], [129])\n",
       "Shopper_102          ([Department Stores], [141])\n",
       "Shopper_103    ([Apparel And Accessories], [123])\n",
       "Shopper_104             ([Qsr Restaurants], [71])\n",
       "Shopper_105    ([Apparel And Accessories], [103])\n",
       "Shopper_106    ([Apparel And Accessories], [125])\n",
       "Shopper_107     ([Apparel And Accessories], [85])\n",
       "Shopper_108            ([Qsr Restaurants], [105])\n",
       "Shopper_109          ([Department Stores], [100])\n",
       "Shopper_11      ([Apparel And Accessories], [76])\n",
       "Shopper_110           ([Department Stores], [77])\n",
       "Shopper_111    ([Apparel And Accessories], [120])\n",
       "Shopper_112             ([Qsr Restaurants], [77])\n",
       "Shopper_113             ([Qsr Restaurants], [96])\n",
       "Shopper_114          ([Department Stores], [105])\n",
       "Shopper_115    ([Apparel And Accessories], [117])\n",
       "Shopper_116          ([Department Stores], [173])\n",
       "Shopper_117            ([Qsr Restaurants], [133])\n",
       "Shopper_118     ([Apparel And Accessories], [92])\n",
       "Shopper_119    ([Apparel And Accessories], [138])\n",
       "Shopper_12           ([Department Stores], [132])\n",
       "Shopper_120    ([Apparel And Accessories], [112])\n",
       "Shopper_121           ([Department Stores], [73])\n",
       "Shopper_122          ([Department Stores], [104])\n",
       "Shopper_123    ([Apparel And Accessories], [110])\n",
       "Shopper_124    ([Apparel And Accessories], [115])\n",
       "Shopper_125     ([Apparel And Accessories], [95])\n",
       "                              ...                \n",
       "Shopper_72            ([Department Stores], [87])\n",
       "Shopper_73            ([Department Stores], [87])\n",
       "Shopper_74     ([Apparel And Accessories], [111])\n",
       "Shopper_75     ([Apparel And Accessories], [119])\n",
       "Shopper_76             ([Qsr Restaurants], [116])\n",
       "Shopper_77            ([Department Stores], [96])\n",
       "Shopper_78     ([Apparel And Accessories], [133])\n",
       "Shopper_79     ([Apparel And Accessories], [132])\n",
       "Shopper_8      ([Apparel And Accessories], [110])\n",
       "Shopper_80            ([Department Stores], [94])\n",
       "Shopper_81      ([Apparel And Accessories], [81])\n",
       "Shopper_82           ([Department Stores], [117])\n",
       "Shopper_83            ([Department Stores], [77])\n",
       "Shopper_84           ([Department Stores], [103])\n",
       "Shopper_85             ([Qsr Restaurants], [107])\n",
       "Shopper_86           ([Department Stores], [101])\n",
       "Shopper_87            ([Department Stores], [86])\n",
       "Shopper_88            ([Department Stores], [79])\n",
       "Shopper_89      ([Apparel And Accessories], [93])\n",
       "Shopper_9               ([Qsr Restaurants], [73])\n",
       "Shopper_90     ([Apparel And Accessories], [111])\n",
       "Shopper_91              ([Qsr Restaurants], [77])\n",
       "Shopper_92     ([Apparel And Accessories], [104])\n",
       "Shopper_93     ([Apparel And Accessories], [103])\n",
       "Shopper_94     ([Apparel And Accessories], [136])\n",
       "Shopper_95     ([Apparel And Accessories], [144])\n",
       "Shopper_96     ([Apparel And Accessories], [106])\n",
       "Shopper_97            ([Department Stores], [97])\n",
       "Shopper_98     ([Apparel And Accessories], [114])\n",
       "Shopper_99            ([Department Stores], [75])\n",
       "Name: Store_Category_visited, Length: 567, dtype: object"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq_category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Store_Category_visited    ([Department Stores], [130])\n",
       "Name: Shopper_10, dtype: object"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_freq_category= df_freq_category.to_frame()\n",
    "df_freq_category.iloc[1,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Department Stores', u'Department Stores',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Department Stores', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Qsr Restaurants', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Qsr Restaurants', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Department Stores', u'Department Stores', u'Qsr Restaurants',\n",
       "       u'Department Stores', u'Department Stores', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Qsr Restaurants',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Apparel And Accessories',\n",
       "       u'Apparel And Accessories', u'Department Stores',\n",
       "       u'Apparel And Accessories', u'Department Stores'], dtype='<U23')"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mostvisitedcategorylist= []\n",
    "for category in df_freq_category['Store_Category_visited']:\n",
    "    mostvisitedcategorylist.append(category[0][0])\n",
    "    \n",
    "mostvisitedcategory_array= np.array(mostvisitedcategorylist)\n",
    "mostvisitedcategory_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Store_Category_visited</th>\n",
       "      <th>New_Store_Category_visited</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Shopper_1</th>\n",
       "      <td>([Department Stores], [112])</td>\n",
       "      <td>Department Stores</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_10</th>\n",
       "      <td>([Department Stores], [130])</td>\n",
       "      <td>Department Stores</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_100</th>\n",
       "      <td>([Department Stores], [96])</td>\n",
       "      <td>Department Stores</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_101</th>\n",
       "      <td>([Apparel And Accessories], [129])</td>\n",
       "      <td>Apparel And Accessories</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopper_102</th>\n",
       "      <td>([Department Stores], [141])</td>\n",
       "      <td>Department Stores</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Store_Category_visited New_Store_Category_visited\n",
       "Shopper_ID                                                                \n",
       "Shopper_1          ([Department Stores], [112])          Department Stores\n",
       "Shopper_10         ([Department Stores], [130])          Department Stores\n",
       "Shopper_100         ([Department Stores], [96])          Department Stores\n",
       "Shopper_101  ([Apparel And Accessories], [129])    Apparel And Accessories\n",
       "Shopper_102        ([Department Stores], [141])          Department Stores"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mostvisitedcategory_array.astype(object)\n",
    "df_freq_category['New_Store_Category_visited']= mostvisitedcategory_array\n",
    "df_freq_category.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_freq_category.to_csv(r\"C:\\Users\\welcome\\Desktop\\exl__svm2ndpart.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "frames = [df_freq, df_freq_category]\n",
    "result = pd.concat(frames, axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_csv(r\"C:\\Users\\welcome\\Desktop\\exl__final.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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