lolanalysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "d2d55851-ff1d-48cf-82d3-3709f54afece",
    "_uuid": "badfcd23e4b3fec82d1b54f558bd3abb4e0fd726"
   },
   "source": [
    "<center>\n",
    "<h1>Does CBLoL's Teams Really Plays Less Matches? </h1>\n",
    "<h3>Analysing Statistics About <b>LoL Competitive Macthes</b></h3><br>\n",
    "<body>\n",
    "    **THIS IS A WORK IN PROGRESS** <br>\n",
    "    I'm a begginer in Data Science, so I'm working in this analysis to learn some stuff about data analysis.\n",
    "        Brazil's LoL fans complain that here we play just a few matches, and that is probably a reason for our bad results in the World's Championships. <br> \n",
    "    So, I decided to analyze the teams who played the most games in their respective league, according to this dataset.<br>\n",
    "    In the final, I made some cool analysis about the win rate of players, champions and teams, most used champions, etc...<br>\n",
    "    If you read this, please give some feedaback and suggestions!\n",
    "\n",
    "\n",
    "\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "3997813f-6fa3-4562-842b-531c6c185de3",
    "_uuid": "b255b338a7e1569d9b115841b43da96261093979"
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "_cell_guid": "7657653e-c816-40ef-83fa-902a019bd4bc",
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "_uuid": "f3e388945b6e9734a5483061e9bda00bf746cbf4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LCK      1323\n",
       "NALCS    1115\n",
       "EULCS     941\n",
       "LMS       716\n",
       "TCL       634\n",
       "OPL       441\n",
       "WC        308\n",
       "CBLoL     282\n",
       "LCL       281\n",
       "LJL       258\n",
       "LLN       242\n",
       "CLS       167\n",
       "IEM       138\n",
       "MSI       111\n",
       "RR        101\n",
       "Name: League, dtype: int64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lol = pd.read_csv('LeagueofLegends.csv')\n",
    "\n",
    "lol = lol.drop('Address', axis = 1) \n",
    "#The match history is not very useful, for now, in this analysis.\n",
    "lol.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "1435b42c-a1ec-40f6-9679-e5c85c058a28",
    "_kg_hide-input": true,
    "_uuid": "7f1da1a5f2b00a2620e2f45c1fe74e64ea55f356"
   },
   "source": [
    "<center>\n",
    "It's interesting to notice that the fastest game had 17 minutes, and the longest 81. <br>\n",
    "The mean is about 36 minutes.\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_cell_guid": "dff35fdc-ee09-4461-b2ad-1e61d2195956",
    "_uuid": "53ef98c0f69c9916b73fe1f504346688cd40f7b3"
   },
   "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>Year</th>\n",
       "      <th>bResult</th>\n",
       "      <th>rResult</th>\n",
       "      <th>gamelength</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7058.000000</td>\n",
       "      <td>7058.000000</td>\n",
       "      <td>7058.000000</td>\n",
       "      <td>7058.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2016.236611</td>\n",
       "      <td>0.544772</td>\n",
       "      <td>0.455228</td>\n",
       "      <td>36.941910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.795949</td>\n",
       "      <td>0.498027</td>\n",
       "      <td>0.498027</td>\n",
       "      <td>7.924203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2014.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>36.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2017.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>41.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2017.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>81.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year      bResult      rResult   gamelength\n",
       "count  7058.000000  7058.000000  7058.000000  7058.000000\n",
       "mean   2016.236611     0.544772     0.455228    36.941910\n",
       "std       0.795949     0.498027     0.498027     7.924203\n",
       "min    2014.000000     0.000000     0.000000    17.000000\n",
       "25%    2016.000000     0.000000     0.000000    31.000000\n",
       "50%    2016.000000     1.000000     0.000000    36.000000\n",
       "75%    2017.000000     1.000000     1.000000    41.000000\n",
       "max    2017.000000     1.000000     1.000000    81.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lol.describe()#Here we do a little statics describe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "295c6d3a-86d3-4837-88c2-357e03c893a5",
    "_uuid": "12a4ae1ed1abdcfffdd6ced43034bb8f7570f5a4"
   },
   "source": [
    "<center>\n",
    "Let's plot the graph of the frequency of game length on a line chart.\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_cell_guid": "b970134b-4d17-4593-957b-1d306b7afdf2",
    "_uuid": "8c4511349dadf66729e4cc508fb33d1da336ab17"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5a46f02710>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a46f20f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lol['gamelength'].value_counts().sort_index().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "8ca5372a-1070-4780-ae2c-ac9407028577",
    "_uuid": "fc13205c62690b89d99bd3550fc96c422e9ec4bb"
   },
   "source": [
    "<center>\n",
    "A histogram would be interesting too.\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "_cell_guid": "b27572ee-d9a5-4110-8e93-97a64f8676eb",
    "_uuid": "e9c9a9c2f04bcf120555c14657edc946617872a8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5a46ecb6d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a46edcf50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lol['gamelength'].plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "2f6dfd25-143b-48c5-80e5-2c1197bcc503",
    "_uuid": "a4d94ee29d6a7b4ff46c5cf4a87faa5390a299cb"
   },
   "source": [
    "Let's see what are the longest and fastest game that we have in this dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "_cell_guid": "ba65441c-3c2a-4922-b062-af91a3de1de4",
    "_uuid": "1d9cebdf6c8d5305bf332fd29d342ab4628c38f0"
   },
   "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>League</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>Type</th>\n",
       "      <th>blueTeamTag</th>\n",
       "      <th>bResult</th>\n",
       "      <th>rResult</th>\n",
       "      <th>redTeamTag</th>\n",
       "      <th>gamelength</th>\n",
       "      <th>blueTop</th>\n",
       "      <th>...</th>\n",
       "      <th>redTop</th>\n",
       "      <th>redTopChamp</th>\n",
       "      <th>redJungle</th>\n",
       "      <th>redJungleChamp</th>\n",
       "      <th>redMiddle</th>\n",
       "      <th>redMiddleChamp</th>\n",
       "      <th>redADC</th>\n",
       "      <th>redADCChamp</th>\n",
       "      <th>redSupport</th>\n",
       "      <th>redSupportChamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1510</th>\n",
       "      <td>EULCS</td>\n",
       "      <td>2016</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Season</td>\n",
       "      <td>OG</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>FNC</td>\n",
       "      <td>81</td>\n",
       "      <td>sOAZ</td>\n",
       "      <td>...</td>\n",
       "      <td>Gamsu</td>\n",
       "      <td>Trundle</td>\n",
       "      <td>Spirit</td>\n",
       "      <td>RekSai</td>\n",
       "      <td>Febiven</td>\n",
       "      <td>Viktor</td>\n",
       "      <td>Rekkles</td>\n",
       "      <td>Ezreal</td>\n",
       "      <td>YellOwStaR</td>\n",
       "      <td>Nami</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2115</th>\n",
       "      <td>LCK</td>\n",
       "      <td>2015</td>\n",
       "      <td>Spring</td>\n",
       "      <td>Season</td>\n",
       "      <td>JAG</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>CJE</td>\n",
       "      <td>81</td>\n",
       "      <td>TrAce</td>\n",
       "      <td>...</td>\n",
       "      <td>Shy</td>\n",
       "      <td>Maokai</td>\n",
       "      <td>Ambition</td>\n",
       "      <td>JarvanIV</td>\n",
       "      <td>Coco</td>\n",
       "      <td>Jayce</td>\n",
       "      <td>Space</td>\n",
       "      <td>Corki</td>\n",
       "      <td>MadLife</td>\n",
       "      <td>Nami</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     League  Year  Season    Type blueTeamTag  bResult  rResult redTeamTag  \\\n",
       "1510  EULCS  2016  Summer  Season          OG        1        0        FNC   \n",
       "2115    LCK  2015  Spring  Season         JAG        1        0        CJE   \n",
       "\n",
       "      gamelength blueTop       ...       redTop redTopChamp redJungle  \\\n",
       "1510          81    sOAZ       ...        Gamsu     Trundle    Spirit   \n",
       "2115          81   TrAce       ...          Shy      Maokai  Ambition   \n",
       "\n",
       "     redJungleChamp redMiddle redMiddleChamp   redADC redADCChamp  redSupport  \\\n",
       "1510         RekSai   Febiven         Viktor  Rekkles      Ezreal  YellOwStaR   \n",
       "2115       JarvanIV      Coco          Jayce    Space       Corki     MadLife   \n",
       "\n",
       "     redSupportChamp  \n",
       "1510            Nami  \n",
       "2115            Nami  \n",
       "\n",
       "[2 rows x 29 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lol[lol['gamelength']>80]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "8379e40d-12b6-42e6-8a66-fcf5169a6819",
    "_uuid": "5a9d6a10d5d0333fb7b9de2e593b78da81f8c01b"
   },
   "source": [
    "Ok, the longests games is both one of EU LCS in 2016 between fNatic and Origen, if you want, you can watch it <a href=\"https://www.youtube.com/watch?v=ExgH8dlbh0s\" >here.</a> <br>\n",
    "And the other were between Jin Air Wing and CJ Entus, but I couldn't find the link."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "_cell_guid": "96ab1f66-6f84-4088-a065-5c61331c2b0f",
    "_uuid": "354884622605f66a89caed30af84475e7f2307d1"
   },
   "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>League</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>Type</th>\n",
       "      <th>blueTeamTag</th>\n",
       "      <th>bResult</th>\n",
       "      <th>rResult</th>\n",
       "      <th>redTeamTag</th>\n",
       "      <th>gamelength</th>\n",
       "      <th>blueTop</th>\n",
       "      <th>...</th>\n",
       "      <th>redTop</th>\n",
       "      <th>redTopChamp</th>\n",
       "      <th>redJungle</th>\n",
       "      <th>redJungleChamp</th>\n",
       "      <th>redMiddle</th>\n",
       "      <th>redMiddleChamp</th>\n",
       "      <th>redADC</th>\n",
       "      <th>redADCChamp</th>\n",
       "      <th>redSupport</th>\n",
       "      <th>redSupportChamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4946</th>\n",
       "      <td>TCL</td>\n",
       "      <td>2017</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Season</td>\n",
       "      <td>FB</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>CLK</td>\n",
       "      <td>17</td>\n",
       "      <td>Thaldrin</td>\n",
       "      <td>...</td>\n",
       "      <td>Smoke</td>\n",
       "      <td>Kled</td>\n",
       "      <td>Kadir</td>\n",
       "      <td>Nocturne</td>\n",
       "      <td>umuut</td>\n",
       "      <td>Vladimir</td>\n",
       "      <td>DarkSide</td>\n",
       "      <td>Kalista</td>\n",
       "      <td>un1tback</td>\n",
       "      <td>Braum</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     League  Year  Season    Type blueTeamTag  bResult  rResult redTeamTag  \\\n",
       "4946    TCL  2017  Summer  Season          FB        1        0        CLK   \n",
       "\n",
       "      gamelength   blueTop       ...       redTop redTopChamp redJungle  \\\n",
       "4946          17  Thaldrin       ...        Smoke        Kled     Kadir   \n",
       "\n",
       "     redJungleChamp redMiddle redMiddleChamp    redADC redADCChamp redSupport  \\\n",
       "4946       Nocturne     umuut       Vladimir  DarkSide     Kalista   un1tback   \n",
       "\n",
       "     redSupportChamp  \n",
       "4946           Braum  \n",
       "\n",
       "[1 rows x 29 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lol[lol['gamelength']<18]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "e6237bd3-f722-4fb6-b2e4-300e8c02a56f",
    "_uuid": "48220f19e3dce0903deffa7e1be0dd85017a449f"
   },
   "source": [
    "The fastest game was in Turkey, between Çilekler and Fenerbahçe , and you can watch it <a href=\"https://www.youtube.com/watch?v=8D7YjcMi5nw\"> here</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "_cell_guid": "e0025523-2792-4596-b405-76e7d50cb657",
    "_uuid": "30bb4cbfd5bac09b28d9764f6abe3f683edfa105"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "League              object\n",
       "Year                 int64\n",
       "Season              object\n",
       "Type                object\n",
       "blueTeamTag         object\n",
       "bResult              int64\n",
       "rResult              int64\n",
       "redTeamTag          object\n",
       "gamelength           int64\n",
       "blueTop             object\n",
       "blueTopChamp        object\n",
       "blueJungle          object\n",
       "blueJungleChamp     object\n",
       "blueMiddle          object\n",
       "blueMiddleChamp     object\n",
       "blueADC             object\n",
       "blueADCChamp        object\n",
       "blueSupport         object\n",
       "blueSupportChamp    object\n",
       "redTop              object\n",
       "redTopChamp         object\n",
       "redJungle           object\n",
       "redJungleChamp      object\n",
       "redMiddle           object\n",
       "redMiddleChamp      object\n",
       "redADC              object\n",
       "redADCChamp         object\n",
       "redSupport          object\n",
       "redSupportChamp     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lol.dtypes #here we see that we'll not have problems with the types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "372f86f3-9c71-441d-a668-912b45ffa1c9",
    "_uuid": "75c87c76667e9b694ec5f249a91ed3e5d09d62a4"
   },
   "source": [
    "<center>\n",
    "<body >\n",
    "<font size = 3>\n",
    "So here it's where I plot the bars for the top teams who played the most games in each local league. <br>\n",
    "It was really difficult for me to think how I could do this and add the correct label for each team.\n",
    "What I thought was:<br>\n",
    "If I do a **general bar graph** with the correct order of the teams, then I make a copy of this general graph and **plot each region graph** on a copy. Ok, did you get it? Now the rest is easy, I just plot the graphs and everything looks beautiful.\n",
    "</font>\n",
    "</body>\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "_cell_guid": "d0f1c8e5-1867-4a54-ac8c-34c5c864a59c",
    "_uuid": "5852867b86f41c2d587bc1875e9a04daf221bf6e"
   },
   "outputs": [],
   "source": [
    "lol2016 = lol[lol['Year'] >= 2016] \n",
    "#2016 It's when the CBLOL starts to get recorde on the dataset.\n",
    "\n",
    "#Here I make the graphs of each region.\n",
    "lcsna = lol2016[lol2016['League'] == 'NALCS']\n",
    "\n",
    "lcseu = lol2016[lol2016['League'] == 'EULCS']\n",
    "\n",
    "lck = lol2016[lol2016['League'] == 'LCK']\n",
    "\n",
    "lms = lol2016[lol2016['League'] == 'LMS']\n",
    "\n",
    "cblol = lol2016[lol2016['League'] == 'CBLoL']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "_cell_guid": "86e2cdb5-3a2c-4d53-88ac-3701e3d9d2cb",
    "_uuid": "2d06af52872ecbb2b83ef5340d5e17a57bdcff72"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f5a421eae90>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a41e3ffd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top = 5 #Here it's a variable so I can change How many teams of each region I want to see.\n",
    "\n",
    "leagues = {\n",
    "'CBLOL': (cblol['blueTeamTag'].value_counts() + cblol['redTeamTag'].value_counts()).sort_values(ascending = False).head(top),\n",
    "'LCSNA': (lcsna['blueTeamTag'].value_counts() + lcsna['redTeamTag'].value_counts()).sort_values(ascending = False).head(top),\n",
    "'LCSEU': (lcseu['blueTeamTag'].value_counts() + lcseu['redTeamTag'].value_counts()).sort_values(ascending = False).head(top),\n",
    "'LCK': (lck['blueTeamTag'].value_counts() + lck['redTeamTag'].value_counts()).sort_values(ascending = False).head(top),\n",
    "'LMS': (lms['blueTeamTag'].value_counts() + lms['redTeamTag'].value_counts()).sort_values(ascending = False).head(top),\n",
    "}\n",
    "\n",
    "allGames = pd.DataFrame()\n",
    "\n",
    "total = pd.Series()\n",
    "total.name = 'total'\n",
    "\n",
    "for i in leagues:\n",
    "    leagues[i].name=i\n",
    "    allGames = allGames.append(leagues[i]).fillna(0)\n",
    "    total = total.append(leagues[i])\n",
    "    \n",
    "allGames = allGames.transpose()\n",
    "\n",
    "allGames['total'] = total\n",
    "allGames = allGames.sort_values('total')\n",
    "allGames = allGames.drop('total', axis = 1)\n",
    "\n",
    "allGames.plot.barh(figsize = (10,10), grid = False, stacked = True)\n",
    "\n",
    "plt.title('Top %s Teams Who Played The Most Games In Their Regions (2016-2017)' % top)\n",
    "plt.ylabel('Teams')\n",
    "plt.xlabel('Matches')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "6972d540-ae16-47bf-aaf7-b5984a26024c",
    "_uuid": "31541586aa897d5e0832857d77433cd96539774a"
   },
   "source": [
    "<center>\n",
    "<body >\n",
    "<font size = 4>\n",
    "Analysing this, it's obviously that the number of matches played can affect on the international perfomances, since the brazillian team who played the most, INTZ, it's not even close to the LCK team who played the less (of the top 8).\n",
    "Fortunately, Riot Games Brazil <a href = \"https://www.maisesports.com.br/cblol-2018-tera-novo-formato-com-md3/\"> already annouced that the format will change in 2018. </a> <br>\n",
    "Let's see if this will help the brazillian players to have a better perfomance on International Events, such as we see on CS:GO, where the brazillians are known to be one of the strongests players.\n",
    "</font>\n",
    "</body>\n",
    "</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "3d1dec8c-16f6-4df3-85bc-f94616ef5e08",
    "_uuid": "26a8e70bdc1e415fdb3b8036b329824b5c9b183e"
   },
   "source": [
    "<center>\n",
    "<h1>\n",
    "<font size = 4>\n",
    "Statistics about champions & players\n",
    "</font>\n",
    "</h1>\n",
    "<body >\n",
    "<font size = 4>\n",
    "Now, lets just view some statistics about the champions and players.\n",
    "</font>\n",
    "</body>\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "_cell_guid": "585080b5-a3d5-4a87-9a6f-f882fed5dfb7",
    "_uuid": "e5ee5fbc29d145f9fa5d11734a8a4ba2e05e2251",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gragas    1906.0\n",
      "Elise     1823.0\n",
      "Braum     1729.0\n",
      "RekSai    1581.0\n",
      "Karma     1561.0\n",
      "Ashe      1443.0\n",
      "Lucian    1343.0\n",
      "Jhin      1340.0\n",
      "Varus     1326.0\n",
      "Thresh    1225.0\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "56160.0"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "champions = lol2016.loc[:, 'blueTopChamp':'redSupportChamp']\n",
    "aux = 0\n",
    "for i in champions:\n",
    "    \n",
    "    if 'Champ' not in i:\n",
    "        champions = champions.drop(i, axis = 1) \n",
    "    else:\n",
    "        aux += champions[i].value_counts()\n",
    "\n",
    "a = pd.Series()\n",
    "for i in champions:\n",
    "    a = (a+champions[i].value_counts().sort_values(ascending=False)).fillna(0)\n",
    "    \n",
    "a[:] = 0\n",
    "champs = a.copy()\n",
    "for i in champions:\n",
    "    champs = champs+(a+champions[i].value_counts().sort_values(ascending=False)).fillna(0)\n",
    "    \n",
    "print(champs.sort_values(ascending = False).head(10))\n",
    "\"\"\"\n",
    "for i in champions:\n",
    "    if 'Gragas' in champions[i].value_counts():\n",
    "        print(champions[i].value_counts()['Gragas'])\n",
    "\"\"\"\n",
    "champs = champs.sort_values(ascending = False)\n",
    "champs.values.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "_cell_guid": "0578cfbd-f760-4e29-bfd4-35c72e9e815d",
    "_uuid": "73332d6e22771fb01cf5e321be5bed0d742eafe5",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,u'Champion')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a4008b910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "champs.head(10).plot(kind = 'bar', figsize=(15,6), grid = False, rot = 0, color = 'red')\n",
    "\n",
    "plt.title('Top 10 Champions Most Picked In Leagues')\n",
    "plt.ylabel('Matches')\n",
    "plt.xlabel('Champion')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "_cell_guid": "ff9f2911-3dec-4fe5-9a5b-4f09c6c8d126",
    "_uuid": "35f9c6f2cc546f6dbce2093f512ebe974bed8f32"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elise     113.0\n",
      "Braum     106.0\n",
      "RekSai     96.0\n",
      "Lucian     95.0\n",
      "Gragas     76.0\n",
      "Karma      74.0\n",
      "Thresh     71.0\n",
      "Varus      68.0\n",
      "Poppy      65.0\n",
      "Ezreal     65.0\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,u'Campeao')"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a4115abd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "champions = cblol.loc[:, 'blueTopChamp':'redSupportChamp']\n",
    "\n",
    "for i in champions:\n",
    "    \n",
    "    if 'Champ' not in i:\n",
    "        champions = champions.drop(i, axis = 1) \n",
    "    else:\n",
    "        aux += champions[i].value_counts()\n",
    "\n",
    "a = 0\n",
    "for i in champions:\n",
    "    a=a+champions[i].value_counts().sort_values(ascending=False)\n",
    "\n",
    "a = a.fillna(0)\n",
    "championsCblol = 0\n",
    "for i in champions:\n",
    "    championsCblol+=(a+champions[i].value_counts().sort_values(ascending=False)).fillna(0)\n",
    "\n",
    "print(championsCblol.sort_values(ascending = False).head(10))\n",
    "championsCblol = championsCblol.sort_values(ascending = False)\n",
    "\n",
    "championsCblol.head(10).plot(kind = 'bar', figsize=(15,6), grid = False, rot = 0, color = 'green')\n",
    "\n",
    "plt.title('Top 10 Champions Most Used In CBLOL')\n",
    "plt.ylabel('Matches')\n",
    "plt.xlabel('Champion')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "_cell_guid": "c978e7bd-165d-478e-8d51-9adad0e0630a",
    "_uuid": "af518c032529e12c57e0db96ff8fda8bb9d2fb0e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a3b664f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shape = 0\n",
    "for i in champions:\n",
    "    if 'blue' in i:\n",
    "        shape = shape + pd.crosstab( lol2016[i] ,lol2016['bResult']).fillna(0)\n",
    "    if 'red' in i:\n",
    "        shape = shape + pd.crosstab( lol2016[i] ,lol2016['rResult']).fillna(0)\n",
    "        \n",
    "shape[:] = 0\n",
    "\n",
    "victories = 0\n",
    "defeats = 0\n",
    "\n",
    "for i in champions:\n",
    "    if 'blue' in i:\n",
    "        victories += (shape + pd.crosstab( lol2016[i] ,lol2016['bResult'])).fillna(0)[1]\n",
    "        defeats += (shape + pd.crosstab( lol2016[i] ,lol2016['bResult'])).fillna(0)[0]\n",
    "    if 'red' in i:\n",
    "        victories += (shape + pd.crosstab( lol2016[i] ,lol2016['rResult'])).fillna(0)[1]\n",
    "        defeats += (shape + pd.crosstab( lol2016[i] ,lol2016['rResult'])).fillna(0)[0]\n",
    "\n",
    "#print(victories)\n",
    "        \n",
    "X = pd.DataFrame()\n",
    "X['total'] = champs.copy()\n",
    "X['victories'] = victories.copy()\n",
    "X['defeats'] = defeats.copy()\n",
    "X['winRate'] = X['victories']/X['total']\n",
    "\n",
    "X = X[X['total']>=100].sort_values('winRate', ascending = False)\n",
    "\n",
    "plt.figure(figsize=(5, 5))\n",
    "\n",
    "X['winRate'].head(10).sort_values().plot.barh() \n",
    "plt.title('Top 10 Champions Win Rate (More Than 100 games) in World 2016-2017')\n",
    "plt.xlabel('Win Rate')\n",
    "plt.ylabel('Champion')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "_cell_guid": "d9860cbc-f115-464a-8dd7-3f2666ccfa72",
    "_uuid": "0f9c5452089743e1dc5f5e733950e377c9d514f7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a3b192cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'Gragas'"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shape = pd.DataFrame()\n",
    "for i in champions:\n",
    "    shape = shape + pd.crosstab( lol2016[i] ,lol2016['League']).fillna(0)\n",
    "\n",
    "shape[:] = 0\n",
    "shape = shape.drop(['IEM', 'MSI', 'WC'], axis = 1)\n",
    "champions_Leagues = shape.copy()\n",
    "\n",
    "for j in champions:\n",
    "    champions_Leagues += (shape + pd.crosstab( lol2016[j] ,lol2016['League'])).fillna(0)\n",
    "\n",
    "    \n",
    "total = champions_Leagues['CBLoL'].copy()\n",
    "total[:]=0\n",
    "for i in champions_Leagues:\n",
    "    total = (total + champions_Leagues[i]).fillna(0)\n",
    "\n",
    "champions_Leagues['total'] = total\n",
    "\n",
    "sns.set(font_scale=1.2)\n",
    "plt.figure(figsize=(15, 8))\n",
    "champions_Leagues = champions_Leagues.sort_values(by = 'total', ascending = False).head(10)\n",
    "sns.heatmap(champions_Leagues, annot=True, vmax=champions_Leagues.loc[:, 'CBLoL':'TCL'].values.max(), vmin=champions_Leagues.loc[:, 'CBLoL':'TCL'].values.min(), fmt='g') \n",
    "\n",
    "plt.title('10 Most Picked Champions Heat Map By Region')\n",
    "plt.xlabel('Region')\n",
    "plt.ylabel('Champion')\n",
    "plt.show()\n",
    "total.idxmax()\n"
   ]
  }
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