RandomForest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This random forest will contain non-numeric feature columns also"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import roc_auc_score\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = pd.read_csv('dengue_features_train.csv')\n",
    "train_label_df = pd.read_csv('dengue_labels_train.csv')\n",
    "test_df = pd.read_csv('dengue_features_test.csv')\n",
    "test_orig_df = pd.DataFrame(test_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>year</th>\n",
       "      <th>weekofyear</th>\n",
       "      <th>week_start_date</th>\n",
       "      <th>ndvi_ne</th>\n",
       "      <th>ndvi_nw</th>\n",
       "      <th>ndvi_se</th>\n",
       "      <th>ndvi_sw</th>\n",
       "      <th>precipitation_amt_mm</th>\n",
       "      <th>reanalysis_air_temp_k</th>\n",
       "      <th>reanalysis_avg_temp_k</th>\n",
       "      <th>reanalysis_dew_point_temp_k</th>\n",
       "      <th>reanalysis_max_air_temp_k</th>\n",
       "      <th>reanalysis_min_air_temp_k</th>\n",
       "      <th>reanalysis_precip_amt_kg_per_m2</th>\n",
       "      <th>reanalysis_relative_humidity_percent</th>\n",
       "      <th>reanalysis_sat_precip_amt_mm</th>\n",
       "      <th>reanalysis_specific_humidity_g_per_kg</th>\n",
       "      <th>reanalysis_tdtr_k</th>\n",
       "      <th>station_avg_temp_c</th>\n",
       "      <th>station_diur_temp_rng_c</th>\n",
       "      <th>station_max_temp_c</th>\n",
       "      <th>station_min_temp_c</th>\n",
       "      <th>station_precip_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>18</td>\n",
       "      <td>1990-04-30</td>\n",
       "      <td>0.122600</td>\n",
       "      <td>0.103725</td>\n",
       "      <td>0.198483</td>\n",
       "      <td>0.177617</td>\n",
       "      <td>12.42</td>\n",
       "      <td>297.572857</td>\n",
       "      <td>297.742857</td>\n",
       "      <td>292.414286</td>\n",
       "      <td>299.8</td>\n",
       "      <td>295.9</td>\n",
       "      <td>32.00</td>\n",
       "      <td>73.365714</td>\n",
       "      <td>12.42</td>\n",
       "      <td>14.012857</td>\n",
       "      <td>2.628571</td>\n",
       "      <td>25.442857</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>29.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>19</td>\n",
       "      <td>1990-05-07</td>\n",
       "      <td>0.169900</td>\n",
       "      <td>0.142175</td>\n",
       "      <td>0.162357</td>\n",
       "      <td>0.155486</td>\n",
       "      <td>22.82</td>\n",
       "      <td>298.211429</td>\n",
       "      <td>298.442857</td>\n",
       "      <td>293.951429</td>\n",
       "      <td>300.9</td>\n",
       "      <td>296.4</td>\n",
       "      <td>17.94</td>\n",
       "      <td>77.368571</td>\n",
       "      <td>22.82</td>\n",
       "      <td>15.372857</td>\n",
       "      <td>2.371429</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.371429</td>\n",
       "      <td>31.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>20</td>\n",
       "      <td>1990-05-14</td>\n",
       "      <td>0.032250</td>\n",
       "      <td>0.172967</td>\n",
       "      <td>0.157200</td>\n",
       "      <td>0.170843</td>\n",
       "      <td>34.54</td>\n",
       "      <td>298.781429</td>\n",
       "      <td>298.878571</td>\n",
       "      <td>295.434286</td>\n",
       "      <td>300.5</td>\n",
       "      <td>297.3</td>\n",
       "      <td>26.10</td>\n",
       "      <td>82.052857</td>\n",
       "      <td>34.54</td>\n",
       "      <td>16.848571</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.485714</td>\n",
       "      <td>32.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>41.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>21</td>\n",
       "      <td>1990-05-21</td>\n",
       "      <td>0.128633</td>\n",
       "      <td>0.245067</td>\n",
       "      <td>0.227557</td>\n",
       "      <td>0.235886</td>\n",
       "      <td>15.36</td>\n",
       "      <td>298.987143</td>\n",
       "      <td>299.228571</td>\n",
       "      <td>295.310000</td>\n",
       "      <td>301.4</td>\n",
       "      <td>297.0</td>\n",
       "      <td>13.90</td>\n",
       "      <td>80.337143</td>\n",
       "      <td>15.36</td>\n",
       "      <td>16.672857</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>27.471429</td>\n",
       "      <td>6.771429</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.3</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>22</td>\n",
       "      <td>1990-05-28</td>\n",
       "      <td>0.196200</td>\n",
       "      <td>0.262200</td>\n",
       "      <td>0.251200</td>\n",
       "      <td>0.247340</td>\n",
       "      <td>7.52</td>\n",
       "      <td>299.518571</td>\n",
       "      <td>299.664286</td>\n",
       "      <td>295.821429</td>\n",
       "      <td>301.9</td>\n",
       "      <td>297.5</td>\n",
       "      <td>12.20</td>\n",
       "      <td>80.460000</td>\n",
       "      <td>7.52</td>\n",
       "      <td>17.210000</td>\n",
       "      <td>3.014286</td>\n",
       "      <td>28.942857</td>\n",
       "      <td>9.371429</td>\n",
       "      <td>35.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>23</td>\n",
       "      <td>1990-06-04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.174850</td>\n",
       "      <td>0.254314</td>\n",
       "      <td>0.181743</td>\n",
       "      <td>9.58</td>\n",
       "      <td>299.630000</td>\n",
       "      <td>299.764286</td>\n",
       "      <td>295.851429</td>\n",
       "      <td>302.4</td>\n",
       "      <td>298.1</td>\n",
       "      <td>26.49</td>\n",
       "      <td>79.891429</td>\n",
       "      <td>9.58</td>\n",
       "      <td>17.212857</td>\n",
       "      <td>2.100000</td>\n",
       "      <td>28.114286</td>\n",
       "      <td>6.942857</td>\n",
       "      <td>34.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>39.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>24</td>\n",
       "      <td>1990-06-11</td>\n",
       "      <td>0.112900</td>\n",
       "      <td>0.092800</td>\n",
       "      <td>0.205071</td>\n",
       "      <td>0.210271</td>\n",
       "      <td>3.48</td>\n",
       "      <td>299.207143</td>\n",
       "      <td>299.221429</td>\n",
       "      <td>295.865714</td>\n",
       "      <td>301.3</td>\n",
       "      <td>297.7</td>\n",
       "      <td>38.60</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>3.48</td>\n",
       "      <td>17.234286</td>\n",
       "      <td>2.042857</td>\n",
       "      <td>27.414286</td>\n",
       "      <td>6.771429</td>\n",
       "      <td>32.2</td>\n",
       "      <td>23.3</td>\n",
       "      <td>29.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>25</td>\n",
       "      <td>1990-06-18</td>\n",
       "      <td>0.072500</td>\n",
       "      <td>0.072500</td>\n",
       "      <td>0.151471</td>\n",
       "      <td>0.133029</td>\n",
       "      <td>151.12</td>\n",
       "      <td>299.591429</td>\n",
       "      <td>299.528571</td>\n",
       "      <td>296.531429</td>\n",
       "      <td>300.6</td>\n",
       "      <td>298.4</td>\n",
       "      <td>30.00</td>\n",
       "      <td>83.375714</td>\n",
       "      <td>151.12</td>\n",
       "      <td>17.977143</td>\n",
       "      <td>1.571429</td>\n",
       "      <td>28.371429</td>\n",
       "      <td>7.685714</td>\n",
       "      <td>33.9</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>26</td>\n",
       "      <td>1990-06-25</td>\n",
       "      <td>0.102450</td>\n",
       "      <td>0.146175</td>\n",
       "      <td>0.125571</td>\n",
       "      <td>0.123600</td>\n",
       "      <td>19.32</td>\n",
       "      <td>299.578571</td>\n",
       "      <td>299.557143</td>\n",
       "      <td>296.378571</td>\n",
       "      <td>302.1</td>\n",
       "      <td>297.7</td>\n",
       "      <td>37.51</td>\n",
       "      <td>82.768571</td>\n",
       "      <td>19.32</td>\n",
       "      <td>17.790000</td>\n",
       "      <td>1.885714</td>\n",
       "      <td>28.328571</td>\n",
       "      <td>7.385714</td>\n",
       "      <td>33.9</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>27</td>\n",
       "      <td>1990-07-02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.121550</td>\n",
       "      <td>0.160683</td>\n",
       "      <td>0.202567</td>\n",
       "      <td>14.41</td>\n",
       "      <td>300.154286</td>\n",
       "      <td>300.278571</td>\n",
       "      <td>296.651429</td>\n",
       "      <td>302.3</td>\n",
       "      <td>298.7</td>\n",
       "      <td>28.40</td>\n",
       "      <td>81.281429</td>\n",
       "      <td>14.41</td>\n",
       "      <td>18.071429</td>\n",
       "      <td>2.014286</td>\n",
       "      <td>28.328571</td>\n",
       "      <td>6.514286</td>\n",
       "      <td>33.9</td>\n",
       "      <td>24.4</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>28</td>\n",
       "      <td>1990-07-09</td>\n",
       "      <td>0.192875</td>\n",
       "      <td>0.082350</td>\n",
       "      <td>0.191943</td>\n",
       "      <td>0.152929</td>\n",
       "      <td>22.27</td>\n",
       "      <td>299.512857</td>\n",
       "      <td>299.592857</td>\n",
       "      <td>296.041429</td>\n",
       "      <td>301.8</td>\n",
       "      <td>298.0</td>\n",
       "      <td>43.72</td>\n",
       "      <td>81.467143</td>\n",
       "      <td>22.27</td>\n",
       "      <td>17.418571</td>\n",
       "      <td>2.157143</td>\n",
       "      <td>27.557143</td>\n",
       "      <td>7.157143</td>\n",
       "      <td>31.7</td>\n",
       "      <td>21.7</td>\n",
       "      <td>63.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>29</td>\n",
       "      <td>1990-07-16</td>\n",
       "      <td>0.291600</td>\n",
       "      <td>0.211800</td>\n",
       "      <td>0.301200</td>\n",
       "      <td>0.280667</td>\n",
       "      <td>59.17</td>\n",
       "      <td>299.667143</td>\n",
       "      <td>299.750000</td>\n",
       "      <td>296.334286</td>\n",
       "      <td>302.0</td>\n",
       "      <td>297.3</td>\n",
       "      <td>40.90</td>\n",
       "      <td>82.144286</td>\n",
       "      <td>59.17</td>\n",
       "      <td>17.737143</td>\n",
       "      <td>2.414286</td>\n",
       "      <td>28.128571</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.9</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>30</td>\n",
       "      <td>1990-07-23</td>\n",
       "      <td>0.150567</td>\n",
       "      <td>0.171700</td>\n",
       "      <td>0.226900</td>\n",
       "      <td>0.214557</td>\n",
       "      <td>16.48</td>\n",
       "      <td>299.558571</td>\n",
       "      <td>299.635714</td>\n",
       "      <td>295.960000</td>\n",
       "      <td>301.8</td>\n",
       "      <td>297.1</td>\n",
       "      <td>42.53</td>\n",
       "      <td>80.742857</td>\n",
       "      <td>16.48</td>\n",
       "      <td>17.341429</td>\n",
       "      <td>2.071429</td>\n",
       "      <td>28.114286</td>\n",
       "      <td>6.357143</td>\n",
       "      <td>31.7</td>\n",
       "      <td>22.8</td>\n",
       "      <td>32.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>31</td>\n",
       "      <td>1990-07-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.247150</td>\n",
       "      <td>0.379700</td>\n",
       "      <td>0.381357</td>\n",
       "      <td>32.66</td>\n",
       "      <td>299.862857</td>\n",
       "      <td>299.950000</td>\n",
       "      <td>296.172857</td>\n",
       "      <td>303.0</td>\n",
       "      <td>298.3</td>\n",
       "      <td>34.60</td>\n",
       "      <td>80.584286</td>\n",
       "      <td>32.66</td>\n",
       "      <td>17.594286</td>\n",
       "      <td>2.585714</td>\n",
       "      <td>28.242857</td>\n",
       "      <td>8.085714</td>\n",
       "      <td>34.4</td>\n",
       "      <td>22.8</td>\n",
       "      <td>37.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>32</td>\n",
       "      <td>1990-08-06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.064333</td>\n",
       "      <td>0.164443</td>\n",
       "      <td>0.138857</td>\n",
       "      <td>28.80</td>\n",
       "      <td>300.391429</td>\n",
       "      <td>300.478571</td>\n",
       "      <td>296.532857</td>\n",
       "      <td>302.5</td>\n",
       "      <td>298.8</td>\n",
       "      <td>20.00</td>\n",
       "      <td>79.650000</td>\n",
       "      <td>28.80</td>\n",
       "      <td>17.950000</td>\n",
       "      <td>2.328571</td>\n",
       "      <td>28.200000</td>\n",
       "      <td>7.557143</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.3</td>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>33</td>\n",
       "      <td>1990-08-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.128033</td>\n",
       "      <td>0.206957</td>\n",
       "      <td>0.168243</td>\n",
       "      <td>90.75</td>\n",
       "      <td>299.958571</td>\n",
       "      <td>299.957143</td>\n",
       "      <td>297.035714</td>\n",
       "      <td>302.6</td>\n",
       "      <td>298.5</td>\n",
       "      <td>101.90</td>\n",
       "      <td>84.178571</td>\n",
       "      <td>90.75</td>\n",
       "      <td>18.515714</td>\n",
       "      <td>1.857143</td>\n",
       "      <td>28.042857</td>\n",
       "      <td>6.685714</td>\n",
       "      <td>32.8</td>\n",
       "      <td>22.8</td>\n",
       "      <td>44.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>34</td>\n",
       "      <td>1990-08-20</td>\n",
       "      <td>0.190233</td>\n",
       "      <td>0.168800</td>\n",
       "      <td>0.167657</td>\n",
       "      <td>0.172286</td>\n",
       "      <td>32.40</td>\n",
       "      <td>300.332857</td>\n",
       "      <td>300.414286</td>\n",
       "      <td>296.728571</td>\n",
       "      <td>302.5</td>\n",
       "      <td>298.1</td>\n",
       "      <td>25.90</td>\n",
       "      <td>80.947143</td>\n",
       "      <td>32.40</td>\n",
       "      <td>18.174286</td>\n",
       "      <td>2.485714</td>\n",
       "      <td>28.342857</td>\n",
       "      <td>7.014286</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.3</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>35</td>\n",
       "      <td>1990-08-27</td>\n",
       "      <td>0.252900</td>\n",
       "      <td>0.330750</td>\n",
       "      <td>0.264171</td>\n",
       "      <td>0.284314</td>\n",
       "      <td>40.94</td>\n",
       "      <td>300.118571</td>\n",
       "      <td>300.221429</td>\n",
       "      <td>297.017143</td>\n",
       "      <td>302.2</td>\n",
       "      <td>298.7</td>\n",
       "      <td>39.80</td>\n",
       "      <td>83.348571</td>\n",
       "      <td>40.94</td>\n",
       "      <td>18.515714</td>\n",
       "      <td>1.900000</td>\n",
       "      <td>28.657143</td>\n",
       "      <td>6.528571</td>\n",
       "      <td>32.2</td>\n",
       "      <td>24.4</td>\n",
       "      <td>13.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>36</td>\n",
       "      <td>1990-09-03</td>\n",
       "      <td>0.235400</td>\n",
       "      <td>0.200025</td>\n",
       "      <td>0.283817</td>\n",
       "      <td>0.230443</td>\n",
       "      <td>28.86</td>\n",
       "      <td>300.530000</td>\n",
       "      <td>300.635714</td>\n",
       "      <td>296.117143</td>\n",
       "      <td>303.8</td>\n",
       "      <td>298.0</td>\n",
       "      <td>30.40</td>\n",
       "      <td>77.172857</td>\n",
       "      <td>28.86</td>\n",
       "      <td>17.560000</td>\n",
       "      <td>3.471429</td>\n",
       "      <td>28.328571</td>\n",
       "      <td>7.614286</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>14.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>37</td>\n",
       "      <td>1990-09-10</td>\n",
       "      <td>0.127967</td>\n",
       "      <td>0.437100</td>\n",
       "      <td>0.123400</td>\n",
       "      <td>0.148283</td>\n",
       "      <td>64.56</td>\n",
       "      <td>300.674286</td>\n",
       "      <td>300.792857</td>\n",
       "      <td>297.192857</td>\n",
       "      <td>302.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>24.18</td>\n",
       "      <td>81.551429</td>\n",
       "      <td>64.56</td>\n",
       "      <td>18.777143</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>28.685714</td>\n",
       "      <td>8.057143</td>\n",
       "      <td>33.9</td>\n",
       "      <td>24.4</td>\n",
       "      <td>25.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>38</td>\n",
       "      <td>1990-09-17</td>\n",
       "      <td>0.196350</td>\n",
       "      <td>0.182433</td>\n",
       "      <td>0.254829</td>\n",
       "      <td>0.305686</td>\n",
       "      <td>143.73</td>\n",
       "      <td>299.857143</td>\n",
       "      <td>299.900000</td>\n",
       "      <td>296.431429</td>\n",
       "      <td>301.7</td>\n",
       "      <td>298.7</td>\n",
       "      <td>36.60</td>\n",
       "      <td>81.637143</td>\n",
       "      <td>143.73</td>\n",
       "      <td>17.892857</td>\n",
       "      <td>1.742857</td>\n",
       "      <td>28.242857</td>\n",
       "      <td>8.114286</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.9</td>\n",
       "      <td>3.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>39</td>\n",
       "      <td>1990-09-24</td>\n",
       "      <td>0.116100</td>\n",
       "      <td>0.260900</td>\n",
       "      <td>0.199443</td>\n",
       "      <td>0.244217</td>\n",
       "      <td>51.39</td>\n",
       "      <td>300.427143</td>\n",
       "      <td>300.600000</td>\n",
       "      <td>296.028571</td>\n",
       "      <td>302.4</td>\n",
       "      <td>299.1</td>\n",
       "      <td>16.40</td>\n",
       "      <td>77.048571</td>\n",
       "      <td>51.39</td>\n",
       "      <td>17.468571</td>\n",
       "      <td>2.257143</td>\n",
       "      <td>28.342857</td>\n",
       "      <td>7.728571</td>\n",
       "      <td>32.8</td>\n",
       "      <td>24.4</td>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>40</td>\n",
       "      <td>1990-10-01</td>\n",
       "      <td>0.228550</td>\n",
       "      <td>0.189750</td>\n",
       "      <td>0.212486</td>\n",
       "      <td>0.201186</td>\n",
       "      <td>31.18</td>\n",
       "      <td>300.775714</td>\n",
       "      <td>300.850000</td>\n",
       "      <td>296.664286</td>\n",
       "      <td>303.3</td>\n",
       "      <td>299.1</td>\n",
       "      <td>36.10</td>\n",
       "      <td>78.520000</td>\n",
       "      <td>31.18</td>\n",
       "      <td>18.180000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>28.771429</td>\n",
       "      <td>8.028571</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>41</td>\n",
       "      <td>1990-10-08</td>\n",
       "      <td>0.171150</td>\n",
       "      <td>0.067550</td>\n",
       "      <td>0.179467</td>\n",
       "      <td>0.157717</td>\n",
       "      <td>51.42</td>\n",
       "      <td>299.857143</td>\n",
       "      <td>299.942857</td>\n",
       "      <td>296.928571</td>\n",
       "      <td>301.8</td>\n",
       "      <td>298.1</td>\n",
       "      <td>132.40</td>\n",
       "      <td>84.110000</td>\n",
       "      <td>51.42</td>\n",
       "      <td>18.512857</td>\n",
       "      <td>2.571429</td>\n",
       "      <td>28.628571</td>\n",
       "      <td>7.314286</td>\n",
       "      <td>33.3</td>\n",
       "      <td>24.4</td>\n",
       "      <td>57.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>42</td>\n",
       "      <td>1990-10-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.070200</td>\n",
       "      <td>0.181617</td>\n",
       "      <td>0.165750</td>\n",
       "      <td>143.55</td>\n",
       "      <td>299.195714</td>\n",
       "      <td>299.307143</td>\n",
       "      <td>296.544286</td>\n",
       "      <td>301.5</td>\n",
       "      <td>297.5</td>\n",
       "      <td>279.60</td>\n",
       "      <td>85.621429</td>\n",
       "      <td>143.55</td>\n",
       "      <td>18.115714</td>\n",
       "      <td>1.871429</td>\n",
       "      <td>27.628571</td>\n",
       "      <td>7.400000</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>61.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>43</td>\n",
       "      <td>1990-10-22</td>\n",
       "      <td>0.146200</td>\n",
       "      <td>0.089750</td>\n",
       "      <td>0.128829</td>\n",
       "      <td>0.123929</td>\n",
       "      <td>127.03</td>\n",
       "      <td>298.902857</td>\n",
       "      <td>299.042857</td>\n",
       "      <td>296.257143</td>\n",
       "      <td>300.9</td>\n",
       "      <td>297.2</td>\n",
       "      <td>94.52</td>\n",
       "      <td>85.502857</td>\n",
       "      <td>127.03</td>\n",
       "      <td>17.750000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>26.771429</td>\n",
       "      <td>7.628571</td>\n",
       "      <td>32.2</td>\n",
       "      <td>21.7</td>\n",
       "      <td>91.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>44</td>\n",
       "      <td>1990-10-29</td>\n",
       "      <td>0.252250</td>\n",
       "      <td>0.183433</td>\n",
       "      <td>0.318000</td>\n",
       "      <td>0.295900</td>\n",
       "      <td>101.35</td>\n",
       "      <td>299.727143</td>\n",
       "      <td>299.778571</td>\n",
       "      <td>296.534286</td>\n",
       "      <td>301.4</td>\n",
       "      <td>298.5</td>\n",
       "      <td>22.26</td>\n",
       "      <td>82.787143</td>\n",
       "      <td>101.35</td>\n",
       "      <td>18.034286</td>\n",
       "      <td>1.785714</td>\n",
       "      <td>27.971429</td>\n",
       "      <td>8.642857</td>\n",
       "      <td>33.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>6.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>45</td>\n",
       "      <td>1990-11-05</td>\n",
       "      <td>0.152600</td>\n",
       "      <td>0.181775</td>\n",
       "      <td>0.178329</td>\n",
       "      <td>0.186629</td>\n",
       "      <td>20.46</td>\n",
       "      <td>299.972857</td>\n",
       "      <td>300.035714</td>\n",
       "      <td>296.564286</td>\n",
       "      <td>302.2</td>\n",
       "      <td>298.5</td>\n",
       "      <td>14.40</td>\n",
       "      <td>81.715714</td>\n",
       "      <td>20.46</td>\n",
       "      <td>18.074286</td>\n",
       "      <td>2.385714</td>\n",
       "      <td>28.471429</td>\n",
       "      <td>8.428571</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>46</td>\n",
       "      <td>1990-11-12</td>\n",
       "      <td>0.290800</td>\n",
       "      <td>0.224600</td>\n",
       "      <td>0.180386</td>\n",
       "      <td>0.234886</td>\n",
       "      <td>20.00</td>\n",
       "      <td>300.350000</td>\n",
       "      <td>300.500000</td>\n",
       "      <td>295.687143</td>\n",
       "      <td>302.3</td>\n",
       "      <td>298.8</td>\n",
       "      <td>7.10</td>\n",
       "      <td>75.728571</td>\n",
       "      <td>20.00</td>\n",
       "      <td>17.085714</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>27.542857</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>32.8</td>\n",
       "      <td>22.2</td>\n",
       "      <td>38.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>47</td>\n",
       "      <td>1990-11-19</td>\n",
       "      <td>0.272200</td>\n",
       "      <td>0.330350</td>\n",
       "      <td>0.131633</td>\n",
       "      <td>0.125383</td>\n",
       "      <td>20.04</td>\n",
       "      <td>299.511429</td>\n",
       "      <td>299.635714</td>\n",
       "      <td>295.375714</td>\n",
       "      <td>301.6</td>\n",
       "      <td>297.0</td>\n",
       "      <td>36.70</td>\n",
       "      <td>78.151429</td>\n",
       "      <td>20.04</td>\n",
       "      <td>16.752857</td>\n",
       "      <td>2.528571</td>\n",
       "      <td>26.800000</td>\n",
       "      <td>7.414286</td>\n",
       "      <td>31.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>9.6</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",
       "      <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>1426</th>\n",
       "      <td>iq</td>\n",
       "      <td>2009</td>\n",
       "      <td>49</td>\n",
       "      <td>2009-12-03</td>\n",
       "      <td>0.348529</td>\n",
       "      <td>0.290400</td>\n",
       "      <td>0.410614</td>\n",
       "      <td>0.370457</td>\n",
       "      <td>73.45</td>\n",
       "      <td>298.762857</td>\n",
       "      <td>299.935714</td>\n",
       "      <td>296.970000</td>\n",
       "      <td>308.9</td>\n",
       "      <td>295.0</td>\n",
       "      <td>134.43</td>\n",
       "      <td>91.708571</td>\n",
       "      <td>73.45</td>\n",
       "      <td>18.671429</td>\n",
       "      <td>7.757143</td>\n",
       "      <td>28.025000</td>\n",
       "      <td>10.375000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>22.2</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1427</th>\n",
       "      <td>iq</td>\n",
       "      <td>2009</td>\n",
       "      <td>50</td>\n",
       "      <td>2009-12-10</td>\n",
       "      <td>0.192200</td>\n",
       "      <td>0.193529</td>\n",
       "      <td>0.239886</td>\n",
       "      <td>0.285886</td>\n",
       "      <td>85.62</td>\n",
       "      <td>299.198571</td>\n",
       "      <td>300.678571</td>\n",
       "      <td>296.595714</td>\n",
       "      <td>308.6</td>\n",
       "      <td>294.6</td>\n",
       "      <td>49.32</td>\n",
       "      <td>87.752857</td>\n",
       "      <td>85.62</td>\n",
       "      <td>18.304286</td>\n",
       "      <td>10.442857</td>\n",
       "      <td>28.550000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>35.2</td>\n",
       "      <td>21.2</td>\n",
       "      <td>41.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1428</th>\n",
       "      <td>iq</td>\n",
       "      <td>2009</td>\n",
       "      <td>51</td>\n",
       "      <td>2009-12-17</td>\n",
       "      <td>0.217600</td>\n",
       "      <td>0.240300</td>\n",
       "      <td>0.181771</td>\n",
       "      <td>0.262300</td>\n",
       "      <td>81.21</td>\n",
       "      <td>298.347143</td>\n",
       "      <td>299.350000</td>\n",
       "      <td>296.905714</td>\n",
       "      <td>307.5</td>\n",
       "      <td>295.0</td>\n",
       "      <td>208.87</td>\n",
       "      <td>92.958571</td>\n",
       "      <td>81.21</td>\n",
       "      <td>18.601429</td>\n",
       "      <td>6.671429</td>\n",
       "      <td>28.200000</td>\n",
       "      <td>11.125000</td>\n",
       "      <td>35.6</td>\n",
       "      <td>22.0</td>\n",
       "      <td>54.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1429</th>\n",
       "      <td>iq</td>\n",
       "      <td>2009</td>\n",
       "      <td>52</td>\n",
       "      <td>2009-12-24</td>\n",
       "      <td>0.210422</td>\n",
       "      <td>0.257138</td>\n",
       "      <td>0.221133</td>\n",
       "      <td>0.300256</td>\n",
       "      <td>98.79</td>\n",
       "      <td>297.181429</td>\n",
       "      <td>298.185714</td>\n",
       "      <td>296.557143</td>\n",
       "      <td>302.9</td>\n",
       "      <td>294.9</td>\n",
       "      <td>66.30</td>\n",
       "      <td>96.885714</td>\n",
       "      <td>98.79</td>\n",
       "      <td>18.180000</td>\n",
       "      <td>5.257143</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>32.2</td>\n",
       "      <td>21.8</td>\n",
       "      <td>31.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1430</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1431</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>0.124571</td>\n",
       "      <td>0.179129</td>\n",
       "      <td>0.163843</td>\n",
       "      <td>0.135471</td>\n",
       "      <td>27.04</td>\n",
       "      <td>299.264286</td>\n",
       "      <td>300.521429</td>\n",
       "      <td>294.530000</td>\n",
       "      <td>308.6</td>\n",
       "      <td>292.8</td>\n",
       "      <td>8.50</td>\n",
       "      <td>78.271429</td>\n",
       "      <td>27.04</td>\n",
       "      <td>16.127143</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>28.600000</td>\n",
       "      <td>12.300000</td>\n",
       "      <td>35.1</td>\n",
       "      <td>21.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1432</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>2010-01-15</td>\n",
       "      <td>0.145286</td>\n",
       "      <td>0.142314</td>\n",
       "      <td>0.135300</td>\n",
       "      <td>0.167529</td>\n",
       "      <td>32.99</td>\n",
       "      <td>298.297143</td>\n",
       "      <td>299.935714</td>\n",
       "      <td>296.147143</td>\n",
       "      <td>308.0</td>\n",
       "      <td>293.8</td>\n",
       "      <td>144.60</td>\n",
       "      <td>89.807143</td>\n",
       "      <td>32.99</td>\n",
       "      <td>17.758571</td>\n",
       "      <td>9.157143</td>\n",
       "      <td>27.833333</td>\n",
       "      <td>11.300000</td>\n",
       "      <td>34.2</td>\n",
       "      <td>22.1</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1433</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td>2010-01-22</td>\n",
       "      <td>0.252114</td>\n",
       "      <td>0.230486</td>\n",
       "      <td>0.187329</td>\n",
       "      <td>0.302786</td>\n",
       "      <td>19.04</td>\n",
       "      <td>298.925714</td>\n",
       "      <td>300.457143</td>\n",
       "      <td>296.380000</td>\n",
       "      <td>307.8</td>\n",
       "      <td>294.8</td>\n",
       "      <td>31.20</td>\n",
       "      <td>87.641429</td>\n",
       "      <td>19.04</td>\n",
       "      <td>18.001429</td>\n",
       "      <td>8.628571</td>\n",
       "      <td>28.966667</td>\n",
       "      <td>11.266667</td>\n",
       "      <td>35.2</td>\n",
       "      <td>22.5</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1434</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td>2010-01-29</td>\n",
       "      <td>0.263271</td>\n",
       "      <td>0.230600</td>\n",
       "      <td>0.218871</td>\n",
       "      <td>0.261286</td>\n",
       "      <td>138.51</td>\n",
       "      <td>298.291429</td>\n",
       "      <td>299.614286</td>\n",
       "      <td>296.560000</td>\n",
       "      <td>308.3</td>\n",
       "      <td>295.0</td>\n",
       "      <td>65.76</td>\n",
       "      <td>91.798571</td>\n",
       "      <td>138.51</td>\n",
       "      <td>18.192857</td>\n",
       "      <td>7.685714</td>\n",
       "      <td>27.800000</td>\n",
       "      <td>10.520000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>22.4</td>\n",
       "      <td>166.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1435</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "      <td>2010-02-05</td>\n",
       "      <td>0.170100</td>\n",
       "      <td>0.142117</td>\n",
       "      <td>0.117914</td>\n",
       "      <td>0.139343</td>\n",
       "      <td>47.31</td>\n",
       "      <td>298.754286</td>\n",
       "      <td>300.342857</td>\n",
       "      <td>296.837143</td>\n",
       "      <td>306.1</td>\n",
       "      <td>295.6</td>\n",
       "      <td>95.83</td>\n",
       "      <td>90.648571</td>\n",
       "      <td>47.31</td>\n",
       "      <td>18.522857</td>\n",
       "      <td>8.314286</td>\n",
       "      <td>27.800000</td>\n",
       "      <td>9.266667</td>\n",
       "      <td>34.2</td>\n",
       "      <td>22.0</td>\n",
       "      <td>62.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1436</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-02-12</td>\n",
       "      <td>0.230757</td>\n",
       "      <td>0.189257</td>\n",
       "      <td>0.163486</td>\n",
       "      <td>0.238871</td>\n",
       "      <td>78.25</td>\n",
       "      <td>298.251429</td>\n",
       "      <td>299.678571</td>\n",
       "      <td>297.568571</td>\n",
       "      <td>306.2</td>\n",
       "      <td>295.5</td>\n",
       "      <td>172.70</td>\n",
       "      <td>96.515714</td>\n",
       "      <td>78.25</td>\n",
       "      <td>19.345714</td>\n",
       "      <td>6.328571</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>8.300000</td>\n",
       "      <td>33.2</td>\n",
       "      <td>22.9</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1437</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>7</td>\n",
       "      <td>2010-02-19</td>\n",
       "      <td>0.293300</td>\n",
       "      <td>0.247829</td>\n",
       "      <td>0.206629</td>\n",
       "      <td>0.266671</td>\n",
       "      <td>32.19</td>\n",
       "      <td>299.648571</td>\n",
       "      <td>300.950000</td>\n",
       "      <td>297.090000</td>\n",
       "      <td>309.2</td>\n",
       "      <td>294.5</td>\n",
       "      <td>54.20</td>\n",
       "      <td>88.365714</td>\n",
       "      <td>32.19</td>\n",
       "      <td>18.857143</td>\n",
       "      <td>9.414286</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>11.800000</td>\n",
       "      <td>35.5</td>\n",
       "      <td>21.4</td>\n",
       "      <td>60.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1438</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-02-26</td>\n",
       "      <td>0.303657</td>\n",
       "      <td>0.260057</td>\n",
       "      <td>0.225486</td>\n",
       "      <td>0.333314</td>\n",
       "      <td>84.67</td>\n",
       "      <td>298.917143</td>\n",
       "      <td>300.485714</td>\n",
       "      <td>297.928571</td>\n",
       "      <td>308.2</td>\n",
       "      <td>295.2</td>\n",
       "      <td>288.40</td>\n",
       "      <td>94.915714</td>\n",
       "      <td>84.67</td>\n",
       "      <td>19.772857</td>\n",
       "      <td>8.171429</td>\n",
       "      <td>28.020000</td>\n",
       "      <td>10.360000</td>\n",
       "      <td>35.4</td>\n",
       "      <td>21.4</td>\n",
       "      <td>29.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1439</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>9</td>\n",
       "      <td>2010-03-05</td>\n",
       "      <td>0.127317</td>\n",
       "      <td>0.181160</td>\n",
       "      <td>0.120467</td>\n",
       "      <td>0.142767</td>\n",
       "      <td>80.58</td>\n",
       "      <td>298.337143</td>\n",
       "      <td>299.664286</td>\n",
       "      <td>297.917143</td>\n",
       "      <td>306.3</td>\n",
       "      <td>295.8</td>\n",
       "      <td>144.98</td>\n",
       "      <td>97.700000</td>\n",
       "      <td>80.58</td>\n",
       "      <td>19.754286</td>\n",
       "      <td>6.242857</td>\n",
       "      <td>28.500000</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>35.4</td>\n",
       "      <td>21.2</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1440</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>10</td>\n",
       "      <td>2010-03-12</td>\n",
       "      <td>0.311729</td>\n",
       "      <td>0.292686</td>\n",
       "      <td>0.272586</td>\n",
       "      <td>0.394800</td>\n",
       "      <td>57.78</td>\n",
       "      <td>298.837143</td>\n",
       "      <td>300.092857</td>\n",
       "      <td>298.141429</td>\n",
       "      <td>306.9</td>\n",
       "      <td>292.8</td>\n",
       "      <td>86.10</td>\n",
       "      <td>96.250000</td>\n",
       "      <td>57.78</td>\n",
       "      <td>20.091429</td>\n",
       "      <td>8.814286</td>\n",
       "      <td>28.550000</td>\n",
       "      <td>10.050000</td>\n",
       "      <td>35.4</td>\n",
       "      <td>21.4</td>\n",
       "      <td>44.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1441</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>11</td>\n",
       "      <td>2010-03-19</td>\n",
       "      <td>0.294600</td>\n",
       "      <td>0.250971</td>\n",
       "      <td>0.281471</td>\n",
       "      <td>0.341643</td>\n",
       "      <td>121.20</td>\n",
       "      <td>299.191429</td>\n",
       "      <td>300.928571</td>\n",
       "      <td>298.450000</td>\n",
       "      <td>307.4</td>\n",
       "      <td>294.0</td>\n",
       "      <td>191.76</td>\n",
       "      <td>96.124286</td>\n",
       "      <td>121.20</td>\n",
       "      <td>20.461429</td>\n",
       "      <td>8.828571</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>36.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1442</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>2010-03-26</td>\n",
       "      <td>0.266286</td>\n",
       "      <td>0.301233</td>\n",
       "      <td>0.296000</td>\n",
       "      <td>0.295743</td>\n",
       "      <td>51.29</td>\n",
       "      <td>299.004286</td>\n",
       "      <td>300.300000</td>\n",
       "      <td>297.555714</td>\n",
       "      <td>307.9</td>\n",
       "      <td>294.6</td>\n",
       "      <td>214.90</td>\n",
       "      <td>93.082857</td>\n",
       "      <td>51.29</td>\n",
       "      <td>19.368571</td>\n",
       "      <td>8.028571</td>\n",
       "      <td>27.466667</td>\n",
       "      <td>9.333333</td>\n",
       "      <td>34.5</td>\n",
       "      <td>21.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1443</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>13</td>\n",
       "      <td>2010-04-02</td>\n",
       "      <td>0.141433</td>\n",
       "      <td>0.204729</td>\n",
       "      <td>0.250971</td>\n",
       "      <td>0.145243</td>\n",
       "      <td>49.80</td>\n",
       "      <td>299.002857</td>\n",
       "      <td>300.714286</td>\n",
       "      <td>296.568571</td>\n",
       "      <td>309.1</td>\n",
       "      <td>294.2</td>\n",
       "      <td>24.25</td>\n",
       "      <td>88.707143</td>\n",
       "      <td>49.80</td>\n",
       "      <td>18.214286</td>\n",
       "      <td>9.514286</td>\n",
       "      <td>27.933333</td>\n",
       "      <td>12.300000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>21.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1444</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>14</td>\n",
       "      <td>2010-04-09</td>\n",
       "      <td>0.242843</td>\n",
       "      <td>0.272757</td>\n",
       "      <td>0.202271</td>\n",
       "      <td>0.260114</td>\n",
       "      <td>93.76</td>\n",
       "      <td>299.115714</td>\n",
       "      <td>300.271429</td>\n",
       "      <td>298.161429</td>\n",
       "      <td>308.4</td>\n",
       "      <td>294.6</td>\n",
       "      <td>164.70</td>\n",
       "      <td>95.182857</td>\n",
       "      <td>93.76</td>\n",
       "      <td>20.078571</td>\n",
       "      <td>7.714286</td>\n",
       "      <td>29.200000</td>\n",
       "      <td>12.300000</td>\n",
       "      <td>35.4</td>\n",
       "      <td>22.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1445</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>15</td>\n",
       "      <td>2010-04-16</td>\n",
       "      <td>0.157686</td>\n",
       "      <td>0.156614</td>\n",
       "      <td>0.184014</td>\n",
       "      <td>0.135886</td>\n",
       "      <td>17.33</td>\n",
       "      <td>298.305714</td>\n",
       "      <td>299.557143</td>\n",
       "      <td>297.002857</td>\n",
       "      <td>307.3</td>\n",
       "      <td>294.3</td>\n",
       "      <td>150.80</td>\n",
       "      <td>93.655714</td>\n",
       "      <td>17.33</td>\n",
       "      <td>18.677143</td>\n",
       "      <td>7.228571</td>\n",
       "      <td>27.150000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>33.0</td>\n",
       "      <td>21.2</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1446</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>16</td>\n",
       "      <td>2010-04-23</td>\n",
       "      <td>0.231486</td>\n",
       "      <td>0.294686</td>\n",
       "      <td>0.331657</td>\n",
       "      <td>0.244400</td>\n",
       "      <td>86.70</td>\n",
       "      <td>298.438571</td>\n",
       "      <td>299.507143</td>\n",
       "      <td>297.678571</td>\n",
       "      <td>304.7</td>\n",
       "      <td>294.7</td>\n",
       "      <td>81.40</td>\n",
       "      <td>95.995714</td>\n",
       "      <td>86.70</td>\n",
       "      <td>19.448571</td>\n",
       "      <td>7.757143</td>\n",
       "      <td>27.850000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>33.5</td>\n",
       "      <td>22.5</td>\n",
       "      <td>51.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1447</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>17</td>\n",
       "      <td>2010-04-30</td>\n",
       "      <td>0.239743</td>\n",
       "      <td>0.259271</td>\n",
       "      <td>0.307786</td>\n",
       "      <td>0.307943</td>\n",
       "      <td>26.00</td>\n",
       "      <td>299.048571</td>\n",
       "      <td>300.028571</td>\n",
       "      <td>296.468571</td>\n",
       "      <td>308.4</td>\n",
       "      <td>294.6</td>\n",
       "      <td>23.60</td>\n",
       "      <td>87.657143</td>\n",
       "      <td>26.00</td>\n",
       "      <td>18.068571</td>\n",
       "      <td>8.257143</td>\n",
       "      <td>28.850000</td>\n",
       "      <td>12.125000</td>\n",
       "      <td>36.2</td>\n",
       "      <td>21.4</td>\n",
       "      <td>35.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1448</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>18</td>\n",
       "      <td>2010-05-07</td>\n",
       "      <td>0.260814</td>\n",
       "      <td>0.255786</td>\n",
       "      <td>0.257771</td>\n",
       "      <td>0.340286</td>\n",
       "      <td>73.97</td>\n",
       "      <td>297.617143</td>\n",
       "      <td>298.585714</td>\n",
       "      <td>296.975714</td>\n",
       "      <td>304.7</td>\n",
       "      <td>294.6</td>\n",
       "      <td>85.46</td>\n",
       "      <td>96.712857</td>\n",
       "      <td>73.97</td>\n",
       "      <td>18.602857</td>\n",
       "      <td>5.714286</td>\n",
       "      <td>27.600000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>33.2</td>\n",
       "      <td>21.4</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1449</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>19</td>\n",
       "      <td>2010-05-14</td>\n",
       "      <td>0.168686</td>\n",
       "      <td>0.158500</td>\n",
       "      <td>0.133071</td>\n",
       "      <td>0.145600</td>\n",
       "      <td>59.40</td>\n",
       "      <td>297.278571</td>\n",
       "      <td>297.935714</td>\n",
       "      <td>296.738571</td>\n",
       "      <td>306.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>87.30</td>\n",
       "      <td>97.445714</td>\n",
       "      <td>59.40</td>\n",
       "      <td>18.391429</td>\n",
       "      <td>6.185714</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>33.7</td>\n",
       "      <td>21.2</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>20</td>\n",
       "      <td>2010-05-21</td>\n",
       "      <td>0.263071</td>\n",
       "      <td>0.272500</td>\n",
       "      <td>0.258271</td>\n",
       "      <td>0.244500</td>\n",
       "      <td>1.15</td>\n",
       "      <td>297.648571</td>\n",
       "      <td>298.707143</td>\n",
       "      <td>293.227143</td>\n",
       "      <td>308.7</td>\n",
       "      <td>290.1</td>\n",
       "      <td>8.80</td>\n",
       "      <td>78.998571</td>\n",
       "      <td>1.15</td>\n",
       "      <td>14.908571</td>\n",
       "      <td>11.242857</td>\n",
       "      <td>25.633333</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>34.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1451</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>21</td>\n",
       "      <td>2010-05-28</td>\n",
       "      <td>0.342750</td>\n",
       "      <td>0.318900</td>\n",
       "      <td>0.256343</td>\n",
       "      <td>0.292514</td>\n",
       "      <td>55.30</td>\n",
       "      <td>299.334286</td>\n",
       "      <td>300.771429</td>\n",
       "      <td>296.825714</td>\n",
       "      <td>309.7</td>\n",
       "      <td>294.5</td>\n",
       "      <td>45.00</td>\n",
       "      <td>88.765714</td>\n",
       "      <td>55.30</td>\n",
       "      <td>18.485714</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>28.633333</td>\n",
       "      <td>11.933333</td>\n",
       "      <td>35.4</td>\n",
       "      <td>22.4</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1452</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>22</td>\n",
       "      <td>2010-06-04</td>\n",
       "      <td>0.160157</td>\n",
       "      <td>0.160371</td>\n",
       "      <td>0.136043</td>\n",
       "      <td>0.225657</td>\n",
       "      <td>86.47</td>\n",
       "      <td>298.330000</td>\n",
       "      <td>299.392857</td>\n",
       "      <td>296.452857</td>\n",
       "      <td>308.5</td>\n",
       "      <td>291.9</td>\n",
       "      <td>207.10</td>\n",
       "      <td>91.600000</td>\n",
       "      <td>86.47</td>\n",
       "      <td>18.070000</td>\n",
       "      <td>7.471429</td>\n",
       "      <td>27.433333</td>\n",
       "      <td>10.500000</td>\n",
       "      <td>34.7</td>\n",
       "      <td>21.7</td>\n",
       "      <td>36.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1453</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>23</td>\n",
       "      <td>2010-06-11</td>\n",
       "      <td>0.247057</td>\n",
       "      <td>0.146057</td>\n",
       "      <td>0.250357</td>\n",
       "      <td>0.233714</td>\n",
       "      <td>58.94</td>\n",
       "      <td>296.598571</td>\n",
       "      <td>297.592857</td>\n",
       "      <td>295.501429</td>\n",
       "      <td>305.5</td>\n",
       "      <td>292.4</td>\n",
       "      <td>50.60</td>\n",
       "      <td>94.280000</td>\n",
       "      <td>58.94</td>\n",
       "      <td>17.008571</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>24.400000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>32.2</td>\n",
       "      <td>19.2</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1454</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>24</td>\n",
       "      <td>2010-06-18</td>\n",
       "      <td>0.333914</td>\n",
       "      <td>0.245771</td>\n",
       "      <td>0.278886</td>\n",
       "      <td>0.325486</td>\n",
       "      <td>59.67</td>\n",
       "      <td>296.345714</td>\n",
       "      <td>297.521429</td>\n",
       "      <td>295.324286</td>\n",
       "      <td>306.1</td>\n",
       "      <td>291.9</td>\n",
       "      <td>62.33</td>\n",
       "      <td>94.660000</td>\n",
       "      <td>59.67</td>\n",
       "      <td>16.815714</td>\n",
       "      <td>7.871429</td>\n",
       "      <td>25.433333</td>\n",
       "      <td>8.733333</td>\n",
       "      <td>31.2</td>\n",
       "      <td>21.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1455</th>\n",
       "      <td>iq</td>\n",
       "      <td>2010</td>\n",
       "      <td>25</td>\n",
       "      <td>2010-06-25</td>\n",
       "      <td>0.298186</td>\n",
       "      <td>0.232971</td>\n",
       "      <td>0.274214</td>\n",
       "      <td>0.315757</td>\n",
       "      <td>63.22</td>\n",
       "      <td>298.097143</td>\n",
       "      <td>299.835714</td>\n",
       "      <td>295.807143</td>\n",
       "      <td>307.8</td>\n",
       "      <td>292.3</td>\n",
       "      <td>36.90</td>\n",
       "      <td>89.082857</td>\n",
       "      <td>63.22</td>\n",
       "      <td>17.355714</td>\n",
       "      <td>11.014286</td>\n",
       "      <td>27.475000</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>33.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>20.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1456 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     city  year  weekofyear week_start_date   ndvi_ne   ndvi_nw   ndvi_se  \\\n",
       "0      sj  1990          18      1990-04-30  0.122600  0.103725  0.198483   \n",
       "1      sj  1990          19      1990-05-07  0.169900  0.142175  0.162357   \n",
       "2      sj  1990          20      1990-05-14  0.032250  0.172967  0.157200   \n",
       "3      sj  1990          21      1990-05-21  0.128633  0.245067  0.227557   \n",
       "4      sj  1990          22      1990-05-28  0.196200  0.262200  0.251200   \n",
       "5      sj  1990          23      1990-06-04       NaN  0.174850  0.254314   \n",
       "6      sj  1990          24      1990-06-11  0.112900  0.092800  0.205071   \n",
       "7      sj  1990          25      1990-06-18  0.072500  0.072500  0.151471   \n",
       "8      sj  1990          26      1990-06-25  0.102450  0.146175  0.125571   \n",
       "9      sj  1990          27      1990-07-02       NaN  0.121550  0.160683   \n",
       "10     sj  1990          28      1990-07-09  0.192875  0.082350  0.191943   \n",
       "11     sj  1990          29      1990-07-16  0.291600  0.211800  0.301200   \n",
       "12     sj  1990          30      1990-07-23  0.150567  0.171700  0.226900   \n",
       "13     sj  1990          31      1990-07-30       NaN  0.247150  0.379700   \n",
       "14     sj  1990          32      1990-08-06       NaN  0.064333  0.164443   \n",
       "15     sj  1990          33      1990-08-13       NaN  0.128033  0.206957   \n",
       "16     sj  1990          34      1990-08-20  0.190233  0.168800  0.167657   \n",
       "17     sj  1990          35      1990-08-27  0.252900  0.330750  0.264171   \n",
       "18     sj  1990          36      1990-09-03  0.235400  0.200025  0.283817   \n",
       "19     sj  1990          37      1990-09-10  0.127967  0.437100  0.123400   \n",
       "20     sj  1990          38      1990-09-17  0.196350  0.182433  0.254829   \n",
       "21     sj  1990          39      1990-09-24  0.116100  0.260900  0.199443   \n",
       "22     sj  1990          40      1990-10-01  0.228550  0.189750  0.212486   \n",
       "23     sj  1990          41      1990-10-08  0.171150  0.067550  0.179467   \n",
       "24     sj  1990          42      1990-10-15       NaN  0.070200  0.181617   \n",
       "25     sj  1990          43      1990-10-22  0.146200  0.089750  0.128829   \n",
       "26     sj  1990          44      1990-10-29  0.252250  0.183433  0.318000   \n",
       "27     sj  1990          45      1990-11-05  0.152600  0.181775  0.178329   \n",
       "28     sj  1990          46      1990-11-12  0.290800  0.224600  0.180386   \n",
       "29     sj  1990          47      1990-11-19  0.272200  0.330350  0.131633   \n",
       "...   ...   ...         ...             ...       ...       ...       ...   \n",
       "1426   iq  2009          49      2009-12-03  0.348529  0.290400  0.410614   \n",
       "1427   iq  2009          50      2009-12-10  0.192200  0.193529  0.239886   \n",
       "1428   iq  2009          51      2009-12-17  0.217600  0.240300  0.181771   \n",
       "1429   iq  2009          52      2009-12-24  0.210422  0.257138  0.221133   \n",
       "1430   iq  2010          53      2010-01-01       NaN       NaN       NaN   \n",
       "1431   iq  2010           1      2010-01-08  0.124571  0.179129  0.163843   \n",
       "1432   iq  2010           2      2010-01-15  0.145286  0.142314  0.135300   \n",
       "1433   iq  2010           3      2010-01-22  0.252114  0.230486  0.187329   \n",
       "1434   iq  2010           4      2010-01-29  0.263271  0.230600  0.218871   \n",
       "1435   iq  2010           5      2010-02-05  0.170100  0.142117  0.117914   \n",
       "1436   iq  2010           6      2010-02-12  0.230757  0.189257  0.163486   \n",
       "1437   iq  2010           7      2010-02-19  0.293300  0.247829  0.206629   \n",
       "1438   iq  2010           8      2010-02-26  0.303657  0.260057  0.225486   \n",
       "1439   iq  2010           9      2010-03-05  0.127317  0.181160  0.120467   \n",
       "1440   iq  2010          10      2010-03-12  0.311729  0.292686  0.272586   \n",
       "1441   iq  2010          11      2010-03-19  0.294600  0.250971  0.281471   \n",
       "1442   iq  2010          12      2010-03-26  0.266286  0.301233  0.296000   \n",
       "1443   iq  2010          13      2010-04-02  0.141433  0.204729  0.250971   \n",
       "1444   iq  2010          14      2010-04-09  0.242843  0.272757  0.202271   \n",
       "1445   iq  2010          15      2010-04-16  0.157686  0.156614  0.184014   \n",
       "1446   iq  2010          16      2010-04-23  0.231486  0.294686  0.331657   \n",
       "1447   iq  2010          17      2010-04-30  0.239743  0.259271  0.307786   \n",
       "1448   iq  2010          18      2010-05-07  0.260814  0.255786  0.257771   \n",
       "1449   iq  2010          19      2010-05-14  0.168686  0.158500  0.133071   \n",
       "1450   iq  2010          20      2010-05-21  0.263071  0.272500  0.258271   \n",
       "1451   iq  2010          21      2010-05-28  0.342750  0.318900  0.256343   \n",
       "1452   iq  2010          22      2010-06-04  0.160157  0.160371  0.136043   \n",
       "1453   iq  2010          23      2010-06-11  0.247057  0.146057  0.250357   \n",
       "1454   iq  2010          24      2010-06-18  0.333914  0.245771  0.278886   \n",
       "1455   iq  2010          25      2010-06-25  0.298186  0.232971  0.274214   \n",
       "\n",
       "       ndvi_sw  precipitation_amt_mm  reanalysis_air_temp_k  \\\n",
       "0     0.177617                 12.42             297.572857   \n",
       "1     0.155486                 22.82             298.211429   \n",
       "2     0.170843                 34.54             298.781429   \n",
       "3     0.235886                 15.36             298.987143   \n",
       "4     0.247340                  7.52             299.518571   \n",
       "5     0.181743                  9.58             299.630000   \n",
       "6     0.210271                  3.48             299.207143   \n",
       "7     0.133029                151.12             299.591429   \n",
       "8     0.123600                 19.32             299.578571   \n",
       "9     0.202567                 14.41             300.154286   \n",
       "10    0.152929                 22.27             299.512857   \n",
       "11    0.280667                 59.17             299.667143   \n",
       "12    0.214557                 16.48             299.558571   \n",
       "13    0.381357                 32.66             299.862857   \n",
       "14    0.138857                 28.80             300.391429   \n",
       "15    0.168243                 90.75             299.958571   \n",
       "16    0.172286                 32.40             300.332857   \n",
       "17    0.284314                 40.94             300.118571   \n",
       "18    0.230443                 28.86             300.530000   \n",
       "19    0.148283                 64.56             300.674286   \n",
       "20    0.305686                143.73             299.857143   \n",
       "21    0.244217                 51.39             300.427143   \n",
       "22    0.201186                 31.18             300.775714   \n",
       "23    0.157717                 51.42             299.857143   \n",
       "24    0.165750                143.55             299.195714   \n",
       "25    0.123929                127.03             298.902857   \n",
       "26    0.295900                101.35             299.727143   \n",
       "27    0.186629                 20.46             299.972857   \n",
       "28    0.234886                 20.00             300.350000   \n",
       "29    0.125383                 20.04             299.511429   \n",
       "...        ...                   ...                    ...   \n",
       "1426  0.370457                 73.45             298.762857   \n",
       "1427  0.285886                 85.62             299.198571   \n",
       "1428  0.262300                 81.21             298.347143   \n",
       "1429  0.300256                 98.79             297.181429   \n",
       "1430       NaN                   NaN                    NaN   \n",
       "1431  0.135471                 27.04             299.264286   \n",
       "1432  0.167529                 32.99             298.297143   \n",
       "1433  0.302786                 19.04             298.925714   \n",
       "1434  0.261286                138.51             298.291429   \n",
       "1435  0.139343                 47.31             298.754286   \n",
       "1436  0.238871                 78.25             298.251429   \n",
       "1437  0.266671                 32.19             299.648571   \n",
       "1438  0.333314                 84.67             298.917143   \n",
       "1439  0.142767                 80.58             298.337143   \n",
       "1440  0.394800                 57.78             298.837143   \n",
       "1441  0.341643                121.20             299.191429   \n",
       "1442  0.295743                 51.29             299.004286   \n",
       "1443  0.145243                 49.80             299.002857   \n",
       "1444  0.260114                 93.76             299.115714   \n",
       "1445  0.135886                 17.33             298.305714   \n",
       "1446  0.244400                 86.70             298.438571   \n",
       "1447  0.307943                 26.00             299.048571   \n",
       "1448  0.340286                 73.97             297.617143   \n",
       "1449  0.145600                 59.40             297.278571   \n",
       "1450  0.244500                  1.15             297.648571   \n",
       "1451  0.292514                 55.30             299.334286   \n",
       "1452  0.225657                 86.47             298.330000   \n",
       "1453  0.233714                 58.94             296.598571   \n",
       "1454  0.325486                 59.67             296.345714   \n",
       "1455  0.315757                 63.22             298.097143   \n",
       "\n",
       "      reanalysis_avg_temp_k  reanalysis_dew_point_temp_k  \\\n",
       "0                297.742857                   292.414286   \n",
       "1                298.442857                   293.951429   \n",
       "2                298.878571                   295.434286   \n",
       "3                299.228571                   295.310000   \n",
       "4                299.664286                   295.821429   \n",
       "5                299.764286                   295.851429   \n",
       "6                299.221429                   295.865714   \n",
       "7                299.528571                   296.531429   \n",
       "8                299.557143                   296.378571   \n",
       "9                300.278571                   296.651429   \n",
       "10               299.592857                   296.041429   \n",
       "11               299.750000                   296.334286   \n",
       "12               299.635714                   295.960000   \n",
       "13               299.950000                   296.172857   \n",
       "14               300.478571                   296.532857   \n",
       "15               299.957143                   297.035714   \n",
       "16               300.414286                   296.728571   \n",
       "17               300.221429                   297.017143   \n",
       "18               300.635714                   296.117143   \n",
       "19               300.792857                   297.192857   \n",
       "20               299.900000                   296.431429   \n",
       "21               300.600000                   296.028571   \n",
       "22               300.850000                   296.664286   \n",
       "23               299.942857                   296.928571   \n",
       "24               299.307143                   296.544286   \n",
       "25               299.042857                   296.257143   \n",
       "26               299.778571                   296.534286   \n",
       "27               300.035714                   296.564286   \n",
       "28               300.500000                   295.687143   \n",
       "29               299.635714                   295.375714   \n",
       "...                     ...                          ...   \n",
       "1426             299.935714                   296.970000   \n",
       "1427             300.678571                   296.595714   \n",
       "1428             299.350000                   296.905714   \n",
       "1429             298.185714                   296.557143   \n",
       "1430                    NaN                          NaN   \n",
       "1431             300.521429                   294.530000   \n",
       "1432             299.935714                   296.147143   \n",
       "1433             300.457143                   296.380000   \n",
       "1434             299.614286                   296.560000   \n",
       "1435             300.342857                   296.837143   \n",
       "1436             299.678571                   297.568571   \n",
       "1437             300.950000                   297.090000   \n",
       "1438             300.485714                   297.928571   \n",
       "1439             299.664286                   297.917143   \n",
       "1440             300.092857                   298.141429   \n",
       "1441             300.928571                   298.450000   \n",
       "1442             300.300000                   297.555714   \n",
       "1443             300.714286                   296.568571   \n",
       "1444             300.271429                   298.161429   \n",
       "1445             299.557143                   297.002857   \n",
       "1446             299.507143                   297.678571   \n",
       "1447             300.028571                   296.468571   \n",
       "1448             298.585714                   296.975714   \n",
       "1449             297.935714                   296.738571   \n",
       "1450             298.707143                   293.227143   \n",
       "1451             300.771429                   296.825714   \n",
       "1452             299.392857                   296.452857   \n",
       "1453             297.592857                   295.501429   \n",
       "1454             297.521429                   295.324286   \n",
       "1455             299.835714                   295.807143   \n",
       "\n",
       "      reanalysis_max_air_temp_k  reanalysis_min_air_temp_k  \\\n",
       "0                         299.8                      295.9   \n",
       "1                         300.9                      296.4   \n",
       "2                         300.5                      297.3   \n",
       "3                         301.4                      297.0   \n",
       "4                         301.9                      297.5   \n",
       "5                         302.4                      298.1   \n",
       "6                         301.3                      297.7   \n",
       "7                         300.6                      298.4   \n",
       "8                         302.1                      297.7   \n",
       "9                         302.3                      298.7   \n",
       "10                        301.8                      298.0   \n",
       "11                        302.0                      297.3   \n",
       "12                        301.8                      297.1   \n",
       "13                        303.0                      298.3   \n",
       "14                        302.5                      298.8   \n",
       "15                        302.6                      298.5   \n",
       "16                        302.5                      298.1   \n",
       "17                        302.2                      298.7   \n",
       "18                        303.8                      298.0   \n",
       "19                        302.9                      299.0   \n",
       "20                        301.7                      298.7   \n",
       "21                        302.4                      299.1   \n",
       "22                        303.3                      299.1   \n",
       "23                        301.8                      298.1   \n",
       "24                        301.5                      297.5   \n",
       "25                        300.9                      297.2   \n",
       "26                        301.4                      298.5   \n",
       "27                        302.2                      298.5   \n",
       "28                        302.3                      298.8   \n",
       "29                        301.6                      297.0   \n",
       "...                         ...                        ...   \n",
       "1426                      308.9                      295.0   \n",
       "1427                      308.6                      294.6   \n",
       "1428                      307.5                      295.0   \n",
       "1429                      302.9                      294.9   \n",
       "1430                        NaN                        NaN   \n",
       "1431                      308.6                      292.8   \n",
       "1432                      308.0                      293.8   \n",
       "1433                      307.8                      294.8   \n",
       "1434                      308.3                      295.0   \n",
       "1435                      306.1                      295.6   \n",
       "1436                      306.2                      295.5   \n",
       "1437                      309.2                      294.5   \n",
       "1438                      308.2                      295.2   \n",
       "1439                      306.3                      295.8   \n",
       "1440                      306.9                      292.8   \n",
       "1441                      307.4                      294.0   \n",
       "1442                      307.9                      294.6   \n",
       "1443                      309.1                      294.2   \n",
       "1444                      308.4                      294.6   \n",
       "1445                      307.3                      294.3   \n",
       "1446                      304.7                      294.7   \n",
       "1447                      308.4                      294.6   \n",
       "1448                      304.7                      294.6   \n",
       "1449                      306.0                      294.0   \n",
       "1450                      308.7                      290.1   \n",
       "1451                      309.7                      294.5   \n",
       "1452                      308.5                      291.9   \n",
       "1453                      305.5                      292.4   \n",
       "1454                      306.1                      291.9   \n",
       "1455                      307.8                      292.3   \n",
       "\n",
       "      reanalysis_precip_amt_kg_per_m2  reanalysis_relative_humidity_percent  \\\n",
       "0                               32.00                             73.365714   \n",
       "1                               17.94                             77.368571   \n",
       "2                               26.10                             82.052857   \n",
       "3                               13.90                             80.337143   \n",
       "4                               12.20                             80.460000   \n",
       "5                               26.49                             79.891429   \n",
       "6                               38.60                             82.000000   \n",
       "7                               30.00                             83.375714   \n",
       "8                               37.51                             82.768571   \n",
       "9                               28.40                             81.281429   \n",
       "10                              43.72                             81.467143   \n",
       "11                              40.90                             82.144286   \n",
       "12                              42.53                             80.742857   \n",
       "13                              34.60                             80.584286   \n",
       "14                              20.00                             79.650000   \n",
       "15                             101.90                             84.178571   \n",
       "16                              25.90                             80.947143   \n",
       "17                              39.80                             83.348571   \n",
       "18                              30.40                             77.172857   \n",
       "19                              24.18                             81.551429   \n",
       "20                              36.60                             81.637143   \n",
       "21                              16.40                             77.048571   \n",
       "22                              36.10                             78.520000   \n",
       "23                             132.40                             84.110000   \n",
       "24                             279.60                             85.621429   \n",
       "25                              94.52                             85.502857   \n",
       "26                              22.26                             82.787143   \n",
       "27                              14.40                             81.715714   \n",
       "28                               7.10                             75.728571   \n",
       "29                              36.70                             78.151429   \n",
       "...                               ...                                   ...   \n",
       "1426                           134.43                             91.708571   \n",
       "1427                            49.32                             87.752857   \n",
       "1428                           208.87                             92.958571   \n",
       "1429                            66.30                             96.885714   \n",
       "1430                              NaN                                   NaN   \n",
       "1431                             8.50                             78.271429   \n",
       "1432                           144.60                             89.807143   \n",
       "1433                            31.20                             87.641429   \n",
       "1434                            65.76                             91.798571   \n",
       "1435                            95.83                             90.648571   \n",
       "1436                           172.70                             96.515714   \n",
       "1437                            54.20                             88.365714   \n",
       "1438                           288.40                             94.915714   \n",
       "1439                           144.98                             97.700000   \n",
       "1440                            86.10                             96.250000   \n",
       "1441                           191.76                             96.124286   \n",
       "1442                           214.90                             93.082857   \n",
       "1443                            24.25                             88.707143   \n",
       "1444                           164.70                             95.182857   \n",
       "1445                           150.80                             93.655714   \n",
       "1446                            81.40                             95.995714   \n",
       "1447                            23.60                             87.657143   \n",
       "1448                            85.46                             96.712857   \n",
       "1449                            87.30                             97.445714   \n",
       "1450                             8.80                             78.998571   \n",
       "1451                            45.00                             88.765714   \n",
       "1452                           207.10                             91.600000   \n",
       "1453                            50.60                             94.280000   \n",
       "1454                            62.33                             94.660000   \n",
       "1455                            36.90                             89.082857   \n",
       "\n",
       "      reanalysis_sat_precip_amt_mm  reanalysis_specific_humidity_g_per_kg  \\\n",
       "0                            12.42                              14.012857   \n",
       "1                            22.82                              15.372857   \n",
       "2                            34.54                              16.848571   \n",
       "3                            15.36                              16.672857   \n",
       "4                             7.52                              17.210000   \n",
       "5                             9.58                              17.212857   \n",
       "6                             3.48                              17.234286   \n",
       "7                           151.12                              17.977143   \n",
       "8                            19.32                              17.790000   \n",
       "9                            14.41                              18.071429   \n",
       "10                           22.27                              17.418571   \n",
       "11                           59.17                              17.737143   \n",
       "12                           16.48                              17.341429   \n",
       "13                           32.66                              17.594286   \n",
       "14                           28.80                              17.950000   \n",
       "15                           90.75                              18.515714   \n",
       "16                           32.40                              18.174286   \n",
       "17                           40.94                              18.515714   \n",
       "18                           28.86                              17.560000   \n",
       "19                           64.56                              18.777143   \n",
       "20                          143.73                              17.892857   \n",
       "21                           51.39                              17.468571   \n",
       "22                           31.18                              18.180000   \n",
       "23                           51.42                              18.512857   \n",
       "24                          143.55                              18.115714   \n",
       "25                          127.03                              17.750000   \n",
       "26                          101.35                              18.034286   \n",
       "27                           20.46                              18.074286   \n",
       "28                           20.00                              17.085714   \n",
       "29                           20.04                              16.752857   \n",
       "...                            ...                                    ...   \n",
       "1426                         73.45                              18.671429   \n",
       "1427                         85.62                              18.304286   \n",
       "1428                         81.21                              18.601429   \n",
       "1429                         98.79                              18.180000   \n",
       "1430                           NaN                                    NaN   \n",
       "1431                         27.04                              16.127143   \n",
       "1432                         32.99                              17.758571   \n",
       "1433                         19.04                              18.001429   \n",
       "1434                        138.51                              18.192857   \n",
       "1435                         47.31                              18.522857   \n",
       "1436                         78.25                              19.345714   \n",
       "1437                         32.19                              18.857143   \n",
       "1438                         84.67                              19.772857   \n",
       "1439                         80.58                              19.754286   \n",
       "1440                         57.78                              20.091429   \n",
       "1441                        121.20                              20.461429   \n",
       "1442                         51.29                              19.368571   \n",
       "1443                         49.80                              18.214286   \n",
       "1444                         93.76                              20.078571   \n",
       "1445                         17.33                              18.677143   \n",
       "1446                         86.70                              19.448571   \n",
       "1447                         26.00                              18.068571   \n",
       "1448                         73.97                              18.602857   \n",
       "1449                         59.40                              18.391429   \n",
       "1450                          1.15                              14.908571   \n",
       "1451                         55.30                              18.485714   \n",
       "1452                         86.47                              18.070000   \n",
       "1453                         58.94                              17.008571   \n",
       "1454                         59.67                              16.815714   \n",
       "1455                         63.22                              17.355714   \n",
       "\n",
       "      reanalysis_tdtr_k  station_avg_temp_c  station_diur_temp_rng_c  \\\n",
       "0              2.628571           25.442857                 6.900000   \n",
       "1              2.371429           26.714286                 6.371429   \n",
       "2              2.300000           26.714286                 6.485714   \n",
       "3              2.428571           27.471429                 6.771429   \n",
       "4              3.014286           28.942857                 9.371429   \n",
       "5              2.100000           28.114286                 6.942857   \n",
       "6              2.042857           27.414286                 6.771429   \n",
       "7              1.571429           28.371429                 7.685714   \n",
       "8              1.885714           28.328571                 7.385714   \n",
       "9              2.014286           28.328571                 6.514286   \n",
       "10             2.157143           27.557143                 7.157143   \n",
       "11             2.414286           28.128571                 6.900000   \n",
       "12             2.071429           28.114286                 6.357143   \n",
       "13             2.585714           28.242857                 8.085714   \n",
       "14             2.328571           28.200000                 7.557143   \n",
       "15             1.857143           28.042857                 6.685714   \n",
       "16             2.485714           28.342857                 7.014286   \n",
       "17             1.900000           28.657143                 6.528571   \n",
       "18             3.471429           28.328571                 7.614286   \n",
       "19             2.900000           28.685714                 8.057143   \n",
       "20             1.742857           28.242857                 8.114286   \n",
       "21             2.257143           28.342857                 7.728571   \n",
       "22             2.900000           28.771429                 8.028571   \n",
       "23             2.571429           28.628571                 7.314286   \n",
       "24             1.871429           27.628571                 7.400000   \n",
       "25             1.800000           26.771429                 7.628571   \n",
       "26             1.785714           27.971429                 8.642857   \n",
       "27             2.385714           28.471429                 8.428571   \n",
       "28             2.200000           27.542857                 8.600000   \n",
       "29             2.528571           26.800000                 7.414286   \n",
       "...                 ...                 ...                      ...   \n",
       "1426           7.757143           28.025000                10.375000   \n",
       "1427          10.442857           28.550000                11.000000   \n",
       "1428           6.671429           28.200000                11.125000   \n",
       "1429           5.257143           27.200000                 8.200000   \n",
       "1430                NaN                 NaN                      NaN   \n",
       "1431          11.100000           28.600000                12.300000   \n",
       "1432           9.157143           27.833333                11.300000   \n",
       "1433           8.628571           28.966667                11.266667   \n",
       "1434           7.685714           27.800000                10.520000   \n",
       "1435           8.314286           27.800000                 9.266667   \n",
       "1436           6.328571           27.000000                 8.300000   \n",
       "1437           9.414286           27.300000                11.800000   \n",
       "1438           8.171429           28.020000                10.360000   \n",
       "1439           6.242857           28.500000                 9.900000   \n",
       "1440           8.814286           28.550000                10.050000   \n",
       "1441           8.828571           30.000000                12.000000   \n",
       "1442           8.028571           27.466667                 9.333333   \n",
       "1443           9.514286           27.933333                12.300000   \n",
       "1444           7.714286           29.200000                12.300000   \n",
       "1445           7.228571           27.150000                 9.600000   \n",
       "1446           7.757143           27.850000                 9.600000   \n",
       "1447           8.257143           28.850000                12.125000   \n",
       "1448           5.714286           27.600000                 9.600000   \n",
       "1449           6.185714           27.400000                10.400000   \n",
       "1450          11.242857           25.633333                 9.200000   \n",
       "1451           9.800000           28.633333                11.933333   \n",
       "1452           7.471429           27.433333                10.500000   \n",
       "1453           7.500000           24.400000                 6.900000   \n",
       "1454           7.871429           25.433333                 8.733333   \n",
       "1455          11.014286           27.475000                 9.900000   \n",
       "\n",
       "      station_max_temp_c  station_min_temp_c  station_precip_mm  \n",
       "0                   29.4                20.0               16.0  \n",
       "1                   31.7                22.2                8.6  \n",
       "2                   32.2                22.8               41.4  \n",
       "3                   33.3                23.3                4.0  \n",
       "4                   35.0                23.9                5.8  \n",
       "5                   34.4                23.9               39.1  \n",
       "6                   32.2                23.3               29.7  \n",
       "7                   33.9                22.8               21.1  \n",
       "8                   33.9                22.8               21.1  \n",
       "9                   33.9                24.4                1.1  \n",
       "10                  31.7                21.7               63.7  \n",
       "11                  32.8                23.9               12.2  \n",
       "12                  31.7                22.8               32.6  \n",
       "13                  34.4                22.8               37.6  \n",
       "14                  33.3                23.3               11.4  \n",
       "15                  32.8                22.8               44.7  \n",
       "16                  33.3                23.3                5.4  \n",
       "17                  32.2                24.4               13.7  \n",
       "18                  32.8                23.3               14.2  \n",
       "19                  33.9                24.4               25.9  \n",
       "20                  32.8                23.9                3.3  \n",
       "21                  32.8                24.4               15.8  \n",
       "22                  33.3                23.9               11.7  \n",
       "23                  33.3                24.4               57.7  \n",
       "24                  32.8                23.3               61.8  \n",
       "25                  32.2                21.7               91.5  \n",
       "26                  33.3                22.8                6.3  \n",
       "27                  33.3                23.9                6.6  \n",
       "28                  32.8                22.2               38.9  \n",
       "29                  31.7                22.2                9.6  \n",
       "...                  ...                 ...                ...  \n",
       "1426                35.3                22.2               49.0  \n",
       "1427                35.2                21.2               41.9  \n",
       "1428                35.6                22.0               54.1  \n",
       "1429                32.2                21.8               31.2  \n",
       "1430                 NaN                 NaN                NaN  \n",
       "1431                35.1                21.8                NaN  \n",
       "1432                34.2                22.1               15.0  \n",
       "1433                35.2                22.5                0.8  \n",
       "1434                35.3                22.4              166.0  \n",
       "1435                34.2                22.0               62.3  \n",
       "1436                33.2                22.9               14.5  \n",
       "1437                35.5                21.4               60.9  \n",
       "1438                35.4                21.4               29.9  \n",
       "1439                35.4                21.2                9.9  \n",
       "1440                35.4                21.4               44.5  \n",
       "1441                36.0                22.0               22.9  \n",
       "1442                34.5                21.0               20.0  \n",
       "1443                35.3                21.0               16.0  \n",
       "1444                35.4                22.5                NaN  \n",
       "1445                33.0                21.2               18.0  \n",
       "1446                33.5                22.5               51.1  \n",
       "1447                36.2                21.4               35.4  \n",
       "1448                33.2                21.4                8.1  \n",
       "1449                33.7                21.2               32.0  \n",
       "1450                34.0                20.0                2.5  \n",
       "1451                35.4                22.4               27.0  \n",
       "1452                34.7                21.7               36.6  \n",
       "1453                32.2                19.2                7.4  \n",
       "1454                31.2                21.0               16.0  \n",
       "1455                33.7                22.2               20.4  \n",
       "\n",
       "[1456 rows x 24 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Fill in all empty entries in training and test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df['ndvi_ne'].fillna(train_df.ndvi_ne.mean(), inplace = True)\n",
    "train_df['ndvi_nw'].fillna(train_df.ndvi_nw.mean(), inplace = True)\n",
    "train_df['ndvi_se'].fillna(train_df.ndvi_se.mean(), inplace = True)\n",
    "train_df['ndvi_sw'].fillna(train_df.ndvi_sw.mean(), inplace = True)\n",
    "train_df['precipitation_amt_mm'].fillna(train_df.precipitation_amt_mm.mean(), inplace = True)\n",
    "train_df['reanalysis_air_temp_k'].fillna(train_df.reanalysis_air_temp_k.mean(), inplace = True)\n",
    "train_df['reanalysis_avg_temp_k'].fillna(train_df.reanalysis_avg_temp_k.mean(), inplace = True)\n",
    "train_df['reanalysis_dew_point_temp_k'].fillna(train_df.reanalysis_max_air_temp_k.mean(), inplace = True)\n",
    "train_df['reanalysis_max_air_temp_k'].fillna(train_df.reanalysis_dew_point_temp_k.mean(), inplace = True)\n",
    "train_df['reanalysis_min_air_temp_k'].fillna(train_df.reanalysis_min_air_temp_k.mean(), inplace = True)\n",
    "train_df['reanalysis_precip_amt_kg_per_m2'].fillna(train_df.reanalysis_precip_amt_kg_per_m2.mean(), inplace = True)\n",
    "train_df['reanalysis_relative_humidity_percent'].fillna(train_df.reanalysis_relative_humidity_percent.mean(), inplace = True)\n",
    "train_df['reanalysis_sat_precip_amt_mm'].fillna(train_df.reanalysis_sat_precip_amt_mm.mean(), inplace = True)\n",
    "train_df['reanalysis_specific_humidity_g_per_kg'].fillna(train_df.reanalysis_specific_humidity_g_per_kg.mean(), inplace = True)\n",
    "train_df['reanalysis_tdtr_k'].fillna(train_df.reanalysis_tdtr_k.mean(), inplace = True)\n",
    "train_df['station_avg_temp_c'].fillna(train_df.station_avg_temp_c.mean(), inplace = True)\n",
    "train_df['station_diur_temp_rng_c'].fillna(train_df.station_diur_temp_rng_c.mean(), inplace = True)\n",
    "train_df['station_max_temp_c'].fillna(train_df.station_max_temp_c.mean(), inplace = True)\n",
    "train_df['station_min_temp_c'].fillna(train_df.station_min_temp_c.mean(), inplace = True)\n",
    "train_df['station_precip_mm'].fillna(train_df.station_precip_mm.mean(), inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df['ndvi_ne'].fillna(test_df.ndvi_ne.mean(), inplace = True)\n",
    "test_df['ndvi_nw'].fillna(test_df.ndvi_nw.mean(), inplace = True)\n",
    "test_df['ndvi_se'].fillna(test_df.ndvi_se.mean(), inplace = True)\n",
    "test_df['ndvi_sw'].fillna(test_df.ndvi_sw.mean(), inplace = True)\n",
    "test_df['precipitation_amt_mm'].fillna(test_df.precipitation_amt_mm.mean(), inplace = True)\n",
    "test_df['reanalysis_air_temp_k'].fillna(test_df.reanalysis_air_temp_k.mean(), inplace = True)\n",
    "test_df['reanalysis_avg_temp_k'].fillna(test_df.reanalysis_avg_temp_k.mean(), inplace = True)\n",
    "test_df['reanalysis_dew_point_temp_k'].fillna(test_df.reanalysis_max_air_temp_k.mean(), inplace = True)\n",
    "test_df['reanalysis_max_air_temp_k'].fillna(test_df.reanalysis_dew_point_temp_k.mean(), inplace = True)\n",
    "test_df['reanalysis_min_air_temp_k'].fillna(test_df.reanalysis_min_air_temp_k.mean(), inplace = True)\n",
    "test_df['reanalysis_precip_amt_kg_per_m2'].fillna(test_df.reanalysis_precip_amt_kg_per_m2.mean(), inplace = True)\n",
    "test_df['reanalysis_relative_humidity_percent'].fillna(test_df.reanalysis_relative_humidity_percent.mean(), inplace = True)\n",
    "test_df['reanalysis_sat_precip_amt_mm'].fillna(test_df.reanalysis_sat_precip_amt_mm.mean(), inplace = True)\n",
    "test_df['reanalysis_specific_humidity_g_per_kg'].fillna(test_df.reanalysis_specific_humidity_g_per_kg.mean(), inplace = True)\n",
    "test_df['reanalysis_tdtr_k'].fillna(test_df.reanalysis_tdtr_k.mean(), inplace = True)\n",
    "test_df['station_avg_temp_c'].fillna(test_df.station_avg_temp_c.mean(), inplace = True)\n",
    "test_df['station_diur_temp_rng_c'].fillna(test_df.station_diur_temp_rng_c.mean(), inplace = True)\n",
    "test_df['station_max_temp_c'].fillna(test_df.station_max_temp_c.mean(), inplace = True)\n",
    "test_df['station_min_temp_c'].fillna(test_df.station_min_temp_c.mean(), inplace = True)\n",
    "test_df['station_precip_mm'].fillna(test_df.station_precip_mm.mean(), inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        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>weekofyear</th>\n",
       "      <th>ndvi_ne</th>\n",
       "      <th>ndvi_nw</th>\n",
       "      <th>ndvi_se</th>\n",
       "      <th>ndvi_sw</th>\n",
       "      <th>precipitation_amt_mm</th>\n",
       "      <th>reanalysis_air_temp_k</th>\n",
       "      <th>reanalysis_avg_temp_k</th>\n",
       "      <th>reanalysis_dew_point_temp_k</th>\n",
       "      <th>reanalysis_max_air_temp_k</th>\n",
       "      <th>reanalysis_min_air_temp_k</th>\n",
       "      <th>reanalysis_precip_amt_kg_per_m2</th>\n",
       "      <th>reanalysis_relative_humidity_percent</th>\n",
       "      <th>reanalysis_sat_precip_amt_mm</th>\n",
       "      <th>reanalysis_specific_humidity_g_per_kg</th>\n",
       "      <th>reanalysis_tdtr_k</th>\n",
       "      <th>station_avg_temp_c</th>\n",
       "      <th>station_diur_temp_rng_c</th>\n",
       "      <th>station_max_temp_c</th>\n",
       "      <th>station_min_temp_c</th>\n",
       "      <th>station_precip_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2001.031593</td>\n",
       "      <td>26.503434</td>\n",
       "      <td>0.142294</td>\n",
       "      <td>0.130553</td>\n",
       "      <td>0.203783</td>\n",
       "      <td>0.202305</td>\n",
       "      <td>45.760388</td>\n",
       "      <td>298.701852</td>\n",
       "      <td>299.225578</td>\n",
       "      <td>295.302543</td>\n",
       "      <td>303.371309</td>\n",
       "      <td>295.719156</td>\n",
       "      <td>40.151819</td>\n",
       "      <td>82.161959</td>\n",
       "      <td>45.760388</td>\n",
       "      <td>16.746427</td>\n",
       "      <td>4.903754</td>\n",
       "      <td>27.185783</td>\n",
       "      <td>8.059328</td>\n",
       "      <td>32.452437</td>\n",
       "      <td>22.102150</td>\n",
       "      <td>39.326360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.408314</td>\n",
       "      <td>15.019437</td>\n",
       "      <td>0.130827</td>\n",
       "      <td>0.117835</td>\n",
       "      <td>0.073299</td>\n",
       "      <td>0.083266</td>\n",
       "      <td>43.519806</td>\n",
       "      <td>1.357730</td>\n",
       "      <td>1.257372</td>\n",
       "      <td>1.665823</td>\n",
       "      <td>3.292611</td>\n",
       "      <td>2.556533</td>\n",
       "      <td>43.284882</td>\n",
       "      <td>7.129271</td>\n",
       "      <td>43.519806</td>\n",
       "      <td>1.537184</td>\n",
       "      <td>3.534237</td>\n",
       "      <td>1.273108</td>\n",
       "      <td>2.096879</td>\n",
       "      <td>1.945806</td>\n",
       "      <td>1.566475</td>\n",
       "      <td>47.095179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1990.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.406250</td>\n",
       "      <td>-0.456100</td>\n",
       "      <td>-0.015533</td>\n",
       "      <td>-0.063457</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>294.635714</td>\n",
       "      <td>294.892857</td>\n",
       "      <td>289.642857</td>\n",
       "      <td>295.302543</td>\n",
       "      <td>286.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>57.787143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11.715714</td>\n",
       "      <td>1.357143</td>\n",
       "      <td>21.400000</td>\n",
       "      <td>4.528571</td>\n",
       "      <td>26.700000</td>\n",
       "      <td>14.700000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1997.000000</td>\n",
       "      <td>13.750000</td>\n",
       "      <td>0.055625</td>\n",
       "      <td>0.051367</td>\n",
       "      <td>0.155625</td>\n",
       "      <td>0.144718</td>\n",
       "      <td>9.960000</td>\n",
       "      <td>297.665000</td>\n",
       "      <td>298.264286</td>\n",
       "      <td>294.130357</td>\n",
       "      <td>300.900000</td>\n",
       "      <td>293.900000</td>\n",
       "      <td>13.200000</td>\n",
       "      <td>77.226429</td>\n",
       "      <td>9.960000</td>\n",
       "      <td>15.561429</td>\n",
       "      <td>2.328571</td>\n",
       "      <td>26.328571</td>\n",
       "      <td>6.528571</td>\n",
       "      <td>31.100000</td>\n",
       "      <td>21.100000</td>\n",
       "      <td>8.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2002.000000</td>\n",
       "      <td>26.500000</td>\n",
       "      <td>0.142294</td>\n",
       "      <td>0.128067</td>\n",
       "      <td>0.196998</td>\n",
       "      <td>0.190993</td>\n",
       "      <td>38.710000</td>\n",
       "      <td>298.662143</td>\n",
       "      <td>299.267857</td>\n",
       "      <td>295.647143</td>\n",
       "      <td>302.400000</td>\n",
       "      <td>296.200000</td>\n",
       "      <td>27.370000</td>\n",
       "      <td>80.369286</td>\n",
       "      <td>38.710000</td>\n",
       "      <td>17.065000</td>\n",
       "      <td>2.864286</td>\n",
       "      <td>27.385714</td>\n",
       "      <td>7.385714</td>\n",
       "      <td>32.800000</td>\n",
       "      <td>22.200000</td>\n",
       "      <td>24.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2005.000000</td>\n",
       "      <td>39.250000</td>\n",
       "      <td>0.229292</td>\n",
       "      <td>0.212325</td>\n",
       "      <td>0.247021</td>\n",
       "      <td>0.246082</td>\n",
       "      <td>70.047500</td>\n",
       "      <td>299.827500</td>\n",
       "      <td>300.207143</td>\n",
       "      <td>296.480000</td>\n",
       "      <td>305.500000</td>\n",
       "      <td>297.900000</td>\n",
       "      <td>52.042500</td>\n",
       "      <td>86.041429</td>\n",
       "      <td>70.047500</td>\n",
       "      <td>17.974643</td>\n",
       "      <td>7.553571</td>\n",
       "      <td>28.128571</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>33.900000</td>\n",
       "      <td>23.300000</td>\n",
       "      <td>53.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2010.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>0.508357</td>\n",
       "      <td>0.454429</td>\n",
       "      <td>0.538314</td>\n",
       "      <td>0.546017</td>\n",
       "      <td>390.600000</td>\n",
       "      <td>302.200000</td>\n",
       "      <td>302.928571</td>\n",
       "      <td>303.427109</td>\n",
       "      <td>314.000000</td>\n",
       "      <td>299.900000</td>\n",
       "      <td>570.500000</td>\n",
       "      <td>98.610000</td>\n",
       "      <td>390.600000</td>\n",
       "      <td>20.461429</td>\n",
       "      <td>16.028571</td>\n",
       "      <td>30.800000</td>\n",
       "      <td>15.800000</td>\n",
       "      <td>42.200000</td>\n",
       "      <td>25.600000</td>\n",
       "      <td>543.300000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year   weekofyear      ndvi_ne      ndvi_nw      ndvi_se  \\\n",
       "count  1456.000000  1456.000000  1456.000000  1456.000000  1456.000000   \n",
       "mean   2001.031593    26.503434     0.142294     0.130553     0.203783   \n",
       "std       5.408314    15.019437     0.130827     0.117835     0.073299   \n",
       "min    1990.000000     1.000000    -0.406250    -0.456100    -0.015533   \n",
       "25%    1997.000000    13.750000     0.055625     0.051367     0.155625   \n",
       "50%    2002.000000    26.500000     0.142294     0.128067     0.196998   \n",
       "75%    2005.000000    39.250000     0.229292     0.212325     0.247021   \n",
       "max    2010.000000    53.000000     0.508357     0.454429     0.538314   \n",
       "\n",
       "           ndvi_sw  precipitation_amt_mm  reanalysis_air_temp_k  \\\n",
       "count  1456.000000           1456.000000            1456.000000   \n",
       "mean      0.202305             45.760388             298.701852   \n",
       "std       0.083266             43.519806               1.357730   \n",
       "min      -0.063457              0.000000             294.635714   \n",
       "25%       0.144718              9.960000             297.665000   \n",
       "50%       0.190993             38.710000             298.662143   \n",
       "75%       0.246082             70.047500             299.827500   \n",
       "max       0.546017            390.600000             302.200000   \n",
       "\n",
       "       reanalysis_avg_temp_k  reanalysis_dew_point_temp_k  \\\n",
       "count            1456.000000                  1456.000000   \n",
       "mean              299.225578                   295.302543   \n",
       "std                 1.257372                     1.665823   \n",
       "min               294.892857                   289.642857   \n",
       "25%               298.264286                   294.130357   \n",
       "50%               299.267857                   295.647143   \n",
       "75%               300.207143                   296.480000   \n",
       "max               302.928571                   303.427109   \n",
       "\n",
       "       reanalysis_max_air_temp_k  reanalysis_min_air_temp_k  \\\n",
       "count                1456.000000                1456.000000   \n",
       "mean                  303.371309                 295.719156   \n",
       "std                     3.292611                   2.556533   \n",
       "min                   295.302543                 286.900000   \n",
       "25%                   300.900000                 293.900000   \n",
       "50%                   302.400000                 296.200000   \n",
       "75%                   305.500000                 297.900000   \n",
       "max                   314.000000                 299.900000   \n",
       "\n",
       "       reanalysis_precip_amt_kg_per_m2  reanalysis_relative_humidity_percent  \\\n",
       "count                      1456.000000                           1456.000000   \n",
       "mean                         40.151819                             82.161959   \n",
       "std                          43.284882                              7.129271   \n",
       "min                           0.000000                             57.787143   \n",
       "25%                          13.200000                             77.226429   \n",
       "50%                          27.370000                             80.369286   \n",
       "75%                          52.042500                             86.041429   \n",
       "max                         570.500000                             98.610000   \n",
       "\n",
       "       reanalysis_sat_precip_amt_mm  reanalysis_specific_humidity_g_per_kg  \\\n",
       "count                   1456.000000                            1456.000000   \n",
       "mean                      45.760388                              16.746427   \n",
       "std                       43.519806                               1.537184   \n",
       "min                        0.000000                              11.715714   \n",
       "25%                        9.960000                              15.561429   \n",
       "50%                       38.710000                              17.065000   \n",
       "75%                       70.047500                              17.974643   \n",
       "max                      390.600000                              20.461429   \n",
       "\n",
       "       reanalysis_tdtr_k  station_avg_temp_c  station_diur_temp_rng_c  \\\n",
       "count        1456.000000         1456.000000              1456.000000   \n",
       "mean            4.903754           27.185783                 8.059328   \n",
       "std             3.534237            1.273108                 2.096879   \n",
       "min             1.357143           21.400000                 4.528571   \n",
       "25%             2.328571           26.328571                 6.528571   \n",
       "50%             2.864286           27.385714                 7.385714   \n",
       "75%             7.553571           28.128571                 9.500000   \n",
       "max            16.028571           30.800000                15.800000   \n",
       "\n",
       "       station_max_temp_c  station_min_temp_c  station_precip_mm  \n",
       "count         1456.000000         1456.000000        1456.000000  \n",
       "mean            32.452437           22.102150          39.326360  \n",
       "std              1.945806            1.566475          47.095179  \n",
       "min             26.700000           14.700000           0.000000  \n",
       "25%             31.100000           21.100000           8.850000  \n",
       "50%             32.800000           22.200000          24.450000  \n",
       "75%             33.900000           23.300000          53.600000  \n",
       "max             42.200000           25.600000         543.300000  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>weekofyear</th>\n",
       "      <th>ndvi_ne</th>\n",
       "      <th>ndvi_nw</th>\n",
       "      <th>ndvi_se</th>\n",
       "      <th>ndvi_sw</th>\n",
       "      <th>precipitation_amt_mm</th>\n",
       "      <th>reanalysis_air_temp_k</th>\n",
       "      <th>reanalysis_avg_temp_k</th>\n",
       "      <th>reanalysis_dew_point_temp_k</th>\n",
       "      <th>reanalysis_max_air_temp_k</th>\n",
       "      <th>reanalysis_min_air_temp_k</th>\n",
       "      <th>reanalysis_precip_amt_kg_per_m2</th>\n",
       "      <th>reanalysis_relative_humidity_percent</th>\n",
       "      <th>reanalysis_sat_precip_amt_mm</th>\n",
       "      <th>reanalysis_specific_humidity_g_per_kg</th>\n",
       "      <th>reanalysis_tdtr_k</th>\n",
       "      <th>station_avg_temp_c</th>\n",
       "      <th>station_diur_temp_rng_c</th>\n",
       "      <th>station_max_temp_c</th>\n",
       "      <th>station_min_temp_c</th>\n",
       "      <th>station_precip_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>416.00000</td>\n",
       "      <td>416.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2010.766827</td>\n",
       "      <td>26.439904</td>\n",
       "      <td>0.126050</td>\n",
       "      <td>0.126803</td>\n",
       "      <td>0.207702</td>\n",
       "      <td>0.201721</td>\n",
       "      <td>38.354324</td>\n",
       "      <td>298.818295</td>\n",
       "      <td>299.353071</td>\n",
       "      <td>295.458622</td>\n",
       "      <td>303.584176</td>\n",
       "      <td>295.743478</td>\n",
       "      <td>42.171135</td>\n",
       "      <td>82.499810</td>\n",
       "      <td>38.354324</td>\n",
       "      <td>16.927088</td>\n",
       "      <td>5.124569</td>\n",
       "      <td>27.369587</td>\n",
       "      <td>7.810991</td>\n",
       "      <td>32.534625</td>\n",
       "      <td>22.36855</td>\n",
       "      <td>34.278589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.434835</td>\n",
       "      <td>14.978257</td>\n",
       "      <td>0.155605</td>\n",
       "      <td>0.139533</td>\n",
       "      <td>0.079007</td>\n",
       "      <td>0.091917</td>\n",
       "      <td>35.086274</td>\n",
       "      <td>1.465956</td>\n",
       "      <td>1.303082</td>\n",
       "      <td>1.622182</td>\n",
       "      <td>3.145572</td>\n",
       "      <td>2.754448</td>\n",
       "      <td>48.791517</td>\n",
       "      <td>7.360442</td>\n",
       "      <td>35.086274</td>\n",
       "      <td>1.554110</td>\n",
       "      <td>3.534323</td>\n",
       "      <td>1.214656</td>\n",
       "      <td>2.414041</td>\n",
       "      <td>1.913475</td>\n",
       "      <td>1.71256</td>\n",
       "      <td>34.446562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2008.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.463400</td>\n",
       "      <td>-0.211800</td>\n",
       "      <td>0.006200</td>\n",
       "      <td>-0.014671</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>294.554286</td>\n",
       "      <td>295.235714</td>\n",
       "      <td>290.818571</td>\n",
       "      <td>295.458622</td>\n",
       "      <td>286.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>64.920000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.537143</td>\n",
       "      <td>1.485714</td>\n",
       "      <td>24.157143</td>\n",
       "      <td>4.042857</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>14.20000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2010.000000</td>\n",
       "      <td>13.750000</td>\n",
       "      <td>0.008150</td>\n",
       "      <td>0.017188</td>\n",
       "      <td>0.148677</td>\n",
       "      <td>0.134132</td>\n",
       "      <td>8.225000</td>\n",
       "      <td>297.751429</td>\n",
       "      <td>298.326786</td>\n",
       "      <td>294.350000</td>\n",
       "      <td>301.400000</td>\n",
       "      <td>293.500000</td>\n",
       "      <td>9.490000</td>\n",
       "      <td>77.400000</td>\n",
       "      <td>8.225000</td>\n",
       "      <td>15.795714</td>\n",
       "      <td>2.453571</td>\n",
       "      <td>26.528571</td>\n",
       "      <td>5.942857</td>\n",
       "      <td>31.100000</td>\n",
       "      <td>21.20000</td>\n",
       "      <td>9.175000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2011.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.126050</td>\n",
       "      <td>0.099163</td>\n",
       "      <td>0.204479</td>\n",
       "      <td>0.186486</td>\n",
       "      <td>31.495000</td>\n",
       "      <td>298.564286</td>\n",
       "      <td>299.328571</td>\n",
       "      <td>295.829286</td>\n",
       "      <td>302.700000</td>\n",
       "      <td>296.250000</td>\n",
       "      <td>25.900000</td>\n",
       "      <td>80.352857</td>\n",
       "      <td>31.495000</td>\n",
       "      <td>17.321429</td>\n",
       "      <td>2.914286</td>\n",
       "      <td>27.433333</td>\n",
       "      <td>6.728571</td>\n",
       "      <td>32.800000</td>\n",
       "      <td>22.20000</td>\n",
       "      <td>23.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2012.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>0.248361</td>\n",
       "      <td>0.241182</td>\n",
       "      <td>0.254807</td>\n",
       "      <td>0.253171</td>\n",
       "      <td>57.717500</td>\n",
       "      <td>300.238214</td>\n",
       "      <td>300.521429</td>\n",
       "      <td>296.661071</td>\n",
       "      <td>305.800000</td>\n",
       "      <td>298.225000</td>\n",
       "      <td>56.225000</td>\n",
       "      <td>87.978214</td>\n",
       "      <td>57.717500</td>\n",
       "      <td>18.172500</td>\n",
       "      <td>8.171429</td>\n",
       "      <td>28.278571</td>\n",
       "      <td>9.750000</td>\n",
       "      <td>33.900000</td>\n",
       "      <td>23.30000</td>\n",
       "      <td>47.275000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2013.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>0.500400</td>\n",
       "      <td>0.649000</td>\n",
       "      <td>0.453043</td>\n",
       "      <td>0.529043</td>\n",
       "      <td>169.340000</td>\n",
       "      <td>301.935714</td>\n",
       "      <td>303.328571</td>\n",
       "      <td>303.623430</td>\n",
       "      <td>314.100000</td>\n",
       "      <td>299.700000</td>\n",
       "      <td>301.400000</td>\n",
       "      <td>97.982857</td>\n",
       "      <td>169.340000</td>\n",
       "      <td>19.598571</td>\n",
       "      <td>14.485714</td>\n",
       "      <td>30.271429</td>\n",
       "      <td>14.725000</td>\n",
       "      <td>38.400000</td>\n",
       "      <td>26.70000</td>\n",
       "      <td>212.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year  weekofyear     ndvi_ne     ndvi_nw     ndvi_se  \\\n",
       "count   416.000000  416.000000  416.000000  416.000000  416.000000   \n",
       "mean   2010.766827   26.439904    0.126050    0.126803    0.207702   \n",
       "std       1.434835   14.978257    0.155605    0.139533    0.079007   \n",
       "min    2008.000000    1.000000   -0.463400   -0.211800    0.006200   \n",
       "25%    2010.000000   13.750000    0.008150    0.017188    0.148677   \n",
       "50%    2011.000000   26.000000    0.126050    0.099163    0.204479   \n",
       "75%    2012.000000   39.000000    0.248361    0.241182    0.254807   \n",
       "max    2013.000000   53.000000    0.500400    0.649000    0.453043   \n",
       "\n",
       "          ndvi_sw  precipitation_amt_mm  reanalysis_air_temp_k  \\\n",
       "count  416.000000            416.000000             416.000000   \n",
       "mean     0.201721             38.354324             298.818295   \n",
       "std      0.091917             35.086274               1.465956   \n",
       "min     -0.014671              0.000000             294.554286   \n",
       "25%      0.134132              8.225000             297.751429   \n",
       "50%      0.186486             31.495000             298.564286   \n",
       "75%      0.253171             57.717500             300.238214   \n",
       "max      0.529043            169.340000             301.935714   \n",
       "\n",
       "       reanalysis_avg_temp_k  reanalysis_dew_point_temp_k  \\\n",
       "count             416.000000                   416.000000   \n",
       "mean              299.353071                   295.458622   \n",
       "std                 1.303082                     1.622182   \n",
       "min               295.235714                   290.818571   \n",
       "25%               298.326786                   294.350000   \n",
       "50%               299.328571                   295.829286   \n",
       "75%               300.521429                   296.661071   \n",
       "max               303.328571                   303.623430   \n",
       "\n",
       "       reanalysis_max_air_temp_k  reanalysis_min_air_temp_k  \\\n",
       "count                 416.000000                 416.000000   \n",
       "mean                  303.584176                 295.743478   \n",
       "std                     3.145572                   2.754448   \n",
       "min                   295.458622                 286.200000   \n",
       "25%                   301.400000                 293.500000   \n",
       "50%                   302.700000                 296.250000   \n",
       "75%                   305.800000                 298.225000   \n",
       "max                   314.100000                 299.700000   \n",
       "\n",
       "       reanalysis_precip_amt_kg_per_m2  reanalysis_relative_humidity_percent  \\\n",
       "count                       416.000000                            416.000000   \n",
       "mean                         42.171135                             82.499810   \n",
       "std                          48.791517                              7.360442   \n",
       "min                           0.000000                             64.920000   \n",
       "25%                           9.490000                             77.400000   \n",
       "50%                          25.900000                             80.352857   \n",
       "75%                          56.225000                             87.978214   \n",
       "max                         301.400000                             97.982857   \n",
       "\n",
       "       reanalysis_sat_precip_amt_mm  reanalysis_specific_humidity_g_per_kg  \\\n",
       "count                    416.000000                             416.000000   \n",
       "mean                      38.354324                              16.927088   \n",
       "std                       35.086274                               1.554110   \n",
       "min                        0.000000                              12.537143   \n",
       "25%                        8.225000                              15.795714   \n",
       "50%                       31.495000                              17.321429   \n",
       "75%                       57.717500                              18.172500   \n",
       "max                      169.340000                              19.598571   \n",
       "\n",
       "       reanalysis_tdtr_k  station_avg_temp_c  station_diur_temp_rng_c  \\\n",
       "count         416.000000          416.000000               416.000000   \n",
       "mean            5.124569           27.369587                 7.810991   \n",
       "std             3.534323            1.214656                 2.414041   \n",
       "min             1.485714           24.157143                 4.042857   \n",
       "25%             2.453571           26.528571                 5.942857   \n",
       "50%             2.914286           27.433333                 6.728571   \n",
       "75%             8.171429           28.278571                 9.750000   \n",
       "max            14.485714           30.271429                14.725000   \n",
       "\n",
       "       station_max_temp_c  station_min_temp_c  station_precip_mm  \n",
       "count          416.000000           416.00000         416.000000  \n",
       "mean            32.534625            22.36855          34.278589  \n",
       "std              1.913475             1.71256          34.446562  \n",
       "min             27.200000            14.20000           0.000000  \n",
       "25%             31.100000            21.20000           9.175000  \n",
       "50%             32.800000            22.20000          23.950000  \n",
       "75%             33.900000            23.30000          47.275000  \n",
       "max             38.400000            26.70000         212.000000  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>year</th>\n",
       "      <th>weekofyear</th>\n",
       "      <th>total_cases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "      <td>1456.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2001.031593</td>\n",
       "      <td>26.503434</td>\n",
       "      <td>24.675137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.408314</td>\n",
       "      <td>15.019437</td>\n",
       "      <td>43.596000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1990.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1997.000000</td>\n",
       "      <td>13.750000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2002.000000</td>\n",
       "      <td>26.500000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2005.000000</td>\n",
       "      <td>39.250000</td>\n",
       "      <td>28.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2010.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>461.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year   weekofyear  total_cases\n",
       "count  1456.000000  1456.000000  1456.000000\n",
       "mean   2001.031593    26.503434    24.675137\n",
       "std       5.408314    15.019437    43.596000\n",
       "min    1990.000000     1.000000     0.000000\n",
       "25%    1997.000000    13.750000     5.000000\n",
       "50%    2002.000000    26.500000    12.000000\n",
       "75%    2005.000000    39.250000    28.000000\n",
       "max    2010.000000    53.000000   461.000000"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_label_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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>city</th>\n",
       "      <th>year</th>\n",
       "      <th>weekofyear</th>\n",
       "      <th>week_start_date</th>\n",
       "      <th>ndvi_ne</th>\n",
       "      <th>ndvi_nw</th>\n",
       "      <th>ndvi_se</th>\n",
       "      <th>ndvi_sw</th>\n",
       "      <th>precipitation_amt_mm</th>\n",
       "      <th>reanalysis_air_temp_k</th>\n",
       "      <th>reanalysis_avg_temp_k</th>\n",
       "      <th>reanalysis_dew_point_temp_k</th>\n",
       "      <th>reanalysis_max_air_temp_k</th>\n",
       "      <th>reanalysis_min_air_temp_k</th>\n",
       "      <th>reanalysis_precip_amt_kg_per_m2</th>\n",
       "      <th>reanalysis_relative_humidity_percent</th>\n",
       "      <th>reanalysis_sat_precip_amt_mm</th>\n",
       "      <th>reanalysis_specific_humidity_g_per_kg</th>\n",
       "      <th>reanalysis_tdtr_k</th>\n",
       "      <th>station_avg_temp_c</th>\n",
       "      <th>station_diur_temp_rng_c</th>\n",
       "      <th>station_max_temp_c</th>\n",
       "      <th>station_min_temp_c</th>\n",
       "      <th>station_precip_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>18</td>\n",
       "      <td>1990-04-30</td>\n",
       "      <td>0.122600</td>\n",
       "      <td>0.103725</td>\n",
       "      <td>0.198483</td>\n",
       "      <td>0.177617</td>\n",
       "      <td>12.42</td>\n",
       "      <td>297.572857</td>\n",
       "      <td>297.742857</td>\n",
       "      <td>292.414286</td>\n",
       "      <td>299.8</td>\n",
       "      <td>295.9</td>\n",
       "      <td>32.00</td>\n",
       "      <td>73.365714</td>\n",
       "      <td>12.42</td>\n",
       "      <td>14.012857</td>\n",
       "      <td>2.628571</td>\n",
       "      <td>25.442857</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>29.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>19</td>\n",
       "      <td>1990-05-07</td>\n",
       "      <td>0.169900</td>\n",
       "      <td>0.142175</td>\n",
       "      <td>0.162357</td>\n",
       "      <td>0.155486</td>\n",
       "      <td>22.82</td>\n",
       "      <td>298.211429</td>\n",
       "      <td>298.442857</td>\n",
       "      <td>293.951429</td>\n",
       "      <td>300.9</td>\n",
       "      <td>296.4</td>\n",
       "      <td>17.94</td>\n",
       "      <td>77.368571</td>\n",
       "      <td>22.82</td>\n",
       "      <td>15.372857</td>\n",
       "      <td>2.371429</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.371429</td>\n",
       "      <td>31.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>20</td>\n",
       "      <td>1990-05-14</td>\n",
       "      <td>0.032250</td>\n",
       "      <td>0.172967</td>\n",
       "      <td>0.157200</td>\n",
       "      <td>0.170843</td>\n",
       "      <td>34.54</td>\n",
       "      <td>298.781429</td>\n",
       "      <td>298.878571</td>\n",
       "      <td>295.434286</td>\n",
       "      <td>300.5</td>\n",
       "      <td>297.3</td>\n",
       "      <td>26.10</td>\n",
       "      <td>82.052857</td>\n",
       "      <td>34.54</td>\n",
       "      <td>16.848571</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.485714</td>\n",
       "      <td>32.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>41.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>21</td>\n",
       "      <td>1990-05-21</td>\n",
       "      <td>0.128633</td>\n",
       "      <td>0.245067</td>\n",
       "      <td>0.227557</td>\n",
       "      <td>0.235886</td>\n",
       "      <td>15.36</td>\n",
       "      <td>298.987143</td>\n",
       "      <td>299.228571</td>\n",
       "      <td>295.310000</td>\n",
       "      <td>301.4</td>\n",
       "      <td>297.0</td>\n",
       "      <td>13.90</td>\n",
       "      <td>80.337143</td>\n",
       "      <td>15.36</td>\n",
       "      <td>16.672857</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>27.471429</td>\n",
       "      <td>6.771429</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.3</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>22</td>\n",
       "      <td>1990-05-28</td>\n",
       "      <td>0.196200</td>\n",
       "      <td>0.262200</td>\n",
       "      <td>0.251200</td>\n",
       "      <td>0.247340</td>\n",
       "      <td>7.52</td>\n",
       "      <td>299.518571</td>\n",
       "      <td>299.664286</td>\n",
       "      <td>295.821429</td>\n",
       "      <td>301.9</td>\n",
       "      <td>297.5</td>\n",
       "      <td>12.20</td>\n",
       "      <td>80.460000</td>\n",
       "      <td>7.52</td>\n",
       "      <td>17.210000</td>\n",
       "      <td>3.014286</td>\n",
       "      <td>28.942857</td>\n",
       "      <td>9.371429</td>\n",
       "      <td>35.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  city  year  weekofyear week_start_date   ndvi_ne   ndvi_nw   ndvi_se  \\\n",
       "0   sj  1990          18      1990-04-30  0.122600  0.103725  0.198483   \n",
       "1   sj  1990          19      1990-05-07  0.169900  0.142175  0.162357   \n",
       "2   sj  1990          20      1990-05-14  0.032250  0.172967  0.157200   \n",
       "3   sj  1990          21      1990-05-21  0.128633  0.245067  0.227557   \n",
       "4   sj  1990          22      1990-05-28  0.196200  0.262200  0.251200   \n",
       "\n",
       "    ndvi_sw  precipitation_amt_mm  reanalysis_air_temp_k  \\\n",
       "0  0.177617                 12.42             297.572857   \n",
       "1  0.155486                 22.82             298.211429   \n",
       "2  0.170843                 34.54             298.781429   \n",
       "3  0.235886                 15.36             298.987143   \n",
       "4  0.247340                  7.52             299.518571   \n",
       "\n",
       "   reanalysis_avg_temp_k  reanalysis_dew_point_temp_k  \\\n",
       "0             297.742857                   292.414286   \n",
       "1             298.442857                   293.951429   \n",
       "2             298.878571                   295.434286   \n",
       "3             299.228571                   295.310000   \n",
       "4             299.664286                   295.821429   \n",
       "\n",
       "   reanalysis_max_air_temp_k  reanalysis_min_air_temp_k  \\\n",
       "0                      299.8                      295.9   \n",
       "1                      300.9                      296.4   \n",
       "2                      300.5                      297.3   \n",
       "3                      301.4                      297.0   \n",
       "4                      301.9                      297.5   \n",
       "\n",
       "   reanalysis_precip_amt_kg_per_m2  reanalysis_relative_humidity_percent  \\\n",
       "0                            32.00                             73.365714   \n",
       "1                            17.94                             77.368571   \n",
       "2                            26.10                             82.052857   \n",
       "3                            13.90                             80.337143   \n",
       "4                            12.20                             80.460000   \n",
       "\n",
       "   reanalysis_sat_precip_amt_mm  reanalysis_specific_humidity_g_per_kg  \\\n",
       "0                         12.42                              14.012857   \n",
       "1                         22.82                              15.372857   \n",
       "2                         34.54                              16.848571   \n",
       "3                         15.36                              16.672857   \n",
       "4                          7.52                              17.210000   \n",
       "\n",
       "   reanalysis_tdtr_k  station_avg_temp_c  station_diur_temp_rng_c  \\\n",
       "0           2.628571           25.442857                 6.900000   \n",
       "1           2.371429           26.714286                 6.371429   \n",
       "2           2.300000           26.714286                 6.485714   \n",
       "3           2.428571           27.471429                 6.771429   \n",
       "4           3.014286           28.942857                 9.371429   \n",
       "\n",
       "   station_max_temp_c  station_min_temp_c  station_precip_mm  \n",
       "0                29.4                20.0               16.0  \n",
       "1                31.7                22.2                8.6  \n",
       "2                32.2                22.8               41.4  \n",
       "3                33.3                23.3                4.0  \n",
       "4                35.0                23.9                5.8  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>year</th>\n",
       "      <th>weekofyear</th>\n",
       "      <th>ndvi_ne</th>\n",
       "      <th>ndvi_nw</th>\n",
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       "      <th>precipitation_amt_mm</th>\n",
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       "      <th>reanalysis_dew_point_temp_k</th>\n",
       "      <th>reanalysis_max_air_temp_k</th>\n",
       "      <th>reanalysis_min_air_temp_k</th>\n",
       "      <th>reanalysis_precip_amt_kg_per_m2</th>\n",
       "      <th>reanalysis_relative_humidity_percent</th>\n",
       "      <th>reanalysis_sat_precip_amt_mm</th>\n",
       "      <th>reanalysis_specific_humidity_g_per_kg</th>\n",
       "      <th>reanalysis_tdtr_k</th>\n",
       "      <th>station_avg_temp_c</th>\n",
       "      <th>station_diur_temp_rng_c</th>\n",
       "      <th>station_max_temp_c</th>\n",
       "      <th>station_min_temp_c</th>\n",
       "      <th>station_precip_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>18</td>\n",
       "      <td>0.122600</td>\n",
       "      <td>0.103725</td>\n",
       "      <td>0.198483</td>\n",
       "      <td>0.177617</td>\n",
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       "      <td>297.742857</td>\n",
       "      <td>292.414286</td>\n",
       "      <td>299.8</td>\n",
       "      <td>295.9</td>\n",
       "      <td>32.00</td>\n",
       "      <td>73.365714</td>\n",
       "      <td>12.42</td>\n",
       "      <td>14.012857</td>\n",
       "      <td>2.628571</td>\n",
       "      <td>25.442857</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>29.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>19</td>\n",
       "      <td>0.169900</td>\n",
       "      <td>0.142175</td>\n",
       "      <td>0.162357</td>\n",
       "      <td>0.155486</td>\n",
       "      <td>22.82</td>\n",
       "      <td>298.211429</td>\n",
       "      <td>298.442857</td>\n",
       "      <td>293.951429</td>\n",
       "      <td>300.9</td>\n",
       "      <td>296.4</td>\n",
       "      <td>17.94</td>\n",
       "      <td>77.368571</td>\n",
       "      <td>22.82</td>\n",
       "      <td>15.372857</td>\n",
       "      <td>2.371429</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.371429</td>\n",
       "      <td>31.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>20</td>\n",
       "      <td>0.032250</td>\n",
       "      <td>0.172967</td>\n",
       "      <td>0.157200</td>\n",
       "      <td>0.170843</td>\n",
       "      <td>34.54</td>\n",
       "      <td>298.781429</td>\n",
       "      <td>298.878571</td>\n",
       "      <td>295.434286</td>\n",
       "      <td>300.5</td>\n",
       "      <td>297.3</td>\n",
       "      <td>26.10</td>\n",
       "      <td>82.052857</td>\n",
       "      <td>34.54</td>\n",
       "      <td>16.848571</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.485714</td>\n",
       "      <td>32.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>41.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>21</td>\n",
       "      <td>0.128633</td>\n",
       "      <td>0.245067</td>\n",
       "      <td>0.227557</td>\n",
       "      <td>0.235886</td>\n",
       "      <td>15.36</td>\n",
       "      <td>298.987143</td>\n",
       "      <td>299.228571</td>\n",
       "      <td>295.310000</td>\n",
       "      <td>301.4</td>\n",
       "      <td>297.0</td>\n",
       "      <td>13.90</td>\n",
       "      <td>80.337143</td>\n",
       "      <td>15.36</td>\n",
       "      <td>16.672857</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>27.471429</td>\n",
       "      <td>6.771429</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.3</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sj</td>\n",
       "      <td>1990</td>\n",
       "      <td>22</td>\n",
       "      <td>0.196200</td>\n",
       "      <td>0.262200</td>\n",
       "      <td>0.251200</td>\n",
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       "      <td>301.9</td>\n",
       "      <td>297.5</td>\n",
       "      <td>12.20</td>\n",
       "      <td>80.460000</td>\n",
       "      <td>7.52</td>\n",
       "      <td>17.210000</td>\n",
       "      <td>3.014286</td>\n",
       "      <td>28.942857</td>\n",
       "      <td>9.371429</td>\n",
       "      <td>35.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  city  year  weekofyear   ndvi_ne   ndvi_nw   ndvi_se   ndvi_sw  \\\n",
       "0   sj  1990          18  0.122600  0.103725  0.198483  0.177617   \n",
       "1   sj  1990          19  0.169900  0.142175  0.162357  0.155486   \n",
       "2   sj  1990          20  0.032250  0.172967  0.157200  0.170843   \n",
       "3   sj  1990          21  0.128633  0.245067  0.227557  0.235886   \n",
       "4   sj  1990          22  0.196200  0.262200  0.251200  0.247340   \n",
       "\n",
       "   precipitation_amt_mm  reanalysis_air_temp_k  reanalysis_avg_temp_k  \\\n",
       "0                 12.42             297.572857             297.742857   \n",
       "1                 22.82             298.211429             298.442857   \n",
       "2                 34.54             298.781429             298.878571   \n",
       "3                 15.36             298.987143             299.228571   \n",
       "4                  7.52             299.518571             299.664286   \n",
       "\n",
       "   reanalysis_dew_point_temp_k  reanalysis_max_air_temp_k  \\\n",
       "0                   292.414286                      299.8   \n",
       "1                   293.951429                      300.9   \n",
       "2                   295.434286                      300.5   \n",
       "3                   295.310000                      301.4   \n",
       "4                   295.821429                      301.9   \n",
       "\n",
       "   reanalysis_min_air_temp_k  reanalysis_precip_amt_kg_per_m2  \\\n",
       "0                      295.9                            32.00   \n",
       "1                      296.4                            17.94   \n",
       "2                      297.3                            26.10   \n",
       "3                      297.0                            13.90   \n",
       "4                      297.5                            12.20   \n",
       "\n",
       "   reanalysis_relative_humidity_percent  reanalysis_sat_precip_amt_mm  \\\n",
       "0                             73.365714                         12.42   \n",
       "1                             77.368571                         22.82   \n",
       "2                             82.052857                         34.54   \n",
       "3                             80.337143                         15.36   \n",
       "4                             80.460000                          7.52   \n",
       "\n",
       "   reanalysis_specific_humidity_g_per_kg  reanalysis_tdtr_k  \\\n",
       "0                              14.012857           2.628571   \n",
       "1                              15.372857           2.371429   \n",
       "2                              16.848571           2.300000   \n",
       "3                              16.672857           2.428571   \n",
       "4                              17.210000           3.014286   \n",
       "\n",
       "   station_avg_temp_c  station_diur_temp_rng_c  station_max_temp_c  \\\n",
       "0           25.442857                 6.900000                29.4   \n",
       "1           26.714286                 6.371429                31.7   \n",
       "2           26.714286                 6.485714                32.2   \n",
       "3           27.471429                 6.771429                33.3   \n",
       "4           28.942857                 9.371429                35.0   \n",
       "\n",
       "   station_min_temp_c  station_precip_mm  \n",
       "0                20.0               16.0  \n",
       "1                22.2                8.6  \n",
       "2                22.8               41.4  \n",
       "3                23.3                4.0  \n",
       "4                23.9                5.8  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.drop('week_start_date',axis=1,inplace=True)\n",
    "test_df.drop('week_start_date',axis=1,inplace=True)\n",
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "dlist = train_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sj    260\n",
       "iq    156\n",
       "Name: city, dtype: int64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df['city'].value_counts()\n",
    "test_df['city'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_dict = {\"city\":{\"sj\":1,\"iq\":2}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df.replace(my_dict,inplace=True)\n",
    "test_df.replace(my_dict,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <td>6.900000</td>\n",
       "      <td>29.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1990</td>\n",
       "      <td>19</td>\n",
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       "      <td>26.714286</td>\n",
       "      <td>6.371429</td>\n",
       "      <td>31.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1990</td>\n",
       "      <td>20</td>\n",
       "      <td>0.032250</td>\n",
       "      <td>0.172967</td>\n",
       "      <td>0.157200</td>\n",
       "      <td>0.170843</td>\n",
       "      <td>34.54</td>\n",
       "      <td>298.781429</td>\n",
       "      <td>298.878571</td>\n",
       "      <td>295.434286</td>\n",
       "      <td>300.5</td>\n",
       "      <td>297.3</td>\n",
       "      <td>26.10</td>\n",
       "      <td>82.052857</td>\n",
       "      <td>34.54</td>\n",
       "      <td>16.848571</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>26.714286</td>\n",
       "      <td>6.485714</td>\n",
       "      <td>32.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>41.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1990</td>\n",
       "      <td>21</td>\n",
       "      <td>0.128633</td>\n",
       "      <td>0.245067</td>\n",
       "      <td>0.227557</td>\n",
       "      <td>0.235886</td>\n",
       "      <td>15.36</td>\n",
       "      <td>298.987143</td>\n",
       "      <td>299.228571</td>\n",
       "      <td>295.310000</td>\n",
       "      <td>301.4</td>\n",
       "      <td>297.0</td>\n",
       "      <td>13.90</td>\n",
       "      <td>80.337143</td>\n",
       "      <td>15.36</td>\n",
       "      <td>16.672857</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>27.471429</td>\n",
       "      <td>6.771429</td>\n",
       "      <td>33.3</td>\n",
       "      <td>23.3</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1990</td>\n",
       "      <td>22</td>\n",
       "      <td>0.196200</td>\n",
       "      <td>0.262200</td>\n",
       "      <td>0.251200</td>\n",
       "      <td>0.247340</td>\n",
       "      <td>7.52</td>\n",
       "      <td>299.518571</td>\n",
       "      <td>299.664286</td>\n",
       "      <td>295.821429</td>\n",
       "      <td>301.9</td>\n",
       "      <td>297.5</td>\n",
       "      <td>12.20</td>\n",
       "      <td>80.460000</td>\n",
       "      <td>7.52</td>\n",
       "      <td>17.210000</td>\n",
       "      <td>3.014286</td>\n",
       "      <td>28.942857</td>\n",
       "      <td>9.371429</td>\n",
       "      <td>35.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city  year  weekofyear   ndvi_ne   ndvi_nw   ndvi_se   ndvi_sw  \\\n",
       "0     1  1990          18  0.122600  0.103725  0.198483  0.177617   \n",
       "1     1  1990          19  0.169900  0.142175  0.162357  0.155486   \n",
       "2     1  1990          20  0.032250  0.172967  0.157200  0.170843   \n",
       "3     1  1990          21  0.128633  0.245067  0.227557  0.235886   \n",
       "4     1  1990          22  0.196200  0.262200  0.251200  0.247340   \n",
       "\n",
       "   precipitation_amt_mm  reanalysis_air_temp_k  reanalysis_avg_temp_k  \\\n",
       "0                 12.42             297.572857             297.742857   \n",
       "1                 22.82             298.211429             298.442857   \n",
       "2                 34.54             298.781429             298.878571   \n",
       "3                 15.36             298.987143             299.228571   \n",
       "4                  7.52             299.518571             299.664286   \n",
       "\n",
       "   reanalysis_dew_point_temp_k  reanalysis_max_air_temp_k  \\\n",
       "0                   292.414286                      299.8   \n",
       "1                   293.951429                      300.9   \n",
       "2                   295.434286                      300.5   \n",
       "3                   295.310000                      301.4   \n",
       "4                   295.821429                      301.9   \n",
       "\n",
       "   reanalysis_min_air_temp_k  reanalysis_precip_amt_kg_per_m2  \\\n",
       "0                      295.9                            32.00   \n",
       "1                      296.4                            17.94   \n",
       "2                      297.3                            26.10   \n",
       "3                      297.0                            13.90   \n",
       "4                      297.5                            12.20   \n",
       "\n",
       "   reanalysis_relative_humidity_percent  reanalysis_sat_precip_amt_mm  \\\n",
       "0                             73.365714                         12.42   \n",
       "1                             77.368571                         22.82   \n",
       "2                             82.052857                         34.54   \n",
       "3                             80.337143                         15.36   \n",
       "4                             80.460000                          7.52   \n",
       "\n",
       "   reanalysis_specific_humidity_g_per_kg  reanalysis_tdtr_k  \\\n",
       "0                              14.012857           2.628571   \n",
       "1                              15.372857           2.371429   \n",
       "2                              16.848571           2.300000   \n",
       "3                              16.672857           2.428571   \n",
       "4                              17.210000           3.014286   \n",
       "\n",
       "   station_avg_temp_c  station_diur_temp_rng_c  station_max_temp_c  \\\n",
       "0           25.442857                 6.900000                29.4   \n",
       "1           26.714286                 6.371429                31.7   \n",
       "2           26.714286                 6.485714                32.2   \n",
       "3           27.471429                 6.771429                33.3   \n",
       "4           28.942857                 9.371429                35.0   \n",
       "\n",
       "   station_min_temp_c  station_precip_mm  \n",
       "0                20.0               16.0  \n",
       "1                22.2                8.6  \n",
       "2                22.8               41.4  \n",
       "3                23.3                4.0  \n",
       "4                23.9                5.8  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = train_df.columns\n",
    "index = train_df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=1456, step=1)"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = MinMaxScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "#train_df=scaler.fit_transform(train_df)\n",
    "#test_df=scaler.transform(test_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[type(train_df),type(test_df)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "#train_df=pd.DataFrame(train_df,columns=cols)\n",
    "#test_df=pd.DataFrame(test_df,columns=cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "random_index  = np.random.permutation(1456)\n",
    "train_df = train_df.reindex(random_index)\n",
    "train_label_df = train_label_df.reindex(random_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Random forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,\n",
       "           max_features='auto', max_leaf_nodes=None,\n",
       "           min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "           min_samples_leaf=1, min_samples_split=2,\n",
       "           min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=1,\n",
       "           oob_score=True, random_state=42, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_forest_model = RandomForestRegressor(n_estimators=100,oob_score=True,random_state=42)\n",
    "random_forest_model.fit(train_df,train_label_df['total_cases'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6807362926592845"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_forest_model.oob_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_oob = random_forest_model.oob_prediction_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([16.83870968,  5.2195122 , 58.04166667, ..., 15.05555556,\n",
       "       22.4516129 , 45.5952381 ])"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_oob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_predict = random_forest_model.predict(test_df)\n",
    "y_predict = y_predict.round()\n",
    "y_predict = y_predict.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\matibudd\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "submit_random_forest = test_orig_df[['city','year','weekofyear']]\n",
    "submit_random_forest['total_cases'] = y_predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "submit_random_forest.to_csv('submit_random_forest_all_col.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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