data prep.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import linear_model\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "import catboost\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "from keras.layers import Dropout\n",
    "from keras.utils import np_utils\n",
    "from keras.constraints import maxnorm\n",
    "from keras.wrappers.scikit_learn import KerasRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/aleksandrbojko/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_24h = pd.read_csv('MODIS_C6_Russia_and_Asia_24h.csv')\n",
    "data_7d = pd.read_csv('MODIS_C6_Russia_and_Asia_7d.csv')\n",
    "data_virs_24h = pd.read_csv('VNP14IMGTDL_NRT_Russia_and_Asia_24h.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13841, 13)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_7d.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "124"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(data_24h['confidence'] == 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>brightness</th>\n",
       "      <th>scan</th>\n",
       "      <th>track</th>\n",
       "      <th>acq_date</th>\n",
       "      <th>acq_time</th>\n",
       "      <th>satellite</th>\n",
       "      <th>confidence</th>\n",
       "      <th>version</th>\n",
       "      <th>bright_t31</th>\n",
       "      <th>frp</th>\n",
       "      <th>daynight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14.487</td>\n",
       "      <td>120.902</td>\n",
       "      <td>311.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>215</td>\n",
       "      <td>T</td>\n",
       "      <td>40</td>\n",
       "      <td>6.0NRT</td>\n",
       "      <td>295.0</td>\n",
       "      <td>12.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36.987</td>\n",
       "      <td>126.694</td>\n",
       "      <td>309.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.1</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>210</td>\n",
       "      <td>T</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0NRT</td>\n",
       "      <td>295.2</td>\n",
       "      <td>11.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.985</td>\n",
       "      <td>126.709</td>\n",
       "      <td>310.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.1</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>210</td>\n",
       "      <td>T</td>\n",
       "      <td>59</td>\n",
       "      <td>6.0NRT</td>\n",
       "      <td>297.9</td>\n",
       "      <td>13.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34.166</td>\n",
       "      <td>135.195</td>\n",
       "      <td>302.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>210</td>\n",
       "      <td>T</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0NRT</td>\n",
       "      <td>289.1</td>\n",
       "      <td>4.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32.160</td>\n",
       "      <td>131.411</td>\n",
       "      <td>314.7</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>210</td>\n",
       "      <td>T</td>\n",
       "      <td>66</td>\n",
       "      <td>6.0NRT</td>\n",
       "      <td>294.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   latitude  longitude  brightness  scan  track    acq_date  acq_time  \\\n",
       "0    14.487    120.902       311.6   1.5    1.2  2018-10-19       215   \n",
       "1    36.987    126.694       309.9   1.3    1.1  2018-10-19       210   \n",
       "2    36.985    126.709       310.7   1.3    1.1  2018-10-19       210   \n",
       "3    34.166    135.195       302.4   1.5    1.2  2018-10-19       210   \n",
       "4    32.160    131.411       314.7   1.1    1.0  2018-10-19       210   \n",
       "\n",
       "  satellite  confidence version  bright_t31   frp daynight  \n",
       "0         T          40  6.0NRT       295.0  12.2        D  \n",
       "1         T           0  6.0NRT       295.2  11.4        D  \n",
       "2         T          59  6.0NRT       297.9  13.2        D  \n",
       "3         T           0  6.0NRT       289.1   4.3        D  \n",
       "4         T          66  6.0NRT       294.7  12.1        D  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_24h.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2305 entries, 0 to 2304\n",
      "Data columns (total 13 columns):\n",
      "latitude      2305 non-null float64\n",
      "longitude     2305 non-null float64\n",
      "brightness    2305 non-null float64\n",
      "scan          2305 non-null float64\n",
      "track         2305 non-null float64\n",
      "acq_date      2305 non-null object\n",
      "acq_time      2305 non-null int64\n",
      "satellite     2305 non-null object\n",
      "confidence    2305 non-null int64\n",
      "version       2305 non-null object\n",
      "bright_t31    2305 non-null float64\n",
      "frp           2305 non-null float64\n",
      "daynight      2305 non-null object\n",
      "dtypes: float64(7), int64(2), object(4)\n",
      "memory usage: 234.2+ KB\n"
     ]
    }
   ],
   "source": [
    "data_24h.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>bright_ti4</th>\n",
       "      <th>scan</th>\n",
       "      <th>track</th>\n",
       "      <th>acq_date</th>\n",
       "      <th>acq_time</th>\n",
       "      <th>satellite</th>\n",
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       "      <th>daynight</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>48.50154</td>\n",
       "      <td>133.34692</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.72</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>309.9</td>\n",
       "      <td>189.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>48.49874</td>\n",
       "      <td>133.33919</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.72</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>325.1</td>\n",
       "      <td>189.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>48.50467</td>\n",
       "      <td>133.33440</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.72</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.4</td>\n",
       "      <td>90.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>48.50780</td>\n",
       "      <td>133.32185</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.72</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>305.6</td>\n",
       "      <td>248.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>48.49657</td>\n",
       "      <td>133.29073</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.72</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>304.4</td>\n",
       "      <td>105.9</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>48.51413</td>\n",
       "      <td>133.28525</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.72</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.6</td>\n",
       "      <td>47.8</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>48.21005</td>\n",
       "      <td>132.06018</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.75</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>303.3</td>\n",
       "      <td>110.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>48.20960</td>\n",
       "      <td>132.06175</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.75</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>230</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>300.0</td>\n",
       "      <td>94.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>38.13045</td>\n",
       "      <td>117.09946</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.67</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>406</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>300.4</td>\n",
       "      <td>9.5</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>38.13631</td>\n",
       "      <td>117.09673</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.67</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>406</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>295.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>41.50864</td>\n",
       "      <td>123.26450</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.45</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>406</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>302.2</td>\n",
       "      <td>16.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>42.11934</td>\n",
       "      <td>118.66417</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>298.3</td>\n",
       "      <td>10.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>42.11829</td>\n",
       "      <td>118.66028</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>297.7</td>\n",
       "      <td>7.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>43.74945</td>\n",
       "      <td>121.96043</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.46</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>300.1</td>\n",
       "      <td>8.9</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
       "      <td>48.15619</td>\n",
       "      <td>132.10388</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>332.8</td>\n",
       "      <td>118.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>48.22026</td>\n",
       "      <td>132.07253</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>293.2</td>\n",
       "      <td>8.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>48.41518</td>\n",
       "      <td>133.40855</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>325.2</td>\n",
       "      <td>131.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>48.41955</td>\n",
       "      <td>133.41417</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>363.2</td>\n",
       "      <td>251.5</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>48.42392</td>\n",
       "      <td>133.41980</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>355.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>48.42323</td>\n",
       "      <td>133.41330</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>297.3</td>\n",
       "      <td>88.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>48.42900</td>\n",
       "      <td>133.43195</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>366.6</td>\n",
       "      <td>268.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>48.42830</td>\n",
       "      <td>133.42543</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>371.0</td>\n",
       "      <td>268.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>48.43407</td>\n",
       "      <td>133.44408</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>370.6</td>\n",
       "      <td>225.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>48.43337</td>\n",
       "      <td>133.43756</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>351.6</td>\n",
       "      <td>225.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>48.43845</td>\n",
       "      <td>133.44972</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>356.4</td>\n",
       "      <td>184.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>467</th>\n",
       "      <td>48.92891</td>\n",
       "      <td>132.56001</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.39</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.2</td>\n",
       "      <td>8.6</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>49.34221</td>\n",
       "      <td>130.20580</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.37</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>332.2</td>\n",
       "      <td>50.8</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>49.34484</td>\n",
       "      <td>130.19925</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.37</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>363.8</td>\n",
       "      <td>127.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>49.34864</td>\n",
       "      <td>130.17513</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.37</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>290.6</td>\n",
       "      <td>7.5</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>51.07117</td>\n",
       "      <td>108.66190</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.64</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>412</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>296.8</td>\n",
       "      <td>19.0</td>\n",
       "      <td>D</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8845</th>\n",
       "      <td>50.35387</td>\n",
       "      <td>116.82705</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.3</td>\n",
       "      <td>13.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8846</th>\n",
       "      <td>50.33525</td>\n",
       "      <td>116.76585</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>295.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8860</th>\n",
       "      <td>50.41251</td>\n",
       "      <td>117.00103</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.3</td>\n",
       "      <td>32.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8861</th>\n",
       "      <td>50.34312</td>\n",
       "      <td>116.77185</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.4</td>\n",
       "      <td>34.8</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8870</th>\n",
       "      <td>50.42306</td>\n",
       "      <td>117.01627</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>290.3</td>\n",
       "      <td>43.9</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8871</th>\n",
       "      <td>50.34956</td>\n",
       "      <td>116.77312</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.6</td>\n",
       "      <td>17.9</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8878</th>\n",
       "      <td>50.42948</td>\n",
       "      <td>117.01778</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>305.9</td>\n",
       "      <td>103.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8879</th>\n",
       "      <td>50.35740</td>\n",
       "      <td>116.77906</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.7</td>\n",
       "      <td>15.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8885</th>\n",
       "      <td>50.36518</td>\n",
       "      <td>116.78481</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>296.1</td>\n",
       "      <td>12.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8890</th>\n",
       "      <td>50.44515</td>\n",
       "      <td>117.03032</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.6</td>\n",
       "      <td>20.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8891</th>\n",
       "      <td>50.37450</td>\n",
       "      <td>116.79562</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.8</td>\n",
       "      <td>12.2</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8899</th>\n",
       "      <td>50.45313</td>\n",
       "      <td>117.03709</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.6</td>\n",
       "      <td>52.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8900</th>\n",
       "      <td>50.45166</td>\n",
       "      <td>117.03219</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>330.7</td>\n",
       "      <td>60.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8901</th>\n",
       "      <td>50.38378</td>\n",
       "      <td>116.80640</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8907</th>\n",
       "      <td>50.45815</td>\n",
       "      <td>117.03398</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>299.2</td>\n",
       "      <td>52.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8908</th>\n",
       "      <td>50.39159</td>\n",
       "      <td>116.81231</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>300.0</td>\n",
       "      <td>36.8</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8916</th>\n",
       "      <td>50.46451</td>\n",
       "      <td>117.03539</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.3</td>\n",
       "      <td>9.6</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8921</th>\n",
       "      <td>50.47214</td>\n",
       "      <td>117.04103</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>312.9</td>\n",
       "      <td>36.8</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8928</th>\n",
       "      <td>50.45025</td>\n",
       "      <td>117.03488</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>290.2</td>\n",
       "      <td>78.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8929</th>\n",
       "      <td>50.37689</td>\n",
       "      <td>116.79573</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>292.3</td>\n",
       "      <td>11.9</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8930</th>\n",
       "      <td>50.37535</td>\n",
       "      <td>116.79073</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>290.3</td>\n",
       "      <td>13.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8937</th>\n",
       "      <td>50.45527</td>\n",
       "      <td>117.03175</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>327.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8938</th>\n",
       "      <td>50.38772</td>\n",
       "      <td>116.81126</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>301.3</td>\n",
       "      <td>42.6</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8947</th>\n",
       "      <td>50.46319</td>\n",
       "      <td>117.03819</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.8</td>\n",
       "      <td>12.7</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8948</th>\n",
       "      <td>50.39412</td>\n",
       "      <td>116.81242</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>293.9</td>\n",
       "      <td>20.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8959</th>\n",
       "      <td>50.47569</td>\n",
       "      <td>117.04006</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>294.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8967</th>\n",
       "      <td>50.47143</td>\n",
       "      <td>117.00645</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>301.8</td>\n",
       "      <td>26.1</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8978</th>\n",
       "      <td>50.47943</td>\n",
       "      <td>117.01314</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>309.7</td>\n",
       "      <td>131.7</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8986</th>\n",
       "      <td>50.48871</td>\n",
       "      <td>117.02406</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.58</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>291.9</td>\n",
       "      <td>11.4</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8993</th>\n",
       "      <td>50.69342</td>\n",
       "      <td>115.76003</td>\n",
       "      <td>367.0</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.60</td>\n",
       "      <td>2018-10-20</td>\n",
       "      <td>354</td>\n",
       "      <td>N</td>\n",
       "      <td>high</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>293.4</td>\n",
       "      <td>12.0</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>465 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      latitude  longitude  bright_ti4  scan  track    acq_date  acq_time  \\\n",
       "63    48.50154  133.34692       367.0  0.62   0.72  2018-10-19       230   \n",
       "64    48.49874  133.33919       367.0  0.62   0.72  2018-10-19       230   \n",
       "68    48.50467  133.33440       367.0  0.62   0.72  2018-10-19       230   \n",
       "73    48.50780  133.32185       367.0  0.62   0.72  2018-10-19       230   \n",
       "74    48.49657  133.29073       367.0  0.63   0.72  2018-10-19       230   \n",
       "93    48.51413  133.28525       367.0  0.62   0.72  2018-10-19       230   \n",
       "95    48.21005  132.06018       367.0  0.71   0.75  2018-10-19       230   \n",
       "100   48.20960  132.06175       367.0  0.71   0.75  2018-10-19       230   \n",
       "161   38.13045  117.09946       367.0  0.52   0.67  2018-10-19       406   \n",
       "162   38.13631  117.09673       367.0  0.52   0.67  2018-10-19       406   \n",
       "190   41.50864  123.26450       367.0  0.42   0.45  2018-10-19       406   \n",
       "244   42.11934  118.66417       367.0  0.34   0.56  2018-10-19       412   \n",
       "245   42.11829  118.66028       367.0  0.34   0.56  2018-10-19       412   \n",
       "269   43.74945  121.96043       367.0  0.43   0.46  2018-10-19       412   \n",
       "319   48.15619  132.10388       367.0  0.43   0.38  2018-10-19       412   \n",
       "375   48.22026  132.07253       367.0  0.43   0.38  2018-10-19       412   \n",
       "381   48.41518  133.40855       367.0  0.48   0.40  2018-10-19       412   \n",
       "384   48.41955  133.41417       367.0  0.48   0.40  2018-10-19       412   \n",
       "388   48.42392  133.41980       367.0  0.48   0.40  2018-10-19       412   \n",
       "389   48.42323  133.41330       367.0  0.48   0.40  2018-10-19       412   \n",
       "394   48.42900  133.43195       367.0  0.48   0.40  2018-10-19       412   \n",
       "395   48.42830  133.42543       367.0  0.48   0.40  2018-10-19       412   \n",
       "402   48.43407  133.44408       367.0  0.48   0.40  2018-10-19       412   \n",
       "403   48.43337  133.43756       367.0  0.48   0.40  2018-10-19       412   \n",
       "410   48.43845  133.44972       367.0  0.48   0.40  2018-10-19       412   \n",
       "467   48.92891  132.56001       367.0  0.46   0.39  2018-10-19       412   \n",
       "494   49.34221  130.20580       367.0  0.40   0.37  2018-10-19       412   \n",
       "500   49.34484  130.19925       367.0  0.40   0.37  2018-10-19       412   \n",
       "512   49.34864  130.17513       367.0  0.40   0.37  2018-10-19       412   \n",
       "576   51.07117  108.66190       367.0  0.48   0.64  2018-10-19       412   \n",
       "...        ...        ...         ...   ...    ...         ...       ...   \n",
       "8845  50.35387  116.82705       367.0  0.37   0.58  2018-10-20       354   \n",
       "8846  50.33525  116.76585       367.0  0.38   0.58  2018-10-20       354   \n",
       "8860  50.41251  117.00103       367.0  0.37   0.58  2018-10-20       354   \n",
       "8861  50.34312  116.77185       367.0  0.38   0.58  2018-10-20       354   \n",
       "8870  50.42306  117.01627       367.0  0.37   0.58  2018-10-20       354   \n",
       "8871  50.34956  116.77312       367.0  0.38   0.58  2018-10-20       354   \n",
       "8878  50.42948  117.01778       367.0  0.36   0.58  2018-10-20       354   \n",
       "8879  50.35740  116.77906       367.0  0.37   0.58  2018-10-20       354   \n",
       "8885  50.36518  116.78481       367.0  0.37   0.58  2018-10-20       354   \n",
       "8890  50.44515  117.03032       367.0  0.36   0.58  2018-10-20       354   \n",
       "8891  50.37450  116.79562       367.0  0.37   0.58  2018-10-20       354   \n",
       "8899  50.45313  117.03709       367.0  0.36   0.58  2018-10-20       354   \n",
       "8900  50.45166  117.03219       367.0  0.36   0.58  2018-10-20       354   \n",
       "8901  50.38378  116.80640       367.0  0.37   0.58  2018-10-20       354   \n",
       "8907  50.45815  117.03398       367.0  0.36   0.58  2018-10-20       354   \n",
       "8908  50.39159  116.81231       367.0  0.37   0.58  2018-10-20       354   \n",
       "8916  50.46451  117.03539       367.0  0.36   0.58  2018-10-20       354   \n",
       "8921  50.47214  117.04103       367.0  0.36   0.58  2018-10-20       354   \n",
       "8928  50.45025  117.03488       367.0  0.36   0.58  2018-10-20       354   \n",
       "8929  50.37689  116.79573       367.0  0.37   0.58  2018-10-20       354   \n",
       "8930  50.37535  116.79073       367.0  0.37   0.58  2018-10-20       354   \n",
       "8937  50.45527  117.03175       367.0  0.36   0.58  2018-10-20       354   \n",
       "8938  50.38772  116.81126       367.0  0.37   0.58  2018-10-20       354   \n",
       "8947  50.46319  117.03819       367.0  0.36   0.58  2018-10-20       354   \n",
       "8948  50.39412  116.81242       367.0  0.37   0.58  2018-10-20       354   \n",
       "8959  50.47569  117.04006       367.0  0.36   0.58  2018-10-20       354   \n",
       "8967  50.47143  117.00645       367.0  0.36   0.58  2018-10-20       354   \n",
       "8978  50.47943  117.01314       367.0  0.36   0.58  2018-10-20       354   \n",
       "8986  50.48871  117.02406       367.0  0.36   0.58  2018-10-20       354   \n",
       "8993  50.69342  115.76003       367.0  0.40   0.60  2018-10-20       354   \n",
       "\n",
       "     satellite confidence version  bright_ti5    frp daynight  \n",
       "63           N       high  1.0NRT       309.9  189.3        D  \n",
       "64           N       high  1.0NRT       325.1  189.3        D  \n",
       "68           N       high  1.0NRT       294.4   90.0        D  \n",
       "73           N       high  1.0NRT       305.6  248.4        D  \n",
       "74           N       high  1.0NRT       304.4  105.9        D  \n",
       "93           N       high  1.0NRT       294.6   47.8        D  \n",
       "95           N       high  1.0NRT       303.3  110.2        D  \n",
       "100          N       high  1.0NRT       300.0   94.2        D  \n",
       "161          N       high  1.0NRT       300.4    9.5        D  \n",
       "162          N       high  1.0NRT       295.5   22.9        D  \n",
       "190          N       high  1.0NRT       302.2   16.1        D  \n",
       "244          N       high  1.0NRT       298.3   10.2        D  \n",
       "245          N       high  1.0NRT       297.7    7.2        D  \n",
       "269          N       high  1.0NRT       300.1    8.9        D  \n",
       "319          N       high  1.0NRT       332.8  118.2        D  \n",
       "375          N       high  1.0NRT       293.2    8.2        D  \n",
       "381          N       high  1.0NRT       325.2  131.2        D  \n",
       "384          N       high  1.0NRT       363.2  251.5        D  \n",
       "388          N       high  1.0NRT       355.0   88.0        D  \n",
       "389          N       high  1.0NRT       297.3   88.0        D  \n",
       "394          N       high  1.0NRT       366.6  268.3        D  \n",
       "395          N       high  1.0NRT       371.0  268.3        D  \n",
       "402          N       high  1.0NRT       370.6  225.0        D  \n",
       "403          N       high  1.0NRT       351.6  225.0        D  \n",
       "410          N       high  1.0NRT       356.4  184.1        D  \n",
       "467          N       high  1.0NRT       291.2    8.6        D  \n",
       "494          N       high  1.0NRT       332.2   50.8        D  \n",
       "500          N       high  1.0NRT       363.8  127.4        D  \n",
       "512          N       high  1.0NRT       290.6    7.5        D  \n",
       "576          N       high  1.0NRT       296.8   19.0        D  \n",
       "...        ...        ...     ...         ...    ...      ...  \n",
       "8845         N       high  1.0NRT       291.3   13.3        D  \n",
       "8846         N       high  1.0NRT       295.7   23.2        D  \n",
       "8860         N       high  1.0NRT       294.3   32.3        D  \n",
       "8861         N       high  1.0NRT       294.4   34.8        D  \n",
       "8870         N       high  1.0NRT       290.3   43.9        D  \n",
       "8871         N       high  1.0NRT       291.6   17.9        D  \n",
       "8878         N       high  1.0NRT       305.9  103.0        D  \n",
       "8879         N       high  1.0NRT       294.7   15.4        D  \n",
       "8885         N       high  1.0NRT       296.1   12.0        D  \n",
       "8890         N       high  1.0NRT       294.6   20.4        D  \n",
       "8891         N       high  1.0NRT       294.8   12.2        D  \n",
       "8899         N       high  1.0NRT       291.6   52.1        D  \n",
       "8900         N       high  1.0NRT       330.7   60.1        D  \n",
       "8901         N       high  1.0NRT       291.4    7.3        D  \n",
       "8907         N       high  1.0NRT       299.2   52.1        D  \n",
       "8908         N       high  1.0NRT       300.0   36.8        D  \n",
       "8916         N       high  1.0NRT       291.3    9.6        D  \n",
       "8921         N       high  1.0NRT       312.9   36.8        D  \n",
       "8928         N       high  1.0NRT       290.2   78.4        D  \n",
       "8929         N       high  1.0NRT       292.3   11.9        D  \n",
       "8930         N       high  1.0NRT       290.3   13.4        D  \n",
       "8937         N       high  1.0NRT       327.4   78.4        D  \n",
       "8938         N       high  1.0NRT       301.3   42.6        D  \n",
       "8947         N       high  1.0NRT       291.8   12.7        D  \n",
       "8948         N       high  1.0NRT       293.9   20.1        D  \n",
       "8959         N       high  1.0NRT       294.2   19.0        D  \n",
       "8967         N       high  1.0NRT       301.8   26.1        D  \n",
       "8978         N       high  1.0NRT       309.7  131.7        D  \n",
       "8986         N       high  1.0NRT       291.9   11.4        D  \n",
       "8993         N       high  1.0NRT       293.4   12.0        D  \n",
       "\n",
       "[465 rows x 13 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_virs_24h[data_virs_24h['confidence'] == 'high']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>bright_ti4</th>\n",
       "      <th>scan</th>\n",
       "      <th>track</th>\n",
       "      <th>acq_date</th>\n",
       "      <th>acq_time</th>\n",
       "      <th>satellite</th>\n",
       "      <th>confidence</th>\n",
       "      <th>version</th>\n",
       "      <th>bright_ti5</th>\n",
       "      <th>frp</th>\n",
       "      <th>daynight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>47.63015</td>\n",
       "      <td>34.32149</td>\n",
       "      <td>320.7</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.76</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>112</td>\n",
       "      <td>N</td>\n",
       "      <td>nominal</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>281.9</td>\n",
       "      <td>4.1</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>47.86716</td>\n",
       "      <td>33.43762</td>\n",
       "      <td>305.7</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.74</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>112</td>\n",
       "      <td>N</td>\n",
       "      <td>nominal</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>280.4</td>\n",
       "      <td>2.5</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>47.87589</td>\n",
       "      <td>33.41182</td>\n",
       "      <td>295.1</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.74</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>112</td>\n",
       "      <td>N</td>\n",
       "      <td>nominal</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>283.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47.86678</td>\n",
       "      <td>33.43653</td>\n",
       "      <td>301.7</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.74</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>112</td>\n",
       "      <td>N</td>\n",
       "      <td>nominal</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>280.5</td>\n",
       "      <td>2.9</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>47.87288</td>\n",
       "      <td>33.39854</td>\n",
       "      <td>296.7</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.74</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>112</td>\n",
       "      <td>N</td>\n",
       "      <td>nominal</td>\n",
       "      <td>1.0NRT</td>\n",
       "      <td>283.7</td>\n",
       "      <td>1.7</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   latitude  longitude  bright_ti4  scan  track    acq_date  acq_time  \\\n",
       "0  47.63015   34.32149       320.7  0.74   0.76  2018-10-19       112   \n",
       "1  47.86716   33.43762       305.7  0.67   0.74  2018-10-19       112   \n",
       "2  47.87589   33.41182       295.1  0.67   0.74  2018-10-19       112   \n",
       "3  47.86678   33.43653       301.7  0.67   0.74  2018-10-19       112   \n",
       "4  47.87288   33.39854       296.7  0.67   0.74  2018-10-19       112   \n",
       "\n",
       "  satellite confidence version  bright_ti5  frp daynight  \n",
       "0         N    nominal  1.0NRT       281.9  4.1        N  \n",
       "1         N    nominal  1.0NRT       280.4  2.5        N  \n",
       "2         N    nominal  1.0NRT       283.9  1.7        N  \n",
       "3         N    nominal  1.0NRT       280.5  2.9        N  \n",
       "4         N    nominal  1.0NRT       283.7  1.7        N  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_virs_24h.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "FRP изображает встроенную в пиксель излучательную мощность огня в МВт (мегаватт). FRP изображает встроенную в пиксель излучательную мощность огня в МВт (мегаватт). Учитывая уникальное пространственное и спектральное разрешение данных, алгоритм обнаружения пожара VIIRS 375 м был настроен и настроен для оптимизации его отклика на небольшие огни при балансировке появления ложных тревог. Частая насыщенность канала I4 среднего инфракрасного диапазона (3,55-3,93 мкм), обеспечивающая обнаружение активных пожаров, требует дополнительных тестов и процедур, чтобы избежать ошибок классификации пикселей. В результате подпиксельная характеристика пожара (например, излучение радиационной мощности [FRP]) является жизнеспособной только при небольших и / или низкоинтенсивных пожарах. Систематические извлечения FRP основаны на гибридном подходе, объединяющем данные 375 и 750 м. Фактически, начиная с 2015 года, алгоритм включал дополнительные данные VIIRS-канала M13 (3.973-4.128 мкм) 750 м как в агрегированном, так и в неагрегированном формате."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle = pd.read_csv('forestfires.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>FFMC</th>\n",
       "      <th>DMC</th>\n",
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       "      <th>138</th>\n",
       "      <td>jul</td>\n",
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       "      <td>513.3</td>\n",
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       "      <th>143</th>\n",
       "      <td>jul</td>\n",
       "      <td>sat</td>\n",
       "      <td>90.0</td>\n",
       "      <td>51.3</td>\n",
       "      <td>296.3</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16.6</td>\n",
       "      <td>53</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
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       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>513.3</td>\n",
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       "      <td>5.4</td>\n",
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       "      <td>0.77</td>\n",
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       "      <th>145</th>\n",
       "      <td>aug</td>\n",
       "      <td>thu</td>\n",
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       "      <td>131.7</td>\n",
       "      <td>578.8</td>\n",
       "      <td>10.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.90</td>\n",
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       "      <th>146</th>\n",
       "      <td>mar</td>\n",
       "      <td>mon</td>\n",
       "      <td>90.1</td>\n",
       "      <td>39.7</td>\n",
       "      <td>86.6</td>\n",
       "      <td>6.2</td>\n",
       "      <td>13.2</td>\n",
       "      <td>40</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.95</td>\n",
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       "      <th>147</th>\n",
       "      <td>sep</td>\n",
       "      <td>tue</td>\n",
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       "      <td>24.2</td>\n",
       "      <td>28</td>\n",
       "      <td>3.6</td>\n",
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       "      <th>148</th>\n",
       "      <td>aug</td>\n",
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       "      <td>94.8</td>\n",
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       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.07</td>\n",
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       "      <th>149</th>\n",
       "      <td>sep</td>\n",
       "      <td>thu</td>\n",
       "      <td>93.7</td>\n",
       "      <td>80.9</td>\n",
       "      <td>685.2</td>\n",
       "      <td>17.9</td>\n",
       "      <td>23.7</td>\n",
       "      <td>25</td>\n",
       "      <td>4.5</td>\n",
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       "      <td>1.12</td>\n",
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       "      <th>150</th>\n",
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       "      <th>151</th>\n",
       "      <td>jul</td>\n",
       "      <td>sun</td>\n",
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       "      <td>355.2</td>\n",
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       "      <td>24.8</td>\n",
       "      <td>29</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.36</td>\n",
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       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>jul</td>\n",
       "      <td>sat</td>\n",
       "      <td>90.1</td>\n",
       "      <td>51.2</td>\n",
       "      <td>424.1</td>\n",
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       "      <td>24.6</td>\n",
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       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.43</td>\n",
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       "      <th>153</th>\n",
       "      <td>sep</td>\n",
       "      <td>fri</td>\n",
       "      <td>94.3</td>\n",
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       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>sep</td>\n",
       "      <td>sat</td>\n",
       "      <td>93.4</td>\n",
       "      <td>145.4</td>\n",
       "      <td>721.4</td>\n",
       "      <td>8.1</td>\n",
       "      <td>29.6</td>\n",
       "      <td>27</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.46</td>\n",
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       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>aug</td>\n",
       "      <td>sun</td>\n",
       "      <td>94.8</td>\n",
       "      <td>108.3</td>\n",
       "      <td>647.1</td>\n",
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       "      <td>47</td>\n",
       "      <td>1.3</td>\n",
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       "      <td>1.56</td>\n",
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       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>sep</td>\n",
       "      <td>sat</td>\n",
       "      <td>93.4</td>\n",
       "      <td>145.4</td>\n",
       "      <td>721.4</td>\n",
       "      <td>8.1</td>\n",
       "      <td>28.6</td>\n",
       "      <td>27</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.61</td>\n",
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       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>92.1</td>\n",
       "      <td>111.2</td>\n",
       "      <td>654.1</td>\n",
       "      <td>9.6</td>\n",
       "      <td>18.4</td>\n",
       "      <td>45</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.63</td>\n",
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       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>92.1</td>\n",
       "      <td>111.2</td>\n",
       "      <td>654.1</td>\n",
       "      <td>9.6</td>\n",
       "      <td>20.5</td>\n",
       "      <td>35</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.64</td>\n",
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       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>sep</td>\n",
       "      <td>fri</td>\n",
       "      <td>92.4</td>\n",
       "      <td>117.9</td>\n",
       "      <td>668.0</td>\n",
       "      <td>12.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>34</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>mar</td>\n",
       "      <td>mon</td>\n",
       "      <td>90.1</td>\n",
       "      <td>39.7</td>\n",
       "      <td>86.6</td>\n",
       "      <td>6.2</td>\n",
       "      <td>16.1</td>\n",
       "      <td>29</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.75</td>\n",
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       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>aug</td>\n",
       "      <td>thu</td>\n",
       "      <td>95.2</td>\n",
       "      <td>131.7</td>\n",
       "      <td>578.8</td>\n",
       "      <td>10.4</td>\n",
       "      <td>20.3</td>\n",
       "      <td>41</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.90</td>\n",
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       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>mar</td>\n",
       "      <td>sat</td>\n",
       "      <td>90.6</td>\n",
       "      <td>50.1</td>\n",
       "      <td>100.4</td>\n",
       "      <td>7.8</td>\n",
       "      <td>15.2</td>\n",
       "      <td>31</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>sep</td>\n",
       "      <td>sat</td>\n",
       "      <td>92.5</td>\n",
       "      <td>121.1</td>\n",
       "      <td>674.4</td>\n",
       "      <td>8.6</td>\n",
       "      <td>17.8</td>\n",
       "      <td>56</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.95</td>\n",
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       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>sep</td>\n",
       "      <td>sun</td>\n",
       "      <td>89.7</td>\n",
       "      <td>90.0</td>\n",
       "      <td>704.4</td>\n",
       "      <td>4.8</td>\n",
       "      <td>17.8</td>\n",
       "      <td>67</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.01</td>\n",
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       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>mar</td>\n",
       "      <td>thu</td>\n",
       "      <td>84.9</td>\n",
       "      <td>18.2</td>\n",
       "      <td>55.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>70</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>92.1</td>\n",
       "      <td>111.2</td>\n",
       "      <td>654.1</td>\n",
       "      <td>9.6</td>\n",
       "      <td>16.6</td>\n",
       "      <td>47</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>96.0</td>\n",
       "      <td>127.1</td>\n",
       "      <td>570.5</td>\n",
       "      <td>16.5</td>\n",
       "      <td>23.4</td>\n",
       "      <td>33</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.51</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>may</td>\n",
       "      <td>fri</td>\n",
       "      <td>89.6</td>\n",
       "      <td>25.4</td>\n",
       "      <td>73.7</td>\n",
       "      <td>5.7</td>\n",
       "      <td>18.0</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>jun</td>\n",
       "      <td>mon</td>\n",
       "      <td>88.2</td>\n",
       "      <td>96.2</td>\n",
       "      <td>229.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>14.3</td>\n",
       "      <td>79</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>jun</td>\n",
       "      <td>sat</td>\n",
       "      <td>90.5</td>\n",
       "      <td>61.1</td>\n",
       "      <td>252.6</td>\n",
       "      <td>9.4</td>\n",
       "      <td>24.5</td>\n",
       "      <td>50</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>70.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>jun</td>\n",
       "      <td>thu</td>\n",
       "      <td>93.0</td>\n",
       "      <td>103.8</td>\n",
       "      <td>316.7</td>\n",
       "      <td>10.8</td>\n",
       "      <td>26.4</td>\n",
       "      <td>35</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>jun</td>\n",
       "      <td>thu</td>\n",
       "      <td>93.7</td>\n",
       "      <td>121.7</td>\n",
       "      <td>350.2</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.7</td>\n",
       "      <td>40</td>\n",
       "      <td>9.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>jul</td>\n",
       "      <td>thu</td>\n",
       "      <td>93.5</td>\n",
       "      <td>85.3</td>\n",
       "      <td>395.0</td>\n",
       "      <td>9.9</td>\n",
       "      <td>27.2</td>\n",
       "      <td>28</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>jul</td>\n",
       "      <td>sun</td>\n",
       "      <td>93.7</td>\n",
       "      <td>101.3</td>\n",
       "      <td>423.4</td>\n",
       "      <td>14.7</td>\n",
       "      <td>26.1</td>\n",
       "      <td>45</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>jul</td>\n",
       "      <td>sun</td>\n",
       "      <td>93.7</td>\n",
       "      <td>101.3</td>\n",
       "      <td>423.4</td>\n",
       "      <td>14.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>82</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>jul</td>\n",
       "      <td>mon</td>\n",
       "      <td>89.2</td>\n",
       "      <td>103.9</td>\n",
       "      <td>431.6</td>\n",
       "      <td>6.4</td>\n",
       "      <td>22.6</td>\n",
       "      <td>57</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>278.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>jul</td>\n",
       "      <td>thu</td>\n",
       "      <td>93.2</td>\n",
       "      <td>114.4</td>\n",
       "      <td>560.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>30.2</td>\n",
       "      <td>25</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>aug</td>\n",
       "      <td>sun</td>\n",
       "      <td>94.9</td>\n",
       "      <td>130.3</td>\n",
       "      <td>587.1</td>\n",
       "      <td>14.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>40</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>484</th>\n",
       "      <td>aug</td>\n",
       "      <td>sun</td>\n",
       "      <td>94.9</td>\n",
       "      <td>130.3</td>\n",
       "      <td>587.1</td>\n",
       "      <td>14.1</td>\n",
       "      <td>33.1</td>\n",
       "      <td>25</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>aug</td>\n",
       "      <td>mon</td>\n",
       "      <td>95.0</td>\n",
       "      <td>135.5</td>\n",
       "      <td>596.3</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.6</td>\n",
       "      <td>28</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>95.1</td>\n",
       "      <td>141.3</td>\n",
       "      <td>605.8</td>\n",
       "      <td>17.7</td>\n",
       "      <td>24.1</td>\n",
       "      <td>43</td>\n",
       "      <td>6.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>95.1</td>\n",
       "      <td>141.3</td>\n",
       "      <td>605.8</td>\n",
       "      <td>17.7</td>\n",
       "      <td>26.4</td>\n",
       "      <td>34</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>95.1</td>\n",
       "      <td>141.3</td>\n",
       "      <td>605.8</td>\n",
       "      <td>17.7</td>\n",
       "      <td>19.4</td>\n",
       "      <td>71</td>\n",
       "      <td>7.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>aug</td>\n",
       "      <td>fri</td>\n",
       "      <td>95.9</td>\n",
       "      <td>158.0</td>\n",
       "      <td>633.6</td>\n",
       "      <td>11.3</td>\n",
       "      <td>27.5</td>\n",
       "      <td>29</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>aug</td>\n",
       "      <td>sat</td>\n",
       "      <td>96.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>643.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>30.8</td>\n",
       "      <td>30</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>aug</td>\n",
       "      <td>mon</td>\n",
       "      <td>96.2</td>\n",
       "      <td>175.5</td>\n",
       "      <td>661.8</td>\n",
       "      <td>16.8</td>\n",
       "      <td>32.6</td>\n",
       "      <td>26</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>96.1</td>\n",
       "      <td>181.1</td>\n",
       "      <td>671.2</td>\n",
       "      <td>14.3</td>\n",
       "      <td>32.3</td>\n",
       "      <td>27</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>96.1</td>\n",
       "      <td>181.1</td>\n",
       "      <td>671.2</td>\n",
       "      <td>14.3</td>\n",
       "      <td>33.3</td>\n",
       "      <td>26</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>96.1</td>\n",
       "      <td>181.1</td>\n",
       "      <td>671.2</td>\n",
       "      <td>14.3</td>\n",
       "      <td>27.3</td>\n",
       "      <td>63</td>\n",
       "      <td>4.9</td>\n",
       "      <td>6.4</td>\n",
       "      <td>10.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>94.5</td>\n",
       "      <td>139.4</td>\n",
       "      <td>689.1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>29.2</td>\n",
       "      <td>30</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>aug</td>\n",
       "      <td>wed</td>\n",
       "      <td>94.5</td>\n",
       "      <td>139.4</td>\n",
       "      <td>689.1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.9</td>\n",
       "      <td>29</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>aug</td>\n",
       "      <td>thu</td>\n",
       "      <td>91.0</td>\n",
       "      <td>163.2</td>\n",
       "      <td>744.4</td>\n",
       "      <td>10.1</td>\n",
       "      <td>26.7</td>\n",
       "      <td>35</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>aug</td>\n",
       "      <td>fri</td>\n",
       "      <td>91.0</td>\n",
       "      <td>166.9</td>\n",
       "      <td>752.6</td>\n",
       "      <td>7.1</td>\n",
       "      <td>21.1</td>\n",
       "      <td>71</td>\n",
       "      <td>7.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>aug</td>\n",
       "      <td>fri</td>\n",
       "      <td>91.0</td>\n",
       "      <td>166.9</td>\n",
       "      <td>752.6</td>\n",
       "      <td>7.1</td>\n",
       "      <td>18.2</td>\n",
       "      <td>62</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>aug</td>\n",
       "      <td>sun</td>\n",
       "      <td>81.6</td>\n",
       "      <td>56.7</td>\n",
       "      <td>665.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>27.8</td>\n",
       "      <td>32</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>aug</td>\n",
       "      <td>sun</td>\n",
       "      <td>81.6</td>\n",
       "      <td>56.7</td>\n",
       "      <td>665.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>21.9</td>\n",
       "      <td>71</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>aug</td>\n",
       "      <td>sun</td>\n",
       "      <td>81.6</td>\n",
       "      <td>56.7</td>\n",
       "      <td>665.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>21.2</td>\n",
       "      <td>70</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>270 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    month  day  FFMC    DMC     DC   ISI  temp  RH  wind  rain    area\n",
       "138   jul  tue  85.8   48.3  313.4   3.9  18.0  42   2.7   0.0    0.36\n",
       "139   sep  tue  91.0  129.5  692.6   7.0  21.7  38   2.2   0.0    0.43\n",
       "140   sep  mon  90.9  126.5  686.5   7.0  21.9  39   1.8   0.0    0.47\n",
       "141   aug  wed  95.5   99.9  513.3  13.2  23.3  31   4.5   0.0    0.55\n",
       "142   aug  fri  90.1  108.0  529.8  12.5  21.2  51   8.9   0.0    0.61\n",
       "143   jul  sat  90.0   51.3  296.3   8.7  16.6  53   5.4   0.0    0.71\n",
       "144   aug  wed  95.5   99.9  513.3  13.2  23.8  32   5.4   0.0    0.77\n",
       "145   aug  thu  95.2  131.7  578.8  10.4  27.4  22   4.0   0.0    0.90\n",
       "146   mar  mon  90.1   39.7   86.6   6.2  13.2  40   5.4   0.0    0.95\n",
       "147   sep  tue  84.4   73.4  671.9   3.2  24.2  28   3.6   0.0    0.96\n",
       "148   aug  tue  94.8  108.3  647.1  17.0  17.4  43   6.7   0.0    1.07\n",
       "149   sep  thu  93.7   80.9  685.2  17.9  23.7  25   4.5   0.0    1.12\n",
       "150   jun  fri  92.5   56.4  433.3   7.1  23.2  39   5.4   0.0    1.19\n",
       "151   jul  sun  90.1   68.6  355.2   7.2  24.8  29   2.2   0.0    1.36\n",
       "152   jul  sat  90.1   51.2  424.1   6.2  24.6  43   1.8   0.0    1.43\n",
       "153   sep  fri  94.3   85.1  692.3  15.9  20.1  47   4.9   0.0    1.46\n",
       "154   sep  sat  93.4  145.4  721.4   8.1  29.6  27   2.7   0.0    1.46\n",
       "155   aug  sun  94.8  108.3  647.1  17.0  16.4  47   1.3   0.0    1.56\n",
       "156   sep  sat  93.4  145.4  721.4   8.1  28.6  27   2.2   0.0    1.61\n",
       "157   aug  wed  92.1  111.2  654.1   9.6  18.4  45   3.6   0.0    1.63\n",
       "158   aug  wed  92.1  111.2  654.1   9.6  20.5  35   4.0   0.0    1.64\n",
       "159   sep  fri  92.4  117.9  668.0  12.2  19.0  34   5.8   0.0    1.69\n",
       "160   mar  mon  90.1   39.7   86.6   6.2  16.1  29   3.1   0.0    1.75\n",
       "161   aug  thu  95.2  131.7  578.8  10.4  20.3  41   4.0   0.0    1.90\n",
       "162   mar  sat  90.6   50.1  100.4   7.8  15.2  31   8.5   0.0    1.94\n",
       "163   sep  sat  92.5  121.1  674.4   8.6  17.8  56   1.8   0.0    1.95\n",
       "164   sep  sun  89.7   90.0  704.4   4.8  17.8  67   2.2   0.0    2.01\n",
       "165   mar  thu  84.9   18.2   55.0   3.0   5.3  70   4.5   0.0    2.14\n",
       "166   aug  wed  92.1  111.2  654.1   9.6  16.6  47   0.9   0.0    2.29\n",
       "167   aug  wed  96.0  127.1  570.5  16.5  23.4  33   4.5   0.0    2.51\n",
       "..    ...  ...   ...    ...    ...   ...   ...  ..   ...   ...     ...\n",
       "471   may  fri  89.6   25.4   73.7   5.7  18.0  40   4.0   0.0   38.48\n",
       "472   jun  mon  88.2   96.2  229.0   4.7  14.3  79   4.0   0.0    1.94\n",
       "473   jun  sat  90.5   61.1  252.6   9.4  24.5  50   3.1   0.0   70.32\n",
       "474   jun  thu  93.0  103.8  316.7  10.8  26.4  35   2.7   0.0   10.08\n",
       "475   jun  thu  93.7  121.7  350.2  18.0  22.7  40   9.4   0.0    3.19\n",
       "476   jul  thu  93.5   85.3  395.0   9.9  27.2  28   1.3   0.0    1.76\n",
       "477   jul  sun  93.7  101.3  423.4  14.7  26.1  45   4.0   0.0    7.36\n",
       "478   jul  sun  93.7  101.3  423.4  14.7  18.2  82   4.5   0.0    2.21\n",
       "479   jul  mon  89.2  103.9  431.6   6.4  22.6  57   4.9   0.0  278.53\n",
       "480   jul  thu  93.2  114.4  560.0   9.5  30.2  25   4.5   0.0    2.75\n",
       "482   aug  sun  94.9  130.3  587.1  14.1  23.4  40   5.8   0.0    1.29\n",
       "484   aug  sun  94.9  130.3  587.1  14.1  33.1  25   4.0   0.0   26.43\n",
       "485   aug  mon  95.0  135.5  596.3  21.3  30.6  28   3.6   0.0    2.07\n",
       "486   aug  tue  95.1  141.3  605.8  17.7  24.1  43   6.3   0.0    2.00\n",
       "487   aug  tue  95.1  141.3  605.8  17.7  26.4  34   3.6   0.0   16.40\n",
       "488   aug  tue  95.1  141.3  605.8  17.7  19.4  71   7.6   0.0   46.70\n",
       "493   aug  fri  95.9  158.0  633.6  11.3  27.5  29   4.5   0.0   43.32\n",
       "494   aug  sat  96.0  164.0  643.0  14.0  30.8  30   4.9   0.0    8.59\n",
       "496   aug  mon  96.2  175.5  661.8  16.8  32.6  26   3.1   0.0    2.77\n",
       "497   aug  tue  96.1  181.1  671.2  14.3  32.3  27   2.2   0.0   14.68\n",
       "498   aug  tue  96.1  181.1  671.2  14.3  33.3  26   2.7   0.0   40.54\n",
       "499   aug  tue  96.1  181.1  671.2  14.3  27.3  63   4.9   6.4   10.82\n",
       "503   aug  wed  94.5  139.4  689.1  20.0  29.2  30   4.9   0.0    1.95\n",
       "504   aug  wed  94.5  139.4  689.1  20.0  28.9  29   4.9   0.0   49.59\n",
       "505   aug  thu  91.0  163.2  744.4  10.1  26.7  35   1.8   0.0    5.80\n",
       "509   aug  fri  91.0  166.9  752.6   7.1  21.1  71   7.6   1.4    2.17\n",
       "510   aug  fri  91.0  166.9  752.6   7.1  18.2  62   5.4   0.0    0.43\n",
       "512   aug  sun  81.6   56.7  665.6   1.9  27.8  32   2.7   0.0    6.44\n",
       "513   aug  sun  81.6   56.7  665.6   1.9  21.9  71   5.8   0.0   54.29\n",
       "514   aug  sun  81.6   56.7  665.6   1.9  21.2  70   6.7   0.0   11.16\n",
       "\n",
       "[270 rows x 11 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle[data_forest_kaggle['area'] != 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle.drop(columns=['X', 'Y'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111ddad68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data_forest_kaggle['area'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 517 entries, 0 to 516\n",
      "Data columns (total 11 columns):\n",
      "month    517 non-null object\n",
      "day      517 non-null object\n",
      "FFMC     517 non-null float64\n",
      "DMC      517 non-null float64\n",
      "DC       517 non-null float64\n",
      "ISI      517 non-null float64\n",
      "temp     517 non-null float64\n",
      "RH       517 non-null int64\n",
      "wind     517 non-null float64\n",
      "rain     517 non-null float64\n",
      "area     517 non-null float64\n",
      "dtypes: float64(8), int64(1), object(2)\n",
      "memory usage: 44.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data_forest_kaggle.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dummy = pd.get_dummies(data_forest_kaggle)\n",
    "target_dummy = data_dummy['area']\n",
    "data_dummy.drop(columns=['area'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FFMC</th>\n",
       "      <th>DMC</th>\n",
       "      <th>DC</th>\n",
       "      <th>ISI</th>\n",
       "      <th>temp</th>\n",
       "      <th>RH</th>\n",
       "      <th>wind</th>\n",
       "      <th>rain</th>\n",
       "      <th>month_apr</th>\n",
       "      <th>month_aug</th>\n",
       "      <th>...</th>\n",
       "      <th>month_nov</th>\n",
       "      <th>month_oct</th>\n",
       "      <th>month_sep</th>\n",
       "      <th>day_fri</th>\n",
       "      <th>day_mon</th>\n",
       "      <th>day_sat</th>\n",
       "      <th>day_sun</th>\n",
       "      <th>day_thu</th>\n",
       "      <th>day_tue</th>\n",
       "      <th>day_wed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86.2</td>\n",
       "      <td>26.2</td>\n",
       "      <td>94.3</td>\n",
       "      <td>5.1</td>\n",
       "      <td>8.2</td>\n",
       "      <td>51</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>90.6</td>\n",
       "      <td>35.4</td>\n",
       "      <td>669.1</td>\n",
       "      <td>6.7</td>\n",
       "      <td>18.0</td>\n",
       "      <td>33</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>90.6</td>\n",
       "      <td>43.7</td>\n",
       "      <td>686.9</td>\n",
       "      <td>6.7</td>\n",
       "      <td>14.6</td>\n",
       "      <td>33</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>91.7</td>\n",
       "      <td>33.3</td>\n",
       "      <td>77.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>97</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89.3</td>\n",
       "      <td>51.3</td>\n",
       "      <td>102.2</td>\n",
       "      <td>9.6</td>\n",
       "      <td>11.4</td>\n",
       "      <td>99</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   FFMC   DMC     DC  ISI  temp  RH  wind  rain  month_apr  month_aug  \\\n",
       "0  86.2  26.2   94.3  5.1   8.2  51   6.7   0.0          0          0   \n",
       "1  90.6  35.4  669.1  6.7  18.0  33   0.9   0.0          0          0   \n",
       "2  90.6  43.7  686.9  6.7  14.6  33   1.3   0.0          0          0   \n",
       "3  91.7  33.3   77.5  9.0   8.3  97   4.0   0.2          0          0   \n",
       "4  89.3  51.3  102.2  9.6  11.4  99   1.8   0.0          0          0   \n",
       "\n",
       "    ...     month_nov  month_oct  month_sep  day_fri  day_mon  day_sat  \\\n",
       "0   ...             0          0          0        1        0        0   \n",
       "1   ...             0          1          0        0        0        0   \n",
       "2   ...             0          1          0        0        0        1   \n",
       "3   ...             0          0          0        1        0        0   \n",
       "4   ...             0          0          0        0        0        0   \n",
       "\n",
       "   day_sun  day_thu  day_tue  day_wed  \n",
       "0        0        0        0        0  \n",
       "1        0        0        1        0  \n",
       "2        0        0        0        0  \n",
       "3        0        0        0        0  \n",
       "4        1        0        0        0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dummy.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.0\n",
       "1    0.0\n",
       "2    0.0\n",
       "3    0.0\n",
       "4    0.0\n",
       "Name: area, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_dummy.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sun    95\n",
       "fri    85\n",
       "sat    84\n",
       "mon    74\n",
       "tue    64\n",
       "thu    61\n",
       "wed    54\n",
       "Name: day, dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle['day'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle.replace(('jan','feb','mar','apr','may','jun','jul','aug','sep','oct','nov','dec'),\n",
    "                           (1,2,3,4,5,6,7,8,9,10,11,12), inplace=True)\n",
    "data_forest_kaggle.replace(('mon', 'tue', 'wed', 'thu', 'fri', 'sat', 'sun'), (1, 2, 3, 4, 5, 6, 7), \n",
    "                           inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>FFMC</th>\n",
       "      <th>DMC</th>\n",
       "      <th>DC</th>\n",
       "      <th>ISI</th>\n",
       "      <th>temp</th>\n",
       "      <th>RH</th>\n",
       "      <th>wind</th>\n",
       "      <th>rain</th>\n",
       "      <th>area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>517.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.475822</td>\n",
       "      <td>4.259188</td>\n",
       "      <td>90.644681</td>\n",
       "      <td>110.872340</td>\n",
       "      <td>547.940039</td>\n",
       "      <td>9.021663</td>\n",
       "      <td>18.889168</td>\n",
       "      <td>44.288201</td>\n",
       "      <td>4.017602</td>\n",
       "      <td>0.021663</td>\n",
       "      <td>12.847292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.275990</td>\n",
       "      <td>2.072929</td>\n",
       "      <td>5.520111</td>\n",
       "      <td>64.046482</td>\n",
       "      <td>248.066192</td>\n",
       "      <td>4.559477</td>\n",
       "      <td>5.806625</td>\n",
       "      <td>16.317469</td>\n",
       "      <td>1.791653</td>\n",
       "      <td>0.295959</td>\n",
       "      <td>63.655818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>18.700000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>7.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>90.200000</td>\n",
       "      <td>68.600000</td>\n",
       "      <td>437.700000</td>\n",
       "      <td>6.500000</td>\n",
       "      <td>15.500000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>2.700000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>91.600000</td>\n",
       "      <td>108.300000</td>\n",
       "      <td>664.200000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>19.300000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.520000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>92.900000</td>\n",
       "      <td>142.400000</td>\n",
       "      <td>713.900000</td>\n",
       "      <td>10.800000</td>\n",
       "      <td>22.800000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>4.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.570000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>96.200000</td>\n",
       "      <td>291.300000</td>\n",
       "      <td>860.600000</td>\n",
       "      <td>56.100000</td>\n",
       "      <td>33.300000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>6.400000</td>\n",
       "      <td>1090.840000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            month         day        FFMC         DMC          DC         ISI  \\\n",
       "count  517.000000  517.000000  517.000000  517.000000  517.000000  517.000000   \n",
       "mean     7.475822    4.259188   90.644681  110.872340  547.940039    9.021663   \n",
       "std      2.275990    2.072929    5.520111   64.046482  248.066192    4.559477   \n",
       "min      1.000000    1.000000   18.700000    1.100000    7.900000    0.000000   \n",
       "25%      7.000000    2.000000   90.200000   68.600000  437.700000    6.500000   \n",
       "50%      8.000000    5.000000   91.600000  108.300000  664.200000    8.400000   \n",
       "75%      9.000000    6.000000   92.900000  142.400000  713.900000   10.800000   \n",
       "max     12.000000    7.000000   96.200000  291.300000  860.600000   56.100000   \n",
       "\n",
       "             temp          RH        wind        rain         area  \n",
       "count  517.000000  517.000000  517.000000  517.000000   517.000000  \n",
       "mean    18.889168   44.288201    4.017602    0.021663    12.847292  \n",
       "std      5.806625   16.317469    1.791653    0.295959    63.655818  \n",
       "min      2.200000   15.000000    0.400000    0.000000     0.000000  \n",
       "25%     15.500000   33.000000    2.700000    0.000000     0.000000  \n",
       "50%     19.300000   42.000000    4.000000    0.000000     0.520000  \n",
       "75%     22.800000   53.000000    4.900000    0.000000     6.570000  \n",
       "max     33.300000  100.000000    9.400000    6.400000  1090.840000  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a281f36a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 5))\n",
    "sns.heatmap(data_forest_kaggle.corr())\n",
    "plt.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>FFMC</th>\n",
       "      <th>DMC</th>\n",
       "      <th>DC</th>\n",
       "      <th>ISI</th>\n",
       "      <th>temp</th>\n",
       "      <th>RH</th>\n",
       "      <th>wind</th>\n",
       "      <th>rain</th>\n",
       "      <th>area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.050837</td>\n",
       "      <td>0.291477</td>\n",
       "      <td>0.466645</td>\n",
       "      <td>0.868698</td>\n",
       "      <td>0.186597</td>\n",
       "      <td>0.368842</td>\n",
       "      <td>-0.095280</td>\n",
       "      <td>-0.086368</td>\n",
       "      <td>0.013438</td>\n",
       "      <td>0.056496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <td>-0.050837</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.041068</td>\n",
       "      <td>0.062870</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.032909</td>\n",
       "      <td>0.052190</td>\n",
       "      <td>0.092151</td>\n",
       "      <td>0.032478</td>\n",
       "      <td>-0.048340</td>\n",
       "      <td>0.023226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FFMC</th>\n",
       "      <td>0.291477</td>\n",
       "      <td>-0.041068</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.382619</td>\n",
       "      <td>0.330512</td>\n",
       "      <td>0.531805</td>\n",
       "      <td>0.431532</td>\n",
       "      <td>-0.300995</td>\n",
       "      <td>-0.028485</td>\n",
       "      <td>0.056702</td>\n",
       "      <td>0.040122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DMC</th>\n",
       "      <td>0.466645</td>\n",
       "      <td>0.062870</td>\n",
       "      <td>0.382619</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.682192</td>\n",
       "      <td>0.305128</td>\n",
       "      <td>0.469594</td>\n",
       "      <td>0.073795</td>\n",
       "      <td>-0.105342</td>\n",
       "      <td>0.074790</td>\n",
       "      <td>0.072994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC</th>\n",
       "      <td>0.868698</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.330512</td>\n",
       "      <td>0.682192</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.229154</td>\n",
       "      <td>0.496208</td>\n",
       "      <td>-0.039192</td>\n",
       "      <td>-0.203466</td>\n",
       "      <td>0.035861</td>\n",
       "      <td>0.049383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISI</th>\n",
       "      <td>0.186597</td>\n",
       "      <td>0.032909</td>\n",
       "      <td>0.531805</td>\n",
       "      <td>0.305128</td>\n",
       "      <td>0.229154</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.394287</td>\n",
       "      <td>-0.132517</td>\n",
       "      <td>0.106826</td>\n",
       "      <td>0.067668</td>\n",
       "      <td>0.008258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>temp</th>\n",
       "      <td>0.368842</td>\n",
       "      <td>0.052190</td>\n",
       "      <td>0.431532</td>\n",
       "      <td>0.469594</td>\n",
       "      <td>0.496208</td>\n",
       "      <td>0.394287</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.527390</td>\n",
       "      <td>-0.227116</td>\n",
       "      <td>0.069491</td>\n",
       "      <td>0.097844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RH</th>\n",
       "      <td>-0.095280</td>\n",
       "      <td>0.092151</td>\n",
       "      <td>-0.300995</td>\n",
       "      <td>0.073795</td>\n",
       "      <td>-0.039192</td>\n",
       "      <td>-0.132517</td>\n",
       "      <td>-0.527390</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.069410</td>\n",
       "      <td>0.099751</td>\n",
       "      <td>-0.075519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wind</th>\n",
       "      <td>-0.086368</td>\n",
       "      <td>0.032478</td>\n",
       "      <td>-0.028485</td>\n",
       "      <td>-0.105342</td>\n",
       "      <td>-0.203466</td>\n",
       "      <td>0.106826</td>\n",
       "      <td>-0.227116</td>\n",
       "      <td>0.069410</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.061119</td>\n",
       "      <td>0.012317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rain</th>\n",
       "      <td>0.013438</td>\n",
       "      <td>-0.048340</td>\n",
       "      <td>0.056702</td>\n",
       "      <td>0.074790</td>\n",
       "      <td>0.035861</td>\n",
       "      <td>0.067668</td>\n",
       "      <td>0.069491</td>\n",
       "      <td>0.099751</td>\n",
       "      <td>0.061119</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.007366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>area</th>\n",
       "      <td>0.056496</td>\n",
       "      <td>0.023226</td>\n",
       "      <td>0.040122</td>\n",
       "      <td>0.072994</td>\n",
       "      <td>0.049383</td>\n",
       "      <td>0.008258</td>\n",
       "      <td>0.097844</td>\n",
       "      <td>-0.075519</td>\n",
       "      <td>0.012317</td>\n",
       "      <td>-0.007366</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          month       day      FFMC       DMC        DC       ISI      temp  \\\n",
       "month  1.000000 -0.050837  0.291477  0.466645  0.868698  0.186597  0.368842   \n",
       "day   -0.050837  1.000000 -0.041068  0.062870  0.000105  0.032909  0.052190   \n",
       "FFMC   0.291477 -0.041068  1.000000  0.382619  0.330512  0.531805  0.431532   \n",
       "DMC    0.466645  0.062870  0.382619  1.000000  0.682192  0.305128  0.469594   \n",
       "DC     0.868698  0.000105  0.330512  0.682192  1.000000  0.229154  0.496208   \n",
       "ISI    0.186597  0.032909  0.531805  0.305128  0.229154  1.000000  0.394287   \n",
       "temp   0.368842  0.052190  0.431532  0.469594  0.496208  0.394287  1.000000   \n",
       "RH    -0.095280  0.092151 -0.300995  0.073795 -0.039192 -0.132517 -0.527390   \n",
       "wind  -0.086368  0.032478 -0.028485 -0.105342 -0.203466  0.106826 -0.227116   \n",
       "rain   0.013438 -0.048340  0.056702  0.074790  0.035861  0.067668  0.069491   \n",
       "area   0.056496  0.023226  0.040122  0.072994  0.049383  0.008258  0.097844   \n",
       "\n",
       "             RH      wind      rain      area  \n",
       "month -0.095280 -0.086368  0.013438  0.056496  \n",
       "day    0.092151  0.032478 -0.048340  0.023226  \n",
       "FFMC  -0.300995 -0.028485  0.056702  0.040122  \n",
       "DMC    0.073795 -0.105342  0.074790  0.072994  \n",
       "DC    -0.039192 -0.203466  0.035861  0.049383  \n",
       "ISI   -0.132517  0.106826  0.067668  0.008258  \n",
       "temp  -0.527390 -0.227116  0.069491  0.097844  \n",
       "RH     1.000000  0.069410  0.099751 -0.075519  \n",
       "wind   0.069410  1.000000  0.061119  0.012317  \n",
       "rain   0.099751  0.061119  1.000000 -0.007366  \n",
       "area  -0.075519  0.012317 -0.007366  1.000000  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>686.9</td>\n",
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       "      <td>91.7</td>\n",
       "      <td>33.3</td>\n",
       "      <td>77.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>97</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
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       "      <td>89.3</td>\n",
       "      <td>51.3</td>\n",
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       "      <td>9.6</td>\n",
       "      <td>11.4</td>\n",
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      ],
      "text/plain": [
       "   month  day  FFMC   DMC     DC  ISI  temp  RH  wind  rain  area\n",
       "0      3    5  86.2  26.2   94.3  5.1   8.2  51   6.7   0.0   0.0\n",
       "1     10    2  90.6  35.4  669.1  6.7  18.0  33   0.9   0.0   0.0\n",
       "2     10    6  90.6  43.7  686.9  6.7  14.6  33   1.3   0.0   0.0\n",
       "3      3    5  91.7  33.3   77.5  9.0   8.3  97   4.0   0.2   0.0\n",
       "4      3    7  89.3  51.3  102.2  9.6  11.4  99   1.8   0.0   0.0"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data_forest_kaggle.copy()\n",
    "data.drop(columns=['area'], inplace=True)\n",
    "target = data_forest_kaggle['area']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>FFMC</th>\n",
       "      <th>DMC</th>\n",
       "      <th>DC</th>\n",
       "      <th>ISI</th>\n",
       "      <th>temp</th>\n",
       "      <th>RH</th>\n",
       "      <th>wind</th>\n",
       "      <th>rain</th>\n",
       "      <th>area</th>\n",
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       "      <td>18.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>8.3</td>\n",
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       "      <td>11.4</td>\n",
       "      <td>99</td>\n",
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      ],
      "text/plain": [
       "   month  day  FFMC   DMC     DC  ISI  temp  RH  wind  rain  area\n",
       "0      3    5  86.2  26.2   94.3  5.1   8.2  51   6.7   0.0   0.0\n",
       "1     10    2  90.6  35.4  669.1  6.7  18.0  33   0.9   0.0   0.0\n",
       "2     10    6  90.6  43.7  686.9  6.7  14.6  33   1.3   0.0   0.0\n",
       "3      3    5  91.7  33.3   77.5  9.0   8.3  97   4.0   0.2   0.0\n",
       "4      3    7  89.3  51.3  102.2  9.6  11.4  99   1.8   0.0   0.0"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle = pd.read_csv('forestfires.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle.replace(('jan','feb','mar','apr','may','jun','jul','aug','sep','oct','nov','dec'),\n",
    "                           (1,2,3,4,5,6,7,8,9,10,11,12), inplace=True)\n",
    "data_forest_kaggle.replace(('mon', 'tue', 'wed', 'thu', 'fri', 'sat', 'sun'), (1, 2, 3, 4, 5, 6, 7), \n",
    "                           inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle.head(5)\n",
    "data_forest_kaggle.drop(columns=['X', 'Y', 'FFMC', 'DMC', 'DC', 'ISI'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   month  day  temp  RH  wind  rain  area\n",
       "0      3    5   8.2  51   6.7   0.0   0.0\n",
       "1     10    2  18.0  33   0.9   0.0   0.0\n",
       "2     10    6  14.6  33   1.3   0.0   0.0\n",
       "3      3    5   8.3  97   4.0   0.2   0.0\n",
       "4      3    7  11.4  99   1.8   0.0   0.0"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>temp</th>\n",
       "      <th>RH</th>\n",
       "      <th>wind</th>\n",
       "      <th>rain</th>\n",
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       "      <th>138</th>\n",
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       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>9</td>\n",
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       "      <th>140</th>\n",
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       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>8</td>\n",
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       "      <td>31</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.55</td>\n",
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       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>21.2</td>\n",
       "      <td>51</td>\n",
       "      <td>8.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.61</td>\n",
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       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>16.6</td>\n",
       "      <td>53</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>23.8</td>\n",
       "      <td>32</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.77</td>\n",
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       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>13.2</td>\n",
       "      <td>40</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>24.2</td>\n",
       "      <td>28</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>17.4</td>\n",
       "      <td>43</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>23.7</td>\n",
       "      <td>25</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>23.2</td>\n",
       "      <td>39</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>24.8</td>\n",
       "      <td>29</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>24.6</td>\n",
       "      <td>43</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.43</td>\n",
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       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>20.1</td>\n",
       "      <td>47</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.46</td>\n",
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       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>29.6</td>\n",
       "      <td>27</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>16.4</td>\n",
       "      <td>47</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>28.6</td>\n",
       "      <td>27</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>18.4</td>\n",
       "      <td>45</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>20.5</td>\n",
       "      <td>35</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>19.0</td>\n",
       "      <td>34</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>16.1</td>\n",
       "      <td>29</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>20.3</td>\n",
       "      <td>41</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>15.2</td>\n",
       "      <td>31</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>17.8</td>\n",
       "      <td>56</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>17.8</td>\n",
       "      <td>67</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5.3</td>\n",
       "      <td>70</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>16.6</td>\n",
       "      <td>47</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>33</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>18.0</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>14.3</td>\n",
       "      <td>79</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>24.5</td>\n",
       "      <td>50</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>70.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>26.4</td>\n",
       "      <td>35</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>22.7</td>\n",
       "      <td>40</td>\n",
       "      <td>9.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>27.2</td>\n",
       "      <td>28</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>26.1</td>\n",
       "      <td>45</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>82</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>57</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>278.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>25</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>23.4</td>\n",
       "      <td>40</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>484</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>33.1</td>\n",
       "      <td>25</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>30.6</td>\n",
       "      <td>28</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>24.1</td>\n",
       "      <td>43</td>\n",
       "      <td>6.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>26.4</td>\n",
       "      <td>34</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>19.4</td>\n",
       "      <td>71</td>\n",
       "      <td>7.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>29</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>30.8</td>\n",
       "      <td>30</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>26</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>32.3</td>\n",
       "      <td>27</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>33.3</td>\n",
       "      <td>26</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>27.3</td>\n",
       "      <td>63</td>\n",
       "      <td>4.9</td>\n",
       "      <td>6.4</td>\n",
       "      <td>10.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>29.2</td>\n",
       "      <td>30</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>28.9</td>\n",
       "      <td>29</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>26.7</td>\n",
       "      <td>35</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>21.1</td>\n",
       "      <td>71</td>\n",
       "      <td>7.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>18.2</td>\n",
       "      <td>62</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>27.8</td>\n",
       "      <td>32</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>21.9</td>\n",
       "      <td>71</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>21.2</td>\n",
       "      <td>70</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>270 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     month  day  temp  RH  wind  rain    area\n",
       "138      7    2  18.0  42   2.7   0.0    0.36\n",
       "139      9    2  21.7  38   2.2   0.0    0.43\n",
       "140      9    1  21.9  39   1.8   0.0    0.47\n",
       "141      8    3  23.3  31   4.5   0.0    0.55\n",
       "142      8    5  21.2  51   8.9   0.0    0.61\n",
       "143      7    6  16.6  53   5.4   0.0    0.71\n",
       "144      8    3  23.8  32   5.4   0.0    0.77\n",
       "145      8    4  27.4  22   4.0   0.0    0.90\n",
       "146      3    1  13.2  40   5.4   0.0    0.95\n",
       "147      9    2  24.2  28   3.6   0.0    0.96\n",
       "148      8    2  17.4  43   6.7   0.0    1.07\n",
       "149      9    4  23.7  25   4.5   0.0    1.12\n",
       "150      6    5  23.2  39   5.4   0.0    1.19\n",
       "151      7    7  24.8  29   2.2   0.0    1.36\n",
       "152      7    6  24.6  43   1.8   0.0    1.43\n",
       "153      9    5  20.1  47   4.9   0.0    1.46\n",
       "154      9    6  29.6  27   2.7   0.0    1.46\n",
       "155      8    7  16.4  47   1.3   0.0    1.56\n",
       "156      9    6  28.6  27   2.2   0.0    1.61\n",
       "157      8    3  18.4  45   3.6   0.0    1.63\n",
       "158      8    3  20.5  35   4.0   0.0    1.64\n",
       "159      9    5  19.0  34   5.8   0.0    1.69\n",
       "160      3    1  16.1  29   3.1   0.0    1.75\n",
       "161      8    4  20.3  41   4.0   0.0    1.90\n",
       "162      3    6  15.2  31   8.5   0.0    1.94\n",
       "163      9    6  17.8  56   1.8   0.0    1.95\n",
       "164      9    7  17.8  67   2.2   0.0    2.01\n",
       "165      3    4   5.3  70   4.5   0.0    2.14\n",
       "166      8    3  16.6  47   0.9   0.0    2.29\n",
       "167      8    3  23.4  33   4.5   0.0    2.51\n",
       "..     ...  ...   ...  ..   ...   ...     ...\n",
       "471      5    5  18.0  40   4.0   0.0   38.48\n",
       "472      6    1  14.3  79   4.0   0.0    1.94\n",
       "473      6    6  24.5  50   3.1   0.0   70.32\n",
       "474      6    4  26.4  35   2.7   0.0   10.08\n",
       "475      6    4  22.7  40   9.4   0.0    3.19\n",
       "476      7    4  27.2  28   1.3   0.0    1.76\n",
       "477      7    7  26.1  45   4.0   0.0    7.36\n",
       "478      7    7  18.2  82   4.5   0.0    2.21\n",
       "479      7    1  22.6  57   4.9   0.0  278.53\n",
       "480      7    4  30.2  25   4.5   0.0    2.75\n",
       "482      8    7  23.4  40   5.8   0.0    1.29\n",
       "484      8    7  33.1  25   4.0   0.0   26.43\n",
       "485      8    1  30.6  28   3.6   0.0    2.07\n",
       "486      8    2  24.1  43   6.3   0.0    2.00\n",
       "487      8    2  26.4  34   3.6   0.0   16.40\n",
       "488      8    2  19.4  71   7.6   0.0   46.70\n",
       "493      8    5  27.5  29   4.5   0.0   43.32\n",
       "494      8    6  30.8  30   4.9   0.0    8.59\n",
       "496      8    1  32.6  26   3.1   0.0    2.77\n",
       "497      8    2  32.3  27   2.2   0.0   14.68\n",
       "498      8    2  33.3  26   2.7   0.0   40.54\n",
       "499      8    2  27.3  63   4.9   6.4   10.82\n",
       "503      8    3  29.2  30   4.9   0.0    1.95\n",
       "504      8    3  28.9  29   4.9   0.0   49.59\n",
       "505      8    4  26.7  35   1.8   0.0    5.80\n",
       "509      8    5  21.1  71   7.6   1.4    2.17\n",
       "510      8    5  18.2  62   5.4   0.0    0.43\n",
       "512      8    7  27.8  32   2.7   0.0    6.44\n",
       "513      8    7  21.9  71   5.8   0.0   54.29\n",
       "514      8    7  21.2  70   6.7   0.0   11.16\n",
       "\n",
       "[270 rows x 7 columns]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_forest_kaggle[data_forest_kaggle['area'] > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "estimator.predict(data_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>temp</th>\n",
       "      <th>RH</th>\n",
       "      <th>wind</th>\n",
       "      <th>rain</th>\n",
       "      <th>area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>8.2</td>\n",
       "      <td>51</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>18.0</td>\n",
       "      <td>33</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>14.6</td>\n",
       "      <td>33</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>8.3</td>\n",
       "      <td>97</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>11.4</td>\n",
       "      <td>99</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>29</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>24.1</td>\n",
       "      <td>27</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>86</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>13.1</td>\n",
       "      <td>63</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>22.8</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>17.8</td>\n",
       "      <td>51</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>19.3</td>\n",
       "      <td>38</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>17.0</td>\n",
       "      <td>72</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>21.3</td>\n",
       "      <td>42</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>26.4</td>\n",
       "      <td>21</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>44</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>15.1</td>\n",
       "      <td>27</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>47</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>15.9</td>\n",
       "      <td>35</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>9.3</td>\n",
       "      <td>44</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>18.3</td>\n",
       "      <td>40</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>19.1</td>\n",
       "      <td>38</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>21.0</td>\n",
       "      <td>44</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>19.5</td>\n",
       "      <td>43</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>23.7</td>\n",
       "      <td>32</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>16.3</td>\n",
       "      <td>60</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>19.0</td>\n",
       "      <td>34</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>19.4</td>\n",
       "      <td>48</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>30.2</td>\n",
       "      <td>24</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>22.8</td>\n",
       "      <td>39</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>26.4</td>\n",
       "      <td>34</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>19.4</td>\n",
       "      <td>71</td>\n",
       "      <td>7.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>20.6</td>\n",
       "      <td>58</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>28.7</td>\n",
       "      <td>33</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>32.4</td>\n",
       "      <td>21</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>32.4</td>\n",
       "      <td>27</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>29</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>30.8</td>\n",
       "      <td>30</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>23.9</td>\n",
       "      <td>42</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>32.6</td>\n",
       "      <td>26</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>32.3</td>\n",
       "      <td>27</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>33.3</td>\n",
       "      <td>26</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>27.3</td>\n",
       "      <td>63</td>\n",
       "      <td>4.9</td>\n",
       "      <td>6.4</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>21.6</td>\n",
       "      <td>65</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>21.6</td>\n",
       "      <td>65</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>69</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>29.2</td>\n",
       "      <td>30</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>28.9</td>\n",
       "      <td>29</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>26.7</td>\n",
       "      <td>35</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>18.5</td>\n",
       "      <td>73</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>25.9</td>\n",
       "      <td>41</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>25.9</td>\n",
       "      <td>41</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>21.1</td>\n",
       "      <td>71</td>\n",
       "      <td>7.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>18.2</td>\n",
       "      <td>62</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>27.8</td>\n",
       "      <td>35</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>27.8</td>\n",
       "      <td>32</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>21.9</td>\n",
       "      <td>71</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>21.2</td>\n",
       "      <td>70</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>25.6</td>\n",
       "      <td>42</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>11.8</td>\n",
       "      <td>31</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>517 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     month  day  temp  RH  wind  rain  area\n",
       "0        3    5   8.2  51   6.7   0.0     0\n",
       "1       10    2  18.0  33   0.9   0.0     0\n",
       "2       10    6  14.6  33   1.3   0.0     0\n",
       "3        3    5   8.3  97   4.0   0.2     0\n",
       "4        3    7  11.4  99   1.8   0.0     0\n",
       "5        8    7  22.2  29   5.4   0.0     0\n",
       "6        8    1  24.1  27   3.1   0.0     0\n",
       "7        8    1   8.0  86   2.2   0.0     0\n",
       "8        9    2  13.1  63   5.4   0.0     0\n",
       "9        9    6  22.8  40   4.0   0.0     0\n",
       "10       9    6  17.8  51   7.2   0.0     0\n",
       "11       9    6  19.3  38   4.0   0.0     0\n",
       "12       8    5  17.0  72   6.7   0.0     0\n",
       "13       9    1  21.3  42   2.2   0.0     0\n",
       "14       9    3  26.4  21   4.5   0.0     0\n",
       "15       9    5  22.9  44   5.4   0.0     0\n",
       "16       3    6  15.1  27   5.4   0.0     0\n",
       "17      10    1  16.7  47   4.9   0.0     0\n",
       "18       3    3  15.9  35   4.0   0.0     0\n",
       "19       4    6   9.3  44   4.5   0.0     0\n",
       "20       9    2  18.3  40   2.7   0.0     0\n",
       "21       9    1  19.1  38   2.7   0.0     0\n",
       "22       6    7  21.0  44   4.5   0.0     0\n",
       "23       8    6  19.5  43   5.8   0.0     0\n",
       "24       8    6  23.7  32   5.8   0.0     0\n",
       "25       8    7  16.3  60   5.4   0.0     0\n",
       "26       9    5  19.0  34   5.8   0.0     0\n",
       "27       9    1  19.4  48   1.3   0.0     0\n",
       "28       9    6  30.2  24   2.7   0.0     0\n",
       "29       9    7  22.8  39   3.6   0.0     0\n",
       "..     ...  ...   ...  ..   ...   ...   ...\n",
       "487      8    2  26.4  34   3.6   0.0    16\n",
       "488      8    2  19.4  71   7.6   0.0    46\n",
       "489      8    3  20.6  58   1.3   0.0     0\n",
       "490      8    3  28.7  33   4.0   0.0     0\n",
       "491      8    4  32.4  21   4.5   0.0     0\n",
       "492      8    5  32.4  27   2.2   0.0     0\n",
       "493      8    5  27.5  29   4.5   0.0    43\n",
       "494      8    6  30.8  30   4.9   0.0     8\n",
       "495      8    1  23.9  42   2.2   0.0     0\n",
       "496      8    1  32.6  26   3.1   0.0     2\n",
       "497      8    2  32.3  27   2.2   0.0    14\n",
       "498      8    2  33.3  26   2.7   0.0    40\n",
       "499      8    2  27.3  63   4.9   6.4    10\n",
       "500      8    2  21.6  65   4.9   0.8     0\n",
       "501      8    2  21.6  65   4.9   0.8     0\n",
       "502      8    2  20.7  69   4.9   0.4     0\n",
       "503      8    3  29.2  30   4.9   0.0     1\n",
       "504      8    3  28.9  29   4.9   0.0    49\n",
       "505      8    4  26.7  35   1.8   0.0     5\n",
       "506      8    5  18.5  73   8.5   0.0     0\n",
       "507      8    5  25.9  41   3.6   0.0     0\n",
       "508      8    5  25.9  41   3.6   0.0     0\n",
       "509      8    5  21.1  71   7.6   1.4     2\n",
       "510      8    5  18.2  62   5.4   0.0     0\n",
       "511      8    7  27.8  35   2.7   0.0     0\n",
       "512      8    7  27.8  32   2.7   0.0     6\n",
       "513      8    7  21.9  71   5.8   0.0    54\n",
       "514      8    7  21.2  70   6.7   0.0    11\n",
       "515      8    6  25.6  42   4.0   0.0     0\n",
       "516     11    2  11.8  31   4.5   0.0     0\n",
       "\n",
       "[517 rows x 7 columns]"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sin, cos, sqrt, atan2, radians"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_coordinates = [55.753960, 37.620393]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_distance = pd.read_csv('MODIS_C6_Russia_and_Asia_24h (1).csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [],
   "source": [
    "lat_long = list(zip(data_distance['latitude'], data_distance['longitude']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(30.535, 26.076999999999998),\n",
       " (30.534000000000002, 26.087),\n",
       " (29.656, 28.361),\n",
       " (29.533, 28.443),\n",
       " (12.991, 26.46),\n",
       " (12.949000000000002, 26.465999999999998),\n",
       " (12.945, 26.489),\n",
       " (12.95, 26.46),\n",
       " (12.946, 26.484),\n",
       " (12.937999999999999, 26.47),\n",
       " (12.908, 26.526),\n",
       " (12.812999999999999, 26.552),\n",
       " (47.875, 33.446999999999996),\n",
       " (35.025999999999996, 136.878),\n",
       " (48.621, 133.043),\n",
       " (48.622, 133.034),\n",
       " (50.056000000000004, 128.31),\n",
       " (49.643, 129.93200000000002),\n",
       " (49.823, 128.719),\n",
       " (48.63399999999999, 133.077),\n",
       " (48.628, 133.10299999999998),\n",
       " (48.63399999999999, 133.02100000000002),\n",
       " (48.628, 133.046),\n",
       " (48.623000000000005, 133.071),\n",
       " (48.623000000000005, 133.015),\n",
       " (48.617, 133.04),\n",
       " (50.463, 118.818),\n",
       " (50.461000000000006, 118.838),\n",
       " (50.696000000000005, 115.76),\n",
       " (50.693999999999996, 115.788),\n",
       " (50.452, 118.816),\n",
       " (50.45, 118.836),\n",
       " (50.683, 115.758),\n",
       " (50.43899999999999, 116.98700000000001),\n",
       " (50.437, 117.01100000000001),\n",
       " (50.428999999999995, 116.959),\n",
       " (50.427, 116.985),\n",
       " (50.425, 117.008),\n",
       " (50.417, 116.958),\n",
       " (50.416000000000004, 116.98200000000001),\n",
       " (50.413999999999994, 117.006),\n",
       " (50.406000000000006, 116.956),\n",
       " (50.385, 116.82),\n",
       " (50.348, 116.84100000000001),\n",
       " (50.338, 116.814),\n",
       " (50.336000000000006, 116.839),\n",
       " (50.315, 116.809),\n",
       " (50.313, 116.834),\n",
       " (50.318999999999996, 116.803),\n",
       " (50.318000000000005, 116.82799999999999),\n",
       " (50.308, 116.801),\n",
       " (50.306000000000004, 116.825),\n",
       " (49.442, 122.469),\n",
       " (50.157, 113.441),\n",
       " (50.152, 113.43299999999999),\n",
       " (48.996, 124.025),\n",
       " (48.576, 124.295),\n",
       " (45.912, 134.454),\n",
       " (45.903999999999996, 134.488),\n",
       " (45.911, 122.21799999999999),\n",
       " (43.708, 131.776),\n",
       " (43.702, 131.803),\n",
       " (45.348, 121.95200000000001),\n",
       " (45.343, 121.99),\n",
       " (45.301, 121.76100000000001),\n",
       " (45.299, 121.773),\n",
       " (43.998999999999995, 123.85),\n",
       " (43.988, 123.86),\n",
       " (43.978, 123.811),\n",
       " (43.976000000000006, 123.824),\n",
       " (43.623999999999995, 121.796),\n",
       " (43.207, 123.57),\n",
       " (43.391000000000005, 121.684),\n",
       " (42.873000000000005, 123.28),\n",
       " (42.476000000000006, 124.005),\n",
       " (42.398, 124.256),\n",
       " (42.41, 124.126),\n",
       " (42.291000000000004, 123.721),\n",
       " (42.288999999999994, 123.73299999999999),\n",
       " (42.626000000000005, 119.63600000000001),\n",
       " (42.013000000000005, 123.83),\n",
       " (42.148, 122.515),\n",
       " (42.146, 122.527),\n",
       " (41.912, 123.821),\n",
       " (41.84, 123.75399999999999),\n",
       " (42.394, 119.213),\n",
       " (41.941, 119.884),\n",
       " (41.994, 119.169),\n",
       " (41.461999999999996, 122.87100000000001),\n",
       " (41.443999999999996, 122.337),\n",
       " (41.174, 123.99600000000001),\n",
       " (41.172, 124.009),\n",
       " (41.22, 123.62200000000001),\n",
       " (41.163000000000004, 122.99600000000001),\n",
       " (41.136, 122.995),\n",
       " (41.04600000000001, 122.68799999999999),\n",
       " (41.044, 122.7),\n",
       " (41.037, 122.686),\n",
       " (41.038999999999994, 122.61200000000001),\n",
       " (40.698, 122.421),\n",
       " (40.696, 122.43299999999999),\n",
       " (40.662, 122.417),\n",
       " (40.541, 122.416),\n",
       " (36.983000000000004, 126.70700000000001),\n",
       " (37.413000000000004, 122.029),\n",
       " (37.411, 122.041),\n",
       " (29.64, 129.718),\n",
       " (58.452, 107.603),\n",
       " (58.428999999999995, 107.568),\n",
       " (58.425, 107.586),\n",
       " (58.42, 107.446),\n",
       " (59.11600000000001, 102.905),\n",
       " (59.113, 102.92299999999999),\n",
       " (58.137, 107.109),\n",
       " (57.988, 106.814),\n",
       " (57.065, 107.65),\n",
       " (51.246, 115.49799999999999),\n",
       " (51.253, 115.495),\n",
       " (51.239, 115.54299999999999),\n",
       " (50.49, 117.052),\n",
       " (50.492, 116.985),\n",
       " (50.475, 117.04),\n",
       " (50.489, 117.046),\n",
       " (50.49, 116.979),\n",
       " (50.473, 117.03399999999999),\n",
       " (50.458, 117.022),\n",
       " (50.426, 116.999),\n",
       " (50.428000000000004, 116.93299999999999),\n",
       " (50.411, 116.98700000000001),\n",
       " (50.413000000000004, 116.92),\n",
       " (50.395, 116.976),\n",
       " (50.456, 117.014),\n",
       " (50.425, 116.99),\n",
       " (50.41, 116.978),\n",
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       " (53.552, 33.69),\n",
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       " (44.995, 64.85),\n",
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       " (45.232, 64.203),\n",
       " (50.77, 63.425),\n",
       " (50.783, 63.416000000000004),\n",
       " (50.784, 63.449),\n",
       " (50.775, 63.413999999999994),\n",
       " (50.305, 59.372),\n",
       " (50.254, 59.144),\n",
       " (50.256, 59.14),\n",
       " (50.861999999999995, 59.233999999999995),\n",
       " (50.86600000000001, 59.228),\n",
       " (24.895, 53.019),\n",
       " (35.075, 36.102),\n",
       " (36.954, 35.644),\n",
       " (37.061, 34.942),\n",
       " ...]"
      ]
     },
     "execution_count": 273,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lat_long"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sin, cos, sqrt, atan2, radians\n",
    "\n",
    "def calculate_distance(lat1, lon1, lat2, lon2):\n",
    "# approximate radius of earth in km\n",
    "    R = 6373.0\n",
    "    \n",
    "    lat1 = radians(lat1)\n",
    "    lon1 = radians(lon1)\n",
    "    lat2 = radians(lat2)\n",
    "    lon2 = radians(lon2)\n",
    "    \n",
    "    dlon = lon2 - lon1\n",
    "    dlat = lat2 - lat1\n",
    "\n",
    "    a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2\n",
    "    c = 2 * atan2(sqrt(a), sqrt(1 - a))\n",
    "\n",
    "    distance = R * c\n",
    "    \n",
    "    return distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sin, cos, sqrt, atan2, radians\n",
    "\n",
    "def min_distance(user_coordinates_lat, user_coordinates_lon):\n",
    "    \n",
    "    def calculate_distance(lat1, lon1, lat2, lon2):\n",
    "        # approximate radius of earth in km\n",
    "        R = 6373.0\n",
    "    \n",
    "        lat1 = radians(lat1)\n",
    "        lon1 = radians(lon1)\n",
    "        lat2 = radians(lat2)\n",
    "        lon2 = radians(lon2)\n",
    "\n",
    "        dlon = lon2 - lon1\n",
    "        dlat = lat2 - lat1\n",
    "\n",
    "        a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2\n",
    "        c = 2 * atan2(sqrt(a), sqrt(1 - a))\n",
    "\n",
    "        distance = R * c\n",
    "\n",
    "        return distance\n",
    "    \n",
    "    data_distance = pd.read_csv('MODIS_C6_Russia_and_Asia_24h (1).csv')\n",
    "    lat_long = list(zip(data_distance['latitude'], data_distance['longitude']))\n",
    "    distance = []\n",
    "    coor = []\n",
    "    for i, j in lat_long:\n",
    "        distance.append(calculate_distance(user_coordinates[0], user_coordinates[1], i, j))\n",
    "        coor.append([j, i])\n",
    "    \n",
    "    dist_coor = sorted(list(zip(distance, coor)))\n",
    "    \n",
    "    \n",
    "    \n",
    "    return dist_coor[0][0], dist_coor[0][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(176.2744053941077, [37.709, 54.17])"
      ]
     },
     "execution_count": 338,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_distance(user_coordinates[0], user_coordinates[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1195.4971863361702"
      ]
     },
     "execution_count": 285,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calculate_distance(user_coordinates[0], user_coordinates[1], 45.040216, 38.975996)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [],
   "source": [
    "import staticmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [],
   "source": [
    "coordinates = [55.753960, 37.620393]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [],
   "source": [
    "from staticmap import StaticMap, Line\n",
    "def img_fire(user_coordinates_lat, user_coordinates_lon):\n",
    "    m = StaticMap(800, 800, 80)\n",
    "\n",
    "    coordinates = [[min_distance(user_coordinates_lat, user_coordinates_lon)[1][0],\n",
    "                    min_distance(user_coordinates_lat, user_coordinates_lon)[1][1]]]\n",
    "    line_outline = Line(coordinates, 'white', 6)\n",
    "    line = Line(coordinates, '#D2322D', 10)\n",
    "\n",
    "    m.add_line(line_outline)\n",
    "    m.add_line(line)\n",
    "\n",
    "    image = m.render()\n",
    "    image.save('ferry.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_fire(user_coordinates[0], user_coordinates[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import curve_fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "data_forest_kaggle.to_csv('new_csv.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_forest_kaggle = pd.read_csv('new_csv.csv')\n",
    "data_forest_kaggle_target = data_forest_kaggle['area']\n",
    "data_forest_kaggle.drop(columns=['area', 'Unnamed: 0'], inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "array([97.17329458, 25.87481046, 20.50757591, 63.53986266, 63.25718493,\n",
    "       27.33511692, 19.80833096, 23.74328342])"
   ]
  }
 ],
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