{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true,
    "pycharm": {
     "is_executing": true
    },
    "ExecuteTime": {
     "end_time": "2024-04-13T16:07:39.757038200Z",
     "start_time": "2024-04-13T16:07:01.476848900Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: kaggle in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (1.6.6)\n",
      "Requirement already satisfied: six>=1.10 in c:\\software\\python3\\lib\\site-packages (from kaggle) (1.16.0)\n",
      "Requirement already satisfied: certifi in c:\\software\\python3\\lib\\site-packages (from kaggle) (2023.7.22)\n",
      "Requirement already satisfied: python-dateutil in c:\\software\\python3\\lib\\site-packages (from kaggle) (2.8.2)\n",
      "Requirement already satisfied: requests in c:\\software\\python3\\lib\\site-packages (from kaggle) (2.31.0)\n",
      "Requirement already satisfied: tqdm in c:\\software\\python3\\lib\\site-packages (from kaggle) (4.66.1)\n",
      "Requirement already satisfied: python-slugify in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from kaggle) (8.0.4)\n",
      "Requirement already satisfied: urllib3 in c:\\software\\python3\\lib\\site-packages (from kaggle) (1.26.16)\n",
      "Requirement already satisfied: bleach in c:\\software\\python3\\lib\\site-packages (from kaggle) (6.0.0)\n",
      "Requirement already satisfied: webencodings in c:\\software\\python3\\lib\\site-packages (from bleach->kaggle) (0.5.1)\n",
      "Requirement already satisfied: text-unidecode>=1.3 in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from python-slugify->kaggle) (1.3)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\software\\python3\\lib\\site-packages (from requests->kaggle) (3.2.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in c:\\software\\python3\\lib\\site-packages (from requests->kaggle) (3.4)\n",
      "Requirement already satisfied: colorama in c:\\software\\python3\\lib\\site-packages (from tqdm->kaggle) (0.4.6)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 23.0.1 -> 24.0\n",
      "[notice] To update, run: python3.exe -m pip install --upgrade pip\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\software\\python3\\lib\\site-packages (2.0.3)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\software\\python3\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\software\\python3\\lib\\site-packages (from pandas) (2023.3)\n",
      "Requirement already satisfied: tzdata>=2022.1 in c:\\software\\python3\\lib\\site-packages (from pandas) (2023.3)\n",
      "Requirement already satisfied: numpy>=1.21.0 in c:\\software\\python3\\lib\\site-packages (from pandas) (1.24.3)\n",
      "Requirement already satisfied: six>=1.5 in c:\\software\\python3\\lib\\site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 23.0.1 -> 24.0\n",
      "[notice] To update, run: python3.exe -m pip install --upgrade pip\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit-learn in c:\\software\\python3\\lib\\site-packages (1.3.0)\n",
      "Requirement already satisfied: numpy>=1.17.3 in c:\\software\\python3\\lib\\site-packages (from scikit-learn) (1.24.3)\n",
      "Requirement already satisfied: scipy>=1.5.0 in c:\\software\\python3\\lib\\site-packages (from scikit-learn) (1.11.2)\n",
      "Requirement already satisfied: joblib>=1.1.1 in c:\\software\\python3\\lib\\site-packages (from scikit-learn) (1.3.2)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\software\\python3\\lib\\site-packages (from scikit-learn) (3.2.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 23.0.1 -> 24.0\n",
      "[notice] To update, run: python3.exe -m pip install --upgrade pip\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: matplotlib in c:\\software\\python3\\lib\\site-packages (3.7.2)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (1.1.0)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (4.42.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (1.4.4)\n",
      "Requirement already satisfied: numpy>=1.20 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (1.24.3)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (23.1)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (10.0.0)\n",
      "Requirement already satisfied: pyparsing<3.1,>=2.3.1 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (3.0.9)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\software\\python3\\lib\\site-packages (from matplotlib) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\software\\python3\\lib\\site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 23.0.1 -> 24.0\n",
      "[notice] To update, run: python3.exe -m pip install --upgrade pip\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: geopandas in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (0.14.3)\n",
      "Requirement already satisfied: fiona>=1.8.21 in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from geopandas) (1.9.6)\n",
      "Requirement already satisfied: packaging in c:\\software\\python3\\lib\\site-packages (from geopandas) (23.1)\n",
      "Requirement already satisfied: pandas>=1.4.0 in c:\\software\\python3\\lib\\site-packages (from geopandas) (2.0.3)\n",
      "Requirement already satisfied: pyproj>=3.3.0 in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from geopandas) (3.6.1)\n",
      "Requirement already satisfied: shapely>=1.8.0 in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from geopandas) (2.0.3)\n",
      "Requirement already satisfied: attrs>=19.2.0 in c:\\software\\python3\\lib\\site-packages (from fiona>=1.8.21->geopandas) (23.1.0)\n",
      "Requirement already satisfied: certifi in c:\\software\\python3\\lib\\site-packages (from fiona>=1.8.21->geopandas) (2023.7.22)\n",
      "Requirement already satisfied: click~=8.0 in c:\\software\\python3\\lib\\site-packages (from fiona>=1.8.21->geopandas) (8.1.7)\n",
      "Requirement already satisfied: click-plugins>=1.0 in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from fiona>=1.8.21->geopandas) (1.1.1)\n",
      "Requirement already satisfied: cligj>=0.5 in \\\\files\\students\\s464914\\.appdata\\python\\python310\\site-packages (from fiona>=1.8.21->geopandas) (0.7.2)\n",
      "Requirement already satisfied: six in c:\\software\\python3\\lib\\site-packages (from fiona>=1.8.21->geopandas) (1.16.0)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\software\\python3\\lib\\site-packages (from pandas>=1.4.0->geopandas) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\software\\python3\\lib\\site-packages (from pandas>=1.4.0->geopandas) (2023.3)\n",
      "Requirement already satisfied: tzdata>=2022.1 in c:\\software\\python3\\lib\\site-packages (from pandas>=1.4.0->geopandas) (2023.3)\n",
      "Requirement already satisfied: numpy>=1.21.0 in c:\\software\\python3\\lib\\site-packages (from pandas>=1.4.0->geopandas) (1.24.3)\n",
      "Requirement already satisfied: colorama in c:\\software\\python3\\lib\\site-packages (from click~=8.0->fiona>=1.8.21->geopandas) (0.4.6)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 23.0.1 -> 24.0\n",
      "[notice] To update, run: python3.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "%pip install --user kaggle \n",
    "%pip install --user pandas\n",
    "%pip install --user scikit-learn\n",
    "%pip install --user matplotlib\n",
    "%pip install --user geopandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-03-17T17:38:40.019389600Z",
     "start_time": "2024-03-17T17:38:36.535384600Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "is_executing": true
    },
    "ExecuteTime": {
     "end_time": "2024-04-13T16:11:03.249257400Z",
     "start_time": "2024-04-13T16:10:58.745694100Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading forest-cover-type-dataset.zip to J:\\PycharmProjects\\ium_464914\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/11.2M [00:00<?, ?B/s]\n",
      "  9%|8         | 1.00M/11.2M [00:00<00:06, 1.56MB/s]\n",
      " 18%|#7        | 2.00M/11.2M [00:00<00:03, 3.10MB/s]\n",
      " 36%|###5      | 4.00M/11.2M [00:00<00:01, 6.25MB/s]\n",
      " 54%|#####3    | 6.00M/11.2M [00:01<00:00, 9.19MB/s]\n",
      " 81%|########  | 9.00M/11.2M [00:01<00:00, 13.0MB/s]\n",
      "100%|##########| 11.2M/11.2M [00:01<00:00, 9.30MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d uciml/forest-cover-type-dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-13T16:11:41.214712500Z",
     "start_time": "2024-04-13T16:11:37.462860300Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  forest-cover-type-dataset.zip\n",
      "  inflating: covtype.csv             \n"
     ]
    }
   ],
   "source": [
    "!unzip -o forest-cover-type-dataset.zip "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Zbiór</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-03-17T17:38:46.756471100Z",
     "start_time": "2024-03-17T17:38:46.335674200Z"
    }
   },
   "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>Elevation</th>\n",
       "      <th>Aspect</th>\n",
       "      <th>Slope</th>\n",
       "      <th>Horizontal_Distance_To_Hydrology</th>\n",
       "      <th>Vertical_Distance_To_Hydrology</th>\n",
       "      <th>Horizontal_Distance_To_Roadways</th>\n",
       "      <th>Hillshade_9am</th>\n",
       "      <th>Hillshade_Noon</th>\n",
       "      <th>Hillshade_3pm</th>\n",
       "      <th>Horizontal_Distance_To_Fire_Points</th>\n",
       "      <th>...</th>\n",
       "      <th>Soil_Type32</th>\n",
       "      <th>Soil_Type33</th>\n",
       "      <th>Soil_Type34</th>\n",
       "      <th>Soil_Type35</th>\n",
       "      <th>Soil_Type36</th>\n",
       "      <th>Soil_Type37</th>\n",
       "      <th>Soil_Type38</th>\n",
       "      <th>Soil_Type39</th>\n",
       "      <th>Soil_Type40</th>\n",
       "      <th>Cover_Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>318054</th>\n",
       "      <td>2517</td>\n",
       "      <td>271</td>\n",
       "      <td>12</td>\n",
       "      <td>272</td>\n",
       "      <td>84</td>\n",
       "      <td>484</td>\n",
       "      <td>189</td>\n",
       "      <td>244</td>\n",
       "      <td>193</td>\n",
       "      <td>162</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30504</th>\n",
       "      <td>2959</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>180</td>\n",
       "      <td>20</td>\n",
       "      <td>5960</td>\n",
       "      <td>217</td>\n",
       "      <td>236</td>\n",
       "      <td>156</td>\n",
       "      <td>3960</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349520</th>\n",
       "      <td>3093</td>\n",
       "      <td>54</td>\n",
       "      <td>19</td>\n",
       "      <td>42</td>\n",
       "      <td>-3</td>\n",
       "      <td>797</td>\n",
       "      <td>227</td>\n",
       "      <td>196</td>\n",
       "      <td>94</td>\n",
       "      <td>1318</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365645</th>\n",
       "      <td>2502</td>\n",
       "      <td>330</td>\n",
       "      <td>17</td>\n",
       "      <td>150</td>\n",
       "      <td>52</td>\n",
       "      <td>738</td>\n",
       "      <td>177</td>\n",
       "      <td>216</td>\n",
       "      <td>178</td>\n",
       "      <td>510</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131114</th>\n",
       "      <td>2962</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>95</td>\n",
       "      <td>7</td>\n",
       "      <td>4270</td>\n",
       "      <td>202</td>\n",
       "      <td>214</td>\n",
       "      <td>148</td>\n",
       "      <td>1999</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>385769</th>\n",
       "      <td>3181</td>\n",
       "      <td>119</td>\n",
       "      <td>5</td>\n",
       "      <td>170</td>\n",
       "      <td>-1</td>\n",
       "      <td>2416</td>\n",
       "      <td>228</td>\n",
       "      <td>235</td>\n",
       "      <td>141</td>\n",
       "      <td>999</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161626</th>\n",
       "      <td>2950</td>\n",
       "      <td>270</td>\n",
       "      <td>4</td>\n",
       "      <td>108</td>\n",
       "      <td>15</td>\n",
       "      <td>2053</td>\n",
       "      <td>210</td>\n",
       "      <td>241</td>\n",
       "      <td>170</td>\n",
       "      <td>2037</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394880</th>\n",
       "      <td>3051</td>\n",
       "      <td>155</td>\n",
       "      <td>22</td>\n",
       "      <td>390</td>\n",
       "      <td>70</td>\n",
       "      <td>1871</td>\n",
       "      <td>239</td>\n",
       "      <td>236</td>\n",
       "      <td>114</td>\n",
       "      <td>1510</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389492</th>\n",
       "      <td>3024</td>\n",
       "      <td>191</td>\n",
       "      <td>16</td>\n",
       "      <td>785</td>\n",
       "      <td>110</td>\n",
       "      <td>3000</td>\n",
       "      <td>218</td>\n",
       "      <td>251</td>\n",
       "      <td>162</td>\n",
       "      <td>1961</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>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52507</th>\n",
       "      <td>2714</td>\n",
       "      <td>349</td>\n",
       "      <td>18</td>\n",
       "      <td>67</td>\n",
       "      <td>20</td>\n",
       "      <td>1599</td>\n",
       "      <td>184</td>\n",
       "      <td>207</td>\n",
       "      <td>160</td>\n",
       "      <td>3234</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Elevation  Aspect  Slope  Horizontal_Distance_To_Hydrology  \\\n",
       "318054       2517     271     12                               272   \n",
       "30504        2959       0      1                               180   \n",
       "349520       3093      54     19                                42   \n",
       "365645       2502     330     17                               150   \n",
       "131114       2962       4     13                                95   \n",
       "385769       3181     119      5                               170   \n",
       "161626       2950     270      4                               108   \n",
       "394880       3051     155     22                               390   \n",
       "389492       3024     191     16                               785   \n",
       "52507        2714     349     18                                67   \n",
       "\n",
       "        Vertical_Distance_To_Hydrology  Horizontal_Distance_To_Roadways  \\\n",
       "318054                              84                              484   \n",
       "30504                               20                             5960   \n",
       "349520                              -3                              797   \n",
       "365645                              52                              738   \n",
       "131114                               7                             4270   \n",
       "385769                              -1                             2416   \n",
       "161626                              15                             2053   \n",
       "394880                              70                             1871   \n",
       "389492                             110                             3000   \n",
       "52507                               20                             1599   \n",
       "\n",
       "        Hillshade_9am  Hillshade_Noon  Hillshade_3pm  \\\n",
       "318054            189             244            193   \n",
       "30504             217             236            156   \n",
       "349520            227             196             94   \n",
       "365645            177             216            178   \n",
       "131114            202             214            148   \n",
       "385769            228             235            141   \n",
       "161626            210             241            170   \n",
       "394880            239             236            114   \n",
       "389492            218             251            162   \n",
       "52507             184             207            160   \n",
       "\n",
       "        Horizontal_Distance_To_Fire_Points  ...  Soil_Type32  Soil_Type33  \\\n",
       "318054                                 162  ...            0            0   \n",
       "30504                                 3960  ...            0            0   \n",
       "349520                                1318  ...            0            0   \n",
       "365645                                 510  ...            0            0   \n",
       "131114                                1999  ...            0            0   \n",
       "385769                                 999  ...            0            0   \n",
       "161626                                2037  ...            0            0   \n",
       "394880                                1510  ...            0            0   \n",
       "389492                                1961  ...            0            1   \n",
       "52507                                 3234  ...            0            0   \n",
       "\n",
       "        Soil_Type34  Soil_Type35  Soil_Type36  Soil_Type37  Soil_Type38  \\\n",
       "318054            0            0            0            0            0   \n",
       "30504             0            0            0            0            0   \n",
       "349520            0            0            0            0            0   \n",
       "365645            0            0            0            0            0   \n",
       "131114            0            0            0            0            0   \n",
       "385769            0            0            0            0            0   \n",
       "161626            0            0            0            0            0   \n",
       "394880            0            0            0            0            0   \n",
       "389492            0            0            0            0            0   \n",
       "52507             0            0            0            0            0   \n",
       "\n",
       "        Soil_Type39  Soil_Type40  Cover_Type  \n",
       "318054            0            0           2  \n",
       "30504             0            0           2  \n",
       "349520            0            0           1  \n",
       "365645            0            0           6  \n",
       "131114            0            0           2  \n",
       "385769            0            0           1  \n",
       "161626            0            0           2  \n",
       "394880            0            0           1  \n",
       "389492            0            0           2  \n",
       "52507             0            0           2  \n",
       "\n",
       "[10 rows x 55 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"covtype.csv\")\n",
    "data = data.sample(frac = 1)\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podział na podzbiory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-03-17T17:38:53.929532900Z",
     "start_time": "2024-03-17T17:38:51.607851900Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "forest_train, forest_test = train_test_split(data, test_size=0.2, random_state=1)\n",
    "forest_train, forest_val = train_test_split(forest_train, test_size=0.25, random_state=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Statystyki</h4>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wielkości zbiorów"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-03-17T17:38:58.202546800Z",
     "start_time": "2024-03-17T17:38:58.143643600Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wielkość zbioru: (581012, 55)\n",
      "wielkość zbioru treningowego: (348606, 55)\n",
      "wielkość zbioru testującego: (116203, 55)\n",
      "wielkość zbioru walidacyjnego: (116203, 55)\n"
     ]
    }
   ],
   "source": [
    "print(f'wielkość zbioru: {data.shape}')\n",
    "print(f'wielkość zbioru treningowego: {forest_train.shape}')\n",
    "print(f'wielkość zbioru testującego: {forest_test.shape}')\n",
    "print(f'wielkość zbioru walidacyjnego: {forest_val.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-03-17T17:39:01.338802400Z",
     "start_time": "2024-03-17T17:39:01.252677700Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 581012 entries, 0 to 581011\n",
      "Data columns (total 55 columns):\n",
      " #   Column                              Non-Null Count   Dtype\n",
      "---  ------                              --------------   -----\n",
      " 0   Elevation                           581012 non-null  int64\n",
      " 1   Aspect                              581012 non-null  int64\n",
      " 2   Slope                               581012 non-null  int64\n",
      " 3   Horizontal_Distance_To_Hydrology    581012 non-null  int64\n",
      " 4   Vertical_Distance_To_Hydrology      581012 non-null  int64\n",
      " 5   Horizontal_Distance_To_Roadways     581012 non-null  int64\n",
      " 6   Hillshade_9am                       581012 non-null  int64\n",
      " 7   Hillshade_Noon                      581012 non-null  int64\n",
      " 8   Hillshade_3pm                       581012 non-null  int64\n",
      " 9   Horizontal_Distance_To_Fire_Points  581012 non-null  int64\n",
      " 10  Wilderness_Area1                    581012 non-null  int64\n",
      " 11  Wilderness_Area2                    581012 non-null  int64\n",
      " 12  Wilderness_Area3                    581012 non-null  int64\n",
      " 13  Wilderness_Area4                    581012 non-null  int64\n",
      " 14  Soil_Type1                          581012 non-null  int64\n",
      " 15  Soil_Type2                          581012 non-null  int64\n",
      " 16  Soil_Type3                          581012 non-null  int64\n",
      " 17  Soil_Type4                          581012 non-null  int64\n",
      " 18  Soil_Type5                          581012 non-null  int64\n",
      " 19  Soil_Type6                          581012 non-null  int64\n",
      " 20  Soil_Type7                          581012 non-null  int64\n",
      " 21  Soil_Type8                          581012 non-null  int64\n",
      " 22  Soil_Type9                          581012 non-null  int64\n",
      " 23  Soil_Type10                         581012 non-null  int64\n",
      " 24  Soil_Type11                         581012 non-null  int64\n",
      " 25  Soil_Type12                         581012 non-null  int64\n",
      " 26  Soil_Type13                         581012 non-null  int64\n",
      " 27  Soil_Type14                         581012 non-null  int64\n",
      " 28  Soil_Type15                         581012 non-null  int64\n",
      " 29  Soil_Type16                         581012 non-null  int64\n",
      " 30  Soil_Type17                         581012 non-null  int64\n",
      " 31  Soil_Type18                         581012 non-null  int64\n",
      " 32  Soil_Type19                         581012 non-null  int64\n",
      " 33  Soil_Type20                         581012 non-null  int64\n",
      " 34  Soil_Type21                         581012 non-null  int64\n",
      " 35  Soil_Type22                         581012 non-null  int64\n",
      " 36  Soil_Type23                         581012 non-null  int64\n",
      " 37  Soil_Type24                         581012 non-null  int64\n",
      " 38  Soil_Type25                         581012 non-null  int64\n",
      " 39  Soil_Type26                         581012 non-null  int64\n",
      " 40  Soil_Type27                         581012 non-null  int64\n",
      " 41  Soil_Type28                         581012 non-null  int64\n",
      " 42  Soil_Type29                         581012 non-null  int64\n",
      " 43  Soil_Type30                         581012 non-null  int64\n",
      " 44  Soil_Type31                         581012 non-null  int64\n",
      " 45  Soil_Type32                         581012 non-null  int64\n",
      " 46  Soil_Type33                         581012 non-null  int64\n",
      " 47  Soil_Type34                         581012 non-null  int64\n",
      " 48  Soil_Type35                         581012 non-null  int64\n",
      " 49  Soil_Type36                         581012 non-null  int64\n",
      " 50  Soil_Type37                         581012 non-null  int64\n",
      " 51  Soil_Type38                         581012 non-null  int64\n",
      " 52  Soil_Type39                         581012 non-null  int64\n",
      " 53  Soil_Type40                         581012 non-null  int64\n",
      " 54  Cover_Type                          581012 non-null  int64\n",
      "dtypes: int64(55)\n",
      "memory usage: 243.8 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nachylenie\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-03-17T17:39:04.561664800Z",
     "start_time": "2024-03-17T17:39:04.530325200Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Średnie nachylenie: 14.103703537964792\n",
      "Maksymalne nachylenie: 66\n",
      "Minimalne nachylenie: 0\n"
     ]
    }
   ],
   "source": [
    "print(f'Średnie nachylenie: {data[\"Slope\"].mean()}')\n",
    "print(f'Maksymalne nachylenie: {data[\"Slope\"].max()}')\n",
    "print(f'Minimalne nachylenie: {data[\"Slope\"].min()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 3000x5000 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "features = data.loc[:,'Elevation':'Horizontal_Distance_To_Fire_Points']\n",
    "\n",
    "plt.figure(figsize=(30, 50))\n",
    "for i,col in enumerate(features.columns.values):\n",
    "    plt.subplot(5,2,i+1)\n",
    "    sns.boxplot(x=data['Cover_Type'], y=col, data=data)\n",
    "    plt.title(col, fontsize=20)\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normalizacja"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Elevation</th>\n",
       "      <th>Aspect</th>\n",
       "      <th>Slope</th>\n",
       "      <th>Horizontal_Distance_To_Hydrology</th>\n",
       "      <th>Vertical_Distance_To_Hydrology</th>\n",
       "      <th>Horizontal_Distance_To_Roadways</th>\n",
       "      <th>Hillshade_9am</th>\n",
       "      <th>Hillshade_Noon</th>\n",
       "      <th>Hillshade_3pm</th>\n",
       "      <th>Horizontal_Distance_To_Fire_Points</th>\n",
       "      <th>...</th>\n",
       "      <th>Soil_Type32</th>\n",
       "      <th>Soil_Type33</th>\n",
       "      <th>Soil_Type34</th>\n",
       "      <th>Soil_Type35</th>\n",
       "      <th>Soil_Type36</th>\n",
       "      <th>Soil_Type37</th>\n",
       "      <th>Soil_Type38</th>\n",
       "      <th>Soil_Type39</th>\n",
       "      <th>Soil_Type40</th>\n",
       "      <th>Cover_Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>318054</th>\n",
       "      <td>-1.579964</td>\n",
       "      <td>1.030645</td>\n",
       "      <td>-0.280934</td>\n",
       "      <td>0.012100</td>\n",
       "      <td>0.644670</td>\n",
       "      <td>-1.196821</td>\n",
       "      <td>-0.864631</td>\n",
       "      <td>1.046164</td>\n",
       "      <td>1.318678</td>\n",
       "      <td>-1.373130</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30504</th>\n",
       "      <td>-0.001305</td>\n",
       "      <td>-1.390866</td>\n",
       "      <td>-1.749905</td>\n",
       "      <td>-0.420741</td>\n",
       "      <td>-0.453191</td>\n",
       "      <td>2.315116</td>\n",
       "      <td>0.181321</td>\n",
       "      <td>0.641484</td>\n",
       "      <td>0.351977</td>\n",
       "      <td>1.495029</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349520</th>\n",
       "      <td>0.477293</td>\n",
       "      <td>-0.908351</td>\n",
       "      <td>0.653865</td>\n",
       "      <td>-1.070003</td>\n",
       "      <td>-0.847735</td>\n",
       "      <td>-0.996083</td>\n",
       "      <td>0.554876</td>\n",
       "      <td>-1.381919</td>\n",
       "      <td>-1.267901</td>\n",
       "      <td>-0.500147</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365645</th>\n",
       "      <td>-1.633538</td>\n",
       "      <td>1.557837</td>\n",
       "      <td>0.386780</td>\n",
       "      <td>-0.561885</td>\n",
       "      <td>0.095739</td>\n",
       "      <td>-1.033922</td>\n",
       "      <td>-1.312896</td>\n",
       "      <td>-0.370218</td>\n",
       "      <td>0.926772</td>\n",
       "      <td>-1.110329</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131114</th>\n",
       "      <td>0.009410</td>\n",
       "      <td>-1.355124</td>\n",
       "      <td>-0.147392</td>\n",
       "      <td>-0.820649</td>\n",
       "      <td>-0.676194</td>\n",
       "      <td>1.231264</td>\n",
       "      <td>-0.379010</td>\n",
       "      <td>-0.471388</td>\n",
       "      <td>0.142960</td>\n",
       "      <td>0.014128</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>385769</th>\n",
       "      <td>0.791596</td>\n",
       "      <td>-0.327546</td>\n",
       "      <td>-1.215734</td>\n",
       "      <td>-0.467789</td>\n",
       "      <td>-0.813427</td>\n",
       "      <td>0.042234</td>\n",
       "      <td>0.592231</td>\n",
       "      <td>0.590899</td>\n",
       "      <td>-0.039929</td>\n",
       "      <td>-0.741048</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161626</th>\n",
       "      <td>-0.033449</td>\n",
       "      <td>1.021709</td>\n",
       "      <td>-1.349277</td>\n",
       "      <td>-0.759486</td>\n",
       "      <td>-0.538961</td>\n",
       "      <td>-0.190570</td>\n",
       "      <td>-0.080167</td>\n",
       "      <td>0.894409</td>\n",
       "      <td>0.717756</td>\n",
       "      <td>0.042825</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394880</th>\n",
       "      <td>0.327285</td>\n",
       "      <td>-0.005869</td>\n",
       "      <td>1.054494</td>\n",
       "      <td>0.567265</td>\n",
       "      <td>0.404513</td>\n",
       "      <td>-0.307292</td>\n",
       "      <td>1.003141</td>\n",
       "      <td>0.641484</td>\n",
       "      <td>-0.745360</td>\n",
       "      <td>-0.355153</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389492</th>\n",
       "      <td>0.230851</td>\n",
       "      <td>0.315808</td>\n",
       "      <td>0.253237</td>\n",
       "      <td>2.425659</td>\n",
       "      <td>1.090676</td>\n",
       "      <td>0.416772</td>\n",
       "      <td>0.218677</td>\n",
       "      <td>1.400260</td>\n",
       "      <td>0.508739</td>\n",
       "      <td>-0.014568</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>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52507</th>\n",
       "      <td>-0.876353</td>\n",
       "      <td>1.727611</td>\n",
       "      <td>0.520322</td>\n",
       "      <td>-0.952383</td>\n",
       "      <td>-0.453191</td>\n",
       "      <td>-0.481735</td>\n",
       "      <td>-1.051408</td>\n",
       "      <td>-0.825483</td>\n",
       "      <td>0.456485</td>\n",
       "      <td>0.946771</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Elevation    Aspect     Slope  Horizontal_Distance_To_Hydrology  \\\n",
       "318054  -1.579964  1.030645 -0.280934                          0.012100   \n",
       "30504   -0.001305 -1.390866 -1.749905                         -0.420741   \n",
       "349520   0.477293 -0.908351  0.653865                         -1.070003   \n",
       "365645  -1.633538  1.557837  0.386780                         -0.561885   \n",
       "131114   0.009410 -1.355124 -0.147392                         -0.820649   \n",
       "385769   0.791596 -0.327546 -1.215734                         -0.467789   \n",
       "161626  -0.033449  1.021709 -1.349277                         -0.759486   \n",
       "394880   0.327285 -0.005869  1.054494                          0.567265   \n",
       "389492   0.230851  0.315808  0.253237                          2.425659   \n",
       "52507   -0.876353  1.727611  0.520322                         -0.952383   \n",
       "\n",
       "        Vertical_Distance_To_Hydrology  Horizontal_Distance_To_Roadways  \\\n",
       "318054                        0.644670                        -1.196821   \n",
       "30504                        -0.453191                         2.315116   \n",
       "349520                       -0.847735                        -0.996083   \n",
       "365645                        0.095739                        -1.033922   \n",
       "131114                       -0.676194                         1.231264   \n",
       "385769                       -0.813427                         0.042234   \n",
       "161626                       -0.538961                        -0.190570   \n",
       "394880                        0.404513                        -0.307292   \n",
       "389492                        1.090676                         0.416772   \n",
       "52507                        -0.453191                        -0.481735   \n",
       "\n",
       "        Hillshade_9am  Hillshade_Noon  Hillshade_3pm  \\\n",
       "318054      -0.864631        1.046164       1.318678   \n",
       "30504        0.181321        0.641484       0.351977   \n",
       "349520       0.554876       -1.381919      -1.267901   \n",
       "365645      -1.312896       -0.370218       0.926772   \n",
       "131114      -0.379010       -0.471388       0.142960   \n",
       "385769       0.592231        0.590899      -0.039929   \n",
       "161626      -0.080167        0.894409       0.717756   \n",
       "394880       1.003141        0.641484      -0.745360   \n",
       "389492       0.218677        1.400260       0.508739   \n",
       "52507       -1.051408       -0.825483       0.456485   \n",
       "\n",
       "        Horizontal_Distance_To_Fire_Points  ...  Soil_Type32  Soil_Type33  \\\n",
       "318054                           -1.373130  ...            0            0   \n",
       "30504                             1.495029  ...            0            0   \n",
       "349520                           -0.500147  ...            0            0   \n",
       "365645                           -1.110329  ...            0            0   \n",
       "131114                            0.014128  ...            0            0   \n",
       "385769                           -0.741048  ...            0            0   \n",
       "161626                            0.042825  ...            0            0   \n",
       "394880                           -0.355153  ...            0            0   \n",
       "389492                           -0.014568  ...            0            1   \n",
       "52507                             0.946771  ...            0            0   \n",
       "\n",
       "        Soil_Type34  Soil_Type35  Soil_Type36  Soil_Type37  Soil_Type38  \\\n",
       "318054            0            0            0            0            0   \n",
       "30504             0            0            0            0            0   \n",
       "349520            0            0            0            0            0   \n",
       "365645            0            0            0            0            0   \n",
       "131114            0            0            0            0            0   \n",
       "385769            0            0            0            0            0   \n",
       "161626            0            0            0            0            0   \n",
       "394880            0            0            0            0            0   \n",
       "389492            0            0            0            0            0   \n",
       "52507             0            0            0            0            0   \n",
       "\n",
       "        Soil_Type39  Soil_Type40  Cover_Type  \n",
       "318054            0            0           2  \n",
       "30504             0            0           2  \n",
       "349520            0            0           1  \n",
       "365645            0            0           6  \n",
       "131114            0            0           2  \n",
       "385769            0            0           1  \n",
       "161626            0            0           2  \n",
       "394880            0            0           1  \n",
       "389492            0            0           2  \n",
       "52507             0            0           2  \n",
       "\n",
       "[10 rows x 55 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "\n",
    "columns_to_normalize = data.columns[~data.columns.str.startswith('Soil_Type')]\n",
    "columns_to_normalize = columns_to_normalize.to_list()\n",
    "columns_to_normalize.remove('Cover_Type')\n",
    "data[columns_to_normalize] = scaler.fit_transform(data[columns_to_normalize])\n",
    "\n",
    "data.head(10)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}