shap_global.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import xgboost\n",
    "import shap\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def xlsx_to_dict(filename: str) -> dict:\n",
    "    df = pd.read_table(filename)\n",
    "    return dict(zip(df.Tagname.str.lower(), df.opis))\n",
    "\n",
    "tag_dict = {\n",
    "    \"min\": \"minimum\",\n",
    "    \"absolute_sum_of_changes\": \"wartość bezwględna zmian\",\n",
    "    \"max\": \"maksimum\",\n",
    "    \"mean\": \"średnia\",\n",
    "    \"skew\": \"skośność\"\n",
    "}\n",
    "\n",
    "def parse_columns(df: pd.DataFrame) -> pd.DataFrame:\n",
    "    new_cols = {}\n",
    "    tags = []\n",
    "    for col in df.columns:\n",
    "        new_cols[col] = col.split(\"_\", 1)[0]\n",
    "        tags.append(col.split(\"_\", 1)[1])\n",
    "        \n",
    "    tags = [tag_dict[tag] for tag in tags]\n",
    "    df = df.rename(columns=new_cols)\n",
    "    tagnames = xlsx_to_dict('../resources/nametags.txt')\n",
    "    df = df.rename(columns=tagnames)\n",
    "    df.columns = [col + \" \" + tags[i] for i, col in enumerate(df.columns)]\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>TEMP.14 POD 2 WARSTWĄ WYMURÓWKI minimum</th>\n",
       "      <th>REG PYL ZWROT LIW4 minimum</th>\n",
       "      <th>REG PYL ZWROT LIW4 wartość bezwględna zmian</th>\n",
       "      <th>WENT.  RF02 ODCZ_ZAD OBROTÓW minimum</th>\n",
       "      <th>TEMP.17 POD 2 WARSTWĄ WYMURÓWKI minimum</th>\n",
       "      <th>WODA POWROTNA KOLEKTORA KZ12 minimum</th>\n",
       "      <th>WODA POWROTNA KOLEKTORA KZ12 maksimum</th>\n",
       "      <th>WODA CHŁODZĄCA DO KOLEKTOR KZ7 maksimum</th>\n",
       "      <th>WODA CHŁODZĄCA DO KOLEKTOR KZ7 średnia</th>\n",
       "      <th>TEMP.  NA KOL.. KAN.1-34 minimum</th>\n",
       "      <th>TEMP.1 POD 2 WARSTWĄ WYMURÓWKI minimum</th>\n",
       "      <th>TEMP22 POD 2 WARSTWĄ WYMURÓWKI minimum</th>\n",
       "      <th>SUMARYCZNA MOC CIEPLNA ODEBRANA - CAŁKOWITA minimum</th>\n",
       "      <th>SUMARYCZNA MOC CIEPLNA ODEBRANA - CAŁKOWITA maksimum</th>\n",
       "      <th>SUMARYCZNA MOC CIEPLNA ODEBRANA - CAŁKOWITA wartość bezwględna zmian</th>\n",
       "      <th>REG NADAWY KONCENTRATU LIW1 skośność</th>\n",
       "      <th>REG NADAWY KONCENTRATU LIW1 wartość bezwględna zmian</th>\n",
       "      <th>WODA CHŁODZĄCA DO KOLEKTOR KZ15 minimum</th>\n",
       "      <th>WODA POWROTNA KOLEKTORA KZ13 minimum</th>\n",
       "      <th>WODA CHŁODZĄCA DO KOLEKTOR KZ13 minimum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>449.890089</td>\n",
       "      <td>19.854799</td>\n",
       "      <td>4.720509</td>\n",
       "      <td>92.045435</td>\n",
       "      <td>427.607628</td>\n",
       "      <td>31.165436</td>\n",
       "      <td>31.595133</td>\n",
       "      <td>109.861116</td>\n",
       "      <td>108.496568</td>\n",
       "      <td>18.612499</td>\n",
       "      <td>385.313782</td>\n",
       "      <td>466.102266</td>\n",
       "      <td>15.074689</td>\n",
       "      <td>15.199544</td>\n",
       "      <td>0.325263</td>\n",
       "      <td>0.473234</td>\n",
       "      <td>14.764852</td>\n",
       "      <td>108.761308</td>\n",
       "      <td>30.874105</td>\n",
       "      <td>142.985941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>449.864485</td>\n",
       "      <td>19.895281</td>\n",
       "      <td>3.925764</td>\n",
       "      <td>92.068457</td>\n",
       "      <td>427.556460</td>\n",
       "      <td>31.391146</td>\n",
       "      <td>31.474224</td>\n",
       "      <td>110.046307</td>\n",
       "      <td>109.715521</td>\n",
       "      <td>18.075895</td>\n",
       "      <td>385.152091</td>\n",
       "      <td>466.051088</td>\n",
       "      <td>14.610781</td>\n",
       "      <td>14.836278</td>\n",
       "      <td>0.347226</td>\n",
       "      <td>0.600669</td>\n",
       "      <td>15.820964</td>\n",
       "      <td>108.938079</td>\n",
       "      <td>31.223456</td>\n",
       "      <td>143.162819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>449.804996</td>\n",
       "      <td>18.327651</td>\n",
       "      <td>9.594162</td>\n",
       "      <td>92.074051</td>\n",
       "      <td>427.505282</td>\n",
       "      <td>31.565242</td>\n",
       "      <td>31.638242</td>\n",
       "      <td>109.937796</td>\n",
       "      <td>109.435776</td>\n",
       "      <td>17.680137</td>\n",
       "      <td>385.100898</td>\n",
       "      <td>465.999910</td>\n",
       "      <td>14.240034</td>\n",
       "      <td>14.509810</td>\n",
       "      <td>0.365595</td>\n",
       "      <td>0.629190</td>\n",
       "      <td>13.578498</td>\n",
       "      <td>108.801151</td>\n",
       "      <td>31.377056</td>\n",
       "      <td>143.046576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>449.753833</td>\n",
       "      <td>20.879188</td>\n",
       "      <td>4.570232</td>\n",
       "      <td>92.072773</td>\n",
       "      <td>427.484597</td>\n",
       "      <td>31.452425</td>\n",
       "      <td>31.609812</td>\n",
       "      <td>109.915863</td>\n",
       "      <td>109.200794</td>\n",
       "      <td>17.494467</td>\n",
       "      <td>385.070390</td>\n",
       "      <td>465.974322</td>\n",
       "      <td>13.879839</td>\n",
       "      <td>14.225614</td>\n",
       "      <td>0.428852</td>\n",
       "      <td>0.848864</td>\n",
       "      <td>17.690807</td>\n",
       "      <td>108.721026</td>\n",
       "      <td>31.227293</td>\n",
       "      <td>142.978945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>449.702670</td>\n",
       "      <td>22.658180</td>\n",
       "      <td>3.476629</td>\n",
       "      <td>92.071197</td>\n",
       "      <td>427.471803</td>\n",
       "      <td>31.320126</td>\n",
       "      <td>31.616741</td>\n",
       "      <td>110.105791</td>\n",
       "      <td>109.723850</td>\n",
       "      <td>17.473172</td>\n",
       "      <td>385.031984</td>\n",
       "      <td>465.948733</td>\n",
       "      <td>13.715085</td>\n",
       "      <td>13.885071</td>\n",
       "      <td>0.334901</td>\n",
       "      <td>0.791855</td>\n",
       "      <td>16.012973</td>\n",
       "      <td>108.796355</td>\n",
       "      <td>31.070268</td>\n",
       "      <td>143.018654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11378</th>\n",
       "      <td>455.368219</td>\n",
       "      <td>30.964217</td>\n",
       "      <td>9.275709</td>\n",
       "      <td>98.125112</td>\n",
       "      <td>411.819196</td>\n",
       "      <td>30.765001</td>\n",
       "      <td>31.059998</td>\n",
       "      <td>102.637480</td>\n",
       "      <td>102.435786</td>\n",
       "      <td>9.675762</td>\n",
       "      <td>376.864078</td>\n",
       "      <td>465.785777</td>\n",
       "      <td>14.707773</td>\n",
       "      <td>15.888954</td>\n",
       "      <td>1.319954</td>\n",
       "      <td>0.687504</td>\n",
       "      <td>14.755280</td>\n",
       "      <td>97.785962</td>\n",
       "      <td>28.319121</td>\n",
       "      <td>138.487628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11379</th>\n",
       "      <td>455.185923</td>\n",
       "      <td>30.082811</td>\n",
       "      <td>8.223297</td>\n",
       "      <td>98.087563</td>\n",
       "      <td>411.713628</td>\n",
       "      <td>30.543753</td>\n",
       "      <td>31.071934</td>\n",
       "      <td>102.894684</td>\n",
       "      <td>102.503158</td>\n",
       "      <td>9.548869</td>\n",
       "      <td>376.776638</td>\n",
       "      <td>465.662067</td>\n",
       "      <td>15.967954</td>\n",
       "      <td>18.655348</td>\n",
       "      <td>2.687394</td>\n",
       "      <td>0.425850</td>\n",
       "      <td>13.151903</td>\n",
       "      <td>97.736368</td>\n",
       "      <td>28.324564</td>\n",
       "      <td>138.490869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11380</th>\n",
       "      <td>455.057994</td>\n",
       "      <td>27.177329</td>\n",
       "      <td>7.758613</td>\n",
       "      <td>98.125081</td>\n",
       "      <td>411.662481</td>\n",
       "      <td>30.029215</td>\n",
       "      <td>30.468298</td>\n",
       "      <td>102.593705</td>\n",
       "      <td>102.013917</td>\n",
       "      <td>9.286221</td>\n",
       "      <td>376.725460</td>\n",
       "      <td>465.610858</td>\n",
       "      <td>15.494876</td>\n",
       "      <td>16.527723</td>\n",
       "      <td>1.426691</td>\n",
       "      <td>0.745125</td>\n",
       "      <td>18.561618</td>\n",
       "      <td>97.713980</td>\n",
       "      <td>28.457689</td>\n",
       "      <td>138.430676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11381</th>\n",
       "      <td>454.930055</td>\n",
       "      <td>27.140972</td>\n",
       "      <td>6.988503</td>\n",
       "      <td>98.080254</td>\n",
       "      <td>411.626677</td>\n",
       "      <td>30.777789</td>\n",
       "      <td>31.202382</td>\n",
       "      <td>101.708210</td>\n",
       "      <td>101.529788</td>\n",
       "      <td>9.092198</td>\n",
       "      <td>376.689209</td>\n",
       "      <td>465.544726</td>\n",
       "      <td>16.267929</td>\n",
       "      <td>17.733470</td>\n",
       "      <td>2.871934</td>\n",
       "      <td>0.772133</td>\n",
       "      <td>18.900025</td>\n",
       "      <td>97.756562</td>\n",
       "      <td>28.455235</td>\n",
       "      <td>138.453558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11382</th>\n",
       "      <td>454.804224</td>\n",
       "      <td>27.340249</td>\n",
       "      <td>9.639408</td>\n",
       "      <td>98.119783</td>\n",
       "      <td>411.667599</td>\n",
       "      <td>30.137065</td>\n",
       "      <td>30.796547</td>\n",
       "      <td>101.251020</td>\n",
       "      <td>101.151966</td>\n",
       "      <td>9.174721</td>\n",
       "      <td>376.689209</td>\n",
       "      <td>465.444058</td>\n",
       "      <td>17.847946</td>\n",
       "      <td>19.967758</td>\n",
       "      <td>3.253821</td>\n",
       "      <td>0.326682</td>\n",
       "      <td>11.367266</td>\n",
       "      <td>97.684348</td>\n",
       "      <td>28.521002</td>\n",
       "      <td>138.377210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11383 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       TEMP.14 POD 2 WARSTWĄ WYMURÓWKI minimum  REG PYL ZWROT LIW4 minimum  \\\n",
       "0                                   449.890089                   19.854799   \n",
       "1                                   449.864485                   19.895281   \n",
       "2                                   449.804996                   18.327651   \n",
       "3                                   449.753833                   20.879188   \n",
       "4                                   449.702670                   22.658180   \n",
       "...                                        ...                         ...   \n",
       "11378                               455.368219                   30.964217   \n",
       "11379                               455.185923                   30.082811   \n",
       "11380                               455.057994                   27.177329   \n",
       "11381                               454.930055                   27.140972   \n",
       "11382                               454.804224                   27.340249   \n",
       "\n",
       "       REG PYL ZWROT LIW4 wartość bezwględna zmian  \\\n",
       "0                                         4.720509   \n",
       "1                                         3.925764   \n",
       "2                                         9.594162   \n",
       "3                                         4.570232   \n",
       "4                                         3.476629   \n",
       "...                                            ...   \n",
       "11378                                     9.275709   \n",
       "11379                                     8.223297   \n",
       "11380                                     7.758613   \n",
       "11381                                     6.988503   \n",
       "11382                                     9.639408   \n",
       "\n",
       "       WENT.  RF02 ODCZ_ZAD OBROTÓW minimum  \\\n",
       "0                                 92.045435   \n",
       "1                                 92.068457   \n",
       "2                                 92.074051   \n",
       "3                                 92.072773   \n",
       "4                                 92.071197   \n",
       "...                                     ...   \n",
       "11378                             98.125112   \n",
       "11379                             98.087563   \n",
       "11380                             98.125081   \n",
       "11381                             98.080254   \n",
       "11382                             98.119783   \n",
       "\n",
       "       TEMP.17 POD 2 WARSTWĄ WYMURÓWKI minimum  \\\n",
       "0                                   427.607628   \n",
       "1                                   427.556460   \n",
       "2                                   427.505282   \n",
       "3                                   427.484597   \n",
       "4                                   427.471803   \n",
       "...                                        ...   \n",
       "11378                               411.819196   \n",
       "11379                               411.713628   \n",
       "11380                               411.662481   \n",
       "11381                               411.626677   \n",
       "11382                               411.667599   \n",
       "\n",
       "       WODA POWROTNA KOLEKTORA KZ12 minimum  \\\n",
       "0                                 31.165436   \n",
       "1                                 31.391146   \n",
       "2                                 31.565242   \n",
       "3                                 31.452425   \n",
       "4                                 31.320126   \n",
       "...                                     ...   \n",
       "11378                             30.765001   \n",
       "11379                             30.543753   \n",
       "11380                             30.029215   \n",
       "11381                             30.777789   \n",
       "11382                             30.137065   \n",
       "\n",
       "       WODA POWROTNA KOLEKTORA KZ12 maksimum  \\\n",
       "0                                  31.595133   \n",
       "1                                  31.474224   \n",
       "2                                  31.638242   \n",
       "3                                  31.609812   \n",
       "4                                  31.616741   \n",
       "...                                      ...   \n",
       "11378                              31.059998   \n",
       "11379                              31.071934   \n",
       "11380                              30.468298   \n",
       "11381                              31.202382   \n",
       "11382                              30.796547   \n",
       "\n",
       "       WODA CHŁODZĄCA DO KOLEKTOR KZ7 maksimum  \\\n",
       "0                                   109.861116   \n",
       "1                                   110.046307   \n",
       "2                                   109.937796   \n",
       "3                                   109.915863   \n",
       "4                                   110.105791   \n",
       "...                                        ...   \n",
       "11378                               102.637480   \n",
       "11379                               102.894684   \n",
       "11380                               102.593705   \n",
       "11381                               101.708210   \n",
       "11382                               101.251020   \n",
       "\n",
       "       WODA CHŁODZĄCA DO KOLEKTOR KZ7 średnia  \\\n",
       "0                                  108.496568   \n",
       "1                                  109.715521   \n",
       "2                                  109.435776   \n",
       "3                                  109.200794   \n",
       "4                                  109.723850   \n",
       "...                                       ...   \n",
       "11378                              102.435786   \n",
       "11379                              102.503158   \n",
       "11380                              102.013917   \n",
       "11381                              101.529788   \n",
       "11382                              101.151966   \n",
       "\n",
       "       TEMP.  NA KOL.. KAN.1-34 minimum  \\\n",
       "0                             18.612499   \n",
       "1                             18.075895   \n",
       "2                             17.680137   \n",
       "3                             17.494467   \n",
       "4                             17.473172   \n",
       "...                                 ...   \n",
       "11378                          9.675762   \n",
       "11379                          9.548869   \n",
       "11380                          9.286221   \n",
       "11381                          9.092198   \n",
       "11382                          9.174721   \n",
       "\n",
       "       TEMP.1 POD 2 WARSTWĄ WYMURÓWKI minimum  \\\n",
       "0                                  385.313782   \n",
       "1                                  385.152091   \n",
       "2                                  385.100898   \n",
       "3                                  385.070390   \n",
       "4                                  385.031984   \n",
       "...                                       ...   \n",
       "11378                              376.864078   \n",
       "11379                              376.776638   \n",
       "11380                              376.725460   \n",
       "11381                              376.689209   \n",
       "11382                              376.689209   \n",
       "\n",
       "       TEMP22 POD 2 WARSTWĄ WYMURÓWKI minimum  \\\n",
       "0                                  466.102266   \n",
       "1                                  466.051088   \n",
       "2                                  465.999910   \n",
       "3                                  465.974322   \n",
       "4                                  465.948733   \n",
       "...                                       ...   \n",
       "11378                              465.785777   \n",
       "11379                              465.662067   \n",
       "11380                              465.610858   \n",
       "11381                              465.544726   \n",
       "11382                              465.444058   \n",
       "\n",
       "       SUMARYCZNA MOC CIEPLNA ODEBRANA - CAŁKOWITA minimum  \\\n",
       "0                                              15.074689     \n",
       "1                                              14.610781     \n",
       "2                                              14.240034     \n",
       "3                                              13.879839     \n",
       "4                                              13.715085     \n",
       "...                                                  ...     \n",
       "11378                                          14.707773     \n",
       "11379                                          15.967954     \n",
       "11380                                          15.494876     \n",
       "11381                                          16.267929     \n",
       "11382                                          17.847946     \n",
       "\n",
       "       SUMARYCZNA MOC CIEPLNA ODEBRANA - CAŁKOWITA maksimum  \\\n",
       "0                                              15.199544      \n",
       "1                                              14.836278      \n",
       "2                                              14.509810      \n",
       "3                                              14.225614      \n",
       "4                                              13.885071      \n",
       "...                                                  ...      \n",
       "11378                                          15.888954      \n",
       "11379                                          18.655348      \n",
       "11380                                          16.527723      \n",
       "11381                                          17.733470      \n",
       "11382                                          19.967758      \n",
       "\n",
       "       SUMARYCZNA MOC CIEPLNA ODEBRANA - CAŁKOWITA wartość bezwględna zmian  \\\n",
       "0                                               0.325263                      \n",
       "1                                               0.347226                      \n",
       "2                                               0.365595                      \n",
       "3                                               0.428852                      \n",
       "4                                               0.334901                      \n",
       "...                                                  ...                      \n",
       "11378                                           1.319954                      \n",
       "11379                                           2.687394                      \n",
       "11380                                           1.426691                      \n",
       "11381                                           2.871934                      \n",
       "11382                                           3.253821                      \n",
       "\n",
       "       REG NADAWY KONCENTRATU LIW1 skośność  \\\n",
       "0                                  0.473234   \n",
       "1                                  0.600669   \n",
       "2                                  0.629190   \n",
       "3                                  0.848864   \n",
       "4                                  0.791855   \n",
       "...                                     ...   \n",
       "11378                              0.687504   \n",
       "11379                              0.425850   \n",
       "11380                              0.745125   \n",
       "11381                              0.772133   \n",
       "11382                              0.326682   \n",
       "\n",
       "       REG NADAWY KONCENTRATU LIW1 wartość bezwględna zmian  \\\n",
       "0                                              14.764852      \n",
       "1                                              15.820964      \n",
       "2                                              13.578498      \n",
       "3                                              17.690807      \n",
       "4                                              16.012973      \n",
       "...                                                  ...      \n",
       "11378                                          14.755280      \n",
       "11379                                          13.151903      \n",
       "11380                                          18.561618      \n",
       "11381                                          18.900025      \n",
       "11382                                          11.367266      \n",
       "\n",
       "       WODA CHŁODZĄCA DO KOLEKTOR KZ15 minimum  \\\n",
       "0                                   108.761308   \n",
       "1                                   108.938079   \n",
       "2                                   108.801151   \n",
       "3                                   108.721026   \n",
       "4                                   108.796355   \n",
       "...                                        ...   \n",
       "11378                                97.785962   \n",
       "11379                                97.736368   \n",
       "11380                                97.713980   \n",
       "11381                                97.756562   \n",
       "11382                                97.684348   \n",
       "\n",
       "       WODA POWROTNA KOLEKTORA KZ13 minimum  \\\n",
       "0                                 30.874105   \n",
       "1                                 31.223456   \n",
       "2                                 31.377056   \n",
       "3                                 31.227293   \n",
       "4                                 31.070268   \n",
       "...                                     ...   \n",
       "11378                             28.319121   \n",
       "11379                             28.324564   \n",
       "11380                             28.457689   \n",
       "11381                             28.455235   \n",
       "11382                             28.521002   \n",
       "\n",
       "       WODA CHŁODZĄCA DO KOLEKTOR KZ13 minimum  \n",
       "0                                   142.985941  \n",
       "1                                   143.162819  \n",
       "2                                   143.046576  \n",
       "3                                   142.978945  \n",
       "4                                   143.018654  \n",
       "...                                        ...  \n",
       "11378                               138.487628  \n",
       "11379                               138.490869  \n",
       "11380                               138.430676  \n",
       "11381                               138.453558  \n",
       "11382                               138.377210  \n",
       "\n",
       "[11383 rows x 20 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"../dataset_30_small.csv\")\n",
    "y = df[\"temp\"]\n",
    "X = df.drop([\"czas\", \"temp\"], axis=1)\n",
    "X = parse_columns(X)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ntree_limit is deprecated, use `iteration_range` or model slicing instead.\n"
     ]
    }
   ],
   "source": [
    "model = pickle.load(open(\"../static/model.pkl\", 'rb'))\n",
    "explainer = shap.Explainer(model)\n",
    "shap_values = explainer(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       ".values =\n",
       "array([[-0.12362036, -1.0394472 ,  0.16710311, ...,  0.73273027,\n",
       "        -0.14399731, -0.4793113 ],\n",
       "       [-0.0646354 , -1.028995  , -1.0598586 , ...,  0.5963412 ,\n",
       "        -0.29103288, -0.20686337],\n",
       "       [-0.35879135,  0.05070164,  0.37786192, ...,  0.76157856,\n",
       "         1.1476983 , -0.1509753 ],\n",
       "       ...,\n",
       "       [ 0.08276886,  0.29778317,  0.84766376, ..., -2.3537512 ,\n",
       "        -0.5610177 ,  0.8786096 ],\n",
       "       [ 0.2597538 ,  0.4396276 ,  0.43107152, ..., -1.8155113 ,\n",
       "         0.91049725,  1.1526583 ],\n",
       "       [ 0.25179708,  0.6131541 ,  0.6161329 , ..., -3.1135776 ,\n",
       "         0.3224214 ,  1.4633043 ]], dtype=float32)\n",
       "\n",
       ".base_values =\n",
       "array([1303.3889, 1303.3889, 1303.3889, ..., 1303.3889, 1303.3889,\n",
       "       1303.3889], dtype=float32)\n",
       "\n",
       ".data =\n",
       "array([[449.89008942,  19.85479933,   4.72050889, ..., 108.76130753,\n",
       "         30.87410523, 142.98594106],\n",
       "       [449.86448517,  19.895281  ,   3.92576418, ..., 108.93807945,\n",
       "         31.22345603, 143.16281865],\n",
       "       [449.80499573,  18.32765115,   9.59416202, ..., 108.80115064,\n",
       "         31.3770559 , 143.04657644],\n",
       "       ...,\n",
       "       [455.05799357,  27.17732938,   7.75861301, ...,  97.7139801 ,\n",
       "         28.45768878, 138.43067627],\n",
       "       [454.93005473,  27.14097214,   6.98850285, ...,  97.75656153,\n",
       "         28.45523526, 138.4535581 ],\n",
       "       [454.80422414,  27.34024897,   9.63940814, ...,  97.68434842,\n",
       "         28.52100245, 138.37720998]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shap_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x468 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.plots.bar(shap_values)"
   ]
  }
 ],
 "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",
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