{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.float_format = '{:.2f}'.format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\micha\\AppData\\Local\\Temp\\ipykernel_26160\\3760256257.py:1: DtypeWarning: Columns (25) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df_dofinansowanie = pd.read_csv(\n"
     ]
    }
   ],
   "source": [
    "df_dofinansowanie = pd.read_csv(\n",
    "    'umowy_pelna_lista_krajowe.csv',\n",
    "    encoding='ISO-8859-2',\n",
    "    converters={'TERYT pe?ny': str},\n",
    "    thousands=',')\n",
    "\n",
    "df_dofinansowanie = df_dofinansowanie.loc[df_dofinansowanie['TERYT pe?ny'] != ''].reset_index(drop=True)\n",
    "\n",
    "df_dofinansowanie['Dofinansowanie UE (PLN)'] = \\\n",
    "    df_dofinansowanie['Dofinansowanie UE (PLN)'].apply(pd.to_numeric)\n",
    "\n",
    "df_dofinansowanie['Data rozpocz?cia realizacji'] = pd.to_datetime(df_dofinansowanie['Data rozpocz?cia realizacji'])\n",
    "df_dofinansowanie['Rok rozpocz?cia realizacji'] = df_dofinansowanie['Data rozpocz?cia realizacji'].dt.year\n",
    "\n",
    "df_dofinansowanie['Data podpisania umowy pierwotnej'] = pd.to_datetime(df_dofinansowanie['Data podpisania umowy pierwotnej'])\n",
    "df_dofinansowanie['Rok podpisania umowy pierwotnej'] = df_dofinansowanie['Data podpisania umowy pierwotnej'].dt.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dofinansowanie_agg = df_dofinansowanie \\\n",
    "    .groupby(['TERYT pe?ny', 'Rok rozpocz?cia realizacji'])['Dofinansowanie UE (PLN)'].sum().reset_index()\n",
    "df_dofinansowanie_agg = df_dofinansowanie_agg \\\n",
    "    .rename(columns={'TERYT pe?ny': 'Kod', 'Rok rozpocz?cia realizacji': 'Rok', 'Dofinansowanie UE (PLN)': 'Suma'})\n",
    "df_dofinansowanie_agg = df_dofinansowanie_agg \\\n",
    "    .loc[df_dofinansowanie_agg['Kod'].str.len() == 7].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_podz = pd.read_csv(\n",
    "    'PODZ_1410_CREL.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str})\n",
    "df_podz = df_podz[['Kod', 'Rok', 'Wartosc']]\n",
    "df_podz = df_podz.loc[df_podz['Kod'].str.endswith(('1', '2', '3'))]\n",
    "df_podz = df_podz.dropna()\n",
    "df_podz = df_podz.rename(columns={\n",
    "    'Wartosc': 'Powierzchnia'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wyna = pd.read_csv(\n",
    "    'WYNA_2497_CREL.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str},\n",
    "    decimal=',')\n",
    "df_wyna = df_wyna[['Kod', 'Wyszczególnienie', 'Rok', 'Wartosc']]\n",
    "df_wyna = df_wyna.dropna()\n",
    "df_wyna = df_wyna.pivot_table(index=['Kod', 'Rok'], columns='Wyszczególnienie', values='Wartosc').reset_index()\n",
    "df_wyna = df_wyna.rename(columns={\n",
    "    'ogółem': 'Wynagrodzenie_ogolem',\n",
    "    'przeciętne miesięczne wynagrodzenia brutto w relacji do średniej krajowej (Polska=100)': 'Wynagrodzenie_w_relacji_do_sredniej'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\micha\\AppData\\Local\\Temp\\ipykernel_26160\\3644708252.py:1: DtypeWarning: Columns (7) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df_fina_1 = pd.read_csv(\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\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>Rodzaje dochodów</th>\n",
       "      <th>Kod</th>\n",
       "      <th>Rok</th>\n",
       "      <th>Dochody_podatek_lesny</th>\n",
       "      <th>Dochody_podatek_PCC</th>\n",
       "      <th>Dochody_podatek_...</th>\n",
       "      <th>Dochody_podatek_od_nieruchomosci</th>\n",
       "      <th>Dochody_podatek_od_spadkow</th>\n",
       "      <th>Dochody_podatek_od_srodkow_transportowych</th>\n",
       "      <th>Dochody_podatek_rolny</th>\n",
       "      <th>Dochody_podatek_odrebne_ustawy</th>\n",
       "      <th>Dochody_razem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>549608.00</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>1</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>609855.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13667398.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700134.00</td>\n",
       "      <td>26634.00</td>\n",
       "      <td>15438121.00</td>\n",
       "      <td>43417443.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2006</td>\n",
       "      <td>NaN</td>\n",
       "      <td>844223.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14633962.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>747182.64</td>\n",
       "      <td>11683.60</td>\n",
       "      <td>16647124.98</td>\n",
       "      <td>50319253.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1344365.01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14944781.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777345.52</td>\n",
       "      <td>19377.36</td>\n",
       "      <td>17436387.93</td>\n",
       "      <td>62025513.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2008</td>\n",
       "      <td>6799.55</td>\n",
       "      <td>1790135.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16089534.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>836441.10</td>\n",
       "      <td>30823.60</td>\n",
       "      <td>19149551.45</td>\n",
       "      <td>80755930.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>47078</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2018</td>\n",
       "      <td>154462.39</td>\n",
       "      <td>5361951.37</td>\n",
       "      <td>572868.36</td>\n",
       "      <td>108107448.79</td>\n",
       "      <td>437144.83</td>\n",
       "      <td>589658.88</td>\n",
       "      <td>51297.75</td>\n",
       "      <td>115274832.37</td>\n",
       "      <td>261780766.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47079</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2019</td>\n",
       "      <td>150329.31</td>\n",
       "      <td>6088184.20</td>\n",
       "      <td>468411.51</td>\n",
       "      <td>38527846.59</td>\n",
       "      <td>228886.23</td>\n",
       "      <td>608637.40</td>\n",
       "      <td>64855.15</td>\n",
       "      <td>46137150.39</td>\n",
       "      <td>167638796.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47080</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2020</td>\n",
       "      <td>156556.52</td>\n",
       "      <td>5125090.74</td>\n",
       "      <td>329522.12</td>\n",
       "      <td>78767466.83</td>\n",
       "      <td>552009.16</td>\n",
       "      <td>558925.68</td>\n",
       "      <td>48689.09</td>\n",
       "      <td>85538260.14</td>\n",
       "      <td>263006955.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47081</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2021</td>\n",
       "      <td>163778.36</td>\n",
       "      <td>9082482.28</td>\n",
       "      <td>492045.28</td>\n",
       "      <td>78491368.35</td>\n",
       "      <td>947992.83</td>\n",
       "      <td>602586.14</td>\n",
       "      <td>59824.46</td>\n",
       "      <td>89840077.70</td>\n",
       "      <td>252345800.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47082</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2022</td>\n",
       "      <td>174823.49</td>\n",
       "      <td>7474079.65</td>\n",
       "      <td>1019054.56</td>\n",
       "      <td>84996948.99</td>\n",
       "      <td>593315.54</td>\n",
       "      <td>627169.86</td>\n",
       "      <td>50987.00</td>\n",
       "      <td>94936379.09</td>\n",
       "      <td>259310641.60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47083 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Rodzaje dochodów      Kod   Rok  Dochody_podatek_lesny  Dochody_podatek_PCC   \n",
       "0                 0201011  2004                    NaN            549608.00  \\\n",
       "1                 0201011  2005                    NaN            609855.00   \n",
       "2                 0201011  2006                    NaN            844223.65   \n",
       "3                 0201011  2007                    NaN           1344365.01   \n",
       "4                 0201011  2008                6799.55           1790135.40   \n",
       "...                   ...   ...                    ...                  ...   \n",
       "47078             3263011  2018              154462.39           5361951.37   \n",
       "47079             3263011  2019              150329.31           6088184.20   \n",
       "47080             3263011  2020              156556.52           5125090.74   \n",
       "47081             3263011  2021              163778.36           9082482.28   \n",
       "47082             3263011  2022              174823.49           7474079.65   \n",
       "\n",
       "Rodzaje dochodów  Dochody_podatek_...  Dochody_podatek_od_nieruchomosci   \n",
       "0                                 NaN                       13532989.00  \\\n",
       "1                                 NaN                       13667398.00   \n",
       "2                                 NaN                       14633962.72   \n",
       "3                                 NaN                       14944781.74   \n",
       "4                                 NaN                       16089534.56   \n",
       "...                               ...                               ...   \n",
       "47078                       572868.36                      108107448.79   \n",
       "47079                       468411.51                       38527846.59   \n",
       "47080                       329522.12                       78767466.83   \n",
       "47081                       492045.28                       78491368.35   \n",
       "47082                      1019054.56                       84996948.99   \n",
       "\n",
       "Rodzaje dochodów  Dochody_podatek_od_spadkow   \n",
       "0                                        NaN  \\\n",
       "1                                        NaN   \n",
       "2                                        NaN   \n",
       "3                                        NaN   \n",
       "4                                        NaN   \n",
       "...                                      ...   \n",
       "47078                              437144.83   \n",
       "47079                              228886.23   \n",
       "47080                              552009.16   \n",
       "47081                              947992.83   \n",
       "47082                              593315.54   \n",
       "\n",
       "Rodzaje dochodów  Dochody_podatek_od_srodkow_transportowych   \n",
       "0                                                 625159.00  \\\n",
       "1                                                 700134.00   \n",
       "2                                                 747182.64   \n",
       "3                                                 777345.52   \n",
       "4                                                 836441.10   \n",
       "...                                                     ...   \n",
       "47078                                             589658.88   \n",
       "47079                                             608637.40   \n",
       "47080                                             558925.68   \n",
       "47081                                             602586.14   \n",
       "47082                                             627169.86   \n",
       "\n",
       "Rodzaje dochodów  Dochody_podatek_rolny  Dochody_podatek_odrebne_ustawy   \n",
       "0                              23687.00                             NaN  \\\n",
       "1                              26634.00                     15438121.00   \n",
       "2                              11683.60                     16647124.98   \n",
       "3                              19377.36                     17436387.93   \n",
       "4                              30823.60                     19149551.45   \n",
       "...                                 ...                             ...   \n",
       "47078                          51297.75                    115274832.37   \n",
       "47079                          64855.15                     46137150.39   \n",
       "47080                          48689.09                     85538260.14   \n",
       "47081                          59824.46                     89840077.70   \n",
       "47082                          50987.00                     94936379.09   \n",
       "\n",
       "Rodzaje dochodów  Dochody_razem  \n",
       "0                   41378568.00  \n",
       "1                   43417443.00  \n",
       "2                   50319253.08  \n",
       "3                   62025513.24  \n",
       "4                   80755930.93  \n",
       "...                         ...  \n",
       "47078              261780766.79  \n",
       "47079              167638796.15  \n",
       "47080              263006955.07  \n",
       "47081              252345800.93  \n",
       "47082              259310641.60  \n",
       "\n",
       "[47083 rows x 11 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_fina_1 = pd.read_csv(\n",
    "    'FINA_2622_CREL_1.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str},\n",
    "    decimal=',')\n",
    "df_fina_1 = df_fina_1[['Kod', 'Rodzaje dochodów', 'Rok', 'Wartosc']]\n",
    "df_fina_1 = df_fina_1.dropna()\n",
    "df_fina_1 = df_fina_1.pivot_table(index=['Kod', 'Rok'], columns='Rodzaje dochodów', values='Wartosc').reset_index()\n",
    "df_fina_1 = df_fina_1.rename(columns={\n",
    "    'dochody podatkowe - podatek leśny': 'Dochody_podatek_lesny',\n",
    "    'dochody podatkowe - podatek od czynności cywilnoprawnych': 'Dochody_podatek_PCC',\n",
    "    'dochody podatkowe - podatek od działalności gospodarczej osób fizycznych, opłacany w formie karty podatkowej': 'Dochody_podatek_...',\n",
    "    'dochody podatkowe - podatek od nieruchomości': 'Dochody_podatek_od_nieruchomosci',\n",
    "    'dochody podatkowe - podatek od spadków i darowizn': 'Dochody_podatek_od_spadkow',\n",
    "    'dochody podatkowe - podatek od środków transportowych': 'Dochody_podatek_od_srodkow_transportowych',\n",
    "    'dochody podatkowe - podatek rolny': 'Dochody_podatek_rolny',\n",
    "    'dochody podatkowe - ustalone i pobierane na podstawie odrębnych ustaw': 'Dochody_podatek_odrebne_ustawy',\n",
    "    'razem': 'Dochody_razem'})\n",
    "\n",
    "df_fina_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\micha\\AppData\\Local\\Temp\\ipykernel_26160\\2161929356.py:1: DtypeWarning: Columns (7) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df_fina_2 = pd.read_csv(\n"
     ]
    },
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       "      <td>44200.00</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2005</td>\n",
       "      <td>4560489.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96462.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9024183.00</td>\n",
       "      <td>15985331.00</td>\n",
       "      <td>1170863.00</td>\n",
       "      <td>17156194.00</td>\n",
       "      <td>42840.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1282943.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2006</td>\n",
       "      <td>8528727.69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>231470.96</td>\n",
       "      <td>8752288.98</td>\n",
       "      <td>8864860.57</td>\n",
       "      <td>18101668.00</td>\n",
       "      <td>1048115.83</td>\n",
       "      <td>19149783.83</td>\n",
       "      <td>37365.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1203990.73</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2007</td>\n",
       "      <td>15042480.34</td>\n",
       "      <td>9219682.12</td>\n",
       "      <td>339654.15</td>\n",
       "      <td>18153240.30</td>\n",
       "      <td>18438743.21</td>\n",
       "      <td>21785308.00</td>\n",
       "      <td>1336702.02</td>\n",
       "      <td>23122010.02</td>\n",
       "      <td>78798.51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1228704.53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2008</td>\n",
       "      <td>22797881.07</td>\n",
       "      <td>9546379.31</td>\n",
       "      <td>787256.69</td>\n",
       "      <td>5046691.69</td>\n",
       "      <td>5182137.79</td>\n",
       "      <td>23974587.00</td>\n",
       "      <td>1532633.44</td>\n",
       "      <td>25507220.44</td>\n",
       "      <td>83882.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1364245.93</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47078</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2018</td>\n",
       "      <td>16419859.31</td>\n",
       "      <td>4261374.83</td>\n",
       "      <td>1996824.80</td>\n",
       "      <td>25285.92</td>\n",
       "      <td>237485.34</td>\n",
       "      <td>52799183.00</td>\n",
       "      <td>2690098.17</td>\n",
       "      <td>55489281.17</td>\n",
       "      <td>10458871.30</td>\n",
       "      <td>4684.54</td>\n",
       "      <td>434077.88</td>\n",
       "      <td>608625.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47079</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2019</td>\n",
       "      <td>8844350.07</td>\n",
       "      <td>4324758.68</td>\n",
       "      <td>2187576.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>225831.84</td>\n",
       "      <td>55319040.00</td>\n",
       "      <td>2770684.17</td>\n",
       "      <td>58089724.17</td>\n",
       "      <td>11369287.11</td>\n",
       "      <td>3456.95</td>\n",
       "      <td>415686.53</td>\n",
       "      <td>610059.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47080</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2020</td>\n",
       "      <td>13485033.97</td>\n",
       "      <td>6159923.01</td>\n",
       "      <td>1917372.55</td>\n",
       "      <td>21002107.00</td>\n",
       "      <td>21192313.05</td>\n",
       "      <td>53739656.00</td>\n",
       "      <td>3144444.38</td>\n",
       "      <td>56884100.38</td>\n",
       "      <td>12281916.71</td>\n",
       "      <td>5157.50</td>\n",
       "      <td>355201.29</td>\n",
       "      <td>507341.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47081</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2021</td>\n",
       "      <td>16928500.75</td>\n",
       "      <td>7582499.62</td>\n",
       "      <td>4110105.72</td>\n",
       "      <td>888293.63</td>\n",
       "      <td>1072910.83</td>\n",
       "      <td>63936763.00</td>\n",
       "      <td>3975531.95</td>\n",
       "      <td>67912294.95</td>\n",
       "      <td>17127683.55</td>\n",
       "      <td>27746.70</td>\n",
       "      <td>416473.03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47082</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2022</td>\n",
       "      <td>30415536.99</td>\n",
       "      <td>8651170.05</td>\n",
       "      <td>4117086.30</td>\n",
       "      <td>207597.50</td>\n",
       "      <td>800347.63</td>\n",
       "      <td>64657287.40</td>\n",
       "      <td>4082611.64</td>\n",
       "      <td>68739899.04</td>\n",
       "      <td>19150342.25</td>\n",
       "      <td>5035.87</td>\n",
       "      <td>421424.91</td>\n",
       "      <td>1233266.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47083 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Rodzaje dochodów      Kod   Rok  Dochody_z_majatku   \n",
       "0                 0201011  2004         5344205.00  \\\n",
       "1                 0201011  2005         4560489.00   \n",
       "2                 0201011  2006         8528727.69   \n",
       "3                 0201011  2007        15042480.34   \n",
       "4                 0201011  2008        22797881.07   \n",
       "...                   ...   ...                ...   \n",
       "47078             3263011  2018        16419859.31   \n",
       "47079             3263011  2019         8844350.07   \n",
       "47080             3263011  2020        13485033.97   \n",
       "47081             3263011  2021        16928500.75   \n",
       "47082             3263011  2022        30415536.99   \n",
       "\n",
       "Rodzaje dochodów  Dochody_z_najmu_i_dzierzawy  Dochody_z_uslug   \n",
       "0                                         NaN        184307.00  \\\n",
       "1                                         NaN         96462.00   \n",
       "2                                         NaN        231470.96   \n",
       "3                                  9219682.12        339654.15   \n",
       "4                                  9546379.31        787256.69   \n",
       "...                                       ...              ...   \n",
       "47078                              4261374.83       1996824.80   \n",
       "47079                              4324758.68       2187576.47   \n",
       "47080                              6159923.01       1917372.55   \n",
       "47081                              7582499.62       4110105.72   \n",
       "47082                              8651170.05       4117086.30   \n",
       "\n",
       "Rodzaje dochodów  Dochody_dofinansowanie_inwestycyjne   \n",
       "0                                                 NaN  \\\n",
       "1                                                 NaN   \n",
       "2                                          8752288.98   \n",
       "3                                         18153240.30   \n",
       "4                                          5046691.69   \n",
       "...                                               ...   \n",
       "47078                                        25285.92   \n",
       "47079                                            0.00   \n",
       "47080                                     21002107.00   \n",
       "47081                                       888293.63   \n",
       "47082                                       207597.50   \n",
       "\n",
       "Rodzaje dochodów  Dochody_dofinansowanie_razem   \n",
       "0                                    519209.00  \\\n",
       "1                                   9024183.00   \n",
       "2                                   8864860.57   \n",
       "3                                  18438743.21   \n",
       "4                                   5182137.79   \n",
       "...                                        ...   \n",
       "47078                                237485.34   \n",
       "47079                                225831.84   \n",
       "47080                              21192313.05   \n",
       "47081                               1072910.83   \n",
       "47082                                800347.63   \n",
       "\n",
       "Rodzaje dochodów  Udzialy_w_podatkach_dochodowych_od_osob_fizycznych   \n",
       "0                                                       13285456.00   \\\n",
       "1                                                       15985331.00    \n",
       "2                                                       18101668.00    \n",
       "3                                                       21785308.00    \n",
       "4                                                       23974587.00    \n",
       "...                                                             ...    \n",
       "47078                                                   52799183.00    \n",
       "47079                                                   55319040.00    \n",
       "47080                                                   53739656.00    \n",
       "47081                                                   63936763.00    \n",
       "47082                                                   64657287.40    \n",
       "\n",
       "Rodzaje dochodów  Udzialy_w_podatkach_dochodowych_od_osob_prywatnych   \n",
       "0                                                        1065169.00   \\\n",
       "1                                                        1170863.00    \n",
       "2                                                        1048115.83    \n",
       "3                                                        1336702.02    \n",
       "4                                                        1532633.44    \n",
       "...                                                             ...    \n",
       "47078                                                    2690098.17    \n",
       "47079                                                    2770684.17    \n",
       "47080                                                    3144444.38    \n",
       "47081                                                    3975531.95    \n",
       "47082                                                    4082611.64    \n",
       "\n",
       "Rodzaje dochodów  Udzialy_w_podatkach_dochodowych_razem   \n",
       "0                                           14350625.00  \\\n",
       "1                                           17156194.00   \n",
       "2                                           19149783.83   \n",
       "3                                           23122010.02   \n",
       "4                                           25507220.44   \n",
       "...                                                 ...   \n",
       "47078                                       55489281.17   \n",
       "47079                                       58089724.17   \n",
       "47080                                       56884100.38   \n",
       "47081                                       67912294.95   \n",
       "47082                                       68739899.04   \n",
       "\n",
       "Rodzaje dochodów  Wplywy_z_innych_lokalnych_oplat   \n",
       "0                                        44200.00  \\\n",
       "1                                        42840.00   \n",
       "2                                        37365.00   \n",
       "3                                        78798.51   \n",
       "4                                        83882.94   \n",
       "...                                           ...   \n",
       "47078                                 10458871.30   \n",
       "47079                                 11369287.11   \n",
       "47080                                 12281916.71   \n",
       "47081                                 17127683.55   \n",
       "47082                                 19150342.25   \n",
       "\n",
       "Rodzaje dochodów  Wplywy_z_oplaty_eksploatacyjnej  Wplywy_z_oplaty_skarbowej   \n",
       "0                                             NaN                 1209998.00  \\\n",
       "1                                             NaN                 1282943.00   \n",
       "2                                             NaN                 1203990.73   \n",
       "3                                             NaN                 1228704.53   \n",
       "4                                             NaN                 1364245.93   \n",
       "...                                           ...                        ...   \n",
       "47078                                     4684.54                  434077.88   \n",
       "47079                                     3456.95                  415686.53   \n",
       "47080                                     5157.50                  355201.29   \n",
       "47081                                    27746.70                  416473.03   \n",
       "47082                                     5035.87                  421424.91   \n",
       "\n",
       "Rodzaje dochodów  Wplywy_z_oplaty_targowej  \n",
       "0                                      NaN  \n",
       "1                                      NaN  \n",
       "2                                      NaN  \n",
       "3                                      NaN  \n",
       "4                                      NaN  \n",
       "...                                    ...  \n",
       "47078                            608625.90  \n",
       "47079                            610059.50  \n",
       "47080                            507341.00  \n",
       "47081                                 0.00  \n",
       "47082                           1233266.30  \n",
       "\n",
       "[47083 rows x 14 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_fina_2 = pd.read_csv(\n",
    "    'FINA_2622_CREL_2.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str},\n",
    "    decimal=',')\n",
    "df_fina_2 = df_fina_2[['Kod', 'Rodzaje dochodów', 'Rok', 'Wartosc']]\n",
    "df_fina_2 = df_fina_2.dropna()\n",
    "df_fina_2 = df_fina_2.pivot_table(index=['Kod', 'Rok'], columns='Rodzaje dochodów', values='Wartosc').reset_index()\n",
    "df_fina_2 = df_fina_2.rename(columns={\n",
    "    'dochody z majątku': 'Dochody_z_majatku',\n",
    "    'dochody z majątku - dochody z najmu i dzierżawy składników majątkowych JST oraz innych umów o podobnym charakterze': 'Dochody_z_najmu_i_dzierzawy',\n",
    "    'pozostałe dochody - wpływy z usług': 'Dochody_z_uslug',\n",
    "    'pozostałe dochody - środki na dofinansowanie własnych zadań pozyskane z innych źródeł - inwestycyjne': 'Dochody_dofinansowanie_inwestycyjne',\n",
    "    'pozostałe dochody - środki na dofinansowanie własnych zadań pozyskane z innych źródeł - razem': 'Dochody_dofinansowanie_razem',\n",
    "    'udziały w podatkach stanowiących dochody budżetu państwa podatek dochodowy od osób fizycznych': 'Udzialy_w_podatkach_dochodowych_od_osob_fizycznych',\n",
    "    'udziały w podatkach stanowiących dochody budżetu państwa podatek dochodowy od osób prawnych': 'Udzialy_w_podatkach_dochodowych_od_osob_prywatnych',\n",
    "    'udziały w podatkach stanowiących dochody budżetu państwa razem': 'Udzialy_w_podatkach_dochodowych_razem',\n",
    "    'wpływy z innych lokalnych opłat pobieranych przez jednostki samorządu terytorialnego na podstawie odrębnych ustaw': 'Wplywy_z_innych_lokalnych_oplat',\n",
    "    'wpływy z opłaty eksploatacyjnej': 'Wplywy_z_oplaty_eksploatacyjnej',\n",
    "    'wpływy z opłaty skarbowej': 'Wplywy_z_oplaty_skarbowej',\n",
    "    'wpływy z opłaty targowej': 'Wplywy_z_oplaty_targowej'})\n",
    "\n",
    "df_fina_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Wiek</th>\n",
       "      <th>Kod</th>\n",
       "      <th>Rok</th>\n",
       "      <th>Ludnosc_ogolem</th>\n",
       "      <th>Ludnosc_w_wieku_poprodukcyjnym</th>\n",
       "      <th>Ludnosc_w_wieku_produkcyjnym</th>\n",
       "      <th>Ludnosc_w_wieku_produkcyjnym_mobilnym</th>\n",
       "      <th>Ludnosc_w_wieku_produkcyjnym_niemobilnym</th>\n",
       "      <th>Ludnosc_w_wieku_przedprodukcyjnym</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2010</td>\n",
       "      <td>40309.00</td>\n",
       "      <td>7683.00</td>\n",
       "      <td>26085.00</td>\n",
       "      <td>15183.00</td>\n",
       "      <td>10902.00</td>\n",
       "      <td>6541.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2011</td>\n",
       "      <td>40119.00</td>\n",
       "      <td>8020.00</td>\n",
       "      <td>25647.00</td>\n",
       "      <td>15047.00</td>\n",
       "      <td>10600.00</td>\n",
       "      <td>6452.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2012</td>\n",
       "      <td>39851.00</td>\n",
       "      <td>8392.00</td>\n",
       "      <td>25160.00</td>\n",
       "      <td>14932.00</td>\n",
       "      <td>10228.00</td>\n",
       "      <td>6299.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2013</td>\n",
       "      <td>39603.00</td>\n",
       "      <td>8678.00</td>\n",
       "      <td>24720.00</td>\n",
       "      <td>14784.00</td>\n",
       "      <td>9936.00</td>\n",
       "      <td>6205.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2014</td>\n",
       "      <td>39464.00</td>\n",
       "      <td>8971.00</td>\n",
       "      <td>24307.00</td>\n",
       "      <td>14645.00</td>\n",
       "      <td>9662.00</td>\n",
       "      <td>6186.00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48606</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2018</td>\n",
       "      <td>40910.00</td>\n",
       "      <td>10472.00</td>\n",
       "      <td>24549.00</td>\n",
       "      <td>14683.00</td>\n",
       "      <td>9866.00</td>\n",
       "      <td>5889.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48607</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2019</td>\n",
       "      <td>40888.00</td>\n",
       "      <td>10788.00</td>\n",
       "      <td>24209.00</td>\n",
       "      <td>14429.00</td>\n",
       "      <td>9780.00</td>\n",
       "      <td>5891.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48608</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2020</td>\n",
       "      <td>40326.00</td>\n",
       "      <td>10962.00</td>\n",
       "      <td>23544.00</td>\n",
       "      <td>13798.00</td>\n",
       "      <td>9746.00</td>\n",
       "      <td>5820.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48609</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2021</td>\n",
       "      <td>39834.00</td>\n",
       "      <td>11050.00</td>\n",
       "      <td>22976.00</td>\n",
       "      <td>13277.00</td>\n",
       "      <td>9699.00</td>\n",
       "      <td>5808.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48610</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2022</td>\n",
       "      <td>39368.00</td>\n",
       "      <td>11157.00</td>\n",
       "      <td>22486.00</td>\n",
       "      <td>12802.00</td>\n",
       "      <td>9684.00</td>\n",
       "      <td>5725.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>48611 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Wiek       Kod   Rok  Ludnosc_ogolem  Ludnosc_w_wieku_poprodukcyjnym   \n",
       "0      0201011  2010        40309.00                         7683.00  \\\n",
       "1      0201011  2011        40119.00                         8020.00   \n",
       "2      0201011  2012        39851.00                         8392.00   \n",
       "3      0201011  2013        39603.00                         8678.00   \n",
       "4      0201011  2014        39464.00                         8971.00   \n",
       "...        ...   ...             ...                             ...   \n",
       "48606  3263011  2018        40910.00                        10472.00   \n",
       "48607  3263011  2019        40888.00                        10788.00   \n",
       "48608  3263011  2020        40326.00                        10962.00   \n",
       "48609  3263011  2021        39834.00                        11050.00   \n",
       "48610  3263011  2022        39368.00                        11157.00   \n",
       "\n",
       "Wiek   Ludnosc_w_wieku_produkcyjnym  Ludnosc_w_wieku_produkcyjnym_mobilnym   \n",
       "0                          26085.00                               15183.00  \\\n",
       "1                          25647.00                               15047.00   \n",
       "2                          25160.00                               14932.00   \n",
       "3                          24720.00                               14784.00   \n",
       "4                          24307.00                               14645.00   \n",
       "...                             ...                                    ...   \n",
       "48606                      24549.00                               14683.00   \n",
       "48607                      24209.00                               14429.00   \n",
       "48608                      23544.00                               13798.00   \n",
       "48609                      22976.00                               13277.00   \n",
       "48610                      22486.00                               12802.00   \n",
       "\n",
       "Wiek   Ludnosc_w_wieku_produkcyjnym_niemobilnym   \n",
       "0                                      10902.00  \\\n",
       "1                                      10600.00   \n",
       "2                                      10228.00   \n",
       "3                                       9936.00   \n",
       "4                                       9662.00   \n",
       "...                                         ...   \n",
       "48606                                   9866.00   \n",
       "48607                                   9780.00   \n",
       "48608                                   9746.00   \n",
       "48609                                   9699.00   \n",
       "48610                                   9684.00   \n",
       "\n",
       "Wiek   Ludnosc_w_wieku_przedprodukcyjnym  \n",
       "0                                6541.00  \n",
       "1                                6452.00  \n",
       "2                                6299.00  \n",
       "3                                6205.00  \n",
       "4                                6186.00  \n",
       "...                                  ...  \n",
       "48606                            5889.00  \n",
       "48607                            5891.00  \n",
       "48608                            5820.00  \n",
       "48609                            5808.00  \n",
       "48610                            5725.00  \n",
       "\n",
       "[48611 rows x 8 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ludn_1 = pd.read_csv(  # ogolem\n",
    "    'LUDN_1342_CREL_1.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str},\n",
    "    decimal=',')\n",
    "df_ludn_1 = df_ludn_1[['Kod', 'Wiek', 'Rok', 'Wartosc']]\n",
    "df_ludn_1 = df_ludn_1.dropna()\n",
    "df_ludn_1 = df_ludn_1.pivot_table(index=['Kod', 'Rok'], columns='Wiek', values='Wartosc').reset_index()\n",
    "df_ludn_1 = df_ludn_1.rename(columns={\n",
    "    'ogółem': 'Ludnosc_ogolem',\n",
    "    'w wieku poprodukcyjnym': 'Ludnosc_w_wieku_poprodukcyjnym',\n",
    "    'w wieku produkcyjnym': 'Ludnosc_w_wieku_produkcyjnym',\n",
    "    'w wieku produkcyjnym mobilnym': 'Ludnosc_w_wieku_produkcyjnym_mobilnym',\n",
    "    'w wieku produkcyjnym niemobilnym': 'Ludnosc_w_wieku_produkcyjnym_niemobilnym',\n",
    "    'w wieku przedprodukcyjnym': 'Ludnosc_w_wieku_przedprodukcyjnym'})\n",
    "\n",
    "df_ludn_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Wiek</th>\n",
       "      <th>Kod</th>\n",
       "      <th>Rok</th>\n",
       "      <th>Ludnosc_mezczyzni</th>\n",
       "      <th>Ludnosc_mezczyzni_w_wieku_poprodukcyjnym</th>\n",
       "      <th>Ludnosc_mezczyzni_w_wieku_produkcyjnym</th>\n",
       "      <th>Ludnosc_mezczyzni_w_wieku_produkcyjnym_mobilnym</th>\n",
       "      <th>Ludnosc_mezczyzni_w_wieku_produkcyjnym_niemobilnym</th>\n",
       "      <th>Ludnosc_mezczyzni_w_wieku_przedprodukcyjnym</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2010</td>\n",
       "      <td>19085.00</td>\n",
       "      <td>2153.00</td>\n",
       "      <td>13535.00</td>\n",
       "      <td>7720.00</td>\n",
       "      <td>5815.00</td>\n",
       "      <td>3397.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2011</td>\n",
       "      <td>18985.00</td>\n",
       "      <td>2222.00</td>\n",
       "      <td>13398.00</td>\n",
       "      <td>7647.00</td>\n",
       "      <td>5751.00</td>\n",
       "      <td>3365.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2012</td>\n",
       "      <td>18859.00</td>\n",
       "      <td>2370.00</td>\n",
       "      <td>13238.00</td>\n",
       "      <td>7611.00</td>\n",
       "      <td>5627.00</td>\n",
       "      <td>3251.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2013</td>\n",
       "      <td>18737.00</td>\n",
       "      <td>2477.00</td>\n",
       "      <td>13028.00</td>\n",
       "      <td>7501.00</td>\n",
       "      <td>5527.00</td>\n",
       "      <td>3232.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2014</td>\n",
       "      <td>18640.00</td>\n",
       "      <td>2620.00</td>\n",
       "      <td>12832.00</td>\n",
       "      <td>7442.00</td>\n",
       "      <td>5390.00</td>\n",
       "      <td>3188.00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48606</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2018</td>\n",
       "      <td>19690.00</td>\n",
       "      <td>3501.00</td>\n",
       "      <td>13202.00</td>\n",
       "      <td>7547.00</td>\n",
       "      <td>5655.00</td>\n",
       "      <td>2987.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48607</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2019</td>\n",
       "      <td>19683.00</td>\n",
       "      <td>3644.00</td>\n",
       "      <td>13044.00</td>\n",
       "      <td>7417.00</td>\n",
       "      <td>5627.00</td>\n",
       "      <td>2995.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48608</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2020</td>\n",
       "      <td>19356.00</td>\n",
       "      <td>3749.00</td>\n",
       "      <td>12617.00</td>\n",
       "      <td>6986.00</td>\n",
       "      <td>5631.00</td>\n",
       "      <td>2990.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48609</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2021</td>\n",
       "      <td>19096.00</td>\n",
       "      <td>3852.00</td>\n",
       "      <td>12267.00</td>\n",
       "      <td>6747.00</td>\n",
       "      <td>5520.00</td>\n",
       "      <td>2977.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48610</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2022</td>\n",
       "      <td>18869.00</td>\n",
       "      <td>3901.00</td>\n",
       "      <td>12009.00</td>\n",
       "      <td>6485.00</td>\n",
       "      <td>5524.00</td>\n",
       "      <td>2959.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>48611 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Wiek       Kod   Rok  Ludnosc_mezczyzni   \n",
       "0      0201011  2010           19085.00  \\\n",
       "1      0201011  2011           18985.00   \n",
       "2      0201011  2012           18859.00   \n",
       "3      0201011  2013           18737.00   \n",
       "4      0201011  2014           18640.00   \n",
       "...        ...   ...                ...   \n",
       "48606  3263011  2018           19690.00   \n",
       "48607  3263011  2019           19683.00   \n",
       "48608  3263011  2020           19356.00   \n",
       "48609  3263011  2021           19096.00   \n",
       "48610  3263011  2022           18869.00   \n",
       "\n",
       "Wiek   Ludnosc_mezczyzni_w_wieku_poprodukcyjnym   \n",
       "0                                       2153.00  \\\n",
       "1                                       2222.00   \n",
       "2                                       2370.00   \n",
       "3                                       2477.00   \n",
       "4                                       2620.00   \n",
       "...                                         ...   \n",
       "48606                                   3501.00   \n",
       "48607                                   3644.00   \n",
       "48608                                   3749.00   \n",
       "48609                                   3852.00   \n",
       "48610                                   3901.00   \n",
       "\n",
       "Wiek   Ludnosc_mezczyzni_w_wieku_produkcyjnym   \n",
       "0                                    13535.00  \\\n",
       "1                                    13398.00   \n",
       "2                                    13238.00   \n",
       "3                                    13028.00   \n",
       "4                                    12832.00   \n",
       "...                                       ...   \n",
       "48606                                13202.00   \n",
       "48607                                13044.00   \n",
       "48608                                12617.00   \n",
       "48609                                12267.00   \n",
       "48610                                12009.00   \n",
       "\n",
       "Wiek   Ludnosc_mezczyzni_w_wieku_produkcyjnym_mobilnym   \n",
       "0                                              7720.00  \\\n",
       "1                                              7647.00   \n",
       "2                                              7611.00   \n",
       "3                                              7501.00   \n",
       "4                                              7442.00   \n",
       "...                                                ...   \n",
       "48606                                          7547.00   \n",
       "48607                                          7417.00   \n",
       "48608                                          6986.00   \n",
       "48609                                          6747.00   \n",
       "48610                                          6485.00   \n",
       "\n",
       "Wiek   Ludnosc_mezczyzni_w_wieku_produkcyjnym_niemobilnym   \n",
       "0                                                5815.00   \\\n",
       "1                                                5751.00    \n",
       "2                                                5627.00    \n",
       "3                                                5527.00    \n",
       "4                                                5390.00    \n",
       "...                                                  ...    \n",
       "48606                                            5655.00    \n",
       "48607                                            5627.00    \n",
       "48608                                            5631.00    \n",
       "48609                                            5520.00    \n",
       "48610                                            5524.00    \n",
       "\n",
       "Wiek   Ludnosc_mezczyzni_w_wieku_przedprodukcyjnym  \n",
       "0                                          3397.00  \n",
       "1                                          3365.00  \n",
       "2                                          3251.00  \n",
       "3                                          3232.00  \n",
       "4                                          3188.00  \n",
       "...                                            ...  \n",
       "48606                                      2987.00  \n",
       "48607                                      2995.00  \n",
       "48608                                      2990.00  \n",
       "48609                                      2977.00  \n",
       "48610                                      2959.00  \n",
       "\n",
       "[48611 rows x 8 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ludn_2 = pd.read_csv(  # mezczyzni\n",
    "    'LUDN_1342_CREL_2.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str},\n",
    "    decimal=',')\n",
    "df_ludn_2 = df_ludn_2[['Kod', 'Wiek', 'Rok', 'Wartosc']]\n",
    "df_ludn_2 = df_ludn_2.dropna()\n",
    "df_ludn_2 = df_ludn_2.pivot_table(index=['Kod', 'Rok'], columns='Wiek', values='Wartosc').reset_index()\n",
    "df_ludn_2 = df_ludn_2.rename(columns={\n",
    "    'ogółem': 'Ludnosc_mezczyzni',\n",
    "    'w wieku poprodukcyjnym': 'Ludnosc_mezczyzni_w_wieku_poprodukcyjnym',\n",
    "    'w wieku produkcyjnym': 'Ludnosc_mezczyzni_w_wieku_produkcyjnym',\n",
    "    'w wieku produkcyjnym mobilnym': 'Ludnosc_mezczyzni_w_wieku_produkcyjnym_mobilnym',\n",
    "    'w wieku produkcyjnym niemobilnym': 'Ludnosc_mezczyzni_w_wieku_produkcyjnym_niemobilnym',\n",
    "    'w wieku przedprodukcyjnym': 'Ludnosc_mezczyzni_w_wieku_przedprodukcyjnym'})\n",
    "\n",
    "df_ludn_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Wiek</th>\n",
       "      <th>Kod</th>\n",
       "      <th>Rok</th>\n",
       "      <th>Ludnosc_kobiety</th>\n",
       "      <th>Ludnosc_kobiety_w_wieku_poprodukcyjnym</th>\n",
       "      <th>Ludnosc_kobiety_w_wieku_produkcyjnym</th>\n",
       "      <th>Ludnosc_kobiety_w_wieku_produkcyjnym_mobilnym</th>\n",
       "      <th>Ludnosc_kobiety_w_wieku_produkcyjnym_niemobilnym</th>\n",
       "      <th>Ludnosc_kobiety_w_wieku_przedprodukcyjnym</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2010</td>\n",
       "      <td>21224.00</td>\n",
       "      <td>5530.00</td>\n",
       "      <td>12550.00</td>\n",
       "      <td>7463.00</td>\n",
       "      <td>5087.00</td>\n",
       "      <td>3144.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2011</td>\n",
       "      <td>21134.00</td>\n",
       "      <td>5798.00</td>\n",
       "      <td>12249.00</td>\n",
       "      <td>7400.00</td>\n",
       "      <td>4849.00</td>\n",
       "      <td>3087.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2012</td>\n",
       "      <td>20992.00</td>\n",
       "      <td>6022.00</td>\n",
       "      <td>11922.00</td>\n",
       "      <td>7321.00</td>\n",
       "      <td>4601.00</td>\n",
       "      <td>3048.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2013</td>\n",
       "      <td>20866.00</td>\n",
       "      <td>6201.00</td>\n",
       "      <td>11692.00</td>\n",
       "      <td>7283.00</td>\n",
       "      <td>4409.00</td>\n",
       "      <td>2973.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2014</td>\n",
       "      <td>20824.00</td>\n",
       "      <td>6351.00</td>\n",
       "      <td>11475.00</td>\n",
       "      <td>7203.00</td>\n",
       "      <td>4272.00</td>\n",
       "      <td>2998.00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48606</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2018</td>\n",
       "      <td>21220.00</td>\n",
       "      <td>6971.00</td>\n",
       "      <td>11347.00</td>\n",
       "      <td>7136.00</td>\n",
       "      <td>4211.00</td>\n",
       "      <td>2902.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48607</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2019</td>\n",
       "      <td>21205.00</td>\n",
       "      <td>7144.00</td>\n",
       "      <td>11165.00</td>\n",
       "      <td>7012.00</td>\n",
       "      <td>4153.00</td>\n",
       "      <td>2896.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48608</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2020</td>\n",
       "      <td>20970.00</td>\n",
       "      <td>7213.00</td>\n",
       "      <td>10927.00</td>\n",
       "      <td>6812.00</td>\n",
       "      <td>4115.00</td>\n",
       "      <td>2830.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48609</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2021</td>\n",
       "      <td>20738.00</td>\n",
       "      <td>7198.00</td>\n",
       "      <td>10709.00</td>\n",
       "      <td>6530.00</td>\n",
       "      <td>4179.00</td>\n",
       "      <td>2831.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48610</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2022</td>\n",
       "      <td>20499.00</td>\n",
       "      <td>7256.00</td>\n",
       "      <td>10477.00</td>\n",
       "      <td>6317.00</td>\n",
       "      <td>4160.00</td>\n",
       "      <td>2766.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>48611 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Wiek       Kod   Rok  Ludnosc_kobiety  Ludnosc_kobiety_w_wieku_poprodukcyjnym   \n",
       "0      0201011  2010         21224.00                                 5530.00  \\\n",
       "1      0201011  2011         21134.00                                 5798.00   \n",
       "2      0201011  2012         20992.00                                 6022.00   \n",
       "3      0201011  2013         20866.00                                 6201.00   \n",
       "4      0201011  2014         20824.00                                 6351.00   \n",
       "...        ...   ...              ...                                     ...   \n",
       "48606  3263011  2018         21220.00                                 6971.00   \n",
       "48607  3263011  2019         21205.00                                 7144.00   \n",
       "48608  3263011  2020         20970.00                                 7213.00   \n",
       "48609  3263011  2021         20738.00                                 7198.00   \n",
       "48610  3263011  2022         20499.00                                 7256.00   \n",
       "\n",
       "Wiek   Ludnosc_kobiety_w_wieku_produkcyjnym   \n",
       "0                                  12550.00  \\\n",
       "1                                  12249.00   \n",
       "2                                  11922.00   \n",
       "3                                  11692.00   \n",
       "4                                  11475.00   \n",
       "...                                     ...   \n",
       "48606                              11347.00   \n",
       "48607                              11165.00   \n",
       "48608                              10927.00   \n",
       "48609                              10709.00   \n",
       "48610                              10477.00   \n",
       "\n",
       "Wiek   Ludnosc_kobiety_w_wieku_produkcyjnym_mobilnym   \n",
       "0                                            7463.00  \\\n",
       "1                                            7400.00   \n",
       "2                                            7321.00   \n",
       "3                                            7283.00   \n",
       "4                                            7203.00   \n",
       "...                                              ...   \n",
       "48606                                        7136.00   \n",
       "48607                                        7012.00   \n",
       "48608                                        6812.00   \n",
       "48609                                        6530.00   \n",
       "48610                                        6317.00   \n",
       "\n",
       "Wiek   Ludnosc_kobiety_w_wieku_produkcyjnym_niemobilnym   \n",
       "0                                               5087.00  \\\n",
       "1                                               4849.00   \n",
       "2                                               4601.00   \n",
       "3                                               4409.00   \n",
       "4                                               4272.00   \n",
       "...                                                 ...   \n",
       "48606                                           4211.00   \n",
       "48607                                           4153.00   \n",
       "48608                                           4115.00   \n",
       "48609                                           4179.00   \n",
       "48610                                           4160.00   \n",
       "\n",
       "Wiek   Ludnosc_kobiety_w_wieku_przedprodukcyjnym  \n",
       "0                                        3144.00  \n",
       "1                                        3087.00  \n",
       "2                                        3048.00  \n",
       "3                                        2973.00  \n",
       "4                                        2998.00  \n",
       "...                                          ...  \n",
       "48606                                    2902.00  \n",
       "48607                                    2896.00  \n",
       "48608                                    2830.00  \n",
       "48609                                    2831.00  \n",
       "48610                                    2766.00  \n",
       "\n",
       "[48611 rows x 8 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ludn_3 = pd.read_csv(  # kobiety\n",
    "    'LUDN_1342_CREL_3.csv',\n",
    "    sep=';',\n",
    "    converters={'Kod': str},\n",
    "    decimal=',')\n",
    "df_ludn_3 = df_ludn_3[['Kod', 'Wiek', 'Rok', 'Wartosc']]\n",
    "df_ludn_3 = df_ludn_3.dropna()\n",
    "df_ludn_3 = df_ludn_3.pivot_table(index=['Kod', 'Rok'], columns='Wiek', values='Wartosc').reset_index()\n",
    "df_ludn_3 = df_ludn_3.rename(columns={\n",
    "    'ogółem': 'Ludnosc_kobiety',\n",
    "    'w wieku poprodukcyjnym': 'Ludnosc_kobiety_w_wieku_poprodukcyjnym',\n",
    "    'w wieku produkcyjnym': 'Ludnosc_kobiety_w_wieku_produkcyjnym',\n",
    "    'w wieku produkcyjnym mobilnym': 'Ludnosc_kobiety_w_wieku_produkcyjnym_mobilnym',\n",
    "    'w wieku produkcyjnym niemobilnym': 'Ludnosc_kobiety_w_wieku_produkcyjnym_niemobilnym',\n",
    "    'w wieku przedprodukcyjnym': 'Ludnosc_kobiety_w_wieku_przedprodukcyjnym'})\n",
    "\n",
    "df_ludn_3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data = df_dofinansowanie_agg.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data = df_data.merge(df_podz, left_on=[df_data['Kod'].str.slice(stop=-1), 'Rok'], right_on=[df_podz['Kod'].str.slice(stop=-1), 'Rok'], how='left', suffixes=(None, '_podz'))\n",
    "df_data = df_data.drop(['key_0', 'Kod_podz'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data = df_data.merge(df_wyna, left_on=[df_data['Kod'].str.slice(stop=-3), 'Rok'], right_on=[df_wyna['Kod'].str.slice(stop=-3), 'Rok'], how='left', suffixes=(None, '_wyna'))\n",
    "df_data = df_data.drop(['key_0', 'Kod_wyna'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data = df_data.merge(df_fina_1, left_on=[df_data['Kod'].str.slice(stop=-1), 'Rok'], right_on=[df_fina_1['Kod'].str.slice(stop=-1), 'Rok'], how='left', suffixes=(None, '_fina_1'))\n",
    "df_data = df_data.drop(['key_0', 'Kod_fina_1'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data = df_data.merge(df_fina_2, left_on=[df_data['Kod'].str.slice(stop=-1), 'Rok'], right_on=[df_fina_2['Kod'].str.slice(stop=-1), 'Rok'], how='left', suffixes=(None, '_fina_2'))\n",
    "df_data = df_data.drop(['key_0', 'Kod_fina_2'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Kod</th>\n",
       "      <th>Rok</th>\n",
       "      <th>Suma</th>\n",
       "      <th>Powierzchnia</th>\n",
       "      <th>Wynagrodzenie_ogolem</th>\n",
       "      <th>Wynagrodzenie_w_relacji_do_sredniej</th>\n",
       "      <th>Dochody_podatek_lesny</th>\n",
       "      <th>Dochody_podatek_PCC</th>\n",
       "      <th>Dochody_podatek_...</th>\n",
       "      <th>Dochody_podatek_od_nieruchomosci</th>\n",
       "      <th>...</th>\n",
       "      <th>Dochody_z_uslug</th>\n",
       "      <th>Dochody_dofinansowanie_inwestycyjne</th>\n",
       "      <th>Dochody_dofinansowanie_razem</th>\n",
       "      <th>Udzialy_w_podatkach_dochodowych_od_osob_fizycznych</th>\n",
       "      <th>Udzialy_w_podatkach_dochodowych_od_osob_prywatnych</th>\n",
       "      <th>Udzialy_w_podatkach_dochodowych_razem</th>\n",
       "      <th>Wplywy_z_innych_lokalnych_oplat</th>\n",
       "      <th>Wplywy_z_oplaty_eksploatacyjnej</th>\n",
       "      <th>Wplywy_z_oplaty_skarbowej</th>\n",
       "      <th>Wplywy_z_oplaty_targowej</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2014</td>\n",
       "      <td>2482706.36</td>\n",
       "      <td>24.00</td>\n",
       "      <td>3422.90</td>\n",
       "      <td>85.50</td>\n",
       "      <td>8755.97</td>\n",
       "      <td>1530935.80</td>\n",
       "      <td>84220.54</td>\n",
       "      <td>23823448.76</td>\n",
       "      <td>...</td>\n",
       "      <td>2380938.91</td>\n",
       "      <td>61031.32</td>\n",
       "      <td>1900308.99</td>\n",
       "      <td>27297399.00</td>\n",
       "      <td>1984447.80</td>\n",
       "      <td>29281846.80</td>\n",
       "      <td>7018623.68</td>\n",
       "      <td>28867.32</td>\n",
       "      <td>928926.81</td>\n",
       "      <td>188736.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2016</td>\n",
       "      <td>1016449.03</td>\n",
       "      <td>24.00</td>\n",
       "      <td>3666.19</td>\n",
       "      <td>85.40</td>\n",
       "      <td>14900.55</td>\n",
       "      <td>1631451.83</td>\n",
       "      <td>77726.70</td>\n",
       "      <td>21961009.53</td>\n",
       "      <td>...</td>\n",
       "      <td>3748786.27</td>\n",
       "      <td>111299.61</td>\n",
       "      <td>284981.40</td>\n",
       "      <td>31878605.00</td>\n",
       "      <td>3726450.74</td>\n",
       "      <td>35605055.74</td>\n",
       "      <td>7277990.62</td>\n",
       "      <td>31466.01</td>\n",
       "      <td>475771.76</td>\n",
       "      <td>158803.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2017</td>\n",
       "      <td>1507540.44</td>\n",
       "      <td>24.00</td>\n",
       "      <td>3901.94</td>\n",
       "      <td>86.20</td>\n",
       "      <td>14988.07</td>\n",
       "      <td>2022884.74</td>\n",
       "      <td>66169.12</td>\n",
       "      <td>22107840.97</td>\n",
       "      <td>...</td>\n",
       "      <td>4137582.84</td>\n",
       "      <td>89949.86</td>\n",
       "      <td>118699.74</td>\n",
       "      <td>34702412.00</td>\n",
       "      <td>2536379.13</td>\n",
       "      <td>37238791.13</td>\n",
       "      <td>7339238.14</td>\n",
       "      <td>24998.04</td>\n",
       "      <td>511127.33</td>\n",
       "      <td>131562.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2018</td>\n",
       "      <td>1125087.75</td>\n",
       "      <td>24.00</td>\n",
       "      <td>4214.66</td>\n",
       "      <td>87.20</td>\n",
       "      <td>15221.03</td>\n",
       "      <td>2519471.86</td>\n",
       "      <td>74351.81</td>\n",
       "      <td>22767685.01</td>\n",
       "      <td>...</td>\n",
       "      <td>5556645.41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>24676.92</td>\n",
       "      <td>39128194.00</td>\n",
       "      <td>1506913.18</td>\n",
       "      <td>40635107.18</td>\n",
       "      <td>7494838.88</td>\n",
       "      <td>16194.57</td>\n",
       "      <td>479489.69</td>\n",
       "      <td>124935.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0201011</td>\n",
       "      <td>2020</td>\n",
       "      <td>9052911.45</td>\n",
       "      <td>24.00</td>\n",
       "      <td>4887.95</td>\n",
       "      <td>88.50</td>\n",
       "      <td>15459.78</td>\n",
       "      <td>2632509.99</td>\n",
       "      <td>74425.14</td>\n",
       "      <td>28336580.30</td>\n",
       "      <td>...</td>\n",
       "      <td>5344170.62</td>\n",
       "      <td>2640028.00</td>\n",
       "      <td>2660441.20</td>\n",
       "      <td>40456699.00</td>\n",
       "      <td>2143819.12</td>\n",
       "      <td>42600518.12</td>\n",
       "      <td>7627128.14</td>\n",
       "      <td>5661.00</td>\n",
       "      <td>440259.90</td>\n",
       "      <td>62502.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9723</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2017</td>\n",
       "      <td>467956789.99</td>\n",
       "      <td>197.00</td>\n",
       "      <td>4536.08</td>\n",
       "      <td>100.20</td>\n",
       "      <td>150527.43</td>\n",
       "      <td>5163900.56</td>\n",
       "      <td>587305.94</td>\n",
       "      <td>74099232.11</td>\n",
       "      <td>...</td>\n",
       "      <td>1859435.58</td>\n",
       "      <td>20000.18</td>\n",
       "      <td>212570.70</td>\n",
       "      <td>47760120.00</td>\n",
       "      <td>1199589.08</td>\n",
       "      <td>48959709.08</td>\n",
       "      <td>10930683.15</td>\n",
       "      <td>38789.78</td>\n",
       "      <td>404331.07</td>\n",
       "      <td>622509.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9724</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2018</td>\n",
       "      <td>11972196.58</td>\n",
       "      <td>202.00</td>\n",
       "      <td>4779.09</td>\n",
       "      <td>98.80</td>\n",
       "      <td>154462.39</td>\n",
       "      <td>5361951.37</td>\n",
       "      <td>572868.36</td>\n",
       "      <td>108107448.79</td>\n",
       "      <td>...</td>\n",
       "      <td>1996824.80</td>\n",
       "      <td>25285.92</td>\n",
       "      <td>237485.34</td>\n",
       "      <td>52799183.00</td>\n",
       "      <td>2690098.17</td>\n",
       "      <td>55489281.17</td>\n",
       "      <td>10458871.30</td>\n",
       "      <td>4684.54</td>\n",
       "      <td>434077.88</td>\n",
       "      <td>608625.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9725</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2019</td>\n",
       "      <td>2074346.69</td>\n",
       "      <td>202.00</td>\n",
       "      <td>5222.62</td>\n",
       "      <td>100.80</td>\n",
       "      <td>150329.31</td>\n",
       "      <td>6088184.20</td>\n",
       "      <td>468411.51</td>\n",
       "      <td>38527846.59</td>\n",
       "      <td>...</td>\n",
       "      <td>2187576.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>225831.84</td>\n",
       "      <td>55319040.00</td>\n",
       "      <td>2770684.17</td>\n",
       "      <td>58089724.17</td>\n",
       "      <td>11369287.11</td>\n",
       "      <td>3456.95</td>\n",
       "      <td>415686.53</td>\n",
       "      <td>610059.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9726</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2020</td>\n",
       "      <td>8314185.11</td>\n",
       "      <td>202.00</td>\n",
       "      <td>5517.68</td>\n",
       "      <td>99.90</td>\n",
       "      <td>156556.52</td>\n",
       "      <td>5125090.74</td>\n",
       "      <td>329522.12</td>\n",
       "      <td>78767466.83</td>\n",
       "      <td>...</td>\n",
       "      <td>1917372.55</td>\n",
       "      <td>21002107.00</td>\n",
       "      <td>21192313.05</td>\n",
       "      <td>53739656.00</td>\n",
       "      <td>3144444.38</td>\n",
       "      <td>56884100.38</td>\n",
       "      <td>12281916.71</td>\n",
       "      <td>5157.50</td>\n",
       "      <td>355201.29</td>\n",
       "      <td>507341.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9727</th>\n",
       "      <td>3263011</td>\n",
       "      <td>2021</td>\n",
       "      <td>752819.71</td>\n",
       "      <td>202.00</td>\n",
       "      <td>5564.41</td>\n",
       "      <td>92.70</td>\n",
       "      <td>163778.36</td>\n",
       "      <td>9082482.28</td>\n",
       "      <td>492045.28</td>\n",
       "      <td>78491368.35</td>\n",
       "      <td>...</td>\n",
       "      <td>4110105.72</td>\n",
       "      <td>888293.63</td>\n",
       "      <td>1072910.83</td>\n",
       "      <td>63936763.00</td>\n",
       "      <td>3975531.95</td>\n",
       "      <td>67912294.95</td>\n",
       "      <td>17127683.55</td>\n",
       "      <td>27746.70</td>\n",
       "      <td>416473.03</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9728 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Kod   Rok         Suma  Powierzchnia  Wynagrodzenie_ogolem   \n",
       "0     0201011  2014   2482706.36         24.00               3422.90  \\\n",
       "1     0201011  2016   1016449.03         24.00               3666.19   \n",
       "2     0201011  2017   1507540.44         24.00               3901.94   \n",
       "3     0201011  2018   1125087.75         24.00               4214.66   \n",
       "4     0201011  2020   9052911.45         24.00               4887.95   \n",
       "...       ...   ...          ...           ...                   ...   \n",
       "9723  3263011  2017 467956789.99        197.00               4536.08   \n",
       "9724  3263011  2018  11972196.58        202.00               4779.09   \n",
       "9725  3263011  2019   2074346.69        202.00               5222.62   \n",
       "9726  3263011  2020   8314185.11        202.00               5517.68   \n",
       "9727  3263011  2021    752819.71        202.00               5564.41   \n",
       "\n",
       "      Wynagrodzenie_w_relacji_do_sredniej  Dochody_podatek_lesny   \n",
       "0                                   85.50                8755.97  \\\n",
       "1                                   85.40               14900.55   \n",
       "2                                   86.20               14988.07   \n",
       "3                                   87.20               15221.03   \n",
       "4                                   88.50               15459.78   \n",
       "...                                   ...                    ...   \n",
       "9723                               100.20              150527.43   \n",
       "9724                                98.80              154462.39   \n",
       "9725                               100.80              150329.31   \n",
       "9726                                99.90              156556.52   \n",
       "9727                                92.70              163778.36   \n",
       "\n",
       "      Dochody_podatek_PCC  Dochody_podatek_...   \n",
       "0              1530935.80             84220.54  \\\n",
       "1              1631451.83             77726.70   \n",
       "2              2022884.74             66169.12   \n",
       "3              2519471.86             74351.81   \n",
       "4              2632509.99             74425.14   \n",
       "...                   ...                  ...   \n",
       "9723           5163900.56            587305.94   \n",
       "9724           5361951.37            572868.36   \n",
       "9725           6088184.20            468411.51   \n",
       "9726           5125090.74            329522.12   \n",
       "9727           9082482.28            492045.28   \n",
       "\n",
       "      Dochody_podatek_od_nieruchomosci  ...  Dochody_z_uslug   \n",
       "0                          23823448.76  ...       2380938.91  \\\n",
       "1                          21961009.53  ...       3748786.27   \n",
       "2                          22107840.97  ...       4137582.84   \n",
       "3                          22767685.01  ...       5556645.41   \n",
       "4                          28336580.30  ...       5344170.62   \n",
       "...                                ...  ...              ...   \n",
       "9723                       74099232.11  ...       1859435.58   \n",
       "9724                      108107448.79  ...       1996824.80   \n",
       "9725                       38527846.59  ...       2187576.47   \n",
       "9726                       78767466.83  ...       1917372.55   \n",
       "9727                       78491368.35  ...       4110105.72   \n",
       "\n",
       "      Dochody_dofinansowanie_inwestycyjne  Dochody_dofinansowanie_razem   \n",
       "0                                61031.32                    1900308.99  \\\n",
       "1                               111299.61                     284981.40   \n",
       "2                                89949.86                     118699.74   \n",
       "3                                    0.00                      24676.92   \n",
       "4                              2640028.00                    2660441.20   \n",
       "...                                   ...                           ...   \n",
       "9723                             20000.18                     212570.70   \n",
       "9724                             25285.92                     237485.34   \n",
       "9725                                 0.00                     225831.84   \n",
       "9726                          21002107.00                   21192313.05   \n",
       "9727                            888293.63                    1072910.83   \n",
       "\n",
       "      Udzialy_w_podatkach_dochodowych_od_osob_fizycznych   \n",
       "0                                           27297399.00   \\\n",
       "1                                           31878605.00    \n",
       "2                                           34702412.00    \n",
       "3                                           39128194.00    \n",
       "4                                           40456699.00    \n",
       "...                                                 ...    \n",
       "9723                                        47760120.00    \n",
       "9724                                        52799183.00    \n",
       "9725                                        55319040.00    \n",
       "9726                                        53739656.00    \n",
       "9727                                        63936763.00    \n",
       "\n",
       "      Udzialy_w_podatkach_dochodowych_od_osob_prywatnych   \n",
       "0                                            1984447.80   \\\n",
       "1                                            3726450.74    \n",
       "2                                            2536379.13    \n",
       "3                                            1506913.18    \n",
       "4                                            2143819.12    \n",
       "...                                                 ...    \n",
       "9723                                         1199589.08    \n",
       "9724                                         2690098.17    \n",
       "9725                                         2770684.17    \n",
       "9726                                         3144444.38    \n",
       "9727                                         3975531.95    \n",
       "\n",
       "      Udzialy_w_podatkach_dochodowych_razem  Wplywy_z_innych_lokalnych_oplat   \n",
       "0                               29281846.80                       7018623.68  \\\n",
       "1                               35605055.74                       7277990.62   \n",
       "2                               37238791.13                       7339238.14   \n",
       "3                               40635107.18                       7494838.88   \n",
       "4                               42600518.12                       7627128.14   \n",
       "...                                     ...                              ...   \n",
       "9723                            48959709.08                      10930683.15   \n",
       "9724                            55489281.17                      10458871.30   \n",
       "9725                            58089724.17                      11369287.11   \n",
       "9726                            56884100.38                      12281916.71   \n",
       "9727                            67912294.95                      17127683.55   \n",
       "\n",
       "      Wplywy_z_oplaty_eksploatacyjnej  Wplywy_z_oplaty_skarbowej   \n",
       "0                            28867.32                  928926.81  \\\n",
       "1                            31466.01                  475771.76   \n",
       "2                            24998.04                  511127.33   \n",
       "3                            16194.57                  479489.69   \n",
       "4                             5661.00                  440259.90   \n",
       "...                               ...                        ...   \n",
       "9723                         38789.78                  404331.07   \n",
       "9724                          4684.54                  434077.88   \n",
       "9725                          3456.95                  415686.53   \n",
       "9726                          5157.50                  355201.29   \n",
       "9727                         27746.70                  416473.03   \n",
       "\n",
       "      Wplywy_z_oplaty_targowej  \n",
       "0                    188736.80  \n",
       "1                    158803.00  \n",
       "2                    131562.90  \n",
       "3                    124935.70  \n",
       "4                     62502.50  \n",
       "...                        ...  \n",
       "9723                 622509.60  \n",
       "9724                 608625.90  \n",
       "9725                 610059.50  \n",
       "9726                 507341.00  \n",
       "9727                      0.00  \n",
       "\n",
       "[9728 rows x 27 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_data[df_data.isna().any(axis=1)]  # ['Rok'].drop_duplicates().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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