main.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1f4e27f1",
   "metadata": {},
   "source": [
    "# The Visualization of the Progress of the Philippines' Sustainable Development Goals (SDGs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "190decc7",
   "metadata": {},
   "source": [
    "## Requirements and Imports\n",
    "Before starting, the relevant libraries and files in building and training the model should be loaded into the notebook first."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21152ad7",
   "metadata": {},
   "source": [
    "### Basic Libraries\n",
    "Several libraries are required to perform a thorough analysis of the dataset. Each of these libraries will be imported and described below:\n",
    "* `pandas` contains a large collection of mathematical functions\n",
    "* `numpy` contains functions that are designed for data manipulation and data analysis\n",
    "* `geopandas` contains functionalities that make operations easier on spatial database \n",
    "* `matplotlib.pyplot` contains functions to create interactive plots\n",
    "* `shapely.geometry` contain functions that allow the modification and inspection of geometric objections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f651dcb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from shapely.geometry import Point\n",
    "\n",
    "%pylab inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a1fd8de",
   "metadata": {},
   "source": [
    "### Datasets and Files\n",
    "\n",
    "There are two files that we would need to import through the use of [`read_csv`](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html) for this project. First is the `combined_data.csv`, which holds the information on the progress of the Philippines on the Sustainable Development Goals. Note that this data includes the data per region and for the country (i.e., national data)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bb1e13cc",
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net SHS Enrolment Rate</th>\n",
       "      <th>...</th>\n",
       "      <th>Gross Capital Formation</th>\n",
       "      <th>GRDP</th>\n",
       "      <th>Population</th>\n",
       "      <th>Primary Drop-out rate</th>\n",
       "      <th>Primary Drop-out rate (Girls)</th>\n",
       "      <th>Primary Drop-out rate (Boys)</th>\n",
       "      <th>Secondary Drop-out rate</th>\n",
       "      <th>Secondary Drop-out rate (Girls)</th>\n",
       "      <th>Secondary Drop-out rate (Boys)</th>\n",
       "      <th>Price Index for Agriculture</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.77</td>\n",
       "      <td>97.28</td>\n",
       "      <td>96.27</td>\n",
       "      <td>66.06</td>\n",
       "      <td>69.49</td>\n",
       "      <td>62.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>579938180.0</td>\n",
       "      <td>3.697556e+09</td>\n",
       "      <td>76723051.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101.00</td>\n",
       "      <td>101.92</td>\n",
       "      <td>100.13</td>\n",
       "      <td>79.05</td>\n",
       "      <td>79.50</td>\n",
       "      <td>78.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>203930819.0</td>\n",
       "      <td>1.237451e+09</td>\n",
       "      <td>9961971.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.42</td>\n",
       "      <td>94.58</td>\n",
       "      <td>94.26</td>\n",
       "      <td>71.19</td>\n",
       "      <td>76.37</td>\n",
       "      <td>66.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13865180.0</td>\n",
       "      <td>9.044601e+07</td>\n",
       "      <td>1369249.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.73</td>\n",
       "      <td>97.01</td>\n",
       "      <td>98.41</td>\n",
       "      <td>87.51</td>\n",
       "      <td>90.05</td>\n",
       "      <td>85.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24454284.0</td>\n",
       "      <td>1.289450e+08</td>\n",
       "      <td>4209083.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.65</td>\n",
       "      <td>95.74</td>\n",
       "      <td>95.57</td>\n",
       "      <td>77.11</td>\n",
       "      <td>81.11</td>\n",
       "      <td>73.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>32773347.0</td>\n",
       "      <td>8.593798e+07</td>\n",
       "      <td>2819641.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\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",
       "      <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>391</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>164566009.0</td>\n",
       "      <td>9.492320e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>257595240.0</td>\n",
       "      <td>9.672276e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>87077953.0</td>\n",
       "      <td>5.039756e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>100730468.0</td>\n",
       "      <td>3.317629e+08</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>47527167.0</td>\n",
       "      <td>2.846570e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>396 rows × 53 columns</p>\n",
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      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "0                                          PHILIPPINES  2000   \n",
       "1                         NCR: National Capital Region  2000   \n",
       "2                CAR: Cordillera Administrative Region  2000   \n",
       "3                              Region 1: Ilocos Region  2000   \n",
       "4                             Region 2: Cagayan Valley  2000   \n",
       "..                                                 ...   ...   \n",
       "391                       Region 10: Northern Mindanao  2021   \n",
       "392                            Region 11: Davao Region  2021   \n",
       "393                            Region 12: SOCCSKSARGEN  2021   \n",
       "394               CARAGA: CARAGA Administrative Region  2021   \n",
       "395  BARMM: Bangsamoro Autonomous Region in Muslim ...  2021   \n",
       "\n",
       "     1.2.1 Poverty Proportion  1.4.1 Net Elem Enrolment Rate  \\\n",
       "0                         NaN                          96.77   \n",
       "1                         NaN                         101.00   \n",
       "2                         NaN                          94.42   \n",
       "3                         NaN                          97.73   \n",
       "4                         NaN                          95.65   \n",
       "..                        ...                            ...   \n",
       "391                       NaN                            NaN   \n",
       "392                       NaN                            NaN   \n",
       "393                       NaN                            NaN   \n",
       "394                       NaN                            NaN   \n",
       "395                       NaN                            NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Girls)  \\\n",
       "0                                    97.28   \n",
       "1                                   101.92   \n",
       "2                                    94.58   \n",
       "3                                    97.01   \n",
       "4                                    95.74   \n",
       "..                                     ...   \n",
       "391                                    NaN   \n",
       "392                                    NaN   \n",
       "393                                    NaN   \n",
       "394                                    NaN   \n",
       "395                                    NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Boys)  1.4.1 Net JHS Enrolment Rate  \\\n",
       "0                                   96.27                         66.06   \n",
       "1                                  100.13                         79.05   \n",
       "2                                   94.26                         71.19   \n",
       "3                                   98.41                         87.51   \n",
       "4                                   95.57                         77.11   \n",
       "..                                    ...                           ...   \n",
       "391                                   NaN                           NaN   \n",
       "392                                   NaN                           NaN   \n",
       "393                                   NaN                           NaN   \n",
       "394                                   NaN                           NaN   \n",
       "395                                   NaN                           NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Girls)  \\\n",
       "0                                   69.49   \n",
       "1                                   79.50   \n",
       "2                                   76.37   \n",
       "3                                   90.05   \n",
       "4                                   81.11   \n",
       "..                                    ...   \n",
       "391                                   NaN   \n",
       "392                                   NaN   \n",
       "393                                   NaN   \n",
       "394                                   NaN   \n",
       "395                                   NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Boys)  1.4.1 Net SHS Enrolment Rate  ...  \\\n",
       "0                                  62.72                           NaN  ...   \n",
       "1                                  78.57                           NaN  ...   \n",
       "2                                  66.14                           NaN  ...   \n",
       "3                                  85.07                           NaN  ...   \n",
       "4                                  73.31                           NaN  ...   \n",
       "..                                   ...                           ...  ...   \n",
       "391                                  NaN                           NaN  ...   \n",
       "392                                  NaN                           NaN  ...   \n",
       "393                                  NaN                           NaN  ...   \n",
       "394                                  NaN                           NaN  ...   \n",
       "395                                  NaN                           NaN  ...   \n",
       "\n",
       "     Gross Capital Formation          GRDP  Population  Primary Drop-out rate  \\\n",
       "0                579938180.0  3.697556e+09  76723051.0                    NaN   \n",
       "1                203930819.0  1.237451e+09   9961971.0                    NaN   \n",
       "2                 13865180.0  9.044601e+07   1369249.0                    NaN   \n",
       "3                 24454284.0  1.289450e+08   4209083.0                    NaN   \n",
       "4                 32773347.0  8.593798e+07   2819641.0                    NaN   \n",
       "..                       ...           ...         ...                    ...   \n",
       "391              164566009.0  9.492320e+08         NaN                    NaN   \n",
       "392              257595240.0  9.672276e+08         NaN                    NaN   \n",
       "393               87077953.0  5.039756e+08         NaN                    NaN   \n",
       "394              100730468.0  3.317629e+08         NaN                    NaN   \n",
       "395               47527167.0  2.846570e+08         NaN                    NaN   \n",
       "\n",
       "     Primary Drop-out rate (Girls)  Primary Drop-out rate (Boys)  \\\n",
       "0                              NaN                           NaN   \n",
       "1                              NaN                           NaN   \n",
       "2                              NaN                           NaN   \n",
       "3                              NaN                           NaN   \n",
       "4                              NaN                           NaN   \n",
       "..                             ...                           ...   \n",
       "391                            NaN                           NaN   \n",
       "392                            NaN                           NaN   \n",
       "393                            NaN                           NaN   \n",
       "394                            NaN                           NaN   \n",
       "395                            NaN                           NaN   \n",
       "\n",
       "     Secondary Drop-out rate  Secondary Drop-out rate (Girls)  \\\n",
       "0                        NaN                              NaN   \n",
       "1                        NaN                              NaN   \n",
       "2                        NaN                              NaN   \n",
       "3                        NaN                              NaN   \n",
       "4                        NaN                              NaN   \n",
       "..                       ...                              ...   \n",
       "391                      NaN                              NaN   \n",
       "392                      NaN                              NaN   \n",
       "393                      NaN                              NaN   \n",
       "394                      NaN                              NaN   \n",
       "395                      NaN                              NaN   \n",
       "\n",
       "     Secondary Drop-out rate (Boys)  Price Index for Agriculture  \n",
       "0                               NaN                          NaN  \n",
       "1                               NaN                          NaN  \n",
       "2                               NaN                          NaN  \n",
       "3                               NaN                          NaN  \n",
       "4                               NaN                          NaN  \n",
       "..                              ...                          ...  \n",
       "391                             NaN                      107.975  \n",
       "392                             NaN                      110.850  \n",
       "393                             NaN                      103.350  \n",
       "394                             NaN                      104.525  \n",
       "395                             NaN                       91.950  \n",
       "\n",
       "[396 rows x 53 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = 'https://raw.githubusercontent.com/francheska-vicente/datapre-project/main_v2/data_output/combined_data.csv'\n",
    "sdg_data = pd.read_csv (url)\n",
    "sdg_data "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aeb7e23f",
   "metadata": {},
   "source": [
    "Second is the file that holds the geospatial information of the regions of the Philippines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d91df069",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>ADM1_EN</th>\n",
       "      <th>ADM1_PCODE</th>\n",
       "      <th>ADM1_REF</th>\n",
       "      <th>ADM1ALT1EN</th>\n",
       "      <th>ADM1ALT2EN</th>\n",
       "      <th>ADM0_EN</th>\n",
       "      <th>ADM0_PCODE</th>\n",
       "      <th>date</th>\n",
       "      <th>validOn</th>\n",
       "      <th>validTo</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>Bangsamoro Autonomous Region in Muslim Mindanao</td>\n",
       "      <td>PH150000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BARMM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>Cordillera Administrative Region</td>\n",
       "      <td>PH140000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((121.22208 18.50058, 121.22086 18.483...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>National Capital Region</td>\n",
       "      <td>PH130000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NCR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((121.03842 14.78525, 121.03876 14.785...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>Region I</td>\n",
       "      <td>PH010000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ilocos Region</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>Region II</td>\n",
       "      <td>PH020000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>Region III</td>\n",
       "      <td>PH030000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Central Luzon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>27.624115</td>\n",
       "      <td>1.326710</td>\n",
       "      <td>Region IV-A</td>\n",
       "      <td>PH040000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Calabarzon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>78.804542</td>\n",
       "      <td>2.220374</td>\n",
       "      <td>Region IV-B</td>\n",
       "      <td>PH170000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mimaropa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>23.181441</td>\n",
       "      <td>1.196677</td>\n",
       "      <td>Region IX</td>\n",
       "      <td>PH090000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Zamboanga Peninsula</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>44.923243</td>\n",
       "      <td>1.446324</td>\n",
       "      <td>Region V</td>\n",
       "      <td>PH050000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bicol Region</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>27.589382</td>\n",
       "      <td>1.657135</td>\n",
       "      <td>Region VI</td>\n",
       "      <td>PH060000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Western Visayas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>29.113105</td>\n",
       "      <td>1.178431</td>\n",
       "      <td>Region VII</td>\n",
       "      <td>PH070000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Central Visayas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>42.021179</td>\n",
       "      <td>1.726804</td>\n",
       "      <td>Region VIII</td>\n",
       "      <td>PH080000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Visayas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>Region X</td>\n",
       "      <td>PH100000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>Region XI</td>\n",
       "      <td>PH110000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Davao Region</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>Region XII</td>\n",
       "      <td>PH120000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Soccsksargen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>Region XIII</td>\n",
       "      <td>PH160000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Caraga</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shape_Leng  Shape_Area                                          ADM1_EN  \\\n",
       "0    53.623497    1.050272  Bangsamoro Autonomous Region in Muslim Mindanao   \n",
       "1     8.027454    1.546712                 Cordillera Administrative Region   \n",
       "2     2.320234    0.050216                          National Capital Region   \n",
       "3    14.995101    1.043983                                         Region I   \n",
       "4    19.139048    2.241812                                        Region II   \n",
       "5    15.949563    1.793513                                       Region III   \n",
       "6    27.624115    1.326710                                      Region IV-A   \n",
       "7    78.804542    2.220374                                      Region IV-B   \n",
       "8    23.181441    1.196677                                        Region IX   \n",
       "9    44.923243    1.446324                                         Region V   \n",
       "10   27.589382    1.657135                                        Region VI   \n",
       "11   29.113105    1.178431                                       Region VII   \n",
       "12   42.021179    1.726804                                      Region VIII   \n",
       "13   15.002953    1.435115                                         Region X   \n",
       "14   17.934222    1.539971                                        Region XI   \n",
       "15   13.229749    1.471068                                       Region XII   \n",
       "16   28.166754    1.540820                                      Region XIII   \n",
       "\n",
       "     ADM1_PCODE  ADM1_REF           ADM1ALT1EN  ADM1ALT2EN            ADM0_EN  \\\n",
       "0   PH150000000       NaN                BARMM         NaN  Philippines (the)   \n",
       "1   PH140000000       NaN                  CAR         NaN  Philippines (the)   \n",
       "2   PH130000000       NaN                  NCR         NaN  Philippines (the)   \n",
       "3   PH010000000       NaN        Ilocos Region         NaN  Philippines (the)   \n",
       "4   PH020000000       NaN       Cagayan Valley         NaN  Philippines (the)   \n",
       "5   PH030000000       NaN        Central Luzon         NaN  Philippines (the)   \n",
       "6   PH040000000       NaN           Calabarzon         NaN  Philippines (the)   \n",
       "7   PH170000000       NaN             Mimaropa         NaN  Philippines (the)   \n",
       "8   PH090000000       NaN  Zamboanga Peninsula         NaN  Philippines (the)   \n",
       "9   PH050000000       NaN         Bicol Region         NaN  Philippines (the)   \n",
       "10  PH060000000       NaN      Western Visayas         NaN  Philippines (the)   \n",
       "11  PH070000000       NaN      Central Visayas         NaN  Philippines (the)   \n",
       "12  PH080000000       NaN      Eastern Visayas         NaN  Philippines (the)   \n",
       "13  PH100000000       NaN    Northern Mindanao         NaN  Philippines (the)   \n",
       "14  PH110000000       NaN         Davao Region         NaN  Philippines (the)   \n",
       "15  PH120000000       NaN         Soccsksargen         NaN  Philippines (the)   \n",
       "16  PH160000000       NaN               Caraga         NaN  Philippines (the)   \n",
       "\n",
       "   ADM0_PCODE        date     validOn  validTo  \\\n",
       "0          PH  2016-06-30  2020-05-29      NaN   \n",
       "1          PH  2016-06-30  2020-05-29      NaN   \n",
       "2          PH  2016-06-30  2020-05-29      NaN   \n",
       "3          PH  2016-06-30  2020-05-29      NaN   \n",
       "4          PH  2016-06-30  2020-05-29      NaN   \n",
       "5          PH  2016-06-30  2020-05-29      NaN   \n",
       "6          PH  2016-06-30  2020-05-29      NaN   \n",
       "7          PH  2016-06-30  2020-05-29      NaN   \n",
       "8          PH  2016-06-30  2020-05-29      NaN   \n",
       "9          PH  2016-06-30  2020-05-29      NaN   \n",
       "10         PH  2016-06-30  2020-05-29      NaN   \n",
       "11         PH  2016-06-30  2020-05-29      NaN   \n",
       "12         PH  2016-06-30  2020-05-29      NaN   \n",
       "13         PH  2016-06-30  2020-05-29      NaN   \n",
       "14         PH  2016-06-30  2020-05-29      NaN   \n",
       "15         PH  2016-06-30  2020-05-29      NaN   \n",
       "16         PH  2016-06-30  2020-05-29      NaN   \n",
       "\n",
       "                                             geometry  \n",
       "0   MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...  \n",
       "1   POLYGON ((121.22208 18.50058, 121.22086 18.483...  \n",
       "2   POLYGON ((121.03842 14.78525, 121.03876 14.785...  \n",
       "3   MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...  \n",
       "4   MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...  \n",
       "5   MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...  \n",
       "6   MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...  \n",
       "7   MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...  \n",
       "8   MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...  \n",
       "9   MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...  \n",
       "10  MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...  \n",
       "11  MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...  \n",
       "12  MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...  \n",
       "13  MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...  \n",
       "14  MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...  \n",
       "15  MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...  \n",
       "16  MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_geo_data = gpd.read_file('./data/phl_adminboundaries_candidate_exclude_adm3/phl_admbnda_adm1_psa_namria_20200529.shp')\n",
    "regional_geo_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abcdddc6",
   "metadata": {},
   "source": [
    "## Data Cleaning and Pre-processing\n",
    "Once we have imported the files that we would need, we would need to the clean and pre-process the dataset so that the two dataset could be combined.\n",
    "\n",
    "Since we would be combining the two datasets based on the regions, let us first see values of the `ADM1_EN` column ni the geospatial data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "110cd892",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     Bangsamoro Autonomous Region in Muslim Mindanao\n",
       "1                    Cordillera Administrative Region\n",
       "2                             National Capital Region\n",
       "3                                            Region I\n",
       "4                                           Region II\n",
       "5                                          Region III\n",
       "6                                         Region IV-A\n",
       "7                                         Region IV-B\n",
       "8                                           Region IX\n",
       "9                                            Region V\n",
       "10                                          Region VI\n",
       "11                                         Region VII\n",
       "12                                        Region VIII\n",
       "13                                           Region X\n",
       "14                                          Region XI\n",
       "15                                         Region XII\n",
       "16                                        Region XIII\n",
       "Name: ADM1_EN, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_geo_data ['ADM1_EN']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4092e194",
   "metadata": {},
   "source": [
    "Next, we will also need to look at the values for the region column (i.e., `Geolocation`) in the data on the SDG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8a62eb24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['PHILIPPINES', 'NCR: National Capital Region',\n",
       "       'CAR: Cordillera Administrative Region', 'Region 1: Ilocos Region',\n",
       "       'Region 2: Cagayan Valley', 'Region 3: Central Luzon',\n",
       "       'Region 4A: CALABARZON', 'MIMAROPA: Southwestern Tagalog Region',\n",
       "       'Region 5: Bicol Region', 'Region 6: Western Visayas',\n",
       "       'Region 7: Central Visayas', 'Region 8: Eastern Visayas',\n",
       "       'Region 9: Zamboanga Peninsula', 'Region 10: Northern Mindanao',\n",
       "       'Region 11: Davao Region', 'Region 12: SOCCSKSARGEN',\n",
       "       'CARAGA: CARAGA Administrative Region',\n",
       "       'BARMM: Bangsamoro Autonomous Region in Muslim Mindanao'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdg_data ['Geolocation'].unique ()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50442ac1",
   "metadata": {},
   "source": [
    "From these, we can see that they have different arrangement of the regions, and the region names are also formatted differently. Thus, we cannot directly merge the two DataFrames. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d87dbbe9",
   "metadata": {},
   "source": [
    "### Separation of the National and Regional DataFrames\n",
    "\n",
    "In the values of `Geolocation` for the SDG dataset, we can see that there is the value **PHILIPPINES**, which holds the national data for the SDGs. As this is not part of the geospatial dataset, we would be separating this from the regional data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c90fbe41",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net SHS Enrolment Rate</th>\n",
       "      <th>...</th>\n",
       "      <th>Gross Capital Formation</th>\n",
       "      <th>GRDP</th>\n",
       "      <th>Population</th>\n",
       "      <th>Primary Drop-out rate</th>\n",
       "      <th>Primary Drop-out rate (Girls)</th>\n",
       "      <th>Primary Drop-out rate (Boys)</th>\n",
       "      <th>Secondary Drop-out rate</th>\n",
       "      <th>Secondary Drop-out rate (Girls)</th>\n",
       "      <th>Secondary Drop-out rate (Boys)</th>\n",
       "      <th>Price Index for Agriculture</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.7700</td>\n",
       "      <td>97.2800</td>\n",
       "      <td>96.2700</td>\n",
       "      <td>66.0600</td>\n",
       "      <td>69.4900</td>\n",
       "      <td>62.7200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.799382e+08</td>\n",
       "      <td>3.697556e+09</td>\n",
       "      <td>76723051.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.1000</td>\n",
       "      <td>90.9100</td>\n",
       "      <td>89.3300</td>\n",
       "      <td>57.5500</td>\n",
       "      <td>62.2400</td>\n",
       "      <td>52.9600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>7.624295e+08</td>\n",
       "      <td>4.024399e+09</td>\n",
       "      <td>78273584.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.2900</td>\n",
       "      <td>91.1000</td>\n",
       "      <td>89.5100</td>\n",
       "      <td>59.0000</td>\n",
       "      <td>63.7200</td>\n",
       "      <td>54.3900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.900870e+08</td>\n",
       "      <td>4.350560e+09</td>\n",
       "      <td>79832103.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88.7400</td>\n",
       "      <td>89.6800</td>\n",
       "      <td>87.8400</td>\n",
       "      <td>60.1500</td>\n",
       "      <td>65.0700</td>\n",
       "      <td>55.3400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9.213284e+08</td>\n",
       "      <td>4.717809e+09</td>\n",
       "      <td>81398610.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.1100</td>\n",
       "      <td>88.0800</td>\n",
       "      <td>86.1700</td>\n",
       "      <td>59.9700</td>\n",
       "      <td>65.0100</td>\n",
       "      <td>55.0400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.103699e+09</td>\n",
       "      <td>5.323904e+09</td>\n",
       "      <td>82977428.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.4400</td>\n",
       "      <td>85.3500</td>\n",
       "      <td>83.5600</td>\n",
       "      <td>58.5400</td>\n",
       "      <td>63.5300</td>\n",
       "      <td>53.6500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.098634e+09</td>\n",
       "      <td>5.917282e+09</td>\n",
       "      <td>84559930.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2006</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83.2200</td>\n",
       "      <td>84.0800</td>\n",
       "      <td>82.3900</td>\n",
       "      <td>58.5900</td>\n",
       "      <td>63.4400</td>\n",
       "      <td>53.8500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.049071e+09</td>\n",
       "      <td>6.550417e+09</td>\n",
       "      <td>86150420.0</td>\n",
       "      <td>6.37</td>\n",
       "      <td>5.00</td>\n",
       "      <td>7.64</td>\n",
       "      <td>8.5</td>\n",
       "      <td>6.7</td>\n",
       "      <td>10.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.9300</td>\n",
       "      <td>85.8300</td>\n",
       "      <td>84.0700</td>\n",
       "      <td>60.2100</td>\n",
       "      <td>64.8700</td>\n",
       "      <td>55.6500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.160980e+09</td>\n",
       "      <td>7.198245e+09</td>\n",
       "      <td>87748896.0</td>\n",
       "      <td>5.99</td>\n",
       "      <td>4.72</td>\n",
       "      <td>7.17</td>\n",
       "      <td>7.5</td>\n",
       "      <td>5.6</td>\n",
       "      <td>9.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2008</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.1100</td>\n",
       "      <td>85.7000</td>\n",
       "      <td>84.5500</td>\n",
       "      <td>60.7400</td>\n",
       "      <td>65.1800</td>\n",
       "      <td>56.3900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.526893e+09</td>\n",
       "      <td>8.050201e+09</td>\n",
       "      <td>89359772.0</td>\n",
       "      <td>6.02</td>\n",
       "      <td>4.87</td>\n",
       "      <td>7.07</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.8</td>\n",
       "      <td>9.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.4800</td>\n",
       "      <td>90.7700</td>\n",
       "      <td>88.2600</td>\n",
       "      <td>59.8900</td>\n",
       "      <td>64.8200</td>\n",
       "      <td>55.1600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.462595e+09</td>\n",
       "      <td>8.390421e+09</td>\n",
       "      <td>90974244.0</td>\n",
       "      <td>6.28</td>\n",
       "      <td>4.93</td>\n",
       "      <td>7.52</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.2</td>\n",
       "      <td>9.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.9200</td>\n",
       "      <td>97.4700</td>\n",
       "      <td>94.4600</td>\n",
       "      <td>64.3000</td>\n",
       "      <td>69.7600</td>\n",
       "      <td>59.1100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.921414e+09</td>\n",
       "      <td>9.399451e+09</td>\n",
       "      <td>92596704.0</td>\n",
       "      <td>6.29</td>\n",
       "      <td>5.02</td>\n",
       "      <td>7.45</td>\n",
       "      <td>7.8</td>\n",
       "      <td>5.7</td>\n",
       "      <td>9.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.0400</td>\n",
       "      <td>99.3300</td>\n",
       "      <td>96.8400</td>\n",
       "      <td>65.1400</td>\n",
       "      <td>70.7500</td>\n",
       "      <td>59.8200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.103996e+09</td>\n",
       "      <td>1.014466e+10</td>\n",
       "      <td>94227150.0</td>\n",
       "      <td>6.36</td>\n",
       "      <td>5.18</td>\n",
       "      <td>7.45</td>\n",
       "      <td>7.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.2900</td>\n",
       "      <td>98.1100</td>\n",
       "      <td>96.5300</td>\n",
       "      <td>66.1700</td>\n",
       "      <td>71.9200</td>\n",
       "      <td>60.7400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.163532e+09</td>\n",
       "      <td>1.106059e+10</td>\n",
       "      <td>95870083.0</td>\n",
       "      <td>6.24</td>\n",
       "      <td>5.12</td>\n",
       "      <td>7.25</td>\n",
       "      <td>8.1</td>\n",
       "      <td>6.2</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.2000</td>\n",
       "      <td>97.6800</td>\n",
       "      <td>96.7400</td>\n",
       "      <td>67.8900</td>\n",
       "      <td>73.6900</td>\n",
       "      <td>62.4200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.487510e+09</td>\n",
       "      <td>1.205059e+10</td>\n",
       "      <td>97516526.0</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.04</td>\n",
       "      <td>5.59</td>\n",
       "      <td>7.6</td>\n",
       "      <td>5.8</td>\n",
       "      <td>9.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.1900</td>\n",
       "      <td>97.5300</td>\n",
       "      <td>96.8700</td>\n",
       "      <td>67.1900</td>\n",
       "      <td>73.0500</td>\n",
       "      <td>61.6800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.763393e+09</td>\n",
       "      <td>1.320683e+10</td>\n",
       "      <td>99170955.0</td>\n",
       "      <td>3.26</td>\n",
       "      <td>2.77</td>\n",
       "      <td>3.70</td>\n",
       "      <td>6.9</td>\n",
       "      <td>5.5</td>\n",
       "      <td>8.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2015</td>\n",
       "      <td>23.5</td>\n",
       "      <td>96.9000</td>\n",
       "      <td>97.1500</td>\n",
       "      <td>96.6600</td>\n",
       "      <td>73.5700</td>\n",
       "      <td>79.4200</td>\n",
       "      <td>68.0900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.975815e+09</td>\n",
       "      <td>1.394416e+10</td>\n",
       "      <td>100833371.0</td>\n",
       "      <td>2.69</td>\n",
       "      <td>2.01</td>\n",
       "      <td>3.30</td>\n",
       "      <td>6.6</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.1500</td>\n",
       "      <td>96.1200</td>\n",
       "      <td>96.1700</td>\n",
       "      <td>74.1900</td>\n",
       "      <td>79.9400</td>\n",
       "      <td>68.7900</td>\n",
       "      <td>37.38</td>\n",
       "      <td>...</td>\n",
       "      <td>3.725366e+09</td>\n",
       "      <td>1.513238e+10</td>\n",
       "      <td>102530196.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.1900</td>\n",
       "      <td>94.2700</td>\n",
       "      <td>94.1200</td>\n",
       "      <td>75.9900</td>\n",
       "      <td>81.4200</td>\n",
       "      <td>70.8800</td>\n",
       "      <td>46.12</td>\n",
       "      <td>...</td>\n",
       "      <td>4.231677e+09</td>\n",
       "      <td>1.655665e+10</td>\n",
       "      <td>104169230.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2018</td>\n",
       "      <td>16.7</td>\n",
       "      <td>94.0500</td>\n",
       "      <td>93.8500</td>\n",
       "      <td>94.2500</td>\n",
       "      <td>81.4100</td>\n",
       "      <td>85.8200</td>\n",
       "      <td>77.2400</td>\n",
       "      <td>51.24</td>\n",
       "      <td>...</td>\n",
       "      <td>4.959105e+09</td>\n",
       "      <td>1.826519e+10</td>\n",
       "      <td>105755180.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.9600</td>\n",
       "      <td>94.1500</td>\n",
       "      <td>93.7900</td>\n",
       "      <td>82.8900</td>\n",
       "      <td>87.2000</td>\n",
       "      <td>78.8000</td>\n",
       "      <td>47.76</td>\n",
       "      <td>...</td>\n",
       "      <td>5.153069e+09</td>\n",
       "      <td>1.951786e+10</td>\n",
       "      <td>107288150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.1064</td>\n",
       "      <td>89.2898</td>\n",
       "      <td>88.9318</td>\n",
       "      <td>81.4869</td>\n",
       "      <td>85.5003</td>\n",
       "      <td>77.6557</td>\n",
       "      <td>49.48</td>\n",
       "      <td>...</td>\n",
       "      <td>3.129566e+09</td>\n",
       "      <td>1.795157e+10</td>\n",
       "      <td>108771978.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.111887e+09</td>\n",
       "      <td>1.941057e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Geolocation  Year  1.2.1 Poverty Proportion  \\\n",
       "0   PHILIPPINES  2000                       NaN   \n",
       "1   PHILIPPINES  2001                       NaN   \n",
       "2   PHILIPPINES  2002                       NaN   \n",
       "3   PHILIPPINES  2003                       NaN   \n",
       "4   PHILIPPINES  2004                       NaN   \n",
       "5   PHILIPPINES  2005                       NaN   \n",
       "6   PHILIPPINES  2006                       NaN   \n",
       "7   PHILIPPINES  2007                       NaN   \n",
       "8   PHILIPPINES  2008                       NaN   \n",
       "9   PHILIPPINES  2009                       NaN   \n",
       "10  PHILIPPINES  2010                       NaN   \n",
       "11  PHILIPPINES  2011                       NaN   \n",
       "12  PHILIPPINES  2012                       NaN   \n",
       "13  PHILIPPINES  2013                       NaN   \n",
       "14  PHILIPPINES  2014                       NaN   \n",
       "15  PHILIPPINES  2015                      23.5   \n",
       "16  PHILIPPINES  2016                       NaN   \n",
       "17  PHILIPPINES  2017                       NaN   \n",
       "18  PHILIPPINES  2018                      16.7   \n",
       "19  PHILIPPINES  2019                       NaN   \n",
       "20  PHILIPPINES  2020                       NaN   \n",
       "21  PHILIPPINES  2021                       NaN   \n",
       "\n",
       "    1.4.1 Net Elem Enrolment Rate  1.4.1 Net Elem Enrolment Rate (Girls)  \\\n",
       "0                         96.7700                                97.2800   \n",
       "1                         90.1000                                90.9100   \n",
       "2                         90.2900                                91.1000   \n",
       "3                         88.7400                                89.6800   \n",
       "4                         87.1100                                88.0800   \n",
       "5                         84.4400                                85.3500   \n",
       "6                         83.2200                                84.0800   \n",
       "7                         84.9300                                85.8300   \n",
       "8                         85.1100                                85.7000   \n",
       "9                         89.4800                                90.7700   \n",
       "10                        95.9200                                97.4700   \n",
       "11                        98.0400                                99.3300   \n",
       "12                        97.2900                                98.1100   \n",
       "13                        97.2000                                97.6800   \n",
       "14                        97.1900                                97.5300   \n",
       "15                        96.9000                                97.1500   \n",
       "16                        96.1500                                96.1200   \n",
       "17                        94.1900                                94.2700   \n",
       "18                        94.0500                                93.8500   \n",
       "19                        93.9600                                94.1500   \n",
       "20                        89.1064                                89.2898   \n",
       "21                            NaN                                    NaN   \n",
       "\n",
       "    1.4.1 Net Elem Enrolment Rate (Boys)  1.4.1 Net JHS Enrolment Rate  \\\n",
       "0                                96.2700                       66.0600   \n",
       "1                                89.3300                       57.5500   \n",
       "2                                89.5100                       59.0000   \n",
       "3                                87.8400                       60.1500   \n",
       "4                                86.1700                       59.9700   \n",
       "5                                83.5600                       58.5400   \n",
       "6                                82.3900                       58.5900   \n",
       "7                                84.0700                       60.2100   \n",
       "8                                84.5500                       60.7400   \n",
       "9                                88.2600                       59.8900   \n",
       "10                               94.4600                       64.3000   \n",
       "11                               96.8400                       65.1400   \n",
       "12                               96.5300                       66.1700   \n",
       "13                               96.7400                       67.8900   \n",
       "14                               96.8700                       67.1900   \n",
       "15                               96.6600                       73.5700   \n",
       "16                               96.1700                       74.1900   \n",
       "17                               94.1200                       75.9900   \n",
       "18                               94.2500                       81.4100   \n",
       "19                               93.7900                       82.8900   \n",
       "20                               88.9318                       81.4869   \n",
       "21                                   NaN                           NaN   \n",
       "\n",
       "    1.4.1 Net JHS Enrolment Rate (Girls)  1.4.1 Net JHS Enrolment Rate (Boys)  \\\n",
       "0                                69.4900                              62.7200   \n",
       "1                                62.2400                              52.9600   \n",
       "2                                63.7200                              54.3900   \n",
       "3                                65.0700                              55.3400   \n",
       "4                                65.0100                              55.0400   \n",
       "5                                63.5300                              53.6500   \n",
       "6                                63.4400                              53.8500   \n",
       "7                                64.8700                              55.6500   \n",
       "8                                65.1800                              56.3900   \n",
       "9                                64.8200                              55.1600   \n",
       "10                               69.7600                              59.1100   \n",
       "11                               70.7500                              59.8200   \n",
       "12                               71.9200                              60.7400   \n",
       "13                               73.6900                              62.4200   \n",
       "14                               73.0500                              61.6800   \n",
       "15                               79.4200                              68.0900   \n",
       "16                               79.9400                              68.7900   \n",
       "17                               81.4200                              70.8800   \n",
       "18                               85.8200                              77.2400   \n",
       "19                               87.2000                              78.8000   \n",
       "20                               85.5003                              77.6557   \n",
       "21                                   NaN                                  NaN   \n",
       "\n",
       "    1.4.1 Net SHS Enrolment Rate  ...  Gross Capital Formation          GRDP  \\\n",
       "0                            NaN  ...             5.799382e+08  3.697556e+09   \n",
       "1                            NaN  ...             7.624295e+08  4.024399e+09   \n",
       "2                            NaN  ...             8.900870e+08  4.350560e+09   \n",
       "3                            NaN  ...             9.213284e+08  4.717809e+09   \n",
       "4                            NaN  ...             1.103699e+09  5.323904e+09   \n",
       "5                            NaN  ...             1.098634e+09  5.917282e+09   \n",
       "6                            NaN  ...             1.049071e+09  6.550417e+09   \n",
       "7                            NaN  ...             1.160980e+09  7.198245e+09   \n",
       "8                            NaN  ...             1.526893e+09  8.050201e+09   \n",
       "9                            NaN  ...             1.462595e+09  8.390421e+09   \n",
       "10                           NaN  ...             1.921414e+09  9.399451e+09   \n",
       "11                           NaN  ...             2.103996e+09  1.014466e+10   \n",
       "12                           NaN  ...             2.163532e+09  1.106059e+10   \n",
       "13                           NaN  ...             2.487510e+09  1.205059e+10   \n",
       "14                           NaN  ...             2.763393e+09  1.320683e+10   \n",
       "15                           NaN  ...             2.975815e+09  1.394416e+10   \n",
       "16                         37.38  ...             3.725366e+09  1.513238e+10   \n",
       "17                         46.12  ...             4.231677e+09  1.655665e+10   \n",
       "18                         51.24  ...             4.959105e+09  1.826519e+10   \n",
       "19                         47.76  ...             5.153069e+09  1.951786e+10   \n",
       "20                         49.48  ...             3.129566e+09  1.795157e+10   \n",
       "21                           NaN  ...             4.111887e+09  1.941057e+10   \n",
       "\n",
       "     Population  Primary Drop-out rate  Primary Drop-out rate (Girls)  \\\n",
       "0    76723051.0                    NaN                            NaN   \n",
       "1    78273584.0                    NaN                            NaN   \n",
       "2    79832103.0                    NaN                            NaN   \n",
       "3    81398610.0                    NaN                            NaN   \n",
       "4    82977428.0                    NaN                            NaN   \n",
       "5    84559930.0                    NaN                            NaN   \n",
       "6    86150420.0                   6.37                           5.00   \n",
       "7    87748896.0                   5.99                           4.72   \n",
       "8    89359772.0                   6.02                           4.87   \n",
       "9    90974244.0                   6.28                           4.93   \n",
       "10   92596704.0                   6.29                           5.02   \n",
       "11   94227150.0                   6.36                           5.18   \n",
       "12   95870083.0                   6.24                           5.12   \n",
       "13   97516526.0                   4.85                           4.04   \n",
       "14   99170955.0                   3.26                           2.77   \n",
       "15  100833371.0                   2.69                           2.01   \n",
       "16  102530196.0                    NaN                            NaN   \n",
       "17  104169230.0                    NaN                            NaN   \n",
       "18  105755180.0                    NaN                            NaN   \n",
       "19  107288150.0                    NaN                            NaN   \n",
       "20  108771978.0                    NaN                            NaN   \n",
       "21          NaN                    NaN                            NaN   \n",
       "\n",
       "    Primary Drop-out rate (Boys)  Secondary Drop-out rate  \\\n",
       "0                            NaN                      NaN   \n",
       "1                            NaN                      NaN   \n",
       "2                            NaN                      NaN   \n",
       "3                            NaN                      NaN   \n",
       "4                            NaN                      NaN   \n",
       "5                            NaN                      NaN   \n",
       "6                           7.64                      8.5   \n",
       "7                           7.17                      7.5   \n",
       "8                           7.07                      7.4   \n",
       "9                           7.52                      8.0   \n",
       "10                          7.45                      7.8   \n",
       "11                          7.45                      7.8   \n",
       "12                          7.25                      8.1   \n",
       "13                          5.59                      7.6   \n",
       "14                          3.70                      6.9   \n",
       "15                          3.30                      6.6   \n",
       "16                           NaN                      NaN   \n",
       "17                           NaN                      NaN   \n",
       "18                           NaN                      NaN   \n",
       "19                           NaN                      NaN   \n",
       "20                           NaN                      NaN   \n",
       "21                           NaN                      NaN   \n",
       "\n",
       "    Secondary Drop-out rate (Girls)  Secondary Drop-out rate (Boys)  \\\n",
       "0                               NaN                             NaN   \n",
       "1                               NaN                             NaN   \n",
       "2                               NaN                             NaN   \n",
       "3                               NaN                             NaN   \n",
       "4                               NaN                             NaN   \n",
       "5                               NaN                             NaN   \n",
       "6                               6.7                            10.4   \n",
       "7                               5.6                             9.3   \n",
       "8                               5.8                             9.1   \n",
       "9                               6.2                             9.7   \n",
       "10                              5.7                             9.5   \n",
       "11                              5.6                            10.0   \n",
       "12                              6.2                            10.0   \n",
       "13                              5.8                             9.4   \n",
       "14                              5.5                             8.3   \n",
       "15                              4.9                             8.3   \n",
       "16                              NaN                             NaN   \n",
       "17                              NaN                             NaN   \n",
       "18                              NaN                             NaN   \n",
       "19                              NaN                             NaN   \n",
       "20                              NaN                             NaN   \n",
       "21                              NaN                             NaN   \n",
       "\n",
       "    Price Index for Agriculture  \n",
       "0                           NaN  \n",
       "1                           NaN  \n",
       "2                           NaN  \n",
       "3                           NaN  \n",
       "4                           NaN  \n",
       "5                           NaN  \n",
       "6                           NaN  \n",
       "7                           NaN  \n",
       "8                           NaN  \n",
       "9                           NaN  \n",
       "10                          NaN  \n",
       "11                          NaN  \n",
       "12                          NaN  \n",
       "13                          NaN  \n",
       "14                          NaN  \n",
       "15                          NaN  \n",
       "16                          NaN  \n",
       "17                          NaN  \n",
       "18                      100.000  \n",
       "19                       94.375  \n",
       "20                       95.050  \n",
       "21                      103.025  \n",
       "\n",
       "[22 rows x 53 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ph_sdg_data = sdg_data [sdg_data ['Geolocation'] == 'PHILIPPINES'].reset_index (drop = True)\n",
    "ph_sdg_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e7f56d1",
   "metadata": {},
   "source": [
    "Now, we can get the SDG data for the regions of the Philippines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c5cf6245",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net SHS Enrolment Rate</th>\n",
       "      <th>...</th>\n",
       "      <th>Gross Capital Formation</th>\n",
       "      <th>GRDP</th>\n",
       "      <th>Population</th>\n",
       "      <th>Primary Drop-out rate</th>\n",
       "      <th>Primary Drop-out rate (Girls)</th>\n",
       "      <th>Primary Drop-out rate (Boys)</th>\n",
       "      <th>Secondary Drop-out rate</th>\n",
       "      <th>Secondary Drop-out rate (Girls)</th>\n",
       "      <th>Secondary Drop-out rate (Boys)</th>\n",
       "      <th>Price Index for Agriculture</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101.00</td>\n",
       "      <td>101.92</td>\n",
       "      <td>100.13</td>\n",
       "      <td>79.05</td>\n",
       "      <td>79.50</td>\n",
       "      <td>78.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>203930819.0</td>\n",
       "      <td>1.237451e+09</td>\n",
       "      <td>9961971.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.42</td>\n",
       "      <td>94.58</td>\n",
       "      <td>94.26</td>\n",
       "      <td>71.19</td>\n",
       "      <td>76.37</td>\n",
       "      <td>66.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13865180.0</td>\n",
       "      <td>9.044601e+07</td>\n",
       "      <td>1369249.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.73</td>\n",
       "      <td>97.01</td>\n",
       "      <td>98.41</td>\n",
       "      <td>87.51</td>\n",
       "      <td>90.05</td>\n",
       "      <td>85.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24454284.0</td>\n",
       "      <td>1.289450e+08</td>\n",
       "      <td>4209083.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.65</td>\n",
       "      <td>95.74</td>\n",
       "      <td>95.57</td>\n",
       "      <td>77.11</td>\n",
       "      <td>81.11</td>\n",
       "      <td>73.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>32773347.0</td>\n",
       "      <td>8.593798e+07</td>\n",
       "      <td>2819641.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.32</td>\n",
       "      <td>97.85</td>\n",
       "      <td>98.77</td>\n",
       "      <td>74.32</td>\n",
       "      <td>76.58</td>\n",
       "      <td>72.13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8037710.0</td>\n",
       "      <td>3.687868e+08</td>\n",
       "      <td>8233671.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</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>369</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>164566009.0</td>\n",
       "      <td>9.492320e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>257595240.0</td>\n",
       "      <td>9.672276e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>87077953.0</td>\n",
       "      <td>5.039756e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>100730468.0</td>\n",
       "      <td>3.317629e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>47527167.0</td>\n",
       "      <td>2.846570e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>374 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "0                         NCR: National Capital Region  2000   \n",
       "1                CAR: Cordillera Administrative Region  2000   \n",
       "2                              Region 1: Ilocos Region  2000   \n",
       "3                             Region 2: Cagayan Valley  2000   \n",
       "4                              Region 3: Central Luzon  2000   \n",
       "..                                                 ...   ...   \n",
       "369                       Region 10: Northern Mindanao  2021   \n",
       "370                            Region 11: Davao Region  2021   \n",
       "371                            Region 12: SOCCSKSARGEN  2021   \n",
       "372               CARAGA: CARAGA Administrative Region  2021   \n",
       "373  BARMM: Bangsamoro Autonomous Region in Muslim ...  2021   \n",
       "\n",
       "     1.2.1 Poverty Proportion  1.4.1 Net Elem Enrolment Rate  \\\n",
       "0                         NaN                         101.00   \n",
       "1                         NaN                          94.42   \n",
       "2                         NaN                          97.73   \n",
       "3                         NaN                          95.65   \n",
       "4                         NaN                          98.32   \n",
       "..                        ...                            ...   \n",
       "369                       NaN                            NaN   \n",
       "370                       NaN                            NaN   \n",
       "371                       NaN                            NaN   \n",
       "372                       NaN                            NaN   \n",
       "373                       NaN                            NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Girls)  \\\n",
       "0                                   101.92   \n",
       "1                                    94.58   \n",
       "2                                    97.01   \n",
       "3                                    95.74   \n",
       "4                                    97.85   \n",
       "..                                     ...   \n",
       "369                                    NaN   \n",
       "370                                    NaN   \n",
       "371                                    NaN   \n",
       "372                                    NaN   \n",
       "373                                    NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Boys)  1.4.1 Net JHS Enrolment Rate  \\\n",
       "0                                  100.13                         79.05   \n",
       "1                                   94.26                         71.19   \n",
       "2                                   98.41                         87.51   \n",
       "3                                   95.57                         77.11   \n",
       "4                                   98.77                         74.32   \n",
       "..                                    ...                           ...   \n",
       "369                                   NaN                           NaN   \n",
       "370                                   NaN                           NaN   \n",
       "371                                   NaN                           NaN   \n",
       "372                                   NaN                           NaN   \n",
       "373                                   NaN                           NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Girls)  \\\n",
       "0                                   79.50   \n",
       "1                                   76.37   \n",
       "2                                   90.05   \n",
       "3                                   81.11   \n",
       "4                                   76.58   \n",
       "..                                    ...   \n",
       "369                                   NaN   \n",
       "370                                   NaN   \n",
       "371                                   NaN   \n",
       "372                                   NaN   \n",
       "373                                   NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Boys)  1.4.1 Net SHS Enrolment Rate  ...  \\\n",
       "0                                  78.57                           NaN  ...   \n",
       "1                                  66.14                           NaN  ...   \n",
       "2                                  85.07                           NaN  ...   \n",
       "3                                  73.31                           NaN  ...   \n",
       "4                                  72.13                           NaN  ...   \n",
       "..                                   ...                           ...  ...   \n",
       "369                                  NaN                           NaN  ...   \n",
       "370                                  NaN                           NaN  ...   \n",
       "371                                  NaN                           NaN  ...   \n",
       "372                                  NaN                           NaN  ...   \n",
       "373                                  NaN                           NaN  ...   \n",
       "\n",
       "     Gross Capital Formation          GRDP  Population  Primary Drop-out rate  \\\n",
       "0                203930819.0  1.237451e+09   9961971.0                    NaN   \n",
       "1                 13865180.0  9.044601e+07   1369249.0                    NaN   \n",
       "2                 24454284.0  1.289450e+08   4209083.0                    NaN   \n",
       "3                 32773347.0  8.593798e+07   2819641.0                    NaN   \n",
       "4                  8037710.0  3.687868e+08   8233671.0                    NaN   \n",
       "..                       ...           ...         ...                    ...   \n",
       "369              164566009.0  9.492320e+08         NaN                    NaN   \n",
       "370              257595240.0  9.672276e+08         NaN                    NaN   \n",
       "371               87077953.0  5.039756e+08         NaN                    NaN   \n",
       "372              100730468.0  3.317629e+08         NaN                    NaN   \n",
       "373               47527167.0  2.846570e+08         NaN                    NaN   \n",
       "\n",
       "     Primary Drop-out rate (Girls)  Primary Drop-out rate (Boys)  \\\n",
       "0                              NaN                           NaN   \n",
       "1                              NaN                           NaN   \n",
       "2                              NaN                           NaN   \n",
       "3                              NaN                           NaN   \n",
       "4                              NaN                           NaN   \n",
       "..                             ...                           ...   \n",
       "369                            NaN                           NaN   \n",
       "370                            NaN                           NaN   \n",
       "371                            NaN                           NaN   \n",
       "372                            NaN                           NaN   \n",
       "373                            NaN                           NaN   \n",
       "\n",
       "     Secondary Drop-out rate  Secondary Drop-out rate (Girls)  \\\n",
       "0                        NaN                              NaN   \n",
       "1                        NaN                              NaN   \n",
       "2                        NaN                              NaN   \n",
       "3                        NaN                              NaN   \n",
       "4                        NaN                              NaN   \n",
       "..                       ...                              ...   \n",
       "369                      NaN                              NaN   \n",
       "370                      NaN                              NaN   \n",
       "371                      NaN                              NaN   \n",
       "372                      NaN                              NaN   \n",
       "373                      NaN                              NaN   \n",
       "\n",
       "     Secondary Drop-out rate (Boys)  Price Index for Agriculture  \n",
       "0                               NaN                          NaN  \n",
       "1                               NaN                          NaN  \n",
       "2                               NaN                          NaN  \n",
       "3                               NaN                          NaN  \n",
       "4                               NaN                          NaN  \n",
       "..                              ...                          ...  \n",
       "369                             NaN                      107.975  \n",
       "370                             NaN                      110.850  \n",
       "371                             NaN                      103.350  \n",
       "372                             NaN                      104.525  \n",
       "373                             NaN                       91.950  \n",
       "\n",
       "[374 rows x 53 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_sdg_data = sdg_data [sdg_data ['Geolocation'] != 'PHILIPPINES'].reset_index (drop = True)\n",
    "regional_sdg_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52458611",
   "metadata": {},
   "source": [
    "To check if the national data for the SDGs were separated, let us check the unique values for the `Geolocation` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8b484ffc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['NCR: National Capital Region',\n",
       "       'CAR: Cordillera Administrative Region', 'Region 1: Ilocos Region',\n",
       "       'Region 2: Cagayan Valley', 'Region 3: Central Luzon',\n",
       "       'Region 4A: CALABARZON', 'MIMAROPA: Southwestern Tagalog Region',\n",
       "       'Region 5: Bicol Region', 'Region 6: Western Visayas',\n",
       "       'Region 7: Central Visayas', 'Region 8: Eastern Visayas',\n",
       "       'Region 9: Zamboanga Peninsula', 'Region 10: Northern Mindanao',\n",
       "       'Region 11: Davao Region', 'Region 12: SOCCSKSARGEN',\n",
       "       'CARAGA: CARAGA Administrative Region',\n",
       "       'BARMM: Bangsamoro Autonomous Region in Muslim Mindanao'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_sdg_data ['Geolocation'].unique ()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09b21dfd",
   "metadata": {},
   "source": [
    "From this, we are now sure that we only have the regional data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e172d0f",
   "metadata": {},
   "source": [
    "### Fixing the Regional DataFrame for the GeoSpatial Data\n",
    "\n",
    "Now that we have separated the regional and national data, we can now focus on the merging of the datasets. From the previous explorations, we know that the regions are named and arranged differently. \n",
    "\n",
    "To easily merge the datasets, let us rearrange the regions on the geospatial dataset to have the same arrangement as the regions on the regional SDG dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "671b9f19",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\3488050636.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\3488050636.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\3488050636.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\3488050636.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\3488050636.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\3488050636.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n"
     ]
    },
    {
     "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>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>ADM1_EN</th>\n",
       "      <th>ADM1_PCODE</th>\n",
       "      <th>ADM1_REF</th>\n",
       "      <th>ADM1ALT1EN</th>\n",
       "      <th>ADM1ALT2EN</th>\n",
       "      <th>ADM0_EN</th>\n",
       "      <th>ADM0_PCODE</th>\n",
       "      <th>date</th>\n",
       "      <th>validOn</th>\n",
       "      <th>validTo</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>National Capital Region</td>\n",
       "      <td>PH130000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NCR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>Cordillera Administrative Region</td>\n",
       "      <td>PH140000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>Region I</td>\n",
       "      <td>PH010000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ilocos Region</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>Region II</td>\n",
       "      <td>PH020000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>Region III</td>\n",
       "      <td>PH030000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Central Luzon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>27.624115</td>\n",
       "      <td>1.326710</td>\n",
       "      <td>Region IV-A</td>\n",
       "      <td>PH040000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Calabarzon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>78.804542</td>\n",
       "      <td>2.220374</td>\n",
       "      <td>Region IV-B</td>\n",
       "      <td>PH170000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mimaropa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>44.923243</td>\n",
       "      <td>1.446324</td>\n",
       "      <td>Region V</td>\n",
       "      <td>PH050000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bicol Region</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27.589382</td>\n",
       "      <td>1.657135</td>\n",
       "      <td>Region VI</td>\n",
       "      <td>PH060000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Western Visayas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>29.113105</td>\n",
       "      <td>1.178431</td>\n",
       "      <td>Region VII</td>\n",
       "      <td>PH070000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Central Visayas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>42.021179</td>\n",
       "      <td>1.726804</td>\n",
       "      <td>Region VIII</td>\n",
       "      <td>PH080000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Visayas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>23.181441</td>\n",
       "      <td>1.196677</td>\n",
       "      <td>Region IX</td>\n",
       "      <td>PH090000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Zamboanga Peninsula</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>Region X</td>\n",
       "      <td>PH100000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>Region XI</td>\n",
       "      <td>PH110000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Davao Region</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>Region XII</td>\n",
       "      <td>PH120000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Soccsksargen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>Region XIII</td>\n",
       "      <td>PH160000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Caraga</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>Bangsamoro Autonomous Region in Muslim Mindanao</td>\n",
       "      <td>PH150000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BARMM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shape_Leng  Shape_Area                                          ADM1_EN  \\\n",
       "0     2.320234    0.050216                          National Capital Region   \n",
       "1     8.027454    1.546712                 Cordillera Administrative Region   \n",
       "2    14.995101    1.043983                                         Region I   \n",
       "3    19.139048    2.241812                                        Region II   \n",
       "4    15.949563    1.793513                                       Region III   \n",
       "5    27.624115    1.326710                                      Region IV-A   \n",
       "6    78.804542    2.220374                                      Region IV-B   \n",
       "7    44.923243    1.446324                                         Region V   \n",
       "8    27.589382    1.657135                                        Region VI   \n",
       "9    29.113105    1.178431                                       Region VII   \n",
       "10   42.021179    1.726804                                      Region VIII   \n",
       "11   23.181441    1.196677                                        Region IX   \n",
       "12   15.002953    1.435115                                         Region X   \n",
       "13   17.934222    1.539971                                        Region XI   \n",
       "14   13.229749    1.471068                                       Region XII   \n",
       "15   28.166754    1.540820                                      Region XIII   \n",
       "16   53.623497    1.050272  Bangsamoro Autonomous Region in Muslim Mindanao   \n",
       "\n",
       "     ADM1_PCODE  ADM1_REF           ADM1ALT1EN  ADM1ALT2EN            ADM0_EN  \\\n",
       "0   PH130000000       NaN                  NCR         NaN  Philippines (the)   \n",
       "1   PH140000000       NaN                  CAR         NaN  Philippines (the)   \n",
       "2   PH010000000       NaN        Ilocos Region         NaN  Philippines (the)   \n",
       "3   PH020000000       NaN       Cagayan Valley         NaN  Philippines (the)   \n",
       "4   PH030000000       NaN        Central Luzon         NaN  Philippines (the)   \n",
       "5   PH040000000       NaN           Calabarzon         NaN  Philippines (the)   \n",
       "6   PH170000000       NaN             Mimaropa         NaN  Philippines (the)   \n",
       "7   PH050000000       NaN         Bicol Region         NaN  Philippines (the)   \n",
       "8   PH060000000       NaN      Western Visayas         NaN  Philippines (the)   \n",
       "9   PH070000000       NaN      Central Visayas         NaN  Philippines (the)   \n",
       "10  PH080000000       NaN      Eastern Visayas         NaN  Philippines (the)   \n",
       "11  PH090000000       NaN  Zamboanga Peninsula         NaN  Philippines (the)   \n",
       "12  PH100000000       NaN    Northern Mindanao         NaN  Philippines (the)   \n",
       "13  PH110000000       NaN         Davao Region         NaN  Philippines (the)   \n",
       "14  PH120000000       NaN         Soccsksargen         NaN  Philippines (the)   \n",
       "15  PH160000000       NaN               Caraga         NaN  Philippines (the)   \n",
       "16  PH150000000       NaN                BARMM         NaN  Philippines (the)   \n",
       "\n",
       "   ADM0_PCODE        date     validOn  validTo  \\\n",
       "0          PH  2016-06-30  2020-05-29      NaN   \n",
       "1          PH  2016-06-30  2020-05-29      NaN   \n",
       "2          PH  2016-06-30  2020-05-29      NaN   \n",
       "3          PH  2016-06-30  2020-05-29      NaN   \n",
       "4          PH  2016-06-30  2020-05-29      NaN   \n",
       "5          PH  2016-06-30  2020-05-29      NaN   \n",
       "6          PH  2016-06-30  2020-05-29      NaN   \n",
       "7          PH  2016-06-30  2020-05-29      NaN   \n",
       "8          PH  2016-06-30  2020-05-29      NaN   \n",
       "9          PH  2016-06-30  2020-05-29      NaN   \n",
       "10         PH  2016-06-30  2020-05-29      NaN   \n",
       "11         PH  2016-06-30  2020-05-29      NaN   \n",
       "12         PH  2016-06-30  2020-05-29      NaN   \n",
       "13         PH  2016-06-30  2020-05-29      NaN   \n",
       "14         PH  2016-06-30  2020-05-29      NaN   \n",
       "15         PH  2016-06-30  2020-05-29      NaN   \n",
       "16         PH  2016-06-30  2020-05-29      NaN   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1   POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2   MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3   MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4   MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "5   MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "6   MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "7   MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "8   MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "9   MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "10  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "11  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "12  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "13  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "14  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "15  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "16  MULTIPOLYGON (((119.46876076500007 4.593602191...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_geo_data = pd.DataFrame (regional_geo_data.loc [2 : 2]).append (\n",
    "    regional_geo_data.loc [1]\n",
    ").append (\n",
    "    regional_geo_data.loc [3 : 7]\n",
    ").append (\n",
    "    regional_geo_data.loc [9 : 12]\n",
    ").append (\n",
    "    regional_geo_data.loc [8]\n",
    ").append(\n",
    "    regional_geo_data.loc [13 : ]\n",
    ").append(\n",
    "    regional_geo_data.loc [0]\n",
    ").reset_index (drop = True)\n",
    "\n",
    "regional_geo_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7afd1af",
   "metadata": {},
   "source": [
    "With this, the geospatial dataset's regions has the same arrangement as the regional SDG data. \n",
    "\n",
    "Although, before combining the datasets, we will need to drop the columns that are all **NaN** values first using the [`dropna`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.dropna.html) function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "95aebff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "        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>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>ADM1_EN</th>\n",
       "      <th>ADM1_PCODE</th>\n",
       "      <th>ADM1ALT1EN</th>\n",
       "      <th>ADM0_EN</th>\n",
       "      <th>ADM0_PCODE</th>\n",
       "      <th>date</th>\n",
       "      <th>validOn</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>National Capital Region</td>\n",
       "      <td>PH130000000</td>\n",
       "      <td>NCR</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>Cordillera Administrative Region</td>\n",
       "      <td>PH140000000</td>\n",
       "      <td>CAR</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>Region I</td>\n",
       "      <td>PH010000000</td>\n",
       "      <td>Ilocos Region</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>Region II</td>\n",
       "      <td>PH020000000</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>Region III</td>\n",
       "      <td>PH030000000</td>\n",
       "      <td>Central Luzon</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>27.624115</td>\n",
       "      <td>1.326710</td>\n",
       "      <td>Region IV-A</td>\n",
       "      <td>PH040000000</td>\n",
       "      <td>Calabarzon</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>78.804542</td>\n",
       "      <td>2.220374</td>\n",
       "      <td>Region IV-B</td>\n",
       "      <td>PH170000000</td>\n",
       "      <td>Mimaropa</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>44.923243</td>\n",
       "      <td>1.446324</td>\n",
       "      <td>Region V</td>\n",
       "      <td>PH050000000</td>\n",
       "      <td>Bicol Region</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27.589382</td>\n",
       "      <td>1.657135</td>\n",
       "      <td>Region VI</td>\n",
       "      <td>PH060000000</td>\n",
       "      <td>Western Visayas</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>29.113105</td>\n",
       "      <td>1.178431</td>\n",
       "      <td>Region VII</td>\n",
       "      <td>PH070000000</td>\n",
       "      <td>Central Visayas</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>42.021179</td>\n",
       "      <td>1.726804</td>\n",
       "      <td>Region VIII</td>\n",
       "      <td>PH080000000</td>\n",
       "      <td>Eastern Visayas</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>23.181441</td>\n",
       "      <td>1.196677</td>\n",
       "      <td>Region IX</td>\n",
       "      <td>PH090000000</td>\n",
       "      <td>Zamboanga Peninsula</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>Region X</td>\n",
       "      <td>PH100000000</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>Region XI</td>\n",
       "      <td>PH110000000</td>\n",
       "      <td>Davao Region</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>Region XII</td>\n",
       "      <td>PH120000000</td>\n",
       "      <td>Soccsksargen</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>Region XIII</td>\n",
       "      <td>PH160000000</td>\n",
       "      <td>Caraga</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>Bangsamoro Autonomous Region in Muslim Mindanao</td>\n",
       "      <td>PH150000000</td>\n",
       "      <td>BARMM</td>\n",
       "      <td>Philippines (the)</td>\n",
       "      <td>PH</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shape_Leng  Shape_Area                                          ADM1_EN  \\\n",
       "0     2.320234    0.050216                          National Capital Region   \n",
       "1     8.027454    1.546712                 Cordillera Administrative Region   \n",
       "2    14.995101    1.043983                                         Region I   \n",
       "3    19.139048    2.241812                                        Region II   \n",
       "4    15.949563    1.793513                                       Region III   \n",
       "5    27.624115    1.326710                                      Region IV-A   \n",
       "6    78.804542    2.220374                                      Region IV-B   \n",
       "7    44.923243    1.446324                                         Region V   \n",
       "8    27.589382    1.657135                                        Region VI   \n",
       "9    29.113105    1.178431                                       Region VII   \n",
       "10   42.021179    1.726804                                      Region VIII   \n",
       "11   23.181441    1.196677                                        Region IX   \n",
       "12   15.002953    1.435115                                         Region X   \n",
       "13   17.934222    1.539971                                        Region XI   \n",
       "14   13.229749    1.471068                                       Region XII   \n",
       "15   28.166754    1.540820                                      Region XIII   \n",
       "16   53.623497    1.050272  Bangsamoro Autonomous Region in Muslim Mindanao   \n",
       "\n",
       "     ADM1_PCODE           ADM1ALT1EN            ADM0_EN ADM0_PCODE  \\\n",
       "0   PH130000000                  NCR  Philippines (the)         PH   \n",
       "1   PH140000000                  CAR  Philippines (the)         PH   \n",
       "2   PH010000000        Ilocos Region  Philippines (the)         PH   \n",
       "3   PH020000000       Cagayan Valley  Philippines (the)         PH   \n",
       "4   PH030000000        Central Luzon  Philippines (the)         PH   \n",
       "5   PH040000000           Calabarzon  Philippines (the)         PH   \n",
       "6   PH170000000             Mimaropa  Philippines (the)         PH   \n",
       "7   PH050000000         Bicol Region  Philippines (the)         PH   \n",
       "8   PH060000000      Western Visayas  Philippines (the)         PH   \n",
       "9   PH070000000      Central Visayas  Philippines (the)         PH   \n",
       "10  PH080000000      Eastern Visayas  Philippines (the)         PH   \n",
       "11  PH090000000  Zamboanga Peninsula  Philippines (the)         PH   \n",
       "12  PH100000000    Northern Mindanao  Philippines (the)         PH   \n",
       "13  PH110000000         Davao Region  Philippines (the)         PH   \n",
       "14  PH120000000         Soccsksargen  Philippines (the)         PH   \n",
       "15  PH160000000               Caraga  Philippines (the)         PH   \n",
       "16  PH150000000                BARMM  Philippines (the)         PH   \n",
       "\n",
       "          date     validOn                                           geometry  \n",
       "0   2016-06-30  2020-05-29  POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1   2016-06-30  2020-05-29  POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2   2016-06-30  2020-05-29  MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3   2016-06-30  2020-05-29  MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4   2016-06-30  2020-05-29  MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "5   2016-06-30  2020-05-29  MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "6   2016-06-30  2020-05-29  MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "7   2016-06-30  2020-05-29  MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "8   2016-06-30  2020-05-29  MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "9   2016-06-30  2020-05-29  MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "10  2016-06-30  2020-05-29  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "11  2016-06-30  2020-05-29  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "12  2016-06-30  2020-05-29  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "13  2016-06-30  2020-05-29  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "14  2016-06-30  2020-05-29  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "15  2016-06-30  2020-05-29  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "16  2016-06-30  2020-05-29  MULTIPOLYGON (((119.46876076500007 4.593602191...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_geo_data = regional_geo_data.dropna (axis = 1)\n",
    "regional_geo_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "373fb095",
   "metadata": {},
   "source": [
    "In addition, since the `ADM0_EN`, `ADM0_PCODE`, `date`, and `validOn` columns only has the same value, we would be removing this from the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a66d5a0d",
   "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>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>ADM1_EN</th>\n",
       "      <th>ADM1_PCODE</th>\n",
       "      <th>ADM1ALT1EN</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>National Capital Region</td>\n",
       "      <td>PH130000000</td>\n",
       "      <td>NCR</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>Cordillera Administrative Region</td>\n",
       "      <td>PH140000000</td>\n",
       "      <td>CAR</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>Region I</td>\n",
       "      <td>PH010000000</td>\n",
       "      <td>Ilocos Region</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>Region II</td>\n",
       "      <td>PH020000000</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>Region III</td>\n",
       "      <td>PH030000000</td>\n",
       "      <td>Central Luzon</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>27.624115</td>\n",
       "      <td>1.326710</td>\n",
       "      <td>Region IV-A</td>\n",
       "      <td>PH040000000</td>\n",
       "      <td>Calabarzon</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>78.804542</td>\n",
       "      <td>2.220374</td>\n",
       "      <td>Region IV-B</td>\n",
       "      <td>PH170000000</td>\n",
       "      <td>Mimaropa</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>44.923243</td>\n",
       "      <td>1.446324</td>\n",
       "      <td>Region V</td>\n",
       "      <td>PH050000000</td>\n",
       "      <td>Bicol Region</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>27.589382</td>\n",
       "      <td>1.657135</td>\n",
       "      <td>Region VI</td>\n",
       "      <td>PH060000000</td>\n",
       "      <td>Western Visayas</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>29.113105</td>\n",
       "      <td>1.178431</td>\n",
       "      <td>Region VII</td>\n",
       "      <td>PH070000000</td>\n",
       "      <td>Central Visayas</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>42.021179</td>\n",
       "      <td>1.726804</td>\n",
       "      <td>Region VIII</td>\n",
       "      <td>PH080000000</td>\n",
       "      <td>Eastern Visayas</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>23.181441</td>\n",
       "      <td>1.196677</td>\n",
       "      <td>Region IX</td>\n",
       "      <td>PH090000000</td>\n",
       "      <td>Zamboanga Peninsula</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>Region X</td>\n",
       "      <td>PH100000000</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>Region XI</td>\n",
       "      <td>PH110000000</td>\n",
       "      <td>Davao Region</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>Region XII</td>\n",
       "      <td>PH120000000</td>\n",
       "      <td>Soccsksargen</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>Region XIII</td>\n",
       "      <td>PH160000000</td>\n",
       "      <td>Caraga</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>Bangsamoro Autonomous Region in Muslim Mindanao</td>\n",
       "      <td>PH150000000</td>\n",
       "      <td>BARMM</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Shape_Leng  Shape_Area                                          ADM1_EN  \\\n",
       "0     2.320234    0.050216                          National Capital Region   \n",
       "1     8.027454    1.546712                 Cordillera Administrative Region   \n",
       "2    14.995101    1.043983                                         Region I   \n",
       "3    19.139048    2.241812                                        Region II   \n",
       "4    15.949563    1.793513                                       Region III   \n",
       "5    27.624115    1.326710                                      Region IV-A   \n",
       "6    78.804542    2.220374                                      Region IV-B   \n",
       "7    44.923243    1.446324                                         Region V   \n",
       "8    27.589382    1.657135                                        Region VI   \n",
       "9    29.113105    1.178431                                       Region VII   \n",
       "10   42.021179    1.726804                                      Region VIII   \n",
       "11   23.181441    1.196677                                        Region IX   \n",
       "12   15.002953    1.435115                                         Region X   \n",
       "13   17.934222    1.539971                                        Region XI   \n",
       "14   13.229749    1.471068                                       Region XII   \n",
       "15   28.166754    1.540820                                      Region XIII   \n",
       "16   53.623497    1.050272  Bangsamoro Autonomous Region in Muslim Mindanao   \n",
       "\n",
       "     ADM1_PCODE           ADM1ALT1EN  \\\n",
       "0   PH130000000                  NCR   \n",
       "1   PH140000000                  CAR   \n",
       "2   PH010000000        Ilocos Region   \n",
       "3   PH020000000       Cagayan Valley   \n",
       "4   PH030000000        Central Luzon   \n",
       "5   PH040000000           Calabarzon   \n",
       "6   PH170000000             Mimaropa   \n",
       "7   PH050000000         Bicol Region   \n",
       "8   PH060000000      Western Visayas   \n",
       "9   PH070000000      Central Visayas   \n",
       "10  PH080000000      Eastern Visayas   \n",
       "11  PH090000000  Zamboanga Peninsula   \n",
       "12  PH100000000    Northern Mindanao   \n",
       "13  PH110000000         Davao Region   \n",
       "14  PH120000000         Soccsksargen   \n",
       "15  PH160000000               Caraga   \n",
       "16  PH150000000                BARMM   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1   POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2   MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3   MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4   MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "5   MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "6   MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "7   MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "8   MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "9   MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "10  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "11  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "12  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "13  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "14  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "15  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "16  MULTIPOLYGON (((119.46876076500007 4.593602191...  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_geo_data = regional_geo_data [['Shape_Leng', 'Shape_Area', 'ADM1_EN', 'ADM1_PCODE', 'ADM1ALT1EN', 'geometry']]\n",
    "regional_geo_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d28322a",
   "metadata": {},
   "source": [
    "Last, since we know that the regional SDG dataset is arranged per year then per regions (i.e., data for the same year are found one after the other) and that this dataset includes data from 2000 to 2022, we would need to repeat the geospatial dataset **22 times**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8696bc56",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
      "C:\\Users\\admin\\AppData\\Local\\Temp\\ipykernel_8560\\4192407329.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>ADM1_EN</th>\n",
       "      <th>ADM1_PCODE</th>\n",
       "      <th>ADM1ALT1EN</th>\n",
       "      <th>geometry</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>National Capital Region</td>\n",
       "      <td>PH130000000</td>\n",
       "      <td>NCR</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>Cordillera Administrative Region</td>\n",
       "      <td>PH140000000</td>\n",
       "      <td>CAR</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>Region I</td>\n",
       "      <td>PH010000000</td>\n",
       "      <td>Ilocos Region</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>Region II</td>\n",
       "      <td>PH020000000</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>Region III</td>\n",
       "      <td>PH030000000</td>\n",
       "      <td>Central Luzon</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</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",
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       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>Region X</td>\n",
       "      <td>PH100000000</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
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       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>Region XI</td>\n",
       "      <td>PH110000000</td>\n",
       "      <td>Davao Region</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>Region XII</td>\n",
       "      <td>PH120000000</td>\n",
       "      <td>Soccsksargen</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>Region XIII</td>\n",
       "      <td>PH160000000</td>\n",
       "      <td>Caraga</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>Bangsamoro Autonomous Region in Muslim Mindanao</td>\n",
       "      <td>PH150000000</td>\n",
       "      <td>BARMM</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>374 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Shape_Leng  Shape_Area                                          ADM1_EN  \\\n",
       "0      2.320234    0.050216                          National Capital Region   \n",
       "1      8.027454    1.546712                 Cordillera Administrative Region   \n",
       "2     14.995101    1.043983                                         Region I   \n",
       "3     19.139048    2.241812                                        Region II   \n",
       "4     15.949563    1.793513                                       Region III   \n",
       "..          ...         ...                                              ...   \n",
       "369   15.002953    1.435115                                         Region X   \n",
       "370   17.934222    1.539971                                        Region XI   \n",
       "371   13.229749    1.471068                                       Region XII   \n",
       "372   28.166754    1.540820                                      Region XIII   \n",
       "373   53.623497    1.050272  Bangsamoro Autonomous Region in Muslim Mindanao   \n",
       "\n",
       "      ADM1_PCODE         ADM1ALT1EN  \\\n",
       "0    PH130000000                NCR   \n",
       "1    PH140000000                CAR   \n",
       "2    PH010000000      Ilocos Region   \n",
       "3    PH020000000     Cagayan Valley   \n",
       "4    PH030000000      Central Luzon   \n",
       "..           ...                ...   \n",
       "369  PH100000000  Northern Mindanao   \n",
       "370  PH110000000       Davao Region   \n",
       "371  PH120000000       Soccsksargen   \n",
       "372  PH160000000             Caraga   \n",
       "373  PH150000000              BARMM   \n",
       "\n",
       "                                              geometry  \n",
       "0    POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1    POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2    MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3    MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4    MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "..                                                 ...  \n",
       "369  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "370  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "371  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "372  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "373  MULTIPOLYGON (((119.46876076500007 4.593602191...  \n",
       "\n",
       "[374 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_regional_geo_data = pd.DataFrame ()\n",
    "\n",
    "for i in range (22):\n",
    "    final_regional_geo_data = final_regional_geo_data.append (regional_geo_data)\n",
    "    \n",
    "final_regional_geo_data = final_regional_geo_data.reset_index (drop = True)\n",
    "final_regional_geo_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "809b537d",
   "metadata": {},
   "source": [
    "Now, we can combine the two datasets using the [`concat`](https://pandas.pydata.org/docs/reference/api/pandas.concat.html) function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0474d348",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1.2.1 Poverty Proportion</th>\n",
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       "      <th>Secondary Drop-out rate (Girls)</th>\n",
       "      <th>Secondary Drop-out rate (Boys)</th>\n",
       "      <th>Price Index for Agriculture</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
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       "      <th>ADM1_PCODE</th>\n",
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       "  <tbody>\n",
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       "      <td>101.92</td>\n",
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       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.42</td>\n",
       "      <td>94.58</td>\n",
       "      <td>94.26</td>\n",
       "      <td>71.19</td>\n",
       "      <td>76.37</td>\n",
       "      <td>66.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>Cordillera Administrative Region</td>\n",
       "      <td>PH140000000</td>\n",
       "      <td>CAR</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.73</td>\n",
       "      <td>97.01</td>\n",
       "      <td>98.41</td>\n",
       "      <td>87.51</td>\n",
       "      <td>90.05</td>\n",
       "      <td>85.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>Region I</td>\n",
       "      <td>PH010000000</td>\n",
       "      <td>Ilocos Region</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.65</td>\n",
       "      <td>95.74</td>\n",
       "      <td>95.57</td>\n",
       "      <td>77.11</td>\n",
       "      <td>81.11</td>\n",
       "      <td>73.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>Region II</td>\n",
       "      <td>PH020000000</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.32</td>\n",
       "      <td>97.85</td>\n",
       "      <td>98.77</td>\n",
       "      <td>74.32</td>\n",
       "      <td>76.58</td>\n",
       "      <td>72.13</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>Region III</td>\n",
       "      <td>PH030000000</td>\n",
       "      <td>Central Luzon</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>369</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.975</td>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>Region X</td>\n",
       "      <td>PH100000000</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.850</td>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>Region XI</td>\n",
       "      <td>PH110000000</td>\n",
       "      <td>Davao Region</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.350</td>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>Region XII</td>\n",
       "      <td>PH120000000</td>\n",
       "      <td>Soccsksargen</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.525</td>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>Region XIII</td>\n",
       "      <td>PH160000000</td>\n",
       "      <td>Caraga</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.950</td>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>Bangsamoro Autonomous Region in Muslim Mindanao</td>\n",
       "      <td>PH150000000</td>\n",
       "      <td>BARMM</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>374 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "0                         NCR: National Capital Region  2000   \n",
       "1                CAR: Cordillera Administrative Region  2000   \n",
       "2                              Region 1: Ilocos Region  2000   \n",
       "3                             Region 2: Cagayan Valley  2000   \n",
       "4                              Region 3: Central Luzon  2000   \n",
       "..                                                 ...   ...   \n",
       "369                       Region 10: Northern Mindanao  2021   \n",
       "370                            Region 11: Davao Region  2021   \n",
       "371                            Region 12: SOCCSKSARGEN  2021   \n",
       "372               CARAGA: CARAGA Administrative Region  2021   \n",
       "373  BARMM: Bangsamoro Autonomous Region in Muslim ...  2021   \n",
       "\n",
       "     1.2.1 Poverty Proportion  1.4.1 Net Elem Enrolment Rate  \\\n",
       "0                         NaN                         101.00   \n",
       "1                         NaN                          94.42   \n",
       "2                         NaN                          97.73   \n",
       "3                         NaN                          95.65   \n",
       "4                         NaN                          98.32   \n",
       "..                        ...                            ...   \n",
       "369                       NaN                            NaN   \n",
       "370                       NaN                            NaN   \n",
       "371                       NaN                            NaN   \n",
       "372                       NaN                            NaN   \n",
       "373                       NaN                            NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Girls)  \\\n",
       "0                                   101.92   \n",
       "1                                    94.58   \n",
       "2                                    97.01   \n",
       "3                                    95.74   \n",
       "4                                    97.85   \n",
       "..                                     ...   \n",
       "369                                    NaN   \n",
       "370                                    NaN   \n",
       "371                                    NaN   \n",
       "372                                    NaN   \n",
       "373                                    NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Boys)  1.4.1 Net JHS Enrolment Rate  \\\n",
       "0                                  100.13                         79.05   \n",
       "1                                   94.26                         71.19   \n",
       "2                                   98.41                         87.51   \n",
       "3                                   95.57                         77.11   \n",
       "4                                   98.77                         74.32   \n",
       "..                                    ...                           ...   \n",
       "369                                   NaN                           NaN   \n",
       "370                                   NaN                           NaN   \n",
       "371                                   NaN                           NaN   \n",
       "372                                   NaN                           NaN   \n",
       "373                                   NaN                           NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Girls)  \\\n",
       "0                                   79.50   \n",
       "1                                   76.37   \n",
       "2                                   90.05   \n",
       "3                                   81.11   \n",
       "4                                   76.58   \n",
       "..                                    ...   \n",
       "369                                   NaN   \n",
       "370                                   NaN   \n",
       "371                                   NaN   \n",
       "372                                   NaN   \n",
       "373                                   NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Boys)  1.4.1 Net SHS Enrolment Rate  ...  \\\n",
       "0                                  78.57                           NaN  ...   \n",
       "1                                  66.14                           NaN  ...   \n",
       "2                                  85.07                           NaN  ...   \n",
       "3                                  73.31                           NaN  ...   \n",
       "4                                  72.13                           NaN  ...   \n",
       "..                                   ...                           ...  ...   \n",
       "369                                  NaN                           NaN  ...   \n",
       "370                                  NaN                           NaN  ...   \n",
       "371                                  NaN                           NaN  ...   \n",
       "372                                  NaN                           NaN  ...   \n",
       "373                                  NaN                           NaN  ...   \n",
       "\n",
       "     Secondary Drop-out rate  Secondary Drop-out rate (Girls)  \\\n",
       "0                        NaN                              NaN   \n",
       "1                        NaN                              NaN   \n",
       "2                        NaN                              NaN   \n",
       "3                        NaN                              NaN   \n",
       "4                        NaN                              NaN   \n",
       "..                       ...                              ...   \n",
       "369                      NaN                              NaN   \n",
       "370                      NaN                              NaN   \n",
       "371                      NaN                              NaN   \n",
       "372                      NaN                              NaN   \n",
       "373                      NaN                              NaN   \n",
       "\n",
       "     Secondary Drop-out rate (Boys)  Price Index for Agriculture  Shape_Leng  \\\n",
       "0                               NaN                          NaN    2.320234   \n",
       "1                               NaN                          NaN    8.027454   \n",
       "2                               NaN                          NaN   14.995101   \n",
       "3                               NaN                          NaN   19.139048   \n",
       "4                               NaN                          NaN   15.949563   \n",
       "..                              ...                          ...         ...   \n",
       "369                             NaN                      107.975   15.002953   \n",
       "370                             NaN                      110.850   17.934222   \n",
       "371                             NaN                      103.350   13.229749   \n",
       "372                             NaN                      104.525   28.166754   \n",
       "373                             NaN                       91.950   53.623497   \n",
       "\n",
       "     Shape_Area                                          ADM1_EN   ADM1_PCODE  \\\n",
       "0      0.050216                          National Capital Region  PH130000000   \n",
       "1      1.546712                 Cordillera Administrative Region  PH140000000   \n",
       "2      1.043983                                         Region I  PH010000000   \n",
       "3      2.241812                                        Region II  PH020000000   \n",
       "4      1.793513                                       Region III  PH030000000   \n",
       "..          ...                                              ...          ...   \n",
       "369    1.435115                                         Region X  PH100000000   \n",
       "370    1.539971                                        Region XI  PH110000000   \n",
       "371    1.471068                                       Region XII  PH120000000   \n",
       "372    1.540820                                      Region XIII  PH160000000   \n",
       "373    1.050272  Bangsamoro Autonomous Region in Muslim Mindanao  PH150000000   \n",
       "\n",
       "            ADM1ALT1EN                                           geometry  \n",
       "0                  NCR  POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1                  CAR  POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2        Ilocos Region  MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3       Cagayan Valley  MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4        Central Luzon  MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "..                 ...                                                ...  \n",
       "369  Northern Mindanao  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "370       Davao Region  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "371       Soccsksargen  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "372             Caraga  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "373              BARMM  MULTIPOLYGON (((119.46876076500007 4.593602191...  \n",
       "\n",
       "[374 rows x 59 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df = pd.concat ([regional_sdg_data, final_regional_geo_data], axis = 1)\n",
    "combined_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbd8b31c",
   "metadata": {},
   "source": [
    "To ensure that we combined the datasets correctly based on the region, we will be looking at the `Geolocation` and the `ADM1ALT1EN` columns, which are the columns from the two datasets that holds the region names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3a31b13d",
   "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>Geolocation</th>\n",
       "      <th>ADM1ALT1EN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>NCR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>CAR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>Ilocos Region</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>Cagayan Valley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>Central Luzon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>Calabarzon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>Mimaropa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>Bicol Region</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>Western Visayas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>Central Visayas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>Eastern Visayas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>Zamboanga Peninsula</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>Northern Mindanao</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>Davao Region</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>Soccsksargen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>Caraga</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>BARMM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>NCR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>CAR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>Ilocos Region</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Geolocation           ADM1ALT1EN\n",
       "0                        NCR: National Capital Region                  NCR\n",
       "1               CAR: Cordillera Administrative Region                  CAR\n",
       "2                             Region 1: Ilocos Region        Ilocos Region\n",
       "3                            Region 2: Cagayan Valley       Cagayan Valley\n",
       "4                             Region 3: Central Luzon        Central Luzon\n",
       "5                               Region 4A: CALABARZON           Calabarzon\n",
       "6               MIMAROPA: Southwestern Tagalog Region             Mimaropa\n",
       "7                              Region 5: Bicol Region         Bicol Region\n",
       "8                           Region 6: Western Visayas      Western Visayas\n",
       "9                           Region 7: Central Visayas      Central Visayas\n",
       "10                          Region 8: Eastern Visayas      Eastern Visayas\n",
       "11                      Region 9: Zamboanga Peninsula  Zamboanga Peninsula\n",
       "12                       Region 10: Northern Mindanao    Northern Mindanao\n",
       "13                            Region 11: Davao Region         Davao Region\n",
       "14                            Region 12: SOCCSKSARGEN         Soccsksargen\n",
       "15               CARAGA: CARAGA Administrative Region               Caraga\n",
       "16  BARMM: Bangsamoro Autonomous Region in Muslim ...                BARMM\n",
       "17                       NCR: National Capital Region                  NCR\n",
       "18              CAR: Cordillera Administrative Region                  CAR\n",
       "19                            Region 1: Ilocos Region        Ilocos Region"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df [['Geolocation', 'ADM1ALT1EN']].head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ea8b55c",
   "metadata": {},
   "source": [
    "We can see that the region names for the two columns refer to the same region. Since these two columns holds the same data, we can remove the `ADM1ALT1EN` column, and the other columns that holds data regarding the region name (i.e., `ADM1_EN`, `ADM1_PCODE`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2f0995f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Geolocation', 'Year', '1.2.1 Poverty Proportion',\n",
       "       '1.4.1 Net Elem Enrolment Rate',\n",
       "       '1.4.1 Net Elem Enrolment Rate (Girls)',\n",
       "       '1.4.1 Net Elem Enrolment Rate (Boys)', '1.4.1 Net JHS Enrolment Rate',\n",
       "       '1.4.1 Net JHS Enrolment Rate (Girls)',\n",
       "       '1.4.1 Net JHS Enrolment Rate (Boys)', '1.4.1 Net SHS Enrolment Rate',\n",
       "       '1.4.1 Net SHS Enrolment Rate (Girls)',\n",
       "       '1.4.1 Net SHS Enrolment Rate (Boys)',\n",
       "       '1.5.4 Proportion of LGU with DRR',\n",
       "       '3.4.1 Mortality rate credited to NCD',\n",
       "       '3.4.1 Mortality rate credited to Cardio',\n",
       "       '3.4.1 Mortality rate credited to Cancer',\n",
       "       '3.4.1 Mortality rate credited to Diabetes',\n",
       "       '3.4.1 Mortality rate credited to Respi',\n",
       "       '3.7.1 Proportion of Contraceptive Use of Women',\n",
       "       '3.7.2 Teenage pregnancy rates per 1000', '4.1 Elem Completion Rate',\n",
       "       '4.1 Elem Completion Rate (Female)', '4.1 Elem Completion Rate (Male)',\n",
       "       '4.1 JHS Completion Rate', '4.1 JHS Completion Rate (Female)',\n",
       "       '4.1 JHS Completion Rate (Male)', '4.1 SHS Completion Rate',\n",
       "       '4.1 SHS Completion Rate (Female)', '4.1 SHS Completion Rate (Male)',\n",
       "       '4.c TVET trainers trained', '7.1.1 Proportion of pop with electricity',\n",
       "       '8.1.1 Growth rate of real GDP per capita',\n",
       "       '10.1.1.1 Income per capita growth rate of bottom 40',\n",
       "       '10.1.1.2 Income per capita growth rate',\n",
       "       '14.5.1.1 Coverage of protected areas',\n",
       "       '14.5.1.2 Coverage of protected NIPAS and Locally managed MPAs',\n",
       "       '16.1.1 Victims of intentional homicide per 100,000',\n",
       "       '16.1.s1 Number of murder cases', 'Changes in Inventories',\n",
       "       'Current Health Expenditure', 'Current Health Expenditure GR',\n",
       "       'Consumption Expenditure %', 'Consumption Expenditure GR',\n",
       "       'Gross Capital Formation', 'GRDP', 'Population',\n",
       "       'Primary Drop-out rate', 'Primary Drop-out rate (Girls)',\n",
       "       'Primary Drop-out rate (Boys)', 'Secondary Drop-out rate',\n",
       "       'Secondary Drop-out rate (Girls)', 'Secondary Drop-out rate (Boys)',\n",
       "       'Price Index for Agriculture', 'Shape_Leng', 'Shape_Area', 'geometry'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_columns = combined_df.columns [: 55].append (combined_df.columns [58: ])\n",
    "final_columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2356f0bc",
   "metadata": {},
   "source": [
    "Now, we will only get these columns in the combined DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f0963796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\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></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net SHS Enrolment Rate</th>\n",
       "      <th>...</th>\n",
       "      <th>Primary Drop-out rate</th>\n",
       "      <th>Primary Drop-out rate (Girls)</th>\n",
       "      <th>Primary Drop-out rate (Boys)</th>\n",
       "      <th>Secondary Drop-out rate</th>\n",
       "      <th>Secondary Drop-out rate (Girls)</th>\n",
       "      <th>Secondary Drop-out rate (Boys)</th>\n",
       "      <th>Price Index for Agriculture</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101.00</td>\n",
       "      <td>101.92</td>\n",
       "      <td>100.13</td>\n",
       "      <td>79.05</td>\n",
       "      <td>79.50</td>\n",
       "      <td>78.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.42</td>\n",
       "      <td>94.58</td>\n",
       "      <td>94.26</td>\n",
       "      <td>71.19</td>\n",
       "      <td>76.37</td>\n",
       "      <td>66.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.73</td>\n",
       "      <td>97.01</td>\n",
       "      <td>98.41</td>\n",
       "      <td>87.51</td>\n",
       "      <td>90.05</td>\n",
       "      <td>85.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.65</td>\n",
       "      <td>95.74</td>\n",
       "      <td>95.57</td>\n",
       "      <td>77.11</td>\n",
       "      <td>81.11</td>\n",
       "      <td>73.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.32</td>\n",
       "      <td>97.85</td>\n",
       "      <td>98.77</td>\n",
       "      <td>74.32</td>\n",
       "      <td>76.58</td>\n",
       "      <td>72.13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</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>369</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.975</td>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.850</td>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.350</td>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.525</td>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.950</td>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>374 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "0                         NCR: National Capital Region  2000   \n",
       "1                CAR: Cordillera Administrative Region  2000   \n",
       "2                              Region 1: Ilocos Region  2000   \n",
       "3                             Region 2: Cagayan Valley  2000   \n",
       "4                              Region 3: Central Luzon  2000   \n",
       "..                                                 ...   ...   \n",
       "369                       Region 10: Northern Mindanao  2021   \n",
       "370                            Region 11: Davao Region  2021   \n",
       "371                            Region 12: SOCCSKSARGEN  2021   \n",
       "372               CARAGA: CARAGA Administrative Region  2021   \n",
       "373  BARMM: Bangsamoro Autonomous Region in Muslim ...  2021   \n",
       "\n",
       "     1.2.1 Poverty Proportion  1.4.1 Net Elem Enrolment Rate  \\\n",
       "0                         NaN                         101.00   \n",
       "1                         NaN                          94.42   \n",
       "2                         NaN                          97.73   \n",
       "3                         NaN                          95.65   \n",
       "4                         NaN                          98.32   \n",
       "..                        ...                            ...   \n",
       "369                       NaN                            NaN   \n",
       "370                       NaN                            NaN   \n",
       "371                       NaN                            NaN   \n",
       "372                       NaN                            NaN   \n",
       "373                       NaN                            NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Girls)  \\\n",
       "0                                   101.92   \n",
       "1                                    94.58   \n",
       "2                                    97.01   \n",
       "3                                    95.74   \n",
       "4                                    97.85   \n",
       "..                                     ...   \n",
       "369                                    NaN   \n",
       "370                                    NaN   \n",
       "371                                    NaN   \n",
       "372                                    NaN   \n",
       "373                                    NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Boys)  1.4.1 Net JHS Enrolment Rate  \\\n",
       "0                                  100.13                         79.05   \n",
       "1                                   94.26                         71.19   \n",
       "2                                   98.41                         87.51   \n",
       "3                                   95.57                         77.11   \n",
       "4                                   98.77                         74.32   \n",
       "..                                    ...                           ...   \n",
       "369                                   NaN                           NaN   \n",
       "370                                   NaN                           NaN   \n",
       "371                                   NaN                           NaN   \n",
       "372                                   NaN                           NaN   \n",
       "373                                   NaN                           NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Girls)  \\\n",
       "0                                   79.50   \n",
       "1                                   76.37   \n",
       "2                                   90.05   \n",
       "3                                   81.11   \n",
       "4                                   76.58   \n",
       "..                                    ...   \n",
       "369                                   NaN   \n",
       "370                                   NaN   \n",
       "371                                   NaN   \n",
       "372                                   NaN   \n",
       "373                                   NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Boys)  1.4.1 Net SHS Enrolment Rate  ...  \\\n",
       "0                                  78.57                           NaN  ...   \n",
       "1                                  66.14                           NaN  ...   \n",
       "2                                  85.07                           NaN  ...   \n",
       "3                                  73.31                           NaN  ...   \n",
       "4                                  72.13                           NaN  ...   \n",
       "..                                   ...                           ...  ...   \n",
       "369                                  NaN                           NaN  ...   \n",
       "370                                  NaN                           NaN  ...   \n",
       "371                                  NaN                           NaN  ...   \n",
       "372                                  NaN                           NaN  ...   \n",
       "373                                  NaN                           NaN  ...   \n",
       "\n",
       "     Primary Drop-out rate  Primary Drop-out rate (Girls)  \\\n",
       "0                      NaN                            NaN   \n",
       "1                      NaN                            NaN   \n",
       "2                      NaN                            NaN   \n",
       "3                      NaN                            NaN   \n",
       "4                      NaN                            NaN   \n",
       "..                     ...                            ...   \n",
       "369                    NaN                            NaN   \n",
       "370                    NaN                            NaN   \n",
       "371                    NaN                            NaN   \n",
       "372                    NaN                            NaN   \n",
       "373                    NaN                            NaN   \n",
       "\n",
       "     Primary Drop-out rate (Boys)  Secondary Drop-out rate  \\\n",
       "0                             NaN                      NaN   \n",
       "1                             NaN                      NaN   \n",
       "2                             NaN                      NaN   \n",
       "3                             NaN                      NaN   \n",
       "4                             NaN                      NaN   \n",
       "..                            ...                      ...   \n",
       "369                           NaN                      NaN   \n",
       "370                           NaN                      NaN   \n",
       "371                           NaN                      NaN   \n",
       "372                           NaN                      NaN   \n",
       "373                           NaN                      NaN   \n",
       "\n",
       "     Secondary Drop-out rate (Girls)  Secondary Drop-out rate (Boys)  \\\n",
       "0                                NaN                             NaN   \n",
       "1                                NaN                             NaN   \n",
       "2                                NaN                             NaN   \n",
       "3                                NaN                             NaN   \n",
       "4                                NaN                             NaN   \n",
       "..                               ...                             ...   \n",
       "369                              NaN                             NaN   \n",
       "370                              NaN                             NaN   \n",
       "371                              NaN                             NaN   \n",
       "372                              NaN                             NaN   \n",
       "373                              NaN                             NaN   \n",
       "\n",
       "     Price Index for Agriculture  Shape_Leng  Shape_Area  \\\n",
       "0                            NaN    2.320234    0.050216   \n",
       "1                            NaN    8.027454    1.546712   \n",
       "2                            NaN   14.995101    1.043983   \n",
       "3                            NaN   19.139048    2.241812   \n",
       "4                            NaN   15.949563    1.793513   \n",
       "..                           ...         ...         ...   \n",
       "369                      107.975   15.002953    1.435115   \n",
       "370                      110.850   17.934222    1.539971   \n",
       "371                      103.350   13.229749    1.471068   \n",
       "372                      104.525   28.166754    1.540820   \n",
       "373                       91.950   53.623497    1.050272   \n",
       "\n",
       "                                              geometry  \n",
       "0    POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1    POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2    MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3    MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4    MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "..                                                 ...  \n",
       "369  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "370  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "371  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "372  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "373  MULTIPOLYGON (((119.46876076500007 4.593602191...  \n",
       "\n",
       "[374 rows x 56 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df = combined_df[final_columns]\n",
    "combined_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecdbf39b",
   "metadata": {},
   "source": [
    "### Converting the Pandas DataFrame to GeoPandas DataFrame\n",
    "\n",
    "Lastly, we would be making a `GeoDataFrame` using the Pandas DataFrame that we have created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "55018f29",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net Elem Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Girls)</th>\n",
       "      <th>1.4.1 Net JHS Enrolment Rate (Boys)</th>\n",
       "      <th>1.4.1 Net SHS Enrolment Rate</th>\n",
       "      <th>...</th>\n",
       "      <th>Primary Drop-out rate</th>\n",
       "      <th>Primary Drop-out rate (Girls)</th>\n",
       "      <th>Primary Drop-out rate (Boys)</th>\n",
       "      <th>Secondary Drop-out rate</th>\n",
       "      <th>Secondary Drop-out rate (Girls)</th>\n",
       "      <th>Secondary Drop-out rate (Boys)</th>\n",
       "      <th>Price Index for Agriculture</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101.00</td>\n",
       "      <td>101.92</td>\n",
       "      <td>100.13</td>\n",
       "      <td>79.05</td>\n",
       "      <td>79.50</td>\n",
       "      <td>78.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.320234</td>\n",
       "      <td>0.050216</td>\n",
       "      <td>POLYGON ((121.03842 14.78525, 121.03876 14.785...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.42</td>\n",
       "      <td>94.58</td>\n",
       "      <td>94.26</td>\n",
       "      <td>71.19</td>\n",
       "      <td>76.37</td>\n",
       "      <td>66.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.027454</td>\n",
       "      <td>1.546712</td>\n",
       "      <td>POLYGON ((121.22208 18.50058, 121.22086 18.483...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.73</td>\n",
       "      <td>97.01</td>\n",
       "      <td>98.41</td>\n",
       "      <td>87.51</td>\n",
       "      <td>90.05</td>\n",
       "      <td>85.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.995101</td>\n",
       "      <td>1.043983</td>\n",
       "      <td>MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.65</td>\n",
       "      <td>95.74</td>\n",
       "      <td>95.57</td>\n",
       "      <td>77.11</td>\n",
       "      <td>81.11</td>\n",
       "      <td>73.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.139048</td>\n",
       "      <td>2.241812</td>\n",
       "      <td>MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.32</td>\n",
       "      <td>97.85</td>\n",
       "      <td>98.77</td>\n",
       "      <td>74.32</td>\n",
       "      <td>76.58</td>\n",
       "      <td>72.13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.949563</td>\n",
       "      <td>1.793513</td>\n",
       "      <td>MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...</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>369</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.975</td>\n",
       "      <td>15.002953</td>\n",
       "      <td>1.435115</td>\n",
       "      <td>MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.850</td>\n",
       "      <td>17.934222</td>\n",
       "      <td>1.539971</td>\n",
       "      <td>MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.350</td>\n",
       "      <td>13.229749</td>\n",
       "      <td>1.471068</td>\n",
       "      <td>MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.525</td>\n",
       "      <td>28.166754</td>\n",
       "      <td>1.540820</td>\n",
       "      <td>MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.950</td>\n",
       "      <td>53.623497</td>\n",
       "      <td>1.050272</td>\n",
       "      <td>MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>374 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "0                         NCR: National Capital Region  2000   \n",
       "1                CAR: Cordillera Administrative Region  2000   \n",
       "2                              Region 1: Ilocos Region  2000   \n",
       "3                             Region 2: Cagayan Valley  2000   \n",
       "4                              Region 3: Central Luzon  2000   \n",
       "..                                                 ...   ...   \n",
       "369                       Region 10: Northern Mindanao  2021   \n",
       "370                            Region 11: Davao Region  2021   \n",
       "371                            Region 12: SOCCSKSARGEN  2021   \n",
       "372               CARAGA: CARAGA Administrative Region  2021   \n",
       "373  BARMM: Bangsamoro Autonomous Region in Muslim ...  2021   \n",
       "\n",
       "     1.2.1 Poverty Proportion  1.4.1 Net Elem Enrolment Rate  \\\n",
       "0                         NaN                         101.00   \n",
       "1                         NaN                          94.42   \n",
       "2                         NaN                          97.73   \n",
       "3                         NaN                          95.65   \n",
       "4                         NaN                          98.32   \n",
       "..                        ...                            ...   \n",
       "369                       NaN                            NaN   \n",
       "370                       NaN                            NaN   \n",
       "371                       NaN                            NaN   \n",
       "372                       NaN                            NaN   \n",
       "373                       NaN                            NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Girls)  \\\n",
       "0                                   101.92   \n",
       "1                                    94.58   \n",
       "2                                    97.01   \n",
       "3                                    95.74   \n",
       "4                                    97.85   \n",
       "..                                     ...   \n",
       "369                                    NaN   \n",
       "370                                    NaN   \n",
       "371                                    NaN   \n",
       "372                                    NaN   \n",
       "373                                    NaN   \n",
       "\n",
       "     1.4.1 Net Elem Enrolment Rate (Boys)  1.4.1 Net JHS Enrolment Rate  \\\n",
       "0                                  100.13                         79.05   \n",
       "1                                   94.26                         71.19   \n",
       "2                                   98.41                         87.51   \n",
       "3                                   95.57                         77.11   \n",
       "4                                   98.77                         74.32   \n",
       "..                                    ...                           ...   \n",
       "369                                   NaN                           NaN   \n",
       "370                                   NaN                           NaN   \n",
       "371                                   NaN                           NaN   \n",
       "372                                   NaN                           NaN   \n",
       "373                                   NaN                           NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Girls)  \\\n",
       "0                                   79.50   \n",
       "1                                   76.37   \n",
       "2                                   90.05   \n",
       "3                                   81.11   \n",
       "4                                   76.58   \n",
       "..                                    ...   \n",
       "369                                   NaN   \n",
       "370                                   NaN   \n",
       "371                                   NaN   \n",
       "372                                   NaN   \n",
       "373                                   NaN   \n",
       "\n",
       "     1.4.1 Net JHS Enrolment Rate (Boys)  1.4.1 Net SHS Enrolment Rate  ...  \\\n",
       "0                                  78.57                           NaN  ...   \n",
       "1                                  66.14                           NaN  ...   \n",
       "2                                  85.07                           NaN  ...   \n",
       "3                                  73.31                           NaN  ...   \n",
       "4                                  72.13                           NaN  ...   \n",
       "..                                   ...                           ...  ...   \n",
       "369                                  NaN                           NaN  ...   \n",
       "370                                  NaN                           NaN  ...   \n",
       "371                                  NaN                           NaN  ...   \n",
       "372                                  NaN                           NaN  ...   \n",
       "373                                  NaN                           NaN  ...   \n",
       "\n",
       "     Primary Drop-out rate  Primary Drop-out rate (Girls)  \\\n",
       "0                      NaN                            NaN   \n",
       "1                      NaN                            NaN   \n",
       "2                      NaN                            NaN   \n",
       "3                      NaN                            NaN   \n",
       "4                      NaN                            NaN   \n",
       "..                     ...                            ...   \n",
       "369                    NaN                            NaN   \n",
       "370                    NaN                            NaN   \n",
       "371                    NaN                            NaN   \n",
       "372                    NaN                            NaN   \n",
       "373                    NaN                            NaN   \n",
       "\n",
       "     Primary Drop-out rate (Boys)  Secondary Drop-out rate  \\\n",
       "0                             NaN                      NaN   \n",
       "1                             NaN                      NaN   \n",
       "2                             NaN                      NaN   \n",
       "3                             NaN                      NaN   \n",
       "4                             NaN                      NaN   \n",
       "..                            ...                      ...   \n",
       "369                           NaN                      NaN   \n",
       "370                           NaN                      NaN   \n",
       "371                           NaN                      NaN   \n",
       "372                           NaN                      NaN   \n",
       "373                           NaN                      NaN   \n",
       "\n",
       "     Secondary Drop-out rate (Girls)  Secondary Drop-out rate (Boys)  \\\n",
       "0                                NaN                             NaN   \n",
       "1                                NaN                             NaN   \n",
       "2                                NaN                             NaN   \n",
       "3                                NaN                             NaN   \n",
       "4                                NaN                             NaN   \n",
       "..                               ...                             ...   \n",
       "369                              NaN                             NaN   \n",
       "370                              NaN                             NaN   \n",
       "371                              NaN                             NaN   \n",
       "372                              NaN                             NaN   \n",
       "373                              NaN                             NaN   \n",
       "\n",
       "     Price Index for Agriculture  Shape_Leng  Shape_Area  \\\n",
       "0                            NaN    2.320234    0.050216   \n",
       "1                            NaN    8.027454    1.546712   \n",
       "2                            NaN   14.995101    1.043983   \n",
       "3                            NaN   19.139048    2.241812   \n",
       "4                            NaN   15.949563    1.793513   \n",
       "..                           ...         ...         ...   \n",
       "369                      107.975   15.002953    1.435115   \n",
       "370                      110.850   17.934222    1.539971   \n",
       "371                      103.350   13.229749    1.471068   \n",
       "372                      104.525   28.166754    1.540820   \n",
       "373                       91.950   53.623497    1.050272   \n",
       "\n",
       "                                              geometry  \n",
       "0    POLYGON ((121.03842 14.78525, 121.03876 14.785...  \n",
       "1    POLYGON ((121.22208 18.50058, 121.22086 18.483...  \n",
       "2    MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...  \n",
       "3    MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...  \n",
       "4    MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...  \n",
       "..                                                 ...  \n",
       "369  MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...  \n",
       "370  MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...  \n",
       "371  MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...  \n",
       "372  MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...  \n",
       "373  MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...  \n",
       "\n",
       "[374 rows x 56 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf = gpd.GeoDataFrame(combined_df, geometry = combined_df ['geometry'])\n",
    "\n",
    "gdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf6d482c",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis\n",
    "\n",
    "To explore that the combined dataset can be used for visualizations, exploratory data analysis was done. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "340bee4e",
   "metadata": {},
   "source": [
    "### Which regions that have the highest number of murder cases from the most recent data?\n",
    "\n",
    "First, since we will be exploring the number of murder cases in the Philippines, we will only get four columns: \n",
    "1. The `Geolocation` column determines the region name\n",
    "2. The `Year` column provides the information on the most recent data \n",
    "3. The `16.1.s1 Number of murder cases` holds the information about the number of the murder cases per region\n",
    "4. The `geometry` will be used for the geospatial visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "7205af20",
   "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>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>16.1.s1 Number of murder cases</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2016</td>\n",
       "      <td>2318.0</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2016</td>\n",
       "      <td>180.0</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2016</td>\n",
       "      <td>560.0</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2016</td>\n",
       "      <td>321.0</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2016</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2021</td>\n",
       "      <td>285.0</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>356.0</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2021</td>\n",
       "      <td>201.0</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2021</td>\n",
       "      <td>217.0</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2021</td>\n",
       "      <td>373.0</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>102 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "272                       NCR: National Capital Region  2016   \n",
       "273              CAR: Cordillera Administrative Region  2016   \n",
       "274                            Region 1: Ilocos Region  2016   \n",
       "275                           Region 2: Cagayan Valley  2016   \n",
       "276                            Region 3: Central Luzon  2016   \n",
       "..                                                 ...   ...   \n",
       "369                       Region 10: Northern Mindanao  2021   \n",
       "370                            Region 11: Davao Region  2021   \n",
       "371                            Region 12: SOCCSKSARGEN  2021   \n",
       "372               CARAGA: CARAGA Administrative Region  2021   \n",
       "373  BARMM: Bangsamoro Autonomous Region in Muslim ...  2021   \n",
       "\n",
       "     16.1.s1 Number of murder cases  \\\n",
       "272                          2318.0   \n",
       "273                           180.0   \n",
       "274                           560.0   \n",
       "275                           321.0   \n",
       "276                          1110.0   \n",
       "..                              ...   \n",
       "369                           285.0   \n",
       "370                           356.0   \n",
       "371                           201.0   \n",
       "372                           217.0   \n",
       "373                           373.0   \n",
       "\n",
       "                                              geometry  \n",
       "272  POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "273  POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "274  MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "275  MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "276  MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "..                                                 ...  \n",
       "369  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "370  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "371  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "372  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "373  MULTIPOLYGON (((119.46876076500007 4.593602191...  \n",
       "\n",
       "[102 rows x 4 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df[['Geolocation', 'Year', '16.1.s1 Number of murder cases', 'geometry']].dropna ()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "543be46a",
   "metadata": {},
   "source": [
    "From the table, we were able to determine that the latest year that we have data on the murder cases is the year **2021**, thus, we will be getting the data on this year. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "b39f726a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>16.1.s1 Number of murder cases</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>496.0</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>49.0</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>148.0</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>102.0</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>315.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>676.0</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>108.0</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>227.0</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>386.0</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>407.0</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>263.0</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>236.0</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>285.0</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>356.0</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>201.0</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>217.0</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>373.0</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
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      "text/plain": [
       "                                          Geolocation  \\\n",
       "0                        NCR: National Capital Region   \n",
       "1               CAR: Cordillera Administrative Region   \n",
       "2                             Region 1: Ilocos Region   \n",
       "3                            Region 2: Cagayan Valley   \n",
       "4                             Region 3: Central Luzon   \n",
       "5                               Region 4A: CALABARZON   \n",
       "6               MIMAROPA: Southwestern Tagalog Region   \n",
       "7                              Region 5: Bicol Region   \n",
       "8                           Region 6: Western Visayas   \n",
       "9                           Region 7: Central Visayas   \n",
       "10                          Region 8: Eastern Visayas   \n",
       "11                      Region 9: Zamboanga Peninsula   \n",
       "12                       Region 10: Northern Mindanao   \n",
       "13                            Region 11: Davao Region   \n",
       "14                            Region 12: SOCCSKSARGEN   \n",
       "15               CARAGA: CARAGA Administrative Region   \n",
       "16  BARMM: Bangsamoro Autonomous Region in Muslim ...   \n",
       "\n",
       "    16.1.s1 Number of murder cases  \\\n",
       "0                            496.0   \n",
       "1                             49.0   \n",
       "2                            148.0   \n",
       "3                            102.0   \n",
       "4                            315.0   \n",
       "5                            676.0   \n",
       "6                            108.0   \n",
       "7                            227.0   \n",
       "8                            386.0   \n",
       "9                            407.0   \n",
       "10                           263.0   \n",
       "11                           236.0   \n",
       "12                           285.0   \n",
       "13                           356.0   \n",
       "14                           201.0   \n",
       "15                           217.0   \n",
       "16                           373.0   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1   POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2   MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3   MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4   MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "5   MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "6   MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "7   MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "8   MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "9   MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "10  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "11  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "12  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "13  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "14  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "15  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "16  MULTIPOLYGON (((119.46876076500007 4.593602191...  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "murder2021 = combined_df[combined_df['Year'] == 2021][['Geolocation','16.1.s1 Number of murder cases', 'geometry']]\n",
    "murder2021 = murder2021.reset_index (drop = True)\n",
    "murder2021"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e019ec09",
   "metadata": {},
   "source": [
    "Now, we will convert the DataFrame that we have into a `GeoDataFrame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "cfd99cfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>16.1.s1 Number of murder cases</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>496.0</td>\n",
       "      <td>POLYGON ((121.03842 14.78525, 121.03876 14.785...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>49.0</td>\n",
       "      <td>POLYGON ((121.22208 18.50058, 121.22086 18.483...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>148.0</td>\n",
       "      <td>MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...</td>\n",
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       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>102.0</td>\n",
       "      <td>MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>315.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>676.0</td>\n",
       "      <td>MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>108.0</td>\n",
       "      <td>MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>227.0</td>\n",
       "      <td>MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>386.0</td>\n",
       "      <td>MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>407.0</td>\n",
       "      <td>MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>263.0</td>\n",
       "      <td>MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>236.0</td>\n",
       "      <td>MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>285.0</td>\n",
       "      <td>MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>356.0</td>\n",
       "      <td>MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>201.0</td>\n",
       "      <td>MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>217.0</td>\n",
       "      <td>MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>373.0</td>\n",
       "      <td>MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                                          Geolocation  \\\n",
       "0                        NCR: National Capital Region   \n",
       "1               CAR: Cordillera Administrative Region   \n",
       "2                             Region 1: Ilocos Region   \n",
       "3                            Region 2: Cagayan Valley   \n",
       "4                             Region 3: Central Luzon   \n",
       "5                               Region 4A: CALABARZON   \n",
       "6               MIMAROPA: Southwestern Tagalog Region   \n",
       "7                              Region 5: Bicol Region   \n",
       "8                           Region 6: Western Visayas   \n",
       "9                           Region 7: Central Visayas   \n",
       "10                          Region 8: Eastern Visayas   \n",
       "11                      Region 9: Zamboanga Peninsula   \n",
       "12                       Region 10: Northern Mindanao   \n",
       "13                            Region 11: Davao Region   \n",
       "14                            Region 12: SOCCSKSARGEN   \n",
       "15               CARAGA: CARAGA Administrative Region   \n",
       "16  BARMM: Bangsamoro Autonomous Region in Muslim ...   \n",
       "\n",
       "    16.1.s1 Number of murder cases  \\\n",
       "0                            496.0   \n",
       "1                             49.0   \n",
       "2                            148.0   \n",
       "3                            102.0   \n",
       "4                            315.0   \n",
       "5                            676.0   \n",
       "6                            108.0   \n",
       "7                            227.0   \n",
       "8                            386.0   \n",
       "9                            407.0   \n",
       "10                           263.0   \n",
       "11                           236.0   \n",
       "12                           285.0   \n",
       "13                           356.0   \n",
       "14                           201.0   \n",
       "15                           217.0   \n",
       "16                           373.0   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03842 14.78525, 121.03876 14.785...  \n",
       "1   POLYGON ((121.22208 18.50058, 121.22086 18.483...  \n",
       "2   MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...  \n",
       "3   MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...  \n",
       "4   MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...  \n",
       "5   MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...  \n",
       "6   MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...  \n",
       "7   MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...  \n",
       "8   MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...  \n",
       "9   MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...  \n",
       "10  MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...  \n",
       "11  MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...  \n",
       "12  MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...  \n",
       "13  MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...  \n",
       "14  MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...  \n",
       "15  MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...  \n",
       "16  MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "murder2021 = gpd.GeoDataFrame(murder2021, geometry = murder2021 ['geometry'])\n",
    "murder2021"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc199812",
   "metadata": {},
   "source": [
    "With a GeoDataFrame, we can now visualize the number of murder cases in the Philippines in 2021."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "ca09f7d7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(113.66153858585, 127.22131926315006, 3.760564947900073, 21.948615028100072)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = murder2021.plot(figsize = (15, 8), \n",
    "                     column = '16.1.s1 Number of murder cases', \n",
    "                     cmap = plt.cm.Reds, \n",
    "                     legend = True, \n",
    "                     edgecolor = 'gainsboro')\n",
    "\n",
    "ax.set_title('Murder Cases in the Philippines in 2021', fontsize = 15)\n",
    "ax.axis(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06471636",
   "metadata": {},
   "source": [
    "From this map, we can easily determine that the highest number of murder cases in the Philippines is found in the National Capital Region."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "accb36e4",
   "metadata": {},
   "source": [
    "### Which region has the highest amount of poverty proportion from the most recent data?\n",
    "\n",
    "Next, we would be looking at the amount of poverty prortion per region. Like in the previous EDA, we have to determine the latest year that has the data for the **1.2.1 Poverty Proportion**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0df9726b",
   "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>Geolocation</th>\n",
       "      <th>Year</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.1</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>22.7</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>18.8</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2015</td>\n",
       "      <td>17.8</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2015</td>\n",
       "      <td>10.5</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>2015</td>\n",
       "      <td>12.5</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>25.2</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>39.8</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>2015</td>\n",
       "      <td>24.6</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>2015</td>\n",
       "      <td>29.4</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>2015</td>\n",
       "      <td>41.3</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>2015</td>\n",
       "      <td>37.7</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2015</td>\n",
       "      <td>38.7</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>23.5</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2015</td>\n",
       "      <td>38.1</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2015</td>\n",
       "      <td>39.7</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>59.4</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>2.2</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>12.0</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>9.9</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>2018</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.1</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>15.1</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>27.0</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>2018</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>2018</td>\n",
       "      <td>17.7</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>2018</td>\n",
       "      <td>30.7</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>2018</td>\n",
       "      <td>32.7</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>2018</td>\n",
       "      <td>23.1</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>19.1</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>2018</td>\n",
       "      <td>28.2</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>321</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>2018</td>\n",
       "      <td>30.5</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>2018</td>\n",
       "      <td>61.8</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Geolocation  Year  \\\n",
       "255                       NCR: National Capital Region  2015   \n",
       "256              CAR: Cordillera Administrative Region  2015   \n",
       "257                            Region 1: Ilocos Region  2015   \n",
       "258                           Region 2: Cagayan Valley  2015   \n",
       "259                            Region 3: Central Luzon  2015   \n",
       "260                              Region 4A: CALABARZON  2015   \n",
       "261              MIMAROPA: Southwestern Tagalog Region  2015   \n",
       "262                             Region 5: Bicol Region  2015   \n",
       "263                          Region 6: Western Visayas  2015   \n",
       "264                          Region 7: Central Visayas  2015   \n",
       "265                          Region 8: Eastern Visayas  2015   \n",
       "266                      Region 9: Zamboanga Peninsula  2015   \n",
       "267                       Region 10: Northern Mindanao  2015   \n",
       "268                            Region 11: Davao Region  2015   \n",
       "269                            Region 12: SOCCSKSARGEN  2015   \n",
       "270               CARAGA: CARAGA Administrative Region  2015   \n",
       "271  BARMM: Bangsamoro Autonomous Region in Muslim ...  2015   \n",
       "306                       NCR: National Capital Region  2018   \n",
       "307              CAR: Cordillera Administrative Region  2018   \n",
       "308                            Region 1: Ilocos Region  2018   \n",
       "309                           Region 2: Cagayan Valley  2018   \n",
       "310                            Region 3: Central Luzon  2018   \n",
       "311                              Region 4A: CALABARZON  2018   \n",
       "312              MIMAROPA: Southwestern Tagalog Region  2018   \n",
       "313                             Region 5: Bicol Region  2018   \n",
       "314                          Region 6: Western Visayas  2018   \n",
       "315                          Region 7: Central Visayas  2018   \n",
       "316                          Region 8: Eastern Visayas  2018   \n",
       "317                      Region 9: Zamboanga Peninsula  2018   \n",
       "318                       Region 10: Northern Mindanao  2018   \n",
       "319                            Region 11: Davao Region  2018   \n",
       "320                            Region 12: SOCCSKSARGEN  2018   \n",
       "321               CARAGA: CARAGA Administrative Region  2018   \n",
       "322  BARMM: Bangsamoro Autonomous Region in Muslim ...  2018   \n",
       "\n",
       "     1.2.1 Poverty Proportion  \\\n",
       "255                       4.1   \n",
       "256                      22.7   \n",
       "257                      18.8   \n",
       "258                      17.8   \n",
       "259                      10.5   \n",
       "260                      12.5   \n",
       "261                      25.2   \n",
       "262                      39.8   \n",
       "263                      24.6   \n",
       "264                      29.4   \n",
       "265                      41.3   \n",
       "266                      37.7   \n",
       "267                      38.7   \n",
       "268                      23.5   \n",
       "269                      38.1   \n",
       "270                      39.7   \n",
       "271                      59.4   \n",
       "306                       2.2   \n",
       "307                      12.0   \n",
       "308                       9.9   \n",
       "309                      16.3   \n",
       "310                       7.0   \n",
       "311                       7.1   \n",
       "312                      15.1   \n",
       "313                      27.0   \n",
       "314                      16.3   \n",
       "315                      17.7   \n",
       "316                      30.7   \n",
       "317                      32.7   \n",
       "318                      23.1   \n",
       "319                      19.1   \n",
       "320                      28.2   \n",
       "321                      30.5   \n",
       "322                      61.8   \n",
       "\n",
       "                                              geometry  \n",
       "255  POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "256  POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "257  MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "258  MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "259  MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "260  MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "261  MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "262  MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "263  MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "264  MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "265  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "266  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "267  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "268  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "269  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "270  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "271  MULTIPOLYGON (((119.46876076500007 4.593602191...  \n",
       "306  POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "307  POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "308  MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "309  MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "310  MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "311  MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "312  MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "313  MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "314  MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "315  MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "316  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "317  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "318  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "319  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "320  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "321  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "322  MULTIPOLYGON (((119.46876076500007 4.593602191...  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df[['Geolocation', 'Year', '1.2.1 Poverty Proportion', 'geometry']].dropna ()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ed15d97",
   "metadata": {},
   "source": [
    "From this, we are able to see that the latest data is from the year **2018**. \n",
    "\n",
    "Next, we would be getting the data (i.e., `Geolocation`, `1.2.1 Poverty Proportion`, and `geometry`) for the year 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "d1893388",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Geolocation</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2.2</td>\n",
       "      <td>POLYGON ((121.03841659800003 14.78524708100002...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>12.0</td>\n",
       "      <td>POLYGON ((121.22208115400008 18.50058094200005...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>9.9</td>\n",
       "      <td>MULTIPOLYGON (((119.8659631480001 15.815394096...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.46666630600009 16.92134842...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>7.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11686801200005 14.76308966...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>7.1</td>\n",
       "      <td>MULTIPOLYGON (((122.7216452990001 13.364847839...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>15.1</td>\n",
       "      <td>MULTIPOLYGON (((117.31259603500007 7.506706648...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>27.0</td>\n",
       "      <td>MULTIPOLYGON (((122.9882253830001 11.730793677...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.4968432280001 9.5560704530...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>17.7</td>\n",
       "      <td>MULTIPOLYGON (((123.27038790600011 9.084596680...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>30.7</td>\n",
       "      <td>MULTIPOLYGON (((125.06042068800002 9.964662372...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>32.7</td>\n",
       "      <td>MULTIPOLYGON (((121.88378639600012 6.691384652...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>23.1</td>\n",
       "      <td>MULTIPOLYGON (((123.57503388200007 8.633431735...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>19.1</td>\n",
       "      <td>MULTIPOLYGON (((125.39719472100012 5.437910860...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>28.2</td>\n",
       "      <td>MULTIPOLYGON (((124.241580956 7.26285967200004...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>30.5</td>\n",
       "      <td>MULTIPOLYGON (((126.34198239000011 8.877101650...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>61.8</td>\n",
       "      <td>MULTIPOLYGON (((119.46876076500007 4.593602191...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Geolocation  \\\n",
       "0                        NCR: National Capital Region   \n",
       "1               CAR: Cordillera Administrative Region   \n",
       "2                             Region 1: Ilocos Region   \n",
       "3                            Region 2: Cagayan Valley   \n",
       "4                             Region 3: Central Luzon   \n",
       "5                               Region 4A: CALABARZON   \n",
       "6               MIMAROPA: Southwestern Tagalog Region   \n",
       "7                              Region 5: Bicol Region   \n",
       "8                           Region 6: Western Visayas   \n",
       "9                           Region 7: Central Visayas   \n",
       "10                          Region 8: Eastern Visayas   \n",
       "11                      Region 9: Zamboanga Peninsula   \n",
       "12                       Region 10: Northern Mindanao   \n",
       "13                            Region 11: Davao Region   \n",
       "14                            Region 12: SOCCSKSARGEN   \n",
       "15               CARAGA: CARAGA Administrative Region   \n",
       "16  BARMM: Bangsamoro Autonomous Region in Muslim ...   \n",
       "\n",
       "    1.2.1 Poverty Proportion  \\\n",
       "0                        2.2   \n",
       "1                       12.0   \n",
       "2                        9.9   \n",
       "3                       16.3   \n",
       "4                        7.0   \n",
       "5                        7.1   \n",
       "6                       15.1   \n",
       "7                       27.0   \n",
       "8                       16.3   \n",
       "9                       17.7   \n",
       "10                      30.7   \n",
       "11                      32.7   \n",
       "12                      23.1   \n",
       "13                      19.1   \n",
       "14                      28.2   \n",
       "15                      30.5   \n",
       "16                      61.8   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03841659800003 14.78524708100002...  \n",
       "1   POLYGON ((121.22208115400008 18.50058094200005...  \n",
       "2   MULTIPOLYGON (((119.8659631480001 15.815394096...  \n",
       "3   MULTIPOLYGON (((122.46666630600009 16.92134842...  \n",
       "4   MULTIPOLYGON (((120.11686801200005 14.76308966...  \n",
       "5   MULTIPOLYGON (((122.7216452990001 13.364847839...  \n",
       "6   MULTIPOLYGON (((117.31259603500007 7.506706648...  \n",
       "7   MULTIPOLYGON (((122.9882253830001 11.730793677...  \n",
       "8   MULTIPOLYGON (((122.4968432280001 9.5560704530...  \n",
       "9   MULTIPOLYGON (((123.27038790600011 9.084596680...  \n",
       "10  MULTIPOLYGON (((125.06042068800002 9.964662372...  \n",
       "11  MULTIPOLYGON (((121.88378639600012 6.691384652...  \n",
       "12  MULTIPOLYGON (((123.57503388200007 8.633431735...  \n",
       "13  MULTIPOLYGON (((125.39719472100012 5.437910860...  \n",
       "14  MULTIPOLYGON (((124.241580956 7.26285967200004...  \n",
       "15  MULTIPOLYGON (((126.34198239000011 8.877101650...  \n",
       "16  MULTIPOLYGON (((119.46876076500007 4.593602191...  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pov_prop_2018 = combined_df[combined_df['Year'] == 2018][['Geolocation','1.2.1 Poverty Proportion', 'geometry']]\n",
    "pov_prop_2018 = pov_prop_2018.reset_index (drop = True)\n",
    "pov_prop_2018"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "564f76a6",
   "metadata": {},
   "source": [
    "Since we plan to create a map for this data, we would have to convert the Pandas DataFrame into a GeoDataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "36454b3f",
   "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>Geolocation</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2.2</td>\n",
       "      <td>POLYGON ((121.03842 14.78525, 121.03876 14.785...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>12.0</td>\n",
       "      <td>POLYGON ((121.22208 18.50058, 121.22086 18.483...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>9.9</td>\n",
       "      <td>MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>7.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>7.1</td>\n",
       "      <td>MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>15.1</td>\n",
       "      <td>MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>27.0</td>\n",
       "      <td>MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>17.7</td>\n",
       "      <td>MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>30.7</td>\n",
       "      <td>MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>32.7</td>\n",
       "      <td>MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>23.1</td>\n",
       "      <td>MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>19.1</td>\n",
       "      <td>MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>28.2</td>\n",
       "      <td>MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>30.5</td>\n",
       "      <td>MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>61.8</td>\n",
       "      <td>MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Geolocation  \\\n",
       "0                        NCR: National Capital Region   \n",
       "1               CAR: Cordillera Administrative Region   \n",
       "2                             Region 1: Ilocos Region   \n",
       "3                            Region 2: Cagayan Valley   \n",
       "4                             Region 3: Central Luzon   \n",
       "5                               Region 4A: CALABARZON   \n",
       "6               MIMAROPA: Southwestern Tagalog Region   \n",
       "7                              Region 5: Bicol Region   \n",
       "8                           Region 6: Western Visayas   \n",
       "9                           Region 7: Central Visayas   \n",
       "10                          Region 8: Eastern Visayas   \n",
       "11                      Region 9: Zamboanga Peninsula   \n",
       "12                       Region 10: Northern Mindanao   \n",
       "13                            Region 11: Davao Region   \n",
       "14                            Region 12: SOCCSKSARGEN   \n",
       "15               CARAGA: CARAGA Administrative Region   \n",
       "16  BARMM: Bangsamoro Autonomous Region in Muslim ...   \n",
       "\n",
       "    1.2.1 Poverty Proportion  \\\n",
       "0                        2.2   \n",
       "1                       12.0   \n",
       "2                        9.9   \n",
       "3                       16.3   \n",
       "4                        7.0   \n",
       "5                        7.1   \n",
       "6                       15.1   \n",
       "7                       27.0   \n",
       "8                       16.3   \n",
       "9                       17.7   \n",
       "10                      30.7   \n",
       "11                      32.7   \n",
       "12                      23.1   \n",
       "13                      19.1   \n",
       "14                      28.2   \n",
       "15                      30.5   \n",
       "16                      61.8   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03842 14.78525, 121.03876 14.785...  \n",
       "1   POLYGON ((121.22208 18.50058, 121.22086 18.483...  \n",
       "2   MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...  \n",
       "3   MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...  \n",
       "4   MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...  \n",
       "5   MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...  \n",
       "6   MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...  \n",
       "7   MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...  \n",
       "8   MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...  \n",
       "9   MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...  \n",
       "10  MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...  \n",
       "11  MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...  \n",
       "12  MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...  \n",
       "13  MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...  \n",
       "14  MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...  \n",
       "15  MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...  \n",
       "16  MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pov_prop_2018 = gpd.GeoDataFrame(pov_prop_2018, geometry = pov_prop_2018 ['geometry'])\n",
    "pov_prop_2018"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c2564a1",
   "metadata": {},
   "source": [
    "Using this GeoDataFrame, we can now create a map to show the poverty propertion in the regions of the Philippines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "a7ca135b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(113.66153858585, 127.22131926315006, 3.760564947900073, 21.948615028100072)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = pov_prop_2018.plot(figsize = (15, 8), \n",
    "                     column = '1.2.1 Poverty Proportion', \n",
    "                     cmap = plt.cm.Reds, \n",
    "                     legend = True, \n",
    "                     edgecolor = 'gainsboro')\n",
    "\n",
    "ax.set_title('Poverty Proportion in the Philippines in 2018', fontsize = 15)\n",
    "ax.axis(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98add2f4",
   "metadata": {},
   "source": [
    "From this, we can see that the highest poverty proportion is in the **BARMM**. However, to ensure this, let us look at the sorted tabular data of the poverty proportion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "f1502bd8",
   "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>Geolocation</th>\n",
       "      <th>1.2.1 Poverty Proportion</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NCR: National Capital Region</td>\n",
       "      <td>2.2</td>\n",
       "      <td>POLYGON ((121.03842 14.78525, 121.03876 14.785...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Region 3: Central Luzon</td>\n",
       "      <td>7.0</td>\n",
       "      <td>MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Region 4A: CALABARZON</td>\n",
       "      <td>7.1</td>\n",
       "      <td>MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Region 1: Ilocos Region</td>\n",
       "      <td>9.9</td>\n",
       "      <td>MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CAR: Cordillera Administrative Region</td>\n",
       "      <td>12.0</td>\n",
       "      <td>POLYGON ((121.22208 18.50058, 121.22086 18.483...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MIMAROPA: Southwestern Tagalog Region</td>\n",
       "      <td>15.1</td>\n",
       "      <td>MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Region 2: Cagayan Valley</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Region 6: Western Visayas</td>\n",
       "      <td>16.3</td>\n",
       "      <td>MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Region 7: Central Visayas</td>\n",
       "      <td>17.7</td>\n",
       "      <td>MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Region 11: Davao Region</td>\n",
       "      <td>19.1</td>\n",
       "      <td>MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Region 10: Northern Mindanao</td>\n",
       "      <td>23.1</td>\n",
       "      <td>MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Region 5: Bicol Region</td>\n",
       "      <td>27.0</td>\n",
       "      <td>MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Region 12: SOCCSKSARGEN</td>\n",
       "      <td>28.2</td>\n",
       "      <td>MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>CARAGA: CARAGA Administrative Region</td>\n",
       "      <td>30.5</td>\n",
       "      <td>MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Region 8: Eastern Visayas</td>\n",
       "      <td>30.7</td>\n",
       "      <td>MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Region 9: Zamboanga Peninsula</td>\n",
       "      <td>32.7</td>\n",
       "      <td>MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BARMM: Bangsamoro Autonomous Region in Muslim ...</td>\n",
       "      <td>61.8</td>\n",
       "      <td>MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Geolocation  \\\n",
       "0                        NCR: National Capital Region   \n",
       "1                             Region 3: Central Luzon   \n",
       "2                               Region 4A: CALABARZON   \n",
       "3                             Region 1: Ilocos Region   \n",
       "4               CAR: Cordillera Administrative Region   \n",
       "5               MIMAROPA: Southwestern Tagalog Region   \n",
       "6                            Region 2: Cagayan Valley   \n",
       "7                           Region 6: Western Visayas   \n",
       "8                           Region 7: Central Visayas   \n",
       "9                             Region 11: Davao Region   \n",
       "10                       Region 10: Northern Mindanao   \n",
       "11                             Region 5: Bicol Region   \n",
       "12                            Region 12: SOCCSKSARGEN   \n",
       "13               CARAGA: CARAGA Administrative Region   \n",
       "14                          Region 8: Eastern Visayas   \n",
       "15                      Region 9: Zamboanga Peninsula   \n",
       "16  BARMM: Bangsamoro Autonomous Region in Muslim ...   \n",
       "\n",
       "    1.2.1 Poverty Proportion  \\\n",
       "0                        2.2   \n",
       "1                        7.0   \n",
       "2                        7.1   \n",
       "3                        9.9   \n",
       "4                       12.0   \n",
       "5                       15.1   \n",
       "6                       16.3   \n",
       "7                       16.3   \n",
       "8                       17.7   \n",
       "9                       19.1   \n",
       "10                      23.1   \n",
       "11                      27.0   \n",
       "12                      28.2   \n",
       "13                      30.5   \n",
       "14                      30.7   \n",
       "15                      32.7   \n",
       "16                      61.8   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((121.03842 14.78525, 121.03876 14.785...  \n",
       "1   MULTIPOLYGON (((120.11687 14.76309, 120.11689 ...  \n",
       "2   MULTIPOLYGON (((122.72165 13.36485, 122.72181 ...  \n",
       "3   MULTIPOLYGON (((119.86596 15.81539, 119.86597 ...  \n",
       "4   POLYGON ((121.22208 18.50058, 121.22086 18.483...  \n",
       "5   MULTIPOLYGON (((117.31260 7.50671, 117.31249 7...  \n",
       "6   MULTIPOLYGON (((122.46667 16.92135, 122.46674 ...  \n",
       "7   MULTIPOLYGON (((122.49684 9.55607, 122.49685 9...  \n",
       "8   MULTIPOLYGON (((123.27039 9.08460, 123.27040 9...  \n",
       "9   MULTIPOLYGON (((125.39719 5.43791, 125.39719 5...  \n",
       "10  MULTIPOLYGON (((123.57503 8.63343, 123.57462 8...  \n",
       "11  MULTIPOLYGON (((122.98823 11.73079, 122.98824 ...  \n",
       "12  MULTIPOLYGON (((124.24158 7.26286, 124.24233 7...  \n",
       "13  MULTIPOLYGON (((126.34198 8.87710, 126.34167 8...  \n",
       "14  MULTIPOLYGON (((125.06042 9.96466, 125.06043 9...  \n",
       "15  MULTIPOLYGON (((121.88379 6.69138, 121.88380 6...  \n",
       "16  MULTIPOLYGON (((119.46876 4.59360, 119.46881 4...  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pov_prop_2018 = pov_prop_2018.sort_values(by = ['1.2.1 Poverty Proportion']).reset_index (drop = True)\n",
    "pov_prop_2018"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8536e5b",
   "metadata": {},
   "source": [
    "To easily visualize these numbers (which are abstracted in the map), let us create a horizontal bar graph. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "abc31642",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(pov_prop_2018 ['Geolocation'], pov_prop_2018 ['1.2.1 Poverty Proportion'])\n",
    "\n",
    "plt.xlabel(\"Poverty Proportion\")\n",
    " \n",
    "plt.ylabel(\"Region Names\")  \n",
    "plt.title(\"Poverty Proportion in the Philippines in 2018\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d0159db",
   "metadata": {},
   "source": [
    "From the table and the two graphs, we can see that the **BARMM** has the highest poverty population, while the **National Capital Region** has the lowest."
   ]
  }
 ],
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