1. Data Cleaning Population.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a039fb8e",
   "metadata": {},
   "source": [
    "# Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aeeccaa7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1fe2149",
   "metadata": {},
   "source": [
    "# Importing the main dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3aa4ee7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "population_df = pd.read_csv('2021_densitat.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32480dfb",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Any</th>\n",
       "      <th>Codi_Districte</th>\n",
       "      <th>Nom_Districte</th>\n",
       "      <th>Codi_Barri</th>\n",
       "      <th>Nom_Barri</th>\n",
       "      <th>Població</th>\n",
       "      <th>Superfície (ha)</th>\n",
       "      <th>Superfície Residencial (ha)</th>\n",
       "      <th>Densitat (hab/ha)</th>\n",
       "      <th>Densitat neta (hab/ha)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>1</td>\n",
       "      <td>el Raval</td>\n",
       "      <td>47228</td>\n",
       "      <td>110.0</td>\n",
       "      <td>49.6</td>\n",
       "      <td>429</td>\n",
       "      <td>952</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>2</td>\n",
       "      <td>el Barri Gòtic</td>\n",
       "      <td>21827</td>\n",
       "      <td>81.6</td>\n",
       "      <td>34.1</td>\n",
       "      <td>268</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>3</td>\n",
       "      <td>la Barceloneta</td>\n",
       "      <td>14643</td>\n",
       "      <td>117.9</td>\n",
       "      <td>13.5</td>\n",
       "      <td>124</td>\n",
       "      <td>1081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>4</td>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>22131</td>\n",
       "      <td>111.0</td>\n",
       "      <td>32.4</td>\n",
       "      <td>199</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>5</td>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>31262</td>\n",
       "      <td>92.9</td>\n",
       "      <td>33.6</td>\n",
       "      <td>336</td>\n",
       "      <td>930</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>69</td>\n",
       "      <td>Diagonal Mar i el Front Marítim del Poblenou</td>\n",
       "      <td>13323</td>\n",
       "      <td>122.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>109</td>\n",
       "      <td>556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>70</td>\n",
       "      <td>el Besòs i el Maresme</td>\n",
       "      <td>25657</td>\n",
       "      <td>120.9</td>\n",
       "      <td>28.1</td>\n",
       "      <td>212</td>\n",
       "      <td>913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>71</td>\n",
       "      <td>Provençals del Poblenou</td>\n",
       "      <td>20949</td>\n",
       "      <td>108.6</td>\n",
       "      <td>15.3</td>\n",
       "      <td>193</td>\n",
       "      <td>1368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>72</td>\n",
       "      <td>Sant Martí de Provençals</td>\n",
       "      <td>26032</td>\n",
       "      <td>73.4</td>\n",
       "      <td>23.4</td>\n",
       "      <td>355</td>\n",
       "      <td>1111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>73</td>\n",
       "      <td>la Verneda i la Pau</td>\n",
       "      <td>28585</td>\n",
       "      <td>113.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>253</td>\n",
       "      <td>714</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 10 columns</p>\n",
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      "text/plain": [
       "     Any  Codi_Districte Nom_Districte  Codi_Barri  \\\n",
       "0   2021               1  Ciutat Vella           1   \n",
       "1   2021               1  Ciutat Vella           2   \n",
       "2   2021               1  Ciutat Vella           3   \n",
       "3   2021               1  Ciutat Vella           4   \n",
       "4   2021               2      Eixample           5   \n",
       "..   ...             ...           ...         ...   \n",
       "68  2021              10    Sant Martí          69   \n",
       "69  2021              10    Sant Martí          70   \n",
       "70  2021              10    Sant Martí          71   \n",
       "71  2021              10    Sant Martí          72   \n",
       "72  2021              10    Sant Martí          73   \n",
       "\n",
       "                                       Nom_Barri  Població  Superfície (ha)  \\\n",
       "0                                       el Raval     47228            110.0   \n",
       "1                                 el Barri Gòtic     21827             81.6   \n",
       "2                                 la Barceloneta     14643            117.9   \n",
       "3          Sant Pere, Santa Caterina i la Ribera     22131            111.0   \n",
       "4                                  el Fort Pienc     31262             92.9   \n",
       "..                                           ...       ...              ...   \n",
       "68  Diagonal Mar i el Front Marítim del Poblenou     13323            122.7   \n",
       "69                         el Besòs i el Maresme     25657            120.9   \n",
       "70                       Provençals del Poblenou     20949            108.6   \n",
       "71                      Sant Martí de Provençals     26032             73.4   \n",
       "72                           la Verneda i la Pau     28585            113.0   \n",
       "\n",
       "    Superfície Residencial (ha)  Densitat (hab/ha)  Densitat neta (hab/ha)  \n",
       "0                          49.6                429                     952  \n",
       "1                          34.1                268                     639  \n",
       "2                          13.5                124                    1081  \n",
       "3                          32.4                199                     683  \n",
       "4                          33.6                336                     930  \n",
       "..                          ...                ...                     ...  \n",
       "68                         24.0                109                     556  \n",
       "69                         28.1                212                     913  \n",
       "70                         15.3                193                    1368  \n",
       "71                         23.4                355                    1111  \n",
       "72                         40.0                253                     714  \n",
       "\n",
       "[73 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d08cdbc",
   "metadata": {},
   "source": [
    "# First look at its main features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "536f52db",
   "metadata": {},
   "outputs": [
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       "      <th>0</th>\n",
       "      <td>2021</td>\n",
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       "      <th>1</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
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       "      <td>el Barri Gòtic</td>\n",
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       "      <td>268</td>\n",
       "      <td>639</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>3</td>\n",
       "      <td>la Barceloneta</td>\n",
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       "      <td>1081</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>4</td>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>22131</td>\n",
       "      <td>111.0</td>\n",
       "      <td>32.4</td>\n",
       "      <td>199</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>5</td>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>31262</td>\n",
       "      <td>92.9</td>\n",
       "      <td>33.6</td>\n",
       "      <td>336</td>\n",
       "      <td>930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>6</td>\n",
       "      <td>la Sagrada Família</td>\n",
       "      <td>51319</td>\n",
       "      <td>104.2</td>\n",
       "      <td>51.0</td>\n",
       "      <td>493</td>\n",
       "      <td>1007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>7</td>\n",
       "      <td>la Dreta de l'Eixample</td>\n",
       "      <td>44675</td>\n",
       "      <td>212.0</td>\n",
       "      <td>113.9</td>\n",
       "      <td>211</td>\n",
       "      <td>392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>8</td>\n",
       "      <td>l'Antiga Esquerra de l'Eixample</td>\n",
       "      <td>41990</td>\n",
       "      <td>122.8</td>\n",
       "      <td>66.9</td>\n",
       "      <td>342</td>\n",
       "      <td>627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>9</td>\n",
       "      <td>la Nova Esquerra de l'Eixample</td>\n",
       "      <td>57054</td>\n",
       "      <td>134.1</td>\n",
       "      <td>65.2</td>\n",
       "      <td>426</td>\n",
       "      <td>876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Antoni</td>\n",
       "      <td>38053</td>\n",
       "      <td>80.4</td>\n",
       "      <td>41.3</td>\n",
       "      <td>473</td>\n",
       "      <td>921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>11</td>\n",
       "      <td>el Poble Sec</td>\n",
       "      <td>39400</td>\n",
       "      <td>458.5</td>\n",
       "      <td>38.1</td>\n",
       "      <td>86</td>\n",
       "      <td>1033</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>12</td>\n",
       "      <td>la Marina del Prat Vermell</td>\n",
       "      <td>1350</td>\n",
       "      <td>1423.7</td>\n",
       "      <td>35.5</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>13</td>\n",
       "      <td>la Marina de Port</td>\n",
       "      <td>30741</td>\n",
       "      <td>126.9</td>\n",
       "      <td>38.9</td>\n",
       "      <td>242</td>\n",
       "      <td>789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>14</td>\n",
       "      <td>la Font de la Guatlla</td>\n",
       "      <td>10084</td>\n",
       "      <td>29.7</td>\n",
       "      <td>11.5</td>\n",
       "      <td>339</td>\n",
       "      <td>873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>15</td>\n",
       "      <td>Hostafrancs</td>\n",
       "      <td>15842</td>\n",
       "      <td>41.0</td>\n",
       "      <td>22.1</td>\n",
       "      <td>386</td>\n",
       "      <td>717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>16</td>\n",
       "      <td>la Bordeta</td>\n",
       "      <td>19292</td>\n",
       "      <td>57.2</td>\n",
       "      <td>20.8</td>\n",
       "      <td>337</td>\n",
       "      <td>928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>17</td>\n",
       "      <td>Sants - Badal</td>\n",
       "      <td>24576</td>\n",
       "      <td>41.5</td>\n",
       "      <td>25.1</td>\n",
       "      <td>593</td>\n",
       "      <td>980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>18</td>\n",
       "      <td>Sants</td>\n",
       "      <td>43082</td>\n",
       "      <td>109.5</td>\n",
       "      <td>59.4</td>\n",
       "      <td>394</td>\n",
       "      <td>726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>19</td>\n",
       "      <td>les Corts</td>\n",
       "      <td>45422</td>\n",
       "      <td>141.0</td>\n",
       "      <td>64.7</td>\n",
       "      <td>322</td>\n",
       "      <td>702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>20</td>\n",
       "      <td>la Maternitat i Sant Ramon</td>\n",
       "      <td>23574</td>\n",
       "      <td>191.5</td>\n",
       "      <td>31.8</td>\n",
       "      <td>123</td>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Any  Codi_Districte   Nom_Districte  Codi_Barri  \\\n",
       "0   2021               1    Ciutat Vella           1   \n",
       "1   2021               1    Ciutat Vella           2   \n",
       "2   2021               1    Ciutat Vella           3   \n",
       "3   2021               1    Ciutat Vella           4   \n",
       "4   2021               2        Eixample           5   \n",
       "5   2021               2        Eixample           6   \n",
       "6   2021               2        Eixample           7   \n",
       "7   2021               2        Eixample           8   \n",
       "8   2021               2        Eixample           9   \n",
       "9   2021               2        Eixample          10   \n",
       "10  2021               3  Sants-Montjuïc          11   \n",
       "11  2021               3  Sants-Montjuïc          12   \n",
       "12  2021               3  Sants-Montjuïc          13   \n",
       "13  2021               3  Sants-Montjuïc          14   \n",
       "14  2021               3  Sants-Montjuïc          15   \n",
       "15  2021               3  Sants-Montjuïc          16   \n",
       "16  2021               3  Sants-Montjuïc          17   \n",
       "17  2021               3  Sants-Montjuïc          18   \n",
       "18  2021               4       Les Corts          19   \n",
       "19  2021               4       Les Corts          20   \n",
       "\n",
       "                                Nom_Barri  Població  Superfície (ha)  \\\n",
       "0                                el Raval     47228            110.0   \n",
       "1                          el Barri Gòtic     21827             81.6   \n",
       "2                          la Barceloneta     14643            117.9   \n",
       "3   Sant Pere, Santa Caterina i la Ribera     22131            111.0   \n",
       "4                           el Fort Pienc     31262             92.9   \n",
       "5                      la Sagrada Família     51319            104.2   \n",
       "6                  la Dreta de l'Eixample     44675            212.0   \n",
       "7         l'Antiga Esquerra de l'Eixample     41990            122.8   \n",
       "8          la Nova Esquerra de l'Eixample     57054            134.1   \n",
       "9                             Sant Antoni     38053             80.4   \n",
       "10                           el Poble Sec     39400            458.5   \n",
       "11             la Marina del Prat Vermell      1350           1423.7   \n",
       "12                      la Marina de Port     30741            126.9   \n",
       "13                  la Font de la Guatlla     10084             29.7   \n",
       "14                            Hostafrancs     15842             41.0   \n",
       "15                             la Bordeta     19292             57.2   \n",
       "16                          Sants - Badal     24576             41.5   \n",
       "17                                  Sants     43082            109.5   \n",
       "18                              les Corts     45422            141.0   \n",
       "19             la Maternitat i Sant Ramon     23574            191.5   \n",
       "\n",
       "    Superfície Residencial (ha)  Densitat (hab/ha)  Densitat neta (hab/ha)  \n",
       "0                          49.6                429                     952  \n",
       "1                          34.1                268                     639  \n",
       "2                          13.5                124                    1081  \n",
       "3                          32.4                199                     683  \n",
       "4                          33.6                336                     930  \n",
       "5                          51.0                493                    1007  \n",
       "6                         113.9                211                     392  \n",
       "7                          66.9                342                     627  \n",
       "8                          65.2                426                     876  \n",
       "9                          41.3                473                     921  \n",
       "10                         38.1                 86                    1033  \n",
       "11                         35.5                  1                      38  \n",
       "12                         38.9                242                     789  \n",
       "13                         11.5                339                     873  \n",
       "14                         22.1                386                     717  \n",
       "15                         20.8                337                     928  \n",
       "16                         25.1                593                     980  \n",
       "17                         59.4                394                     726  \n",
       "18                         64.7                322                     702  \n",
       "19                         31.8                123                     741  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bfd77176",
   "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>Any</th>\n",
       "      <th>Codi_Districte</th>\n",
       "      <th>Nom_Districte</th>\n",
       "      <th>Codi_Barri</th>\n",
       "      <th>Nom_Barri</th>\n",
       "      <th>Població</th>\n",
       "      <th>Superfície (ha)</th>\n",
       "      <th>Superfície Residencial (ha)</th>\n",
       "      <th>Densitat (hab/ha)</th>\n",
       "      <th>Densitat neta (hab/ha)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2021</td>\n",
       "      <td>8</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>54</td>\n",
       "      <td>Torre Baró</td>\n",
       "      <td>2890</td>\n",
       "      <td>174.2</td>\n",
       "      <td>21.2</td>\n",
       "      <td>17</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2021</td>\n",
       "      <td>8</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>55</td>\n",
       "      <td>Ciutat Meridiana</td>\n",
       "      <td>11026</td>\n",
       "      <td>37.7</td>\n",
       "      <td>15.1</td>\n",
       "      <td>293</td>\n",
       "      <td>729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2021</td>\n",
       "      <td>8</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>56</td>\n",
       "      <td>Vallbona</td>\n",
       "      <td>1384</td>\n",
       "      <td>61.4</td>\n",
       "      <td>6.8</td>\n",
       "      <td>23</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>57</td>\n",
       "      <td>la Trinitat Vella</td>\n",
       "      <td>10364</td>\n",
       "      <td>80.8</td>\n",
       "      <td>12.7</td>\n",
       "      <td>128</td>\n",
       "      <td>817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>58</td>\n",
       "      <td>Baró de Viver</td>\n",
       "      <td>2645</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>115</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>59</td>\n",
       "      <td>el Bon Pastor</td>\n",
       "      <td>13582</td>\n",
       "      <td>186.8</td>\n",
       "      <td>17.8</td>\n",
       "      <td>73</td>\n",
       "      <td>763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>60</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>57954</td>\n",
       "      <td>186.7</td>\n",
       "      <td>76.5</td>\n",
       "      <td>310</td>\n",
       "      <td>758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>61</td>\n",
       "      <td>la Sagrera</td>\n",
       "      <td>29351</td>\n",
       "      <td>98.6</td>\n",
       "      <td>38.1</td>\n",
       "      <td>298</td>\n",
       "      <td>770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>62</td>\n",
       "      <td>el Congrés i els Indians</td>\n",
       "      <td>14420</td>\n",
       "      <td>40.9</td>\n",
       "      <td>19.1</td>\n",
       "      <td>352</td>\n",
       "      <td>753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>63</td>\n",
       "      <td>Navas</td>\n",
       "      <td>22091</td>\n",
       "      <td>42.4</td>\n",
       "      <td>22.4</td>\n",
       "      <td>521</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>64</td>\n",
       "      <td>el Camp de l'Arpa del Clot</td>\n",
       "      <td>38360</td>\n",
       "      <td>74.1</td>\n",
       "      <td>42.9</td>\n",
       "      <td>518</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>65</td>\n",
       "      <td>el Clot</td>\n",
       "      <td>26520</td>\n",
       "      <td>69.7</td>\n",
       "      <td>23.4</td>\n",
       "      <td>381</td>\n",
       "      <td>1131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>66</td>\n",
       "      <td>el Parc i la Llacuna del Poblenou</td>\n",
       "      <td>15603</td>\n",
       "      <td>112.2</td>\n",
       "      <td>22.3</td>\n",
       "      <td>139</td>\n",
       "      <td>699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>67</td>\n",
       "      <td>la Vila Olímpica del Poblenou</td>\n",
       "      <td>9240</td>\n",
       "      <td>92.5</td>\n",
       "      <td>24.3</td>\n",
       "      <td>100</td>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>68</td>\n",
       "      <td>el Poblenou</td>\n",
       "      <td>33976</td>\n",
       "      <td>156.7</td>\n",
       "      <td>45.0</td>\n",
       "      <td>217</td>\n",
       "      <td>755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>69</td>\n",
       "      <td>Diagonal Mar i el Front Marítim del Poblenou</td>\n",
       "      <td>13323</td>\n",
       "      <td>122.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>109</td>\n",
       "      <td>556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>70</td>\n",
       "      <td>el Besòs i el Maresme</td>\n",
       "      <td>25657</td>\n",
       "      <td>120.9</td>\n",
       "      <td>28.1</td>\n",
       "      <td>212</td>\n",
       "      <td>913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>71</td>\n",
       "      <td>Provençals del Poblenou</td>\n",
       "      <td>20949</td>\n",
       "      <td>108.6</td>\n",
       "      <td>15.3</td>\n",
       "      <td>193</td>\n",
       "      <td>1368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>72</td>\n",
       "      <td>Sant Martí de Provençals</td>\n",
       "      <td>26032</td>\n",
       "      <td>73.4</td>\n",
       "      <td>23.4</td>\n",
       "      <td>355</td>\n",
       "      <td>1111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>73</td>\n",
       "      <td>la Verneda i la Pau</td>\n",
       "      <td>28585</td>\n",
       "      <td>113.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>253</td>\n",
       "      <td>714</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Any  Codi_Districte Nom_Districte  Codi_Barri  \\\n",
       "53  2021               8    Nou Barris          54   \n",
       "54  2021               8    Nou Barris          55   \n",
       "55  2021               8    Nou Barris          56   \n",
       "56  2021               9   Sant Andreu          57   \n",
       "57  2021               9   Sant Andreu          58   \n",
       "58  2021               9   Sant Andreu          59   \n",
       "59  2021               9   Sant Andreu          60   \n",
       "60  2021               9   Sant Andreu          61   \n",
       "61  2021               9   Sant Andreu          62   \n",
       "62  2021               9   Sant Andreu          63   \n",
       "63  2021              10    Sant Martí          64   \n",
       "64  2021              10    Sant Martí          65   \n",
       "65  2021              10    Sant Martí          66   \n",
       "66  2021              10    Sant Martí          67   \n",
       "67  2021              10    Sant Martí          68   \n",
       "68  2021              10    Sant Martí          69   \n",
       "69  2021              10    Sant Martí          70   \n",
       "70  2021              10    Sant Martí          71   \n",
       "71  2021              10    Sant Martí          72   \n",
       "72  2021              10    Sant Martí          73   \n",
       "\n",
       "                                       Nom_Barri  Població  Superfície (ha)  \\\n",
       "53                                    Torre Baró      2890            174.2   \n",
       "54                              Ciutat Meridiana     11026             37.7   \n",
       "55                                      Vallbona      1384             61.4   \n",
       "56                             la Trinitat Vella     10364             80.8   \n",
       "57                                 Baró de Viver      2645             23.0   \n",
       "58                                 el Bon Pastor     13582            186.8   \n",
       "59                                   Sant Andreu     57954            186.7   \n",
       "60                                    la Sagrera     29351             98.6   \n",
       "61                      el Congrés i els Indians     14420             40.9   \n",
       "62                                         Navas     22091             42.4   \n",
       "63                    el Camp de l'Arpa del Clot     38360             74.1   \n",
       "64                                       el Clot     26520             69.7   \n",
       "65             el Parc i la Llacuna del Poblenou     15603            112.2   \n",
       "66                 la Vila Olímpica del Poblenou      9240             92.5   \n",
       "67                                   el Poblenou     33976            156.7   \n",
       "68  Diagonal Mar i el Front Marítim del Poblenou     13323            122.7   \n",
       "69                         el Besòs i el Maresme     25657            120.9   \n",
       "70                       Provençals del Poblenou     20949            108.6   \n",
       "71                      Sant Martí de Provençals     26032             73.4   \n",
       "72                           la Verneda i la Pau     28585            113.0   \n",
       "\n",
       "    Superfície Residencial (ha)  Densitat (hab/ha)  Densitat neta (hab/ha)  \n",
       "53                         21.2                 17                     136  \n",
       "54                         15.1                293                     729  \n",
       "55                          6.8                 23                     204  \n",
       "56                         12.7                128                     817  \n",
       "57                          3.9                115                     673  \n",
       "58                         17.8                 73                     763  \n",
       "59                         76.5                310                     758  \n",
       "60                         38.1                298                     770  \n",
       "61                         19.1                352                     753  \n",
       "62                         22.4                521                     984  \n",
       "63                         42.9                518                     894  \n",
       "64                         23.4                381                    1131  \n",
       "65                         22.3                139                     699  \n",
       "66                         24.3                100                     380  \n",
       "67                         45.0                217                     755  \n",
       "68                         24.0                109                     556  \n",
       "69                         28.1                212                     913  \n",
       "70                         15.3                193                    1368  \n",
       "71                         23.4                355                    1111  \n",
       "72                         40.0                253                     714  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df.tail(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2dcf8756",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(73, 10)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4edbfd72",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 73 entries, 0 to 72\n",
      "Data columns (total 10 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   Any                          73 non-null     int64  \n",
      " 1   Codi_Districte               73 non-null     int64  \n",
      " 2   Nom_Districte                73 non-null     object \n",
      " 3   Codi_Barri                   73 non-null     int64  \n",
      " 4   Nom_Barri                    73 non-null     object \n",
      " 5   Població                     73 non-null     int64  \n",
      " 6   Superfície (ha)              73 non-null     float64\n",
      " 7   Superfície Residencial (ha)  73 non-null     float64\n",
      " 8   Densitat (hab/ha)            73 non-null     int64  \n",
      " 9   Densitat neta (hab/ha)       73 non-null     int64  \n",
      "dtypes: float64(2), int64(6), object(2)\n",
      "memory usage: 5.8+ KB\n"
     ]
    }
   ],
   "source": [
    "population_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "743825f8",
   "metadata": {},
   "source": [
    "We don't have null values, and the data types seem correct except the column \"Any\" that represents a year so it should be transformed to a date type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "29ad8517",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Any                            0\n",
       "Codi_Districte                 0\n",
       "Nom_Districte                  0\n",
       "Codi_Barri                     0\n",
       "Nom_Barri                      0\n",
       "Població                       0\n",
       "Superfície (ha)                0\n",
       "Superfície Residencial (ha)    0\n",
       "Densitat (hab/ha)              0\n",
       "Densitat neta (hab/ha)         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To check for duplicates in all the rows:\n",
    "duplicates = population_df[population_df.duplicated()]\n",
    "duplicates.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2e5a5b5",
   "metadata": {},
   "source": [
    "We don't have duplicates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "490c5e6f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Column: Any\n",
      "Unique Values:\n",
      "[2021]\n",
      "Value Counts:\n",
      "2021    73\n",
      "Name: Any, dtype: int64\n",
      "Column: Codi_Districte\n",
      "Unique Values:\n",
      "[ 1  2  3  4  5  6  7  8  9 10]\n",
      "Value Counts:\n",
      "8     13\n",
      "7     11\n",
      "10    10\n",
      "3      8\n",
      "9      7\n",
      "2      6\n",
      "5      6\n",
      "6      5\n",
      "1      4\n",
      "4      3\n",
      "Name: Codi_Districte, dtype: int64\n",
      "Column: Nom_Districte\n",
      "Unique Values:\n",
      "['Ciutat Vella' 'Eixample' 'Sants-Montjuïc' 'Les Corts'\n",
      " 'Sarrià-Sant Gervasi' 'Gràcia' 'Horta-Guinardó' 'Nou Barris'\n",
      " 'Sant Andreu' 'Sant Martí']\n",
      "Value Counts:\n",
      "Nou Barris             13\n",
      "Horta-Guinardó         11\n",
      "Sant Martí             10\n",
      "Sants-Montjuïc          8\n",
      "Sant Andreu             7\n",
      "Eixample                6\n",
      "Sarrià-Sant Gervasi     6\n",
      "Gràcia                  5\n",
      "Ciutat Vella            4\n",
      "Les Corts               3\n",
      "Name: Nom_Districte, dtype: int64\n",
      "Column: Codi_Barri\n",
      "Unique Values:\n",
      "[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24\n",
      " 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48\n",
      " 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72\n",
      " 73]\n",
      "Value Counts:\n",
      "1     1\n",
      "38    1\n",
      "54    1\n",
      "53    1\n",
      "52    1\n",
      "     ..\n",
      "25    1\n",
      "24    1\n",
      "23    1\n",
      "22    1\n",
      "73    1\n",
      "Name: Codi_Barri, Length: 73, dtype: int64\n",
      "Column: Nom_Barri\n",
      "Unique Values:\n",
      "['el Raval' 'el Barri Gòtic' 'la Barceloneta'\n",
      " 'Sant Pere, Santa Caterina i la Ribera' 'el Fort Pienc'\n",
      " 'la Sagrada Família' \"la Dreta de l'Eixample\"\n",
      " \"l'Antiga Esquerra de l'Eixample\" \"la Nova Esquerra de l'Eixample\"\n",
      " 'Sant Antoni' 'el Poble Sec' 'la Marina del Prat Vermell'\n",
      " 'la Marina de Port' 'la Font de la Guatlla' 'Hostafrancs' 'la Bordeta'\n",
      " 'Sants - Badal' 'Sants' 'les Corts' 'la Maternitat i Sant Ramon'\n",
      " 'Pedralbes' 'Vallvidrera, el Tibidabo i les Planes' 'Sarrià'\n",
      " 'les Tres Torres' 'Sant Gervasi - la Bonanova' 'Sant Gervasi - Galvany'\n",
      " 'el Putxet i el Farró' 'Vallcarca i els Penitents' 'el Coll' 'la Salut'\n",
      " 'la Vila de Gràcia' \"el Camp d'en Grassot i Gràcia Nova\"\n",
      " 'el Baix Guinardó' 'Can Baró' 'el Guinardó' \"la Font d'en Fargues\"\n",
      " 'el Carmel' 'la Teixonera' 'Sant Genís dels Agudells' 'Montbau'\n",
      " \"la Vall d'Hebron\" 'la Clota' 'Horta' 'Vilapicina i la Torre Llobeta'\n",
      " 'Porta' 'el Turó de la Peira' 'Can Peguera' 'la Guineueta' 'Canyelles'\n",
      " 'les Roquetes' 'Verdun' 'la Prosperitat' 'la Trinitat Nova' 'Torre Baró'\n",
      " 'Ciutat Meridiana' 'Vallbona' 'la Trinitat Vella' 'Baró de Viver'\n",
      " 'el Bon Pastor' 'Sant Andreu' 'la Sagrera' 'el Congrés i els Indians'\n",
      " 'Navas' \"el Camp de l'Arpa del Clot\" 'el Clot'\n",
      " 'el Parc i la Llacuna del Poblenou' 'la Vila Olímpica del Poblenou'\n",
      " 'el Poblenou' 'Diagonal Mar i el Front Marítim del Poblenou'\n",
      " 'el Besòs i el Maresme' 'Provençals del Poblenou'\n",
      " 'Sant Martí de Provençals' 'la Verneda i la Pau']\n",
      "Value Counts:\n",
      "el Raval                                 1\n",
      "la Teixonera                             1\n",
      "Torre Baró                               1\n",
      "la Trinitat Nova                         1\n",
      "la Prosperitat                           1\n",
      "                                        ..\n",
      "Sant Gervasi - la Bonanova               1\n",
      "les Tres Torres                          1\n",
      "Sarrià                                   1\n",
      "Vallvidrera, el Tibidabo i les Planes    1\n",
      "la Verneda i la Pau                      1\n",
      "Name: Nom_Barri, Length: 73, dtype: int64\n",
      "Column: Població\n",
      "Unique Values:\n",
      "[47228 21827 14643 22131 31262 51319 44675 41990 57054 38053 39400  1350\n",
      " 30741 10084 15842 19292 24576 43082 45422 23574 11581  4697 24405 16228\n",
      " 25659 46816 29629 16142  7590 13282 49492 34932 25601  9233 36939  9458\n",
      " 32444 11926  7249  5071  5882   689 27707 25674 27418 16025  2204 15189\n",
      "  6797 16373 12727 26669  7507  2890 11026  1384 10364  2645 13582 57954\n",
      " 29351 14420 22091 38360 26520 15603  9240 33976 13323 25657 20949 26032\n",
      " 28585]\n",
      "Value Counts:\n",
      "47228    1\n",
      "11926    1\n",
      "2890     1\n",
      "7507     1\n",
      "26669    1\n",
      "        ..\n",
      "25659    1\n",
      "16228    1\n",
      "24405    1\n",
      "4697     1\n",
      "28585    1\n",
      "Name: Població, Length: 73, dtype: int64\n",
      "Column: Superfície (ha)\n",
      "Unique Values:\n",
      "[ 110.    81.6  117.9  111.    92.9  104.2  212.   122.8  134.1   80.4\n",
      "  458.5 1423.7  126.9   29.7   41.    57.2   41.5  109.5  141.   191.5\n",
      "  268.5 1132.9  304.7   78.8  223.4  166.9   84.8  125.1   35.3   64.8\n",
      "  132.1   65.1   56.2   38.4  130.9   65.7   94.    33.8  168.1  205.5\n",
      "   74.5   17.8  307.    56.4   83.7   35.4   11.9   61.2   79.    64.3\n",
      "   23.7   59.1   57.7  174.2   37.7   61.4   80.8   23.   186.8  186.7\n",
      "   98.6   40.9   42.4   74.1   69.7  112.2   92.5  156.7  122.7  120.9\n",
      "  108.6   73.4  113. ]\n",
      "Value Counts:\n",
      "110.0     1\n",
      "33.8      1\n",
      "174.2     1\n",
      "57.7      1\n",
      "59.1      1\n",
      "         ..\n",
      "223.4     1\n",
      "78.8      1\n",
      "304.7     1\n",
      "1132.9    1\n",
      "113.0     1\n",
      "Name: Superfície (ha), Length: 73, dtype: int64\n",
      "Column: Superfície Residencial (ha)\n",
      "Unique Values:\n",
      "[ 49.6  34.1  13.5  32.4  33.6  51.  113.9  66.9  65.2  41.3  38.1  35.5\n",
      "  38.9  11.5  22.1  20.8  25.1  59.4  64.7  31.8  81.7 242.   95.4  42.5\n",
      "  82.1  53.1  48.2  12.4  19.5  84.   38.5  23.7  14.3  52.   38.8  39.4\n",
      "  16.9  11.4   7.2   6.1  63.2  29.3  35.7  13.3  22.   11.   18.2  14.2\n",
      "  27.1  12.6  21.2  15.1   6.8  12.7   3.9  17.8  76.5  19.1  22.4  42.9\n",
      "  23.4  22.3  24.3  45.   24.   28.1  15.3  40. ]\n",
      "Value Counts:\n",
      "16.9    2\n",
      "38.1    2\n",
      "95.4    2\n",
      "6.1     2\n",
      "23.4    2\n",
      "       ..\n",
      "84.0    1\n",
      "38.5    1\n",
      "23.7    1\n",
      "14.3    1\n",
      "40.0    1\n",
      "Name: Superfície Residencial (ha), Length: 68, dtype: int64\n",
      "Column: Densitat (hab/ha)\n",
      "Unique Values:\n",
      "[429 268 124 199 336 493 211 342 426 473  86   1 242 339 386 337 593 394\n",
      " 322 123  43   4  80 206 115 280 349 129 215 205 375 537 455 240 282 144\n",
      " 345 353  25  79  39  90 328 452 186 248 255 451 130  17 293  23 128  73\n",
      " 310 298 352 521 518 381 139 100 217 109 212 193 355 253]\n",
      "Value Counts:\n",
      "43     2\n",
      "86     2\n",
      "455    2\n",
      "537    2\n",
      "115    2\n",
      "      ..\n",
      "205    1\n",
      "375    1\n",
      "240    1\n",
      "268    1\n",
      "253    1\n",
      "Name: Densitat (hab/ha), Length: 68, dtype: int64\n",
      "Column: Densitat neta (hab/ha)\n",
      "Unique Values:\n",
      "[ 952  639 1081  683  930 1007  392  627  876  921 1033   38  789  873\n",
      "  717  928  980  726  702  741  142   19  256  382  313  491  558  335\n",
      "  611  680  589  907 1079  645  710  244  822  707  430  447  813  114\n",
      "  439  875  768 1204  359  689  620  897  894  985  598  136  729  204\n",
      "  817  673  763  758  770  753  984 1131  699  380  755  556  913 1368\n",
      " 1111  714]\n",
      "Value Counts:\n",
      "894    2\n",
      "952    1\n",
      "639    1\n",
      "598    1\n",
      "985    1\n",
      "      ..\n",
      "382    1\n",
      "256    1\n",
      "19     1\n",
      "142    1\n",
      "714    1\n",
      "Name: Densitat neta (hab/ha), Length: 72, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# For loop to iterate through all columns \n",
    "# View unique values and count values\n",
    "for column in population_df.columns:\n",
    "    unique_values = population_df[column].unique()\n",
    "    value_counts = population_df[column].value_counts()\n",
    "    print(f\"Column: {column}\")\n",
    "    print(\"Unique Values:\")\n",
    "    print(unique_values)\n",
    "    print(\"Value Counts:\")\n",
    "    print(value_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa9f8cc4",
   "metadata": {},
   "source": [
    "In Barcelona, there are 10 districts, and when checking the 'Nom_Districte' column, we see that everything is correct because there are 10 unique values that correctly represent the names of the 10 districts.\n",
    "\n",
    "Also in the 'Nom_Barri' column, we observe that the 73 neighborhoods of Barcelona are listed."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b93352fa",
   "metadata": {},
   "source": [
    "# Formatting the dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0648ddb",
   "metadata": {},
   "source": [
    "## Removing Unnecessary Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c84ab5d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Any', 'Codi_Districte', 'Nom_Districte', 'Codi_Barri', 'Nom_Barri',\n",
       "       'Població', 'Superfície (ha)', 'Superfície Residencial (ha)',\n",
       "       'Densitat (hab/ha)', 'Densitat neta (hab/ha)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1db4f138",
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of columns to be removed\n",
    "columns_to_remove = ['Codi_Districte', 'Codi_Barri', 'Superfície (ha)', 'Densitat (hab/ha)']\n",
    "\n",
    "# Remove the columns\n",
    "population_df = population_df.drop(columns=columns_to_remove)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "80432157",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Any', 'Nom_Districte', 'Nom_Barri', 'Població',\n",
       "       'Superfície Residencial (ha)', 'Densitat neta (hab/ha)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the change\n",
    "population_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4600070f",
   "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>Any</th>\n",
       "      <th>Nom_Districte</th>\n",
       "      <th>Nom_Barri</th>\n",
       "      <th>Població</th>\n",
       "      <th>Superfície Residencial (ha)</th>\n",
       "      <th>Densitat neta (hab/ha)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Raval</td>\n",
       "      <td>47228</td>\n",
       "      <td>49.6</td>\n",
       "      <td>952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Barri Gòtic</td>\n",
       "      <td>21827</td>\n",
       "      <td>34.1</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>la Barceloneta</td>\n",
       "      <td>14643</td>\n",
       "      <td>13.5</td>\n",
       "      <td>1081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>22131</td>\n",
       "      <td>32.4</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>31262</td>\n",
       "      <td>33.6</td>\n",
       "      <td>930</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Any Nom_Districte                              Nom_Barri  Població  \\\n",
       "0  2021  Ciutat Vella                               el Raval     47228   \n",
       "1  2021  Ciutat Vella                         el Barri Gòtic     21827   \n",
       "2  2021  Ciutat Vella                         la Barceloneta     14643   \n",
       "3  2021  Ciutat Vella  Sant Pere, Santa Caterina i la Ribera     22131   \n",
       "4  2021      Eixample                          el Fort Pienc     31262   \n",
       "\n",
       "   Superfície Residencial (ha)  Densitat neta (hab/ha)  \n",
       "0                         49.6                     952  \n",
       "1                         34.1                     639  \n",
       "2                         13.5                    1081  \n",
       "3                         32.4                     683  \n",
       "4                         33.6                     930  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3b826f5",
   "metadata": {},
   "source": [
    "## Bringing the dataset into one format"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da2631e2",
   "metadata": {},
   "source": [
    "##  Rename the columns so they follow the PE8 (snake case)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b5dbc3d",
   "metadata": {},
   "source": [
    "I have the column names in Catalan. I am going to translate them into English and also change it accordingly and format the names to snake case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4f66e11e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename columns to English and format to snake_case\n",
    "population_df = population_df.rename(columns={\n",
    "    'Any': 'Year',\n",
    "    'Nom_Districte': 'District_Name',\n",
    "    'Nom_Barri': 'Neighborhood_Name',\n",
    "    'Població': 'Population',\n",
    "    'Superfície Residencial (ha)': 'Residential_Area_ha',\n",
    "    'Densitat neta (hab/ha)': 'Net_Density_hab_ha'\n",
    "})\n",
    "\n",
    "# Convert column names to snake_case\n",
    "population_df.columns = population_df.columns.str.replace(' ', '_').str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8707f9a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['year', 'district_name', 'neighborhood_name', 'population',\n",
       "       'residential_area_ha', 'net_density_hab_ha'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check\n",
    "population_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2d07920",
   "metadata": {},
   "source": [
    "## Correcting Data Types\n",
    "\n",
    "#### Converting 'year' to a date type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3f8da4d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the 'year' column to date type\n",
    "population_df['year'] = pd.to_datetime(population_df['year'], format='%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6bdff591",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year                   datetime64[ns]\n",
       "district_name                  object\n",
       "neighborhood_name              object\n",
       "population                      int64\n",
       "residential_area_ha           float64\n",
       "net_density_hab_ha              int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the conversion\n",
    "population_df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7213297b",
   "metadata": {},
   "source": [
    "## Inspecting each column"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8e3bd21",
   "metadata": {},
   "source": [
    "### · year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "422e45ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2021-01-01T00:00:00.000000000'], dtype='datetime64[ns]')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[\"year\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cdb9b1e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2021-01-01    73\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[\"year\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc8b7de8",
   "metadata": {},
   "source": [
    "### · district_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2800904b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Ciutat Vella', 'Eixample', 'Sants-Montjuïc', 'Les Corts',\n",
       "       'Sarrià-Sant Gervasi', 'Gràcia', 'Horta-Guinardó', 'Nou Barris',\n",
       "       'Sant Andreu', 'Sant Martí'], dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[\"district_name\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c2b9bf2",
   "metadata": {},
   "source": [
    "All the names of the 10 districts are correct and in the correct format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b6d76373",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Nou Barris             13\n",
       "Horta-Guinardó         11\n",
       "Sant Martí             10\n",
       "Sants-Montjuïc          8\n",
       "Sant Andreu             7\n",
       "Eixample                6\n",
       "Sarrià-Sant Gervasi     6\n",
       "Gràcia                  5\n",
       "Ciutat Vella            4\n",
       "Les Corts               3\n",
       "Name: district_name, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[\"district_name\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbd93454",
   "metadata": {},
   "source": [
    "In each district, the value count matches the number of neighborhoods for that district, so we assume that no neighborhood is missing."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a15875ea",
   "metadata": {},
   "source": [
    "### · neighborhood_name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b169db3e",
   "metadata": {},
   "source": [
    "Sort the value counts for each unique neighborhood name alphabetically so I can check on them easily:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "25f08962",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baró de Viver                                   1\n",
      "Can Baró                                        1\n",
      "Can Peguera                                     1\n",
      "Canyelles                                       1\n",
      "Ciutat Meridiana                                1\n",
      "Diagonal Mar i el Front Marítim del Poblenou    1\n",
      "Horta                                           1\n",
      "Hostafrancs                                     1\n",
      "Montbau                                         1\n",
      "Navas                                           1\n",
      "Pedralbes                                       1\n",
      "Porta                                           1\n",
      "Provençals del Poblenou                         1\n",
      "Sant Andreu                                     1\n",
      "Sant Antoni                                     1\n",
      "Sant Genís dels Agudells                        1\n",
      "Sant Gervasi - Galvany                          1\n",
      "Sant Gervasi - la Bonanova                      1\n",
      "Sant Martí de Provençals                        1\n",
      "Sant Pere, Santa Caterina i la Ribera           1\n",
      "Sants                                           1\n",
      "Sants - Badal                                   1\n",
      "Sarrià                                          1\n",
      "Torre Baró                                      1\n",
      "Vallbona                                        1\n",
      "Vallcarca i els Penitents                       1\n",
      "Vallvidrera, el Tibidabo i les Planes           1\n",
      "Verdun                                          1\n",
      "Vilapicina i la Torre Llobeta                   1\n",
      "el Baix Guinardó                                1\n",
      "el Barri Gòtic                                  1\n",
      "el Besòs i el Maresme                           1\n",
      "el Bon Pastor                                   1\n",
      "el Camp d'en Grassot i Gràcia Nova              1\n",
      "el Camp de l'Arpa del Clot                      1\n",
      "el Carmel                                       1\n",
      "el Clot                                         1\n",
      "el Coll                                         1\n",
      "el Congrés i els Indians                        1\n",
      "el Fort Pienc                                   1\n",
      "el Guinardó                                     1\n",
      "el Parc i la Llacuna del Poblenou               1\n",
      "el Poble Sec                                    1\n",
      "el Poblenou                                     1\n",
      "el Putxet i el Farró                            1\n",
      "el Raval                                        1\n",
      "el Turó de la Peira                             1\n",
      "l'Antiga Esquerra de l'Eixample                 1\n",
      "la Barceloneta                                  1\n",
      "la Bordeta                                      1\n",
      "la Clota                                        1\n",
      "la Dreta de l'Eixample                          1\n",
      "la Font d'en Fargues                            1\n",
      "la Font de la Guatlla                           1\n",
      "la Guineueta                                    1\n",
      "la Marina de Port                               1\n",
      "la Marina del Prat Vermell                      1\n",
      "la Maternitat i Sant Ramon                      1\n",
      "la Nova Esquerra de l'Eixample                  1\n",
      "la Prosperitat                                  1\n",
      "la Sagrada Família                              1\n",
      "la Sagrera                                      1\n",
      "la Salut                                        1\n",
      "la Teixonera                                    1\n",
      "la Trinitat Nova                                1\n",
      "la Trinitat Vella                               1\n",
      "la Vall d'Hebron                                1\n",
      "la Verneda i la Pau                             1\n",
      "la Vila Olímpica del Poblenou                   1\n",
      "la Vila de Gràcia                               1\n",
      "les Corts                                       1\n",
      "les Roquetes                                    1\n",
      "les Tres Torres                                 1\n",
      "Name: neighborhood_name, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Set pandas display options to show all rows\n",
    "pd.set_option('display.max_rows', None)\n",
    "\n",
    "# Get the value counts for each unique neighborhood name and sort alphabetically\n",
    "neighborhood_counts = population_df['neighborhood_name'].value_counts().sort_index()\n",
    "\n",
    "# Print the sorted value counts\n",
    "print(neighborhood_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cda97729",
   "metadata": {},
   "source": [
    "It seems we have a complete and accurate list of Barcelona's neighborhoods. Also the format of each name seems correct."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c8776b5",
   "metadata": {},
   "source": [
    "### Check if the neighborhoods assigned by district are correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "12f0ed46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "District: Ciutat Vella\n",
      "- el Raval\n",
      "- el Barri Gòtic\n",
      "- la Barceloneta\n",
      "- Sant Pere, Santa Caterina i la Ribera\n",
      "\n",
      "District: Eixample\n",
      "- el Fort Pienc\n",
      "- la Sagrada Família\n",
      "- la Dreta de l'Eixample\n",
      "- l'Antiga Esquerra de l'Eixample\n",
      "- la Nova Esquerra de l'Eixample\n",
      "- Sant Antoni\n",
      "\n",
      "District: Gràcia\n",
      "- Vallcarca i els Penitents\n",
      "- el Coll\n",
      "- la Salut\n",
      "- la Vila de Gràcia\n",
      "- el Camp d'en Grassot i Gràcia Nova\n",
      "\n",
      "District: Horta-Guinardó\n",
      "- el Baix Guinardó\n",
      "- Can Baró\n",
      "- el Guinardó\n",
      "- la Font d'en Fargues\n",
      "- el Carmel\n",
      "- la Teixonera\n",
      "- Sant Genís dels Agudells\n",
      "- Montbau\n",
      "- la Vall d'Hebron\n",
      "- la Clota\n",
      "- Horta\n",
      "\n",
      "District: Les Corts\n",
      "- les Corts\n",
      "- la Maternitat i Sant Ramon\n",
      "- Pedralbes\n",
      "\n",
      "District: Nou Barris\n",
      "- Vilapicina i la Torre Llobeta\n",
      "- Porta\n",
      "- el Turó de la Peira\n",
      "- Can Peguera\n",
      "- la Guineueta\n",
      "- Canyelles\n",
      "- les Roquetes\n",
      "- Verdun\n",
      "- la Prosperitat\n",
      "- la Trinitat Nova\n",
      "- Torre Baró\n",
      "- Ciutat Meridiana\n",
      "- Vallbona\n",
      "\n",
      "District: Sant Andreu\n",
      "- la Trinitat Vella\n",
      "- Baró de Viver\n",
      "- el Bon Pastor\n",
      "- Sant Andreu\n",
      "- la Sagrera\n",
      "- el Congrés i els Indians\n",
      "- Navas\n",
      "\n",
      "District: Sant Martí\n",
      "- el Camp de l'Arpa del Clot\n",
      "- el Clot\n",
      "- el Parc i la Llacuna del Poblenou\n",
      "- la Vila Olímpica del Poblenou\n",
      "- el Poblenou\n",
      "- Diagonal Mar i el Front Marítim del Poblenou\n",
      "- el Besòs i el Maresme\n",
      "- Provençals del Poblenou\n",
      "- Sant Martí de Provençals\n",
      "- la Verneda i la Pau\n",
      "\n",
      "District: Sants-Montjuïc\n",
      "- el Poble Sec\n",
      "- la Marina del Prat Vermell\n",
      "- la Marina de Port\n",
      "- la Font de la Guatlla\n",
      "- Hostafrancs\n",
      "- la Bordeta\n",
      "- Sants - Badal\n",
      "- Sants\n",
      "\n",
      "District: Sarrià-Sant Gervasi\n",
      "- Vallvidrera, el Tibidabo i les Planes\n",
      "- Sarrià\n",
      "- les Tres Torres\n",
      "- Sant Gervasi - la Bonanova\n",
      "- Sant Gervasi - Galvany\n",
      "- el Putxet i el Farró\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Create a DataFrame to show neighborhood_name assigned to each district_name\n",
    "neighborhoods_by_district = population_df.groupby('district_name')['neighborhood_name'].unique().reset_index()\n",
    "\n",
    "# Loop through each district and print its assigned neighborhoods\n",
    "for index, row in neighborhoods_by_district.iterrows():\n",
    "    district_name = row['district_name']\n",
    "    neighborhood_names = row['neighborhood_name']\n",
    "    \n",
    "    print(f\"District: {district_name}\")\n",
    "    for neighborhood in neighborhood_names:\n",
    "        print(f\"- {neighborhood}\")\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9d8a73c",
   "metadata": {},
   "source": [
    "Everything is correct."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97a5064a",
   "metadata": {},
   "source": [
    "### · population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0ffe5f7f",
   "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>year</th>\n",
       "      <th>district_name</th>\n",
       "      <th>neighborhood_name</th>\n",
       "      <th>population</th>\n",
       "      <th>residential_area_ha</th>\n",
       "      <th>net_density_hab_ha</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Raval</td>\n",
       "      <td>47228</td>\n",
       "      <td>49.6</td>\n",
       "      <td>952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Barri Gòtic</td>\n",
       "      <td>21827</td>\n",
       "      <td>34.1</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>la Barceloneta</td>\n",
       "      <td>14643</td>\n",
       "      <td>13.5</td>\n",
       "      <td>1081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>22131</td>\n",
       "      <td>32.4</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>31262</td>\n",
       "      <td>33.6</td>\n",
       "      <td>930</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        year district_name                      neighborhood_name  population  \\\n",
       "0 2021-01-01  Ciutat Vella                               el Raval       47228   \n",
       "1 2021-01-01  Ciutat Vella                         el Barri Gòtic       21827   \n",
       "2 2021-01-01  Ciutat Vella                         la Barceloneta       14643   \n",
       "3 2021-01-01  Ciutat Vella  Sant Pere, Santa Caterina i la Ribera       22131   \n",
       "4 2021-01-01      Eixample                          el Fort Pienc       31262   \n",
       "\n",
       "   residential_area_ha  net_density_hab_ha  \n",
       "0                 49.6                 952  \n",
       "1                 34.1                 639  \n",
       "2                 13.5                1081  \n",
       "3                 32.4                 683  \n",
       "4                 33.6                 930  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4a0b60a1",
   "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>neighborhood_name</th>\n",
       "      <th>total_population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Baró de Viver</td>\n",
       "      <td>2645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Can Baró</td>\n",
       "      <td>9233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Can Peguera</td>\n",
       "      <td>2204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Canyelles</td>\n",
       "      <td>6797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ciutat Meridiana</td>\n",
       "      <td>11026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Diagonal Mar i el Front Marítim del Poblenou</td>\n",
       "      <td>13323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Horta</td>\n",
       "      <td>27707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Hostafrancs</td>\n",
       "      <td>15842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Montbau</td>\n",
       "      <td>5071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Navas</td>\n",
       "      <td>22091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Pedralbes</td>\n",
       "      <td>11581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Porta</td>\n",
       "      <td>27418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Provençals del Poblenou</td>\n",
       "      <td>20949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>57954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sant Antoni</td>\n",
       "      <td>38053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sant Genís dels Agudells</td>\n",
       "      <td>7249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Sant Gervasi - Galvany</td>\n",
       "      <td>46816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sant Gervasi - la Bonanova</td>\n",
       "      <td>25659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Sant Martí de Provençals</td>\n",
       "      <td>26032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>22131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sants</td>\n",
       "      <td>43082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sants - Badal</td>\n",
       "      <td>24576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sarrià</td>\n",
       "      <td>24405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Torre Baró</td>\n",
       "      <td>2890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Vallbona</td>\n",
       "      <td>1384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Vallcarca i els Penitents</td>\n",
       "      <td>16142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Vallvidrera, el Tibidabo i les Planes</td>\n",
       "      <td>4697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Verdun</td>\n",
       "      <td>12727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Vilapicina i la Torre Llobeta</td>\n",
       "      <td>25674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>el Baix Guinardó</td>\n",
       "      <td>25601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>el Barri Gòtic</td>\n",
       "      <td>21827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>el Besòs i el Maresme</td>\n",
       "      <td>25657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>el Bon Pastor</td>\n",
       "      <td>13582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>el Camp d'en Grassot i Gràcia Nova</td>\n",
       "      <td>34932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>el Camp de l'Arpa del Clot</td>\n",
       "      <td>38360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>el Carmel</td>\n",
       "      <td>32444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>el Clot</td>\n",
       "      <td>26520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>el Coll</td>\n",
       "      <td>7590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>el Congrés i els Indians</td>\n",
       "      <td>14420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>31262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>el Guinardó</td>\n",
       "      <td>36939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>el Parc i la Llacuna del Poblenou</td>\n",
       "      <td>15603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>el Poble Sec</td>\n",
       "      <td>39400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>el Poblenou</td>\n",
       "      <td>33976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>el Putxet i el Farró</td>\n",
       "      <td>29629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>el Raval</td>\n",
       "      <td>47228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>el Turó de la Peira</td>\n",
       "      <td>16025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>l'Antiga Esquerra de l'Eixample</td>\n",
       "      <td>41990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>la Barceloneta</td>\n",
       "      <td>14643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>la Bordeta</td>\n",
       "      <td>19292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>la Clota</td>\n",
       "      <td>689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>la Dreta de l'Eixample</td>\n",
       "      <td>44675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>la Font d'en Fargues</td>\n",
       "      <td>9458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>la Font de la Guatlla</td>\n",
       "      <td>10084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>la Guineueta</td>\n",
       "      <td>15189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>la Marina de Port</td>\n",
       "      <td>30741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>la Marina del Prat Vermell</td>\n",
       "      <td>1350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>la Maternitat i Sant Ramon</td>\n",
       "      <td>23574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>la Nova Esquerra de l'Eixample</td>\n",
       "      <td>57054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>la Prosperitat</td>\n",
       "      <td>26669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>la Sagrada Família</td>\n",
       "      <td>51319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>la Sagrera</td>\n",
       "      <td>29351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>la Salut</td>\n",
       "      <td>13282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>la Teixonera</td>\n",
       "      <td>11926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>la Trinitat Nova</td>\n",
       "      <td>7507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>la Trinitat Vella</td>\n",
       "      <td>10364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>la Vall d'Hebron</td>\n",
       "      <td>5882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>la Verneda i la Pau</td>\n",
       "      <td>28585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>la Vila Olímpica del Poblenou</td>\n",
       "      <td>9240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>la Vila de Gràcia</td>\n",
       "      <td>49492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>les Corts</td>\n",
       "      <td>45422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>les Roquetes</td>\n",
       "      <td>16373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>les Tres Torres</td>\n",
       "      <td>16228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               neighborhood_name  total_population\n",
       "0                                  Baró de Viver              2645\n",
       "1                                       Can Baró              9233\n",
       "2                                    Can Peguera              2204\n",
       "3                                      Canyelles              6797\n",
       "4                               Ciutat Meridiana             11026\n",
       "5   Diagonal Mar i el Front Marítim del Poblenou             13323\n",
       "6                                          Horta             27707\n",
       "7                                    Hostafrancs             15842\n",
       "8                                        Montbau              5071\n",
       "9                                          Navas             22091\n",
       "10                                     Pedralbes             11581\n",
       "11                                         Porta             27418\n",
       "12                       Provençals del Poblenou             20949\n",
       "13                                   Sant Andreu             57954\n",
       "14                                   Sant Antoni             38053\n",
       "15                      Sant Genís dels Agudells              7249\n",
       "16                        Sant Gervasi - Galvany             46816\n",
       "17                    Sant Gervasi - la Bonanova             25659\n",
       "18                      Sant Martí de Provençals             26032\n",
       "19         Sant Pere, Santa Caterina i la Ribera             22131\n",
       "20                                         Sants             43082\n",
       "21                                 Sants - Badal             24576\n",
       "22                                        Sarrià             24405\n",
       "23                                    Torre Baró              2890\n",
       "24                                      Vallbona              1384\n",
       "25                     Vallcarca i els Penitents             16142\n",
       "26         Vallvidrera, el Tibidabo i les Planes              4697\n",
       "27                                        Verdun             12727\n",
       "28                 Vilapicina i la Torre Llobeta             25674\n",
       "29                              el Baix Guinardó             25601\n",
       "30                                el Barri Gòtic             21827\n",
       "31                         el Besòs i el Maresme             25657\n",
       "32                                 el Bon Pastor             13582\n",
       "33            el Camp d'en Grassot i Gràcia Nova             34932\n",
       "34                    el Camp de l'Arpa del Clot             38360\n",
       "35                                     el Carmel             32444\n",
       "36                                       el Clot             26520\n",
       "37                                       el Coll              7590\n",
       "38                      el Congrés i els Indians             14420\n",
       "39                                 el Fort Pienc             31262\n",
       "40                                   el Guinardó             36939\n",
       "41             el Parc i la Llacuna del Poblenou             15603\n",
       "42                                  el Poble Sec             39400\n",
       "43                                   el Poblenou             33976\n",
       "44                          el Putxet i el Farró             29629\n",
       "45                                      el Raval             47228\n",
       "46                           el Turó de la Peira             16025\n",
       "47               l'Antiga Esquerra de l'Eixample             41990\n",
       "48                                la Barceloneta             14643\n",
       "49                                    la Bordeta             19292\n",
       "50                                      la Clota               689\n",
       "51                        la Dreta de l'Eixample             44675\n",
       "52                          la Font d'en Fargues              9458\n",
       "53                         la Font de la Guatlla             10084\n",
       "54                                  la Guineueta             15189\n",
       "55                             la Marina de Port             30741\n",
       "56                    la Marina del Prat Vermell              1350\n",
       "57                    la Maternitat i Sant Ramon             23574\n",
       "58                la Nova Esquerra de l'Eixample             57054\n",
       "59                                la Prosperitat             26669\n",
       "60                            la Sagrada Família             51319\n",
       "61                                    la Sagrera             29351\n",
       "62                                      la Salut             13282\n",
       "63                                  la Teixonera             11926\n",
       "64                              la Trinitat Nova              7507\n",
       "65                             la Trinitat Vella             10364\n",
       "66                              la Vall d'Hebron              5882\n",
       "67                           la Verneda i la Pau             28585\n",
       "68                 la Vila Olímpica del Poblenou              9240\n",
       "69                             la Vila de Gràcia             49492\n",
       "70                                     les Corts             45422\n",
       "71                                  les Roquetes             16373\n",
       "72                               les Tres Torres             16228"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Group the data by \"neighborhood_name\" and sum the population within each neighborhood\n",
    "neighborhood_population_df = population_df.groupby('neighborhood_name')['population'].sum().reset_index()\n",
    "\n",
    "# Rename the columns for clarity\n",
    "neighborhood_population_df.columns = ['neighborhood_name', 'total_population']\n",
    "\n",
    "# Display the resulting DataFrame\n",
    "neighborhood_population_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a8f456e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/09/qkspll5d37l0g2941hv9rvs80000gn/T/ipykernel_4828/4245690688.py:8: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.\n",
      "  colors = plt.cm.get_cmap('tab20', len(population_df['district_name'].unique()))\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Group the data by \"neighborhood_name\" and sum the population within each neighborhood\n",
    "neighborhood_population_df = population_df.groupby('neighborhood_name')['population'].sum().reset_index()\n",
    "\n",
    "# Rename the columns for clarity\n",
    "neighborhood_population_df.columns = ['neighborhood_name', 'total_population']\n",
    "\n",
    "# Create a colormap with a color for each district\n",
    "colors = plt.cm.get_cmap('tab20', len(population_df['district_name'].unique()))\n",
    "\n",
    "# Create a figure and axis\n",
    "plt.figure(figsize=(12, 6))\n",
    "ax = plt.subplot(111)\n",
    "\n",
    "# Plot the total population for each neighborhood with its associated district's color\n",
    "for district_name, color in zip(population_df['district_name'].unique(), colors.colors):\n",
    "    district_df = population_df[population_df['district_name'] == district_name]\n",
    "    ax.bar(district_df['neighborhood_name'], district_df['population'], color=color, label=district_name)\n",
    "\n",
    "# Customize the plot\n",
    "plt.xlabel('Neighborhood Name')\n",
    "plt.ylabel('Total Population')\n",
    "plt.title('Total Population by Neighborhood and District')\n",
    "plt.xticks(rotation=90)\n",
    "plt.tight_layout()\n",
    "\n",
    "# Add the legend with the title \"District Names\"\n",
    "ax.legend(title=\"District Names\", loc='upper left', bbox_to_anchor=(1, 1))\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d80f97a",
   "metadata": {},
   "source": [
    "### · residential_area_ha"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51beda8c",
   "metadata": {},
   "source": [
    "#### Check if all surface area units are in hectares"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "557f71db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 49.6,  34.1,  13.5,  32.4,  33.6,  51. , 113.9,  66.9,  65.2,\n",
       "        41.3,  38.1,  35.5,  38.9,  11.5,  22.1,  20.8,  25.1,  59.4,\n",
       "        64.7,  31.8,  81.7, 242. ,  95.4,  42.5,  82.1,  53.1,  48.2,\n",
       "        12.4,  19.5,  84. ,  38.5,  23.7,  14.3,  52. ,  38.8,  39.4,\n",
       "        16.9,  11.4,   7.2,   6.1,  63.2,  29.3,  35.7,  13.3,  22. ,\n",
       "        11. ,  18.2,  14.2,  27.1,  12.6,  21.2,  15.1,   6.8,  12.7,\n",
       "         3.9,  17.8,  76.5,  19.1,  22.4,  42.9,  23.4,  22.3,  24.3,\n",
       "        45. ,  24. ,  28.1,  15.3,  40. ])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[\"residential_area_ha\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecd3dbf8",
   "metadata": {},
   "source": [
    "#### Examine the residential_area_ha by neighborhood_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ceeccc2e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "neighborhood_name\n",
      "Baró de Viver                                     3.9\n",
      "Can Baró                                         14.3\n",
      "Can Peguera                                       6.1\n",
      "Canyelles                                        11.0\n",
      "Ciutat Meridiana                                 15.1\n",
      "Diagonal Mar i el Front Marítim del Poblenou     24.0\n",
      "Horta                                            63.2\n",
      "Hostafrancs                                      22.1\n",
      "Montbau                                          11.4\n",
      "Navas                                            22.4\n",
      "Pedralbes                                        81.7\n",
      "Porta                                            35.7\n",
      "Provençals del Poblenou                          15.3\n",
      "Sant Andreu                                      76.5\n",
      "Sant Antoni                                      41.3\n",
      "Sant Genís dels Agudells                         16.9\n",
      "Sant Gervasi - Galvany                           95.4\n",
      "Sant Gervasi - la Bonanova                       82.1\n",
      "Sant Martí de Provençals                         23.4\n",
      "Sant Pere, Santa Caterina i la Ribera            32.4\n",
      "Sants                                            59.4\n",
      "Sants - Badal                                    25.1\n",
      "Sarrià                                           95.4\n",
      "Torre Baró                                       21.2\n",
      "Vallbona                                          6.8\n",
      "Vallcarca i els Penitents                        48.2\n",
      "Vallvidrera, el Tibidabo i les Planes           242.0\n",
      "Verdun                                           14.2\n",
      "Vilapicina i la Torre Llobeta                    29.3\n",
      "el Baix Guinardó                                 23.7\n",
      "el Barri Gòtic                                   34.1\n",
      "el Besòs i el Maresme                            28.1\n",
      "el Bon Pastor                                    17.8\n",
      "el Camp d'en Grassot i Gràcia Nova               38.5\n",
      "el Camp de l'Arpa del Clot                       42.9\n",
      "el Carmel                                        39.4\n",
      "el Clot                                          23.4\n",
      "el Coll                                          12.4\n",
      "el Congrés i els Indians                         19.1\n",
      "el Fort Pienc                                    33.6\n",
      "el Guinardó                                      52.0\n",
      "el Parc i la Llacuna del Poblenou                22.3\n",
      "el Poble Sec                                     38.1\n",
      "el Poblenou                                      45.0\n",
      "el Putxet i el Farró                             53.1\n",
      "el Raval                                         49.6\n",
      "el Turó de la Peira                              13.3\n",
      "l'Antiga Esquerra de l'Eixample                  66.9\n",
      "la Barceloneta                                   13.5\n",
      "la Bordeta                                       20.8\n",
      "la Clota                                          6.1\n",
      "la Dreta de l'Eixample                          113.9\n",
      "la Font d'en Fargues                             38.8\n",
      "la Font de la Guatlla                            11.5\n",
      "la Guineueta                                     22.0\n",
      "la Marina de Port                                38.9\n",
      "la Marina del Prat Vermell                       35.5\n",
      "la Maternitat i Sant Ramon                       31.8\n",
      "la Nova Esquerra de l'Eixample                   65.2\n",
      "la Prosperitat                                   27.1\n",
      "la Sagrada Família                               51.0\n",
      "la Sagrera                                       38.1\n",
      "la Salut                                         19.5\n",
      "la Teixonera                                     16.9\n",
      "la Trinitat Nova                                 12.6\n",
      "la Trinitat Vella                                12.7\n",
      "la Vall d'Hebron                                  7.2\n",
      "la Verneda i la Pau                              40.0\n",
      "la Vila Olímpica del Poblenou                    24.3\n",
      "la Vila de Gràcia                                84.0\n",
      "les Corts                                        64.7\n",
      "les Roquetes                                     18.2\n",
      "les Tres Torres                                  42.5\n",
      "Name: residential_area_ha, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Group the data by 'neighborhood_name' and calculate the mean surface area for each neighborhood\n",
    "neighborhood_residential_area = population_df.groupby('neighborhood_name')['residential_area_ha'].mean()\n",
    "\n",
    "# Print the result\n",
    "print(neighborhood_residential_area)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "804c34b7",
   "metadata": {},
   "source": [
    "#### Plot the residential_area_ha by neighborhood_name and district_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "20542b22",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/09/qkspll5d37l0g2941hv9rvs80000gn/T/ipykernel_4828/1835228519.py:6: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.\n",
      "  colors = plt.cm.get_cmap('tab20', len(district_names))\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Group the data by district and get unique district names\n",
    "district_data = population_df.groupby('district_name')\n",
    "district_names = district_data.groups.keys()\n",
    "\n",
    "# Create a colormap with a color for each district\n",
    "colors = plt.cm.get_cmap('tab20', len(district_names))\n",
    "\n",
    "# Create a figure and axis\n",
    "plt.figure(figsize=(12, 6))\n",
    "ax = plt.subplot(111)\n",
    "\n",
    "# Plot residential area for each neighborhood with its associated district's color\n",
    "for district_name, color in zip(district_names, colors.colors):\n",
    "    district_df = district_data.get_group(district_name)\n",
    "    ax.bar(district_df['neighborhood_name'], district_df['residential_area_ha'],\n",
    "           color=color, label=district_name)\n",
    "\n",
    "# Customize the plot\n",
    "plt.xlabel('Neighborhood Name')\n",
    "plt.ylabel('Residential Area (ha)')\n",
    "plt.title('Residential Area by Neighborhood and District')\n",
    "plt.xticks(rotation=90)\n",
    "plt.tight_layout()\n",
    "\n",
    "# Add the legend to the current axes (from the previous cell)\n",
    "legend = ax.legend(loc='upper left', bbox_to_anchor=(1, 1))\n",
    "\n",
    "# Set a custom title for the legend\n",
    "legend.set_title(\"District Name\")\n",
    "\n",
    "# Show the legend\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22cf17b9",
   "metadata": {},
   "source": [
    "### · net_density_hab_ha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a9a20baa",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 952,  639, 1081,  683,  930, 1007,  392,  627,  876,  921, 1033,\n",
       "         38,  789,  873,  717,  928,  980,  726,  702,  741,  142,   19,\n",
       "        256,  382,  313,  491,  558,  335,  611,  680,  589,  907, 1079,\n",
       "        645,  710,  244,  822,  707,  430,  447,  813,  114,  439,  875,\n",
       "        768, 1204,  359,  689,  620,  897,  894,  985,  598,  136,  729,\n",
       "        204,  817,  673,  763,  758,  770,  753,  984, 1131,  699,  380,\n",
       "        755,  556,  913, 1368, 1111,  714])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[\"net_density_hab_ha\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fe0849f",
   "metadata": {},
   "source": [
    "#### Examine the net_density_hab_ha_ha by neighborhood_name and district_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ac460d6c",
   "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>neighborhood_name</th>\n",
       "      <th>district_name</th>\n",
       "      <th>net_density_hab_ha</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>el Raval</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>el Barri Gòtic</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>la Barceloneta</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>1081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>la Sagrada Família</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>1007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>la Dreta de l'Eixample</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>l'Antiga Esquerra de l'Eixample</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>la Nova Esquerra de l'Eixample</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sant Antoni</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>el Poble Sec</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>1033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>la Marina del Prat Vermell</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>la Marina de Port</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>la Font de la Guatlla</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Hostafrancs</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>la Bordeta</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Sants - Badal</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sants</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>les Corts</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>la Maternitat i Sant Ramon</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Pedralbes</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Vallvidrera, el Tibidabo i les Planes</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sarrià</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>les Tres Torres</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Sant Gervasi - la Bonanova</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sant Gervasi - Galvany</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>el Putxet i el Farró</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Vallcarca i els Penitents</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>el Coll</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>la Salut</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>la Vila de Gràcia</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>el Camp d'en Grassot i Gràcia Nova</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>el Baix Guinardó</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>1079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Can Baró</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>el Guinardó</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>la Font d'en Fargues</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>el Carmel</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>la Teixonera</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Sant Genís dels Agudells</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Montbau</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>la Vall d'Hebron</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>la Clota</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Horta</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Vilapicina i la Torre Llobeta</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Porta</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>el Turó de la Peira</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>1204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Can Peguera</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>la Guineueta</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Canyelles</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>les Roquetes</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Verdun</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>la Prosperitat</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>la Trinitat Nova</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Torre Baró</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Ciutat Meridiana</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Vallbona</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>la Trinitat Vella</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Baró de Viver</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>el Bon Pastor</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>la Sagrera</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>el Congrés i els Indians</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Navas</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>el Camp de l'Arpa del Clot</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>el Clot</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>1131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>el Parc i la Llacuna del Poblenou</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>la Vila Olímpica del Poblenou</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>el Poblenou</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Diagonal Mar i el Front Marítim del Poblenou</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>el Besòs i el Maresme</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Provençals del Poblenou</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>1368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Sant Martí de Provençals</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>1111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>la Verneda i la Pau</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>714</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               neighborhood_name        district_name  \\\n",
       "0                                       el Raval         Ciutat Vella   \n",
       "1                                 el Barri Gòtic         Ciutat Vella   \n",
       "2                                 la Barceloneta         Ciutat Vella   \n",
       "3          Sant Pere, Santa Caterina i la Ribera         Ciutat Vella   \n",
       "4                                  el Fort Pienc             Eixample   \n",
       "5                             la Sagrada Família             Eixample   \n",
       "6                         la Dreta de l'Eixample             Eixample   \n",
       "7                l'Antiga Esquerra de l'Eixample             Eixample   \n",
       "8                 la Nova Esquerra de l'Eixample             Eixample   \n",
       "9                                    Sant Antoni             Eixample   \n",
       "10                                  el Poble Sec       Sants-Montjuïc   \n",
       "11                    la Marina del Prat Vermell       Sants-Montjuïc   \n",
       "12                             la Marina de Port       Sants-Montjuïc   \n",
       "13                         la Font de la Guatlla       Sants-Montjuïc   \n",
       "14                                   Hostafrancs       Sants-Montjuïc   \n",
       "15                                    la Bordeta       Sants-Montjuïc   \n",
       "16                                 Sants - Badal       Sants-Montjuïc   \n",
       "17                                         Sants       Sants-Montjuïc   \n",
       "18                                     les Corts            Les Corts   \n",
       "19                    la Maternitat i Sant Ramon            Les Corts   \n",
       "20                                     Pedralbes            Les Corts   \n",
       "21         Vallvidrera, el Tibidabo i les Planes  Sarrià-Sant Gervasi   \n",
       "22                                        Sarrià  Sarrià-Sant Gervasi   \n",
       "23                               les Tres Torres  Sarrià-Sant Gervasi   \n",
       "24                    Sant Gervasi - la Bonanova  Sarrià-Sant Gervasi   \n",
       "25                        Sant Gervasi - Galvany  Sarrià-Sant Gervasi   \n",
       "26                          el Putxet i el Farró  Sarrià-Sant Gervasi   \n",
       "27                     Vallcarca i els Penitents               Gràcia   \n",
       "28                                       el Coll               Gràcia   \n",
       "29                                      la Salut               Gràcia   \n",
       "30                             la Vila de Gràcia               Gràcia   \n",
       "31            el Camp d'en Grassot i Gràcia Nova               Gràcia   \n",
       "32                              el Baix Guinardó       Horta-Guinardó   \n",
       "33                                      Can Baró       Horta-Guinardó   \n",
       "34                                   el Guinardó       Horta-Guinardó   \n",
       "35                          la Font d'en Fargues       Horta-Guinardó   \n",
       "36                                     el Carmel       Horta-Guinardó   \n",
       "37                                  la Teixonera       Horta-Guinardó   \n",
       "38                      Sant Genís dels Agudells       Horta-Guinardó   \n",
       "39                                       Montbau       Horta-Guinardó   \n",
       "40                              la Vall d'Hebron       Horta-Guinardó   \n",
       "41                                      la Clota       Horta-Guinardó   \n",
       "42                                         Horta       Horta-Guinardó   \n",
       "43                 Vilapicina i la Torre Llobeta           Nou Barris   \n",
       "44                                         Porta           Nou Barris   \n",
       "45                           el Turó de la Peira           Nou Barris   \n",
       "46                                   Can Peguera           Nou Barris   \n",
       "47                                  la Guineueta           Nou Barris   \n",
       "48                                     Canyelles           Nou Barris   \n",
       "49                                  les Roquetes           Nou Barris   \n",
       "50                                        Verdun           Nou Barris   \n",
       "51                                la Prosperitat           Nou Barris   \n",
       "52                              la Trinitat Nova           Nou Barris   \n",
       "53                                    Torre Baró           Nou Barris   \n",
       "54                              Ciutat Meridiana           Nou Barris   \n",
       "55                                      Vallbona           Nou Barris   \n",
       "56                             la Trinitat Vella          Sant Andreu   \n",
       "57                                 Baró de Viver          Sant Andreu   \n",
       "58                                 el Bon Pastor          Sant Andreu   \n",
       "59                                   Sant Andreu          Sant Andreu   \n",
       "60                                    la Sagrera          Sant Andreu   \n",
       "61                      el Congrés i els Indians          Sant Andreu   \n",
       "62                                         Navas          Sant Andreu   \n",
       "63                    el Camp de l'Arpa del Clot           Sant Martí   \n",
       "64                                       el Clot           Sant Martí   \n",
       "65             el Parc i la Llacuna del Poblenou           Sant Martí   \n",
       "66                 la Vila Olímpica del Poblenou           Sant Martí   \n",
       "67                                   el Poblenou           Sant Martí   \n",
       "68  Diagonal Mar i el Front Marítim del Poblenou           Sant Martí   \n",
       "69                         el Besòs i el Maresme           Sant Martí   \n",
       "70                       Provençals del Poblenou           Sant Martí   \n",
       "71                      Sant Martí de Provençals           Sant Martí   \n",
       "72                           la Verneda i la Pau           Sant Martí   \n",
       "\n",
       "    net_density_hab_ha  \n",
       "0                  952  \n",
       "1                  639  \n",
       "2                 1081  \n",
       "3                  683  \n",
       "4                  930  \n",
       "5                 1007  \n",
       "6                  392  \n",
       "7                  627  \n",
       "8                  876  \n",
       "9                  921  \n",
       "10                1033  \n",
       "11                  38  \n",
       "12                 789  \n",
       "13                 873  \n",
       "14                 717  \n",
       "15                 928  \n",
       "16                 980  \n",
       "17                 726  \n",
       "18                 702  \n",
       "19                 741  \n",
       "20                 142  \n",
       "21                  19  \n",
       "22                 256  \n",
       "23                 382  \n",
       "24                 313  \n",
       "25                 491  \n",
       "26                 558  \n",
       "27                 335  \n",
       "28                 611  \n",
       "29                 680  \n",
       "30                 589  \n",
       "31                 907  \n",
       "32                1079  \n",
       "33                 645  \n",
       "34                 710  \n",
       "35                 244  \n",
       "36                 822  \n",
       "37                 707  \n",
       "38                 430  \n",
       "39                 447  \n",
       "40                 813  \n",
       "41                 114  \n",
       "42                 439  \n",
       "43                 875  \n",
       "44                 768  \n",
       "45                1204  \n",
       "46                 359  \n",
       "47                 689  \n",
       "48                 620  \n",
       "49                 897  \n",
       "50                 894  \n",
       "51                 985  \n",
       "52                 598  \n",
       "53                 136  \n",
       "54                 729  \n",
       "55                 204  \n",
       "56                 817  \n",
       "57                 673  \n",
       "58                 763  \n",
       "59                 758  \n",
       "60                 770  \n",
       "61                 753  \n",
       "62                 984  \n",
       "63                 894  \n",
       "64                1131  \n",
       "65                 699  \n",
       "66                 380  \n",
       "67                 755  \n",
       "68                 556  \n",
       "69                 913  \n",
       "70                1368  \n",
       "71                1111  \n",
       "72                 714  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the columns you want to keep\n",
    "selected_columns = ['neighborhood_name', 'district_name', 'net_density_hab_ha']\n",
    "\n",
    "# Create a new DataFrame with the selected columns\n",
    "filtered_population_df = population_df[selected_columns]\n",
    "\n",
    "# Display the new DataFrame\n",
    "filtered_population_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd5cbc7e",
   "metadata": {},
   "source": [
    "#### Plot the net_density_hab_ha_ha by neighborhood_name and district_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2557b4d7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use pivot_table to create a pivot table\n",
    "pivot_table = population_df.pivot_table(index='neighborhood_name', columns='district_name', values='net_density_hab_ha', fill_value=0)\n",
    "\n",
    "# Set the plot size\n",
    "plt.figure(figsize=(14, 10))\n",
    "\n",
    "# Create a heatmap with seaborn for better visualization\n",
    "sns.heatmap(pivot_table, cmap='YlGnBu', annot=True, fmt=\".1f\", cbar_kws={'label': 'Net Density (hab/ha)'})\n",
    "\n",
    "# Axis labels and title\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Net Population Density by Neighborhood and District')\n",
    "plt.xlabel('District')\n",
    "plt.ylabel('Neighborhood')\n",
    "\n",
    "# Show the plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b7d1168",
   "metadata": {},
   "source": [
    "## Split numerical and categorical columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "105f2593",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['population', 'residential_area_ha', 'net_density_hab_ha'], dtype='object')\n",
      "Index(['district_name', 'neighborhood_name'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Separate numerical and categorical columns\n",
    "numerical_columns = population_df.select_dtypes(include=['int64', 'float64']).columns\n",
    "categorical_columns = population_df.select_dtypes(include=['object']).columns\n",
    "\n",
    "# Display numerical and categorical columns\n",
    "print(numerical_columns)\n",
    "print(categorical_columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb3b9a69",
   "metadata": {},
   "source": [
    "## Cleaning, Wrangling and EDA for numerical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "221458bf",
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>73.0</td>\n",
       "      <td>22420.986301</td>\n",
       "      <td>14524.540457</td>\n",
       "      <td>689.0</td>\n",
       "      <td>11026.0</td>\n",
       "      <td>21827.0</td>\n",
       "      <td>30741.0</td>\n",
       "      <td>57954.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>residential_area_ha</th>\n",
       "      <td>73.0</td>\n",
       "      <td>37.615068</td>\n",
       "      <td>34.129324</td>\n",
       "      <td>3.9</td>\n",
       "      <td>16.9</td>\n",
       "      <td>28.1</td>\n",
       "      <td>45.0</td>\n",
       "      <td>242.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>net_density_hab_ha</th>\n",
       "      <td>73.0</td>\n",
       "      <td>689.931507</td>\n",
       "      <td>287.046131</td>\n",
       "      <td>19.0</td>\n",
       "      <td>556.0</td>\n",
       "      <td>717.0</td>\n",
       "      <td>894.0</td>\n",
       "      <td>1368.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     count          mean           std    min      25%  \\\n",
       "population            73.0  22420.986301  14524.540457  689.0  11026.0   \n",
       "residential_area_ha   73.0     37.615068     34.129324    3.9     16.9   \n",
       "net_density_hab_ha    73.0    689.931507    287.046131   19.0    556.0   \n",
       "\n",
       "                         50%      75%      max  \n",
       "population           21827.0  30741.0  57954.0  \n",
       "residential_area_ha     28.1     45.0    242.0  \n",
       "net_density_hab_ha     717.0    894.0   1368.0  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[numerical_columns].describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fafd60fb",
   "metadata": {},
   "source": [
    "## Detect and manage outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "054c6889",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a function to detect outliers using IQR method\n",
    "def detect_outliers_iqr(column):\n",
    "    \"\"\"\n",
    "    Detect outliers in a numerical column using the Interquartile Range (IQR) method.\n",
    "\n",
    "    Parameters:\n",
    "    column (pandas.Series): The numerical column to detect outliers in.\n",
    "\n",
    "    Returns:\n",
    "    pandas.Series: A boolean series where True indicates outliers and False indicates non-outliers.\n",
    "    \"\"\"\n",
    "    # Calculate the IQR (Interquartile Range)\n",
    "    Q1 = np.percentile(column, 25)\n",
    "    Q3 = np.percentile(column, 75)\n",
    "    IQR = Q3 - Q1\n",
    "\n",
    "    # Define lower and upper bounds for outliers\n",
    "    lower_bound = Q1 - 1.5 * IQR\n",
    "    upper_bound = Q3 + 1.5 * IQR\n",
    "\n",
    "    # Identify outliers\n",
    "    outliers = (column < lower_bound) | (column > upper_bound)\n",
    "    \n",
    "    return outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a86f5307",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers in column \"population\":\n",
      "Empty DataFrame\n",
      "Columns: [year, district_name, neighborhood_name, population, residential_area_ha, net_density_hab_ha]\n",
      "Index: []\n",
      "Outliers in column \"residential_area_ha\":\n",
      "         year        district_name                      neighborhood_name  \\\n",
      "6  2021-01-01             Eixample                 la Dreta de l'Eixample   \n",
      "21 2021-01-01  Sarrià-Sant Gervasi  Vallvidrera, el Tibidabo i les Planes   \n",
      "22 2021-01-01  Sarrià-Sant Gervasi                                 Sarrià   \n",
      "25 2021-01-01  Sarrià-Sant Gervasi                 Sant Gervasi - Galvany   \n",
      "\n",
      "    population  residential_area_ha  net_density_hab_ha  \n",
      "6        44675                113.9                 392  \n",
      "21        4697                242.0                  19  \n",
      "22       24405                 95.4                 256  \n",
      "25       46816                 95.4                 491  \n",
      "Outliers in column \"net_density_hab_ha\":\n",
      "         year        district_name                      neighborhood_name  \\\n",
      "11 2021-01-01       Sants-Montjuïc             la Marina del Prat Vermell   \n",
      "21 2021-01-01  Sarrià-Sant Gervasi  Vallvidrera, el Tibidabo i les Planes   \n",
      "\n",
      "    population  residential_area_ha  net_density_hab_ha  \n",
      "11        1350                 35.5                  38  \n",
      "21        4697                242.0                  19  \n"
     ]
    }
   ],
   "source": [
    "# Apply the detect_outliers_iqr function to each numerical column\n",
    "numerical_columns = population_df.select_dtypes(include=['int64', 'float64']).columns\n",
    "outliers_dict = {}  # Dictionary to store outliers for each column\n",
    "\n",
    "for column in numerical_columns:\n",
    "    outliers = detect_outliers_iqr(population_df[column])\n",
    "    outliers_dict[column] = outliers\n",
    "\n",
    "# Display the outliers for each numerical column\n",
    "for column, outliers in outliers_dict.items():\n",
    "    print(f'Outliers in column \"{column}\":')\n",
    "    print(population_df[outliers])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "41c1270c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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XS9xwww3Rrl272HTTTeOMM86IefPmFdbV175Ykboyj9TF87q6r1WrQ01dq1WH7bffPv75z3/G66+/HhERzz//fDz66KOx++67Z1/70mrymrgmzJo1K0pKSqJ169bZ115RURGHHXZYjBw5MjbZZJNl1tdk7VmGVzNmzIjFixcXDU4RER06dIj333+/lqr6ektqW1nd77//fqy99tpF60tLS2OttdYq2mZ5+/jqMVa0TVX1T0VFRQwfPjx22GGH2HTTTQvHLCsrKzzIVtS+1a199uzZ8fnnn1fb/f/iiy9G8+bNo7y8PI477ri49dZbo3fv3nW+XRERf/vb3+LZZ5+NUaNGLbOurrevX79+cc0118Q999wTo0ePjqlTp0b//v1jzpw5db5tb775ZowePTo22GCDuPfee+P444+PH/7wh/HnP/+5qL76MKbUlLo6f6ypNX2c1FdV9RiqL3bbbbe49tpr45///GdceOGF8dBDD8Xuu+8eixcvjoj62RfVeT1T1yyvLyIivv/978f1118fDz74YJxxxhlx3XXXxaGHHlpYXx/7YmXqwjxSF8/rmrhWrQ41da1WHX7yk5/EQQcdFL169YpGjRrFlltuGcOHD49DDjkk+9qXVpPXxNVt/vz58eMf/zgOPvjgaNmyZeHYudZ+4YUXRmlpafzwhz9c7vqarL20MoXzzXHiiSfGSy+9FI8++mhtl1JlNtpoo5g4cWLMmjUrbrnllhg6dGg89NBDtV3WGvv3v/8dp5xyStx3333RuHHj2i6nyi15dSgiYrPNNot+/fpF9+7d46abboomTZrUYmVrrqKiIrbeeuv45S9/GRERW265Zbz00ktxxRVXxNChQ2u5OuqS+vw4oeocdNBBhf/v06dPbLbZZtGzZ88YP3587LzzzrVYWfWpj9czq2tFfXHMMccU/r9Pnz7RqVOn2HnnneONN96Inj171nSZrIK6dl7X5WvVunytdtNNN8UNN9wQf/nLX2KTTTaJiRMnxvDhw6Nz587Z115fffHFF3HAAQdESilGjx5d2+V8rWeeeSZ++9vfxrPPPhslJSW1XU6e77xq165dNGzYcJlfmPjggw+iY8eOtVTV11tS28rq7tixY3z44YdF6xctWhSffPJJ0TbL28dXj7Gibaqif0466aQYN25cPPjgg9GlS5fC8o4dO8bChQtj5syZK23f6tbesmXLaNKkSbXd/2VlZbH++utH3759Y9SoUbH55pvHb3/72zrfrmeeeSY+/PDD2GqrraK0tDRKS0vjoYceit/97ndRWloaHTp0qNPtW1rr1q1jww03jClTptT5+65Tp07Ru3fvomUbb7xx4eNe9WVMqUl1df6oapV9nNRXVfUYqq/WW2+9aNeuXUyZMiUi6l9fVPf1TF2yor5Ynn79+kVEFJ0X9akvvk7u80hdPK9r6lq1OtTUtVp1GDlyZOHdV3369InDDjssfvSjHxXe/ZZz7UuryWvi6rIkuHrrrbfivvvuK7zrKufaH3nkkfjwww+jW7duhcfuW2+9FSNGjIgePXrUeO1ZhldlZWXRt2/f+Oc//1lYVlFREf/85z9ju+22q8XKVm7dddeNjh07FtU9e/bseOKJJwp1b7fddjFz5sx45plnCts88MADUVFRUbhY2G677eLhhx+OL774orDNfffdFxtttFG0adOmsM1Xj7NkmzXpn5RSnHTSSXHrrbfGAw88EOuuu27R+r59+0ajRo2Kjjtp0qSYPn16UftefPHFohN4yYNzycD/dbXX1P1fUVERCxYsqPPt2nnnnePFF1+MiRMnFv5tvfXWccghhxT+vy63b2lz586NN954Izp16lTn77sddthhmZ+5fv3116N79+4RUffHlNpQV+ePqlbZx0l9VVWPofrq7bffjo8//jg6deoUEfWnL2rqeqYu+Lq+WJ6JEydGRBSdF/WhL1ZVrvNIXT6va+patTrU1LVadZg3b140aFD8dL9hw4ZRUVGRfe1Lq8lr4uqwJLiaPHly3H///dG2bdui9bnWfthhh8ULL7xQ9Njt3LlzjBw5Mu69996ar71SX+9eg/72t7+l8vLydM0116RXXnklHXPMMal169ZFvzBRG+bMmZOee+659Nxzz6WISL/+9a/Tc889V/ilgF/96lepdevW6fbbb08vvPBC2nvvvZf7E55bbrlleuKJJ9Kjjz6aNthgg6Kfkpw5c2bq0KFDOuyww9JLL72U/va3v6WmTZsu87P2paWl6ZJLLkmvvvpqOvvss9f4Z+2PP/741KpVqzR+/Piin0ueN29eYZvjjjsudevWLT3wwAPp6aefTtttt13abrvtCuuX/IztrrvumiZOnJjuueee1L59+6KfsX3zzTdT06ZN08iRI9Orr76a/vCHP6SGDRume+65p7BNVd//P/nJT9JDDz2Upk6dml544YX0k5/8JJWUlKR//OMfdbpdK7L0LwfV5faNGDEijR8/Pk2dOjU99thjaZdddknt2rVLH374YZ1v25NPPplKS0vTL37xizR58uR0ww03pKZNm6brr7++sE1dHlNqS67zR3Va08dJXVYT83JdsbK+mDNnTjrttNPShAkT0tSpU9P999+fttpqq7TBBhuk+fPnF/ZRH/qipq5n6oKv64spU6ak8847Lz399NNp6tSp6fbbb0/rrbde2mmnnQr7qC99URk5ziP17byujmvV6lBT12rVYejQoWmdddZJ48aNS1OnTk1jx45N7dq1S6effnqWtefyPLuqa1+4cGHaa6+9UpcuXdLEiROLHr9f/fW9HGtfnqV/bbAma882vEoppcsvvzx169YtlZWVpW9961vpX//6V22XlB588MEUEcv8Gzp0aErpy5/x/PnPf546dOiQysvL084775wmTZpUtI+PP/44HXzwwal58+apZcuW6Ygjjkhz5swp2ub5559PO+64YyovL0/rrLNO+tWvfrVMLTfddFPacMMNU1lZWdpkk03SXXfdtUZtW167IiKNGTOmsM3nn3+eTjjhhNSmTZvUtGnTtO+++6b33nuvaD/Tpk1Lu+++e2rSpElq165dGjFiRPriiy+KtnnwwQfTFltskcrKytJ6661XdIwlqvL+P/LII1P37t1TWVlZat++fdp5550LwVVdbteKLH1BUJfbd+CBB6ZOnTqlsrKytM4666QDDzwwTZkypV60LaWU7rzzzrTpppum8vLy1KtXr3TllVcWra/LY0ptynH+qE5V8Tipq2pqXq4LVtYX8+bNS7vuumtq3759atSoUerevXv6wQ9+sMyT8frQFzV5PZO7r+uL6dOnp5122imttdZaqby8PK2//vpp5MiRadasWUX7qQ99UVm5zSP17byurmvV6lBT12pVbfbs2emUU05J3bp1S40bN07rrbde+tnPflYUmORUe07Ps6uy9qlTp67w8fvggw9mXfvyLC+8qqnaS1JKadXfpwUAAAAANSfL77wCAAAAgAjhFQAAAAAZE14BAAAAkC3hFQAAAADZEl4BAAAAkC3hFQAAAADZEl4BAAAAkC3hFQAAAADZEl7B1xg4cGAMHz68tssAoA4yhwCwuswh8F/CK+q1PffcM3bbbbflrnvkkUeipKQkXnjhhRquCoC6wBwCwOoyh0DVEl5Rrx111FFx3333xdtvv73MujFjxsTWW28dm222WS1UBkDuzCEArC5zCFQt4RX12pAhQ6J9+/ZxzTXXFC2fO3du3HzzzbHPPvvEwQcfHOuss040bdo0+vTpE3/9619Xus+SkpK47bbbipa1bt266Bj//ve/44ADDojWrVvHWmutFXvvvXdMmzatahoFQI0whwCwuswhULWEV9RrpaWlcfjhh8c111wTKaXC8ptvvjkWL14chx56aPTt2zfuuuuueOmll+KYY46Jww47LJ588snVPuYXX3wRgwYNihYtWsQjjzwSjz32WDRv3jx22223WLhwYVU0C4AaYA4BYHWZQ6BqCa+o94488sh444034qGHHiosGzNmTOy///7RvXv3OO2002KLLbaI9dZbL04++eTYbbfd4qabblrt4914441RUVERf/rTn6JPnz6x8cYbx5gxY2L69Okxfvz4KmgRADXFHALA6jKHQNURXlHv9erVK7bffvu4+uqrIyJiypQp8cgjj8RRRx0VixcvjvPPPz/69OkTa621VjRv3jzuvffemD59+mof7/nnn48pU6ZEixYtonnz5tG8efNYa621Yv78+fHGG29UVbMAqAHmEABWlzkEqk5pbRcANeGoo46Kk08+Of7whz/EmDFjomfPnjFgwIC48MIL47e//W385je/iT59+kSzZs1i+PDhK31bbUlJSdFbfyO+fIvuEnPnzo2+ffvGDTfcsMzftm/fvuoaBUCNMIcAsLrMIVA1hFd8IxxwwAFxyimnxF/+8pe49tpr4/jjj4+SkpJ47LHHYu+9945DDz00IiIqKiri9ddfj969e69wX+3bt4/33nuvcHvy5Mkxb968wu2tttoqbrzxxlh77bWjZcuW1dcoAGqEOQSA1WUOgarhY4N8IzRv3jwOPPDAOOOMM+K9996LYcOGRUTEBhtsEPfdd188/vjj8eqrr8axxx4bH3zwwUr39Z3vfCd+//vfx3PPPRdPP/10HHfccdGoUaPC+kMOOSTatWsXe++9dzzyyCMxderUGD9+fPzwhz9c7k/lApA3cwgAq8scAlVDeMU3xlFHHRWffvppDBo0KDp37hwREWeeeWZstdVWMWjQoBg4cGB07Ngx9tlnn5Xu59JLL42uXbtG//794/vf/36cdtpp0bRp08L6pk2bxsMPPxzdunWL/fbbLzbeeOM46qijYv78+V4BAaijzCEArC5zCKy5krT0h2YBAAAAIBPeeQUAAABAtoRXAAAAAGRLeAUAAABAtoRXAAAAAGRLeAUAAABAtoRXAAAAAGRLeAUAAABAtoRXAAAAAGRLeAUAAABAtoRXAAAAAGRLeAUAAABAtoRXAAAAAGTr/wOdbwTXfSoEBAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select numerical columns\n",
    "numerical_columns = population_df.select_dtypes(include=['int64', 'float64'])\n",
    "\n",
    "# Define colors for the boxplots\n",
    "colors = ['blue', 'green', 'red', 'purple', 'orange']\n",
    "\n",
    "# Create a boxplot for each numerical column with different colors\n",
    "plt.figure(figsize=(12, 6))  # Set the figure size\n",
    "\n",
    "for i, column in enumerate(numerical_columns.columns):\n",
    "    plt.subplot(1, len(numerical_columns.columns), i + 1)  # Create subplots\n",
    "    \n",
    "    # Create boxplot with custom color\n",
    "    box = plt.boxplot(population_df[column], vert=False, patch_artist=True)\n",
    "    \n",
    "    # Set the color for the boxplot\n",
    "    for patch in box['boxes']:\n",
    "        patch.set_facecolor(colors[i])\n",
    "    \n",
    "    plt.title(column)  # Set title\n",
    "    plt.xlabel('Value')  # Label x-axis\n",
    "\n",
    "plt.tight_layout()  # Ensure proper spacing between subplots\n",
    "plt.show()  # Display the boxplots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf67fea5",
   "metadata": {},
   "source": [
    "This outputs depict a process of identifying outliers for a dataset that includes population, residential area, and net density for the neighborhoods of Barcelona. Using the Interquartile Range (IQR) method, potential outliers have been detected. Additionally, numerical data has been visualized using boxplots, which illustrate the data distribution and highlight outliers.\n",
    "\n",
    "**When interpreting outliers, it is essential to consider the context and nature of the data. In a dataset representing urban characteristics such as neighborhood population and density, the presence of outliers can reflect real and significant variations that are important for analysis. For example:**\n",
    "\n",
    "**1. Differences in Population and Residential Area:**\n",
    "Outliers in population and residential area may be due to neighborhoods that are unusually large or small, densely populated, or sparsely populated. Barcelona has a variety of neighborhoods with different characteristics, including tourist areas and commercial centers that may have high or low population density.\n",
    "\n",
    "**2. Variations in Net Density:**\n",
    "Net density can vary significantly between neighborhoods due to urban planning and land use. For instance, Barceloneta has a high net density due to its small area and high population, while other more extensive neighborhoods may have lower density.\n",
    "\n",
    "**3. Justification for Retaining Outliers:**\n",
    "The identified outliers may represent unique neighborhoods that are essential for a comprehensive analysis of the city. Removing these neighborhoods could bias the results and omit important information about variability within the city.\n",
    "\n",
    "Furthermore, neighborhoods with outliers may be of particular interest for specific research questions, such as studying the relationship between population density and service availability.\n",
    "\n",
    "**Since the detected outliers do not appear to be errors but natural variations within urban data, the decision not to remove or modify them is justified. Retaining these outliers preserves data integrity and ensures that the analysis reflects the reality of urban diversity in Barcelona. By not altering this data, a more representative and meaningful analysis of trends and relationships in population and urban structure in the city can be conducted.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d647edf9",
   "metadata": {},
   "source": [
    "## Cleaning categorical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3a1893f4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>district_name</th>\n",
       "      <th>neighborhood_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Raval</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Barri Gòtic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>la Barceloneta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eixample</td>\n",
       "      <td>el Fort Pienc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Eixample</td>\n",
       "      <td>la Sagrada Família</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Eixample</td>\n",
       "      <td>la Dreta de l'Eixample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Eixample</td>\n",
       "      <td>l'Antiga Esquerra de l'Eixample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Eixample</td>\n",
       "      <td>la Nova Esquerra de l'Eixample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Eixample</td>\n",
       "      <td>Sant Antoni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>el Poble Sec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Marina del Prat Vermell</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Marina de Port</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Font de la Guatlla</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>Hostafrancs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Bordeta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>Sants - Badal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>Sants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Les Corts</td>\n",
       "      <td>les Corts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Les Corts</td>\n",
       "      <td>la Maternitat i Sant Ramon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Les Corts</td>\n",
       "      <td>Pedralbes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Vallvidrera, el Tibidabo i les Planes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Sarrià</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>les Tres Torres</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Sant Gervasi - la Bonanova</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Sant Gervasi - Galvany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>el Putxet i el Farró</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Gràcia</td>\n",
       "      <td>Vallcarca i els Penitents</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Gràcia</td>\n",
       "      <td>el Coll</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Gràcia</td>\n",
       "      <td>la Salut</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Gràcia</td>\n",
       "      <td>la Vila de Gràcia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Gràcia</td>\n",
       "      <td>el Camp d'en Grassot i Gràcia Nova</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>el Baix Guinardó</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Can Baró</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>el Guinardó</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Font d'en Fargues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>el Carmel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Teixonera</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Sant Genís dels Agudells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Montbau</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Vall d'Hebron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Clota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Horta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Vilapicina i la Torre Llobeta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Porta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>el Turó de la Peira</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Can Peguera</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>la Guineueta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Canyelles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>les Roquetes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Verdun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>la Prosperitat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>la Trinitat Nova</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Torre Baró</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Ciutat Meridiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Vallbona</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>la Trinitat Vella</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Baró de Viver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>el Bon Pastor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Sant Andreu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>la Sagrera</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>el Congrés i els Indians</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Navas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Camp de l'Arpa del Clot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Clot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Parc i la Llacuna del Poblenou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>la Vila Olímpica del Poblenou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Poblenou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>Diagonal Mar i el Front Marítim del Poblenou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Besòs i el Maresme</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>Provençals del Poblenou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>Sant Martí de Provençals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>la Verneda i la Pau</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          district_name                             neighborhood_name\n",
       "0          Ciutat Vella                                      el Raval\n",
       "1          Ciutat Vella                                el Barri Gòtic\n",
       "2          Ciutat Vella                                la Barceloneta\n",
       "3          Ciutat Vella         Sant Pere, Santa Caterina i la Ribera\n",
       "4              Eixample                                 el Fort Pienc\n",
       "5              Eixample                            la Sagrada Família\n",
       "6              Eixample                        la Dreta de l'Eixample\n",
       "7              Eixample               l'Antiga Esquerra de l'Eixample\n",
       "8              Eixample                la Nova Esquerra de l'Eixample\n",
       "9              Eixample                                   Sant Antoni\n",
       "10       Sants-Montjuïc                                  el Poble Sec\n",
       "11       Sants-Montjuïc                    la Marina del Prat Vermell\n",
       "12       Sants-Montjuïc                             la Marina de Port\n",
       "13       Sants-Montjuïc                         la Font de la Guatlla\n",
       "14       Sants-Montjuïc                                   Hostafrancs\n",
       "15       Sants-Montjuïc                                    la Bordeta\n",
       "16       Sants-Montjuïc                                 Sants - Badal\n",
       "17       Sants-Montjuïc                                         Sants\n",
       "18            Les Corts                                     les Corts\n",
       "19            Les Corts                    la Maternitat i Sant Ramon\n",
       "20            Les Corts                                     Pedralbes\n",
       "21  Sarrià-Sant Gervasi         Vallvidrera, el Tibidabo i les Planes\n",
       "22  Sarrià-Sant Gervasi                                        Sarrià\n",
       "23  Sarrià-Sant Gervasi                               les Tres Torres\n",
       "24  Sarrià-Sant Gervasi                    Sant Gervasi - la Bonanova\n",
       "25  Sarrià-Sant Gervasi                        Sant Gervasi - Galvany\n",
       "26  Sarrià-Sant Gervasi                          el Putxet i el Farró\n",
       "27               Gràcia                     Vallcarca i els Penitents\n",
       "28               Gràcia                                       el Coll\n",
       "29               Gràcia                                      la Salut\n",
       "30               Gràcia                             la Vila de Gràcia\n",
       "31               Gràcia            el Camp d'en Grassot i Gràcia Nova\n",
       "32       Horta-Guinardó                              el Baix Guinardó\n",
       "33       Horta-Guinardó                                      Can Baró\n",
       "34       Horta-Guinardó                                   el Guinardó\n",
       "35       Horta-Guinardó                          la Font d'en Fargues\n",
       "36       Horta-Guinardó                                     el Carmel\n",
       "37       Horta-Guinardó                                  la Teixonera\n",
       "38       Horta-Guinardó                      Sant Genís dels Agudells\n",
       "39       Horta-Guinardó                                       Montbau\n",
       "40       Horta-Guinardó                              la Vall d'Hebron\n",
       "41       Horta-Guinardó                                      la Clota\n",
       "42       Horta-Guinardó                                         Horta\n",
       "43           Nou Barris                 Vilapicina i la Torre Llobeta\n",
       "44           Nou Barris                                         Porta\n",
       "45           Nou Barris                           el Turó de la Peira\n",
       "46           Nou Barris                                   Can Peguera\n",
       "47           Nou Barris                                  la Guineueta\n",
       "48           Nou Barris                                     Canyelles\n",
       "49           Nou Barris                                  les Roquetes\n",
       "50           Nou Barris                                        Verdun\n",
       "51           Nou Barris                                la Prosperitat\n",
       "52           Nou Barris                              la Trinitat Nova\n",
       "53           Nou Barris                                    Torre Baró\n",
       "54           Nou Barris                              Ciutat Meridiana\n",
       "55           Nou Barris                                      Vallbona\n",
       "56          Sant Andreu                             la Trinitat Vella\n",
       "57          Sant Andreu                                 Baró de Viver\n",
       "58          Sant Andreu                                 el Bon Pastor\n",
       "59          Sant Andreu                                   Sant Andreu\n",
       "60          Sant Andreu                                    la Sagrera\n",
       "61          Sant Andreu                      el Congrés i els Indians\n",
       "62          Sant Andreu                                         Navas\n",
       "63           Sant Martí                    el Camp de l'Arpa del Clot\n",
       "64           Sant Martí                                       el Clot\n",
       "65           Sant Martí             el Parc i la Llacuna del Poblenou\n",
       "66           Sant Martí                 la Vila Olímpica del Poblenou\n",
       "67           Sant Martí                                   el Poblenou\n",
       "68           Sant Martí  Diagonal Mar i el Front Marítim del Poblenou\n",
       "69           Sant Martí                         el Besòs i el Maresme\n",
       "70           Sant Martí                       Provençals del Poblenou\n",
       "71           Sant Martí                      Sant Martí de Provençals\n",
       "72           Sant Martí                           la Verneda i la Pau"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df[categorical_columns]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3500e9f",
   "metadata": {},
   "source": [
    "Both numerical and categorical are already cleaned so I left the population_df as it is."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff463a27",
   "metadata": {},
   "source": [
    "## Sort neighborhood_name column alphabetically"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "71f9ea0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort the DataFrame by the 'neighborhood_name' column in alphabetical order\n",
    "population_df.sort_values(by='neighborhood_name', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "43815d7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reset the index to reflect the new order\n",
    "population_df = population_df.reset_index()\n",
    "\n",
    "# Remove the 'index' column\n",
    "population_df = population_df.drop(columns=['index'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "e9e4f83f",
   "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>year</th>\n",
       "      <th>district_name</th>\n",
       "      <th>neighborhood_name</th>\n",
       "      <th>population</th>\n",
       "      <th>residential_area_ha</th>\n",
       "      <th>net_density_hab_ha</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Baró de Viver</td>\n",
       "      <td>2645</td>\n",
       "      <td>3.9</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Can Baró</td>\n",
       "      <td>9233</td>\n",
       "      <td>14.3</td>\n",
       "      <td>645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Can Peguera</td>\n",
       "      <td>2204</td>\n",
       "      <td>6.1</td>\n",
       "      <td>359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Canyelles</td>\n",
       "      <td>6797</td>\n",
       "      <td>11.0</td>\n",
       "      <td>620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Ciutat Meridiana</td>\n",
       "      <td>11026</td>\n",
       "      <td>15.1</td>\n",
       "      <td>729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>Diagonal Mar i el Front Marítim del Poblenou</td>\n",
       "      <td>13323</td>\n",
       "      <td>24.0</td>\n",
       "      <td>556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Horta</td>\n",
       "      <td>27707</td>\n",
       "      <td>63.2</td>\n",
       "      <td>439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>Hostafrancs</td>\n",
       "      <td>15842</td>\n",
       "      <td>22.1</td>\n",
       "      <td>717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Montbau</td>\n",
       "      <td>5071</td>\n",
       "      <td>11.4</td>\n",
       "      <td>447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Navas</td>\n",
       "      <td>22091</td>\n",
       "      <td>22.4</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>Pedralbes</td>\n",
       "      <td>11581</td>\n",
       "      <td>81.7</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Porta</td>\n",
       "      <td>27418</td>\n",
       "      <td>35.7</td>\n",
       "      <td>768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>Provençals del Poblenou</td>\n",
       "      <td>20949</td>\n",
       "      <td>15.3</td>\n",
       "      <td>1368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>57954</td>\n",
       "      <td>76.5</td>\n",
       "      <td>758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>Sant Antoni</td>\n",
       "      <td>38053</td>\n",
       "      <td>41.3</td>\n",
       "      <td>921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>Sant Genís dels Agudells</td>\n",
       "      <td>7249</td>\n",
       "      <td>16.9</td>\n",
       "      <td>430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Sant Gervasi - Galvany</td>\n",
       "      <td>46816</td>\n",
       "      <td>95.4</td>\n",
       "      <td>491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Sant Gervasi - la Bonanova</td>\n",
       "      <td>25659</td>\n",
       "      <td>82.1</td>\n",
       "      <td>313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>Sant Martí de Provençals</td>\n",
       "      <td>26032</td>\n",
       "      <td>23.4</td>\n",
       "      <td>1111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>Sant Pere, Santa Caterina i la Ribera</td>\n",
       "      <td>22131</td>\n",
       "      <td>32.4</td>\n",
       "      <td>683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>Sants</td>\n",
       "      <td>43082</td>\n",
       "      <td>59.4</td>\n",
       "      <td>726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>Sants - Badal</td>\n",
       "      <td>24576</td>\n",
       "      <td>25.1</td>\n",
       "      <td>980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Sarrià</td>\n",
       "      <td>24405</td>\n",
       "      <td>95.4</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Torre Baró</td>\n",
       "      <td>2890</td>\n",
       "      <td>21.2</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Vallbona</td>\n",
       "      <td>1384</td>\n",
       "      <td>6.8</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>Vallcarca i els Penitents</td>\n",
       "      <td>16142</td>\n",
       "      <td>48.2</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>Vallvidrera, el Tibidabo i les Planes</td>\n",
       "      <td>4697</td>\n",
       "      <td>242.0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Verdun</td>\n",
       "      <td>12727</td>\n",
       "      <td>14.2</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>Vilapicina i la Torre Llobeta</td>\n",
       "      <td>25674</td>\n",
       "      <td>29.3</td>\n",
       "      <td>875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>el Baix Guinardó</td>\n",
       "      <td>25601</td>\n",
       "      <td>23.7</td>\n",
       "      <td>1079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Barri Gòtic</td>\n",
       "      <td>21827</td>\n",
       "      <td>34.1</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Besòs i el Maresme</td>\n",
       "      <td>25657</td>\n",
       "      <td>28.1</td>\n",
       "      <td>913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>el Bon Pastor</td>\n",
       "      <td>13582</td>\n",
       "      <td>17.8</td>\n",
       "      <td>763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>el Camp d'en Grassot i Gràcia Nova</td>\n",
       "      <td>34932</td>\n",
       "      <td>38.5</td>\n",
       "      <td>907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Camp de l'Arpa del Clot</td>\n",
       "      <td>38360</td>\n",
       "      <td>42.9</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>el Carmel</td>\n",
       "      <td>32444</td>\n",
       "      <td>39.4</td>\n",
       "      <td>822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Clot</td>\n",
       "      <td>26520</td>\n",
       "      <td>23.4</td>\n",
       "      <td>1131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>el Coll</td>\n",
       "      <td>7590</td>\n",
       "      <td>12.4</td>\n",
       "      <td>611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>el Congrés i els Indians</td>\n",
       "      <td>14420</td>\n",
       "      <td>19.1</td>\n",
       "      <td>753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>el Fort Pienc</td>\n",
       "      <td>31262</td>\n",
       "      <td>33.6</td>\n",
       "      <td>930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>el Guinardó</td>\n",
       "      <td>36939</td>\n",
       "      <td>52.0</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Parc i la Llacuna del Poblenou</td>\n",
       "      <td>15603</td>\n",
       "      <td>22.3</td>\n",
       "      <td>699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>el Poble Sec</td>\n",
       "      <td>39400</td>\n",
       "      <td>38.1</td>\n",
       "      <td>1033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>el Poblenou</td>\n",
       "      <td>33976</td>\n",
       "      <td>45.0</td>\n",
       "      <td>755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>el Putxet i el Farró</td>\n",
       "      <td>29629</td>\n",
       "      <td>53.1</td>\n",
       "      <td>558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>el Raval</td>\n",
       "      <td>47228</td>\n",
       "      <td>49.6</td>\n",
       "      <td>952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>el Turó de la Peira</td>\n",
       "      <td>16025</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>l'Antiga Esquerra de l'Eixample</td>\n",
       "      <td>41990</td>\n",
       "      <td>66.9</td>\n",
       "      <td>627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Ciutat Vella</td>\n",
       "      <td>la Barceloneta</td>\n",
       "      <td>14643</td>\n",
       "      <td>13.5</td>\n",
       "      <td>1081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Bordeta</td>\n",
       "      <td>19292</td>\n",
       "      <td>20.8</td>\n",
       "      <td>928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Clota</td>\n",
       "      <td>689</td>\n",
       "      <td>6.1</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>la Dreta de l'Eixample</td>\n",
       "      <td>44675</td>\n",
       "      <td>113.9</td>\n",
       "      <td>392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Font d'en Fargues</td>\n",
       "      <td>9458</td>\n",
       "      <td>38.8</td>\n",
       "      <td>244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Font de la Guatlla</td>\n",
       "      <td>10084</td>\n",
       "      <td>11.5</td>\n",
       "      <td>873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>la Guineueta</td>\n",
       "      <td>15189</td>\n",
       "      <td>22.0</td>\n",
       "      <td>689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Marina de Port</td>\n",
       "      <td>30741</td>\n",
       "      <td>38.9</td>\n",
       "      <td>789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sants-Montjuïc</td>\n",
       "      <td>la Marina del Prat Vermell</td>\n",
       "      <td>1350</td>\n",
       "      <td>35.5</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>la Maternitat i Sant Ramon</td>\n",
       "      <td>23574</td>\n",
       "      <td>31.8</td>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>la Nova Esquerra de l'Eixample</td>\n",
       "      <td>57054</td>\n",
       "      <td>65.2</td>\n",
       "      <td>876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>la Prosperitat</td>\n",
       "      <td>26669</td>\n",
       "      <td>27.1</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Eixample</td>\n",
       "      <td>la Sagrada Família</td>\n",
       "      <td>51319</td>\n",
       "      <td>51.0</td>\n",
       "      <td>1007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>la Sagrera</td>\n",
       "      <td>29351</td>\n",
       "      <td>38.1</td>\n",
       "      <td>770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>la Salut</td>\n",
       "      <td>13282</td>\n",
       "      <td>19.5</td>\n",
       "      <td>680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Teixonera</td>\n",
       "      <td>11926</td>\n",
       "      <td>16.9</td>\n",
       "      <td>707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>la Trinitat Nova</td>\n",
       "      <td>7507</td>\n",
       "      <td>12.6</td>\n",
       "      <td>598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Andreu</td>\n",
       "      <td>la Trinitat Vella</td>\n",
       "      <td>10364</td>\n",
       "      <td>12.7</td>\n",
       "      <td>817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Horta-Guinardó</td>\n",
       "      <td>la Vall d'Hebron</td>\n",
       "      <td>5882</td>\n",
       "      <td>7.2</td>\n",
       "      <td>813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>la Verneda i la Pau</td>\n",
       "      <td>28585</td>\n",
       "      <td>40.0</td>\n",
       "      <td>714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sant Martí</td>\n",
       "      <td>la Vila Olímpica del Poblenou</td>\n",
       "      <td>9240</td>\n",
       "      <td>24.3</td>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Gràcia</td>\n",
       "      <td>la Vila de Gràcia</td>\n",
       "      <td>49492</td>\n",
       "      <td>84.0</td>\n",
       "      <td>589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Les Corts</td>\n",
       "      <td>les Corts</td>\n",
       "      <td>45422</td>\n",
       "      <td>64.7</td>\n",
       "      <td>702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Nou Barris</td>\n",
       "      <td>les Roquetes</td>\n",
       "      <td>16373</td>\n",
       "      <td>18.2</td>\n",
       "      <td>897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>Sarrià-Sant Gervasi</td>\n",
       "      <td>les Tres Torres</td>\n",
       "      <td>16228</td>\n",
       "      <td>42.5</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         year        district_name  \\\n",
       "0  2021-01-01          Sant Andreu   \n",
       "1  2021-01-01       Horta-Guinardó   \n",
       "2  2021-01-01           Nou Barris   \n",
       "3  2021-01-01           Nou Barris   \n",
       "4  2021-01-01           Nou Barris   \n",
       "5  2021-01-01           Sant Martí   \n",
       "6  2021-01-01       Horta-Guinardó   \n",
       "7  2021-01-01       Sants-Montjuïc   \n",
       "8  2021-01-01       Horta-Guinardó   \n",
       "9  2021-01-01          Sant Andreu   \n",
       "10 2021-01-01            Les Corts   \n",
       "11 2021-01-01           Nou Barris   \n",
       "12 2021-01-01           Sant Martí   \n",
       "13 2021-01-01          Sant Andreu   \n",
       "14 2021-01-01             Eixample   \n",
       "15 2021-01-01       Horta-Guinardó   \n",
       "16 2021-01-01  Sarrià-Sant Gervasi   \n",
       "17 2021-01-01  Sarrià-Sant Gervasi   \n",
       "18 2021-01-01           Sant Martí   \n",
       "19 2021-01-01         Ciutat Vella   \n",
       "20 2021-01-01       Sants-Montjuïc   \n",
       "21 2021-01-01       Sants-Montjuïc   \n",
       "22 2021-01-01  Sarrià-Sant Gervasi   \n",
       "23 2021-01-01           Nou Barris   \n",
       "24 2021-01-01           Nou Barris   \n",
       "25 2021-01-01               Gràcia   \n",
       "26 2021-01-01  Sarrià-Sant Gervasi   \n",
       "27 2021-01-01           Nou Barris   \n",
       "28 2021-01-01           Nou Barris   \n",
       "29 2021-01-01       Horta-Guinardó   \n",
       "30 2021-01-01         Ciutat Vella   \n",
       "31 2021-01-01           Sant Martí   \n",
       "32 2021-01-01          Sant Andreu   \n",
       "33 2021-01-01               Gràcia   \n",
       "34 2021-01-01           Sant Martí   \n",
       "35 2021-01-01       Horta-Guinardó   \n",
       "36 2021-01-01           Sant Martí   \n",
       "37 2021-01-01               Gràcia   \n",
       "38 2021-01-01          Sant Andreu   \n",
       "39 2021-01-01             Eixample   \n",
       "40 2021-01-01       Horta-Guinardó   \n",
       "41 2021-01-01           Sant Martí   \n",
       "42 2021-01-01       Sants-Montjuïc   \n",
       "43 2021-01-01           Sant Martí   \n",
       "44 2021-01-01  Sarrià-Sant Gervasi   \n",
       "45 2021-01-01         Ciutat Vella   \n",
       "46 2021-01-01           Nou Barris   \n",
       "47 2021-01-01             Eixample   \n",
       "48 2021-01-01         Ciutat Vella   \n",
       "49 2021-01-01       Sants-Montjuïc   \n",
       "50 2021-01-01       Horta-Guinardó   \n",
       "51 2021-01-01             Eixample   \n",
       "52 2021-01-01       Horta-Guinardó   \n",
       "53 2021-01-01       Sants-Montjuïc   \n",
       "54 2021-01-01           Nou Barris   \n",
       "55 2021-01-01       Sants-Montjuïc   \n",
       "56 2021-01-01       Sants-Montjuïc   \n",
       "57 2021-01-01            Les Corts   \n",
       "58 2021-01-01             Eixample   \n",
       "59 2021-01-01           Nou Barris   \n",
       "60 2021-01-01             Eixample   \n",
       "61 2021-01-01          Sant Andreu   \n",
       "62 2021-01-01               Gràcia   \n",
       "63 2021-01-01       Horta-Guinardó   \n",
       "64 2021-01-01           Nou Barris   \n",
       "65 2021-01-01          Sant Andreu   \n",
       "66 2021-01-01       Horta-Guinardó   \n",
       "67 2021-01-01           Sant Martí   \n",
       "68 2021-01-01           Sant Martí   \n",
       "69 2021-01-01               Gràcia   \n",
       "70 2021-01-01            Les Corts   \n",
       "71 2021-01-01           Nou Barris   \n",
       "72 2021-01-01  Sarrià-Sant Gervasi   \n",
       "\n",
       "                               neighborhood_name  population  \\\n",
       "0                                  Baró de Viver        2645   \n",
       "1                                       Can Baró        9233   \n",
       "2                                    Can Peguera        2204   \n",
       "3                                      Canyelles        6797   \n",
       "4                               Ciutat Meridiana       11026   \n",
       "5   Diagonal Mar i el Front Marítim del Poblenou       13323   \n",
       "6                                          Horta       27707   \n",
       "7                                    Hostafrancs       15842   \n",
       "8                                        Montbau        5071   \n",
       "9                                          Navas       22091   \n",
       "10                                     Pedralbes       11581   \n",
       "11                                         Porta       27418   \n",
       "12                       Provençals del Poblenou       20949   \n",
       "13                                   Sant Andreu       57954   \n",
       "14                                   Sant Antoni       38053   \n",
       "15                      Sant Genís dels Agudells        7249   \n",
       "16                        Sant Gervasi - Galvany       46816   \n",
       "17                    Sant Gervasi - la Bonanova       25659   \n",
       "18                      Sant Martí de Provençals       26032   \n",
       "19         Sant Pere, Santa Caterina i la Ribera       22131   \n",
       "20                                         Sants       43082   \n",
       "21                                 Sants - Badal       24576   \n",
       "22                                        Sarrià       24405   \n",
       "23                                    Torre Baró        2890   \n",
       "24                                      Vallbona        1384   \n",
       "25                     Vallcarca i els Penitents       16142   \n",
       "26         Vallvidrera, el Tibidabo i les Planes        4697   \n",
       "27                                        Verdun       12727   \n",
       "28                 Vilapicina i la Torre Llobeta       25674   \n",
       "29                              el Baix Guinardó       25601   \n",
       "30                                el Barri Gòtic       21827   \n",
       "31                         el Besòs i el Maresme       25657   \n",
       "32                                 el Bon Pastor       13582   \n",
       "33            el Camp d'en Grassot i Gràcia Nova       34932   \n",
       "34                    el Camp de l'Arpa del Clot       38360   \n",
       "35                                     el Carmel       32444   \n",
       "36                                       el Clot       26520   \n",
       "37                                       el Coll        7590   \n",
       "38                      el Congrés i els Indians       14420   \n",
       "39                                 el Fort Pienc       31262   \n",
       "40                                   el Guinardó       36939   \n",
       "41             el Parc i la Llacuna del Poblenou       15603   \n",
       "42                                  el Poble Sec       39400   \n",
       "43                                   el Poblenou       33976   \n",
       "44                          el Putxet i el Farró       29629   \n",
       "45                                      el Raval       47228   \n",
       "46                           el Turó de la Peira       16025   \n",
       "47               l'Antiga Esquerra de l'Eixample       41990   \n",
       "48                                la Barceloneta       14643   \n",
       "49                                    la Bordeta       19292   \n",
       "50                                      la Clota         689   \n",
       "51                        la Dreta de l'Eixample       44675   \n",
       "52                          la Font d'en Fargues        9458   \n",
       "53                         la Font de la Guatlla       10084   \n",
       "54                                  la Guineueta       15189   \n",
       "55                             la Marina de Port       30741   \n",
       "56                    la Marina del Prat Vermell        1350   \n",
       "57                    la Maternitat i Sant Ramon       23574   \n",
       "58                la Nova Esquerra de l'Eixample       57054   \n",
       "59                                la Prosperitat       26669   \n",
       "60                            la Sagrada Família       51319   \n",
       "61                                    la Sagrera       29351   \n",
       "62                                      la Salut       13282   \n",
       "63                                  la Teixonera       11926   \n",
       "64                              la Trinitat Nova        7507   \n",
       "65                             la Trinitat Vella       10364   \n",
       "66                              la Vall d'Hebron        5882   \n",
       "67                           la Verneda i la Pau       28585   \n",
       "68                 la Vila Olímpica del Poblenou        9240   \n",
       "69                             la Vila de Gràcia       49492   \n",
       "70                                     les Corts       45422   \n",
       "71                                  les Roquetes       16373   \n",
       "72                               les Tres Torres       16228   \n",
       "\n",
       "    residential_area_ha  net_density_hab_ha  \n",
       "0                   3.9                 673  \n",
       "1                  14.3                 645  \n",
       "2                   6.1                 359  \n",
       "3                  11.0                 620  \n",
       "4                  15.1                 729  \n",
       "5                  24.0                 556  \n",
       "6                  63.2                 439  \n",
       "7                  22.1                 717  \n",
       "8                  11.4                 447  \n",
       "9                  22.4                 984  \n",
       "10                 81.7                 142  \n",
       "11                 35.7                 768  \n",
       "12                 15.3                1368  \n",
       "13                 76.5                 758  \n",
       "14                 41.3                 921  \n",
       "15                 16.9                 430  \n",
       "16                 95.4                 491  \n",
       "17                 82.1                 313  \n",
       "18                 23.4                1111  \n",
       "19                 32.4                 683  \n",
       "20                 59.4                 726  \n",
       "21                 25.1                 980  \n",
       "22                 95.4                 256  \n",
       "23                 21.2                 136  \n",
       "24                  6.8                 204  \n",
       "25                 48.2                 335  \n",
       "26                242.0                  19  \n",
       "27                 14.2                 894  \n",
       "28                 29.3                 875  \n",
       "29                 23.7                1079  \n",
       "30                 34.1                 639  \n",
       "31                 28.1                 913  \n",
       "32                 17.8                 763  \n",
       "33                 38.5                 907  \n",
       "34                 42.9                 894  \n",
       "35                 39.4                 822  \n",
       "36                 23.4                1131  \n",
       "37                 12.4                 611  \n",
       "38                 19.1                 753  \n",
       "39                 33.6                 930  \n",
       "40                 52.0                 710  \n",
       "41                 22.3                 699  \n",
       "42                 38.1                1033  \n",
       "43                 45.0                 755  \n",
       "44                 53.1                 558  \n",
       "45                 49.6                 952  \n",
       "46                 13.3                1204  \n",
       "47                 66.9                 627  \n",
       "48                 13.5                1081  \n",
       "49                 20.8                 928  \n",
       "50                  6.1                 114  \n",
       "51                113.9                 392  \n",
       "52                 38.8                 244  \n",
       "53                 11.5                 873  \n",
       "54                 22.0                 689  \n",
       "55                 38.9                 789  \n",
       "56                 35.5                  38  \n",
       "57                 31.8                 741  \n",
       "58                 65.2                 876  \n",
       "59                 27.1                 985  \n",
       "60                 51.0                1007  \n",
       "61                 38.1                 770  \n",
       "62                 19.5                 680  \n",
       "63                 16.9                 707  \n",
       "64                 12.6                 598  \n",
       "65                 12.7                 817  \n",
       "66                  7.2                 813  \n",
       "67                 40.0                 714  \n",
       "68                 24.3                 380  \n",
       "69                 84.0                 589  \n",
       "70                 64.7                 702  \n",
       "71                 18.2                 897  \n",
       "72                 42.5                 382  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "133b9475",
   "metadata": {},
   "source": [
    "# Saving"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96d1ee4e",
   "metadata": {},
   "source": [
    "Now that we have the clean DataFrame ready for analysis, let's save it in CSV format to use it later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b43c5ae5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the cleaned DataFrame to a CSV file\n",
    "population_df.to_csv('population_df_cleaned.csv', index=False)"
   ]
  }
 ],
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