{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Extracting and analyzing data form `idescat.com`**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Requirements**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "pd.options.mode.chained_assignment = None \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from bs4 import BeautifulSoup\n",
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Maria's analysis in Catalonia**\n",
    "\n",
    "### **Extracting and processing the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "years = ['2018', '2019', '2020', '2021', '2022']\n",
    "Maria_abs_freq, Maria_total_position, Maria_girls_position, Maria_total_percent, Maria_girls_percent = [], [], [], [], []\n",
    "\n",
    "for year in years :\n",
    "\n",
    "    url = f'https://api.idescat.cat/onomastica/v1/nadons/dades.json?id=40683&t={year}&lang=es'\n",
    "    response = requests.get(url)\n",
    "    data_json = response.json() \n",
    "\n",
    "    Maria_abs_freq.append(data_json['onomastica_nadons']['ff']['f']['pos1']['v']) # abs freq name Maria over the names of childs born in Catalonia in {year}\n",
    "    Maria_total_position.append(data_json['onomastica_nadons']['ff']['f']['rank']['total']) # rank of name Maria over the names of childs born in Catalonia in {year}\n",
    "    Maria_girls_position.append(data_json['onomastica_nadons']['ff']['f']['rank']['sex']) # rank of name Maria over the names of girls born in Catalonia in {year}\n",
    "    Maria_total_percent.append(data_json['onomastica_nadons']['ff']['f']['pos1']['w']['total']) # % of childs born in Catalonia in {year} whose name is Maria\n",
    "    Maria_girls_percent.append(data_json['onomastica_nadons']['ff']['f']['pos1']['w']['sex'])  # % of girls born in Catalonia in {year} whose name is Maria\n",
    "\n",
    "Maria_dict = dict()\n",
    "Maria_dict['years'] = years\n",
    "Maria_dict['Maria_abs_freq'] = Maria_abs_freq\n",
    "Maria_dict['Maria_total_position'] = Maria_total_position\n",
    "Maria_dict['Maria_girls_position'] = Maria_girls_position\n",
    "Maria_dict['Maria_total_percent'] = Maria_total_percent\n",
    "Maria_dict['Maria_girls_percent'] = Maria_girls_percent\n",
    "\n",
    "Maria_df = pd.DataFrame(Maria_dict)\n",
    "\n",
    "for col_name in Maria_df.columns :\n",
    "    if col_name in ['Maria_abs_freq', 'Maria_total_position', 'Maria_girls_position'] :\n",
    "        Maria_df[col_name] = Maria_df[col_name].astype('int64')\n",
    "    elif col_name in ['Maria_total_percent', 'Maria_girls_percent'] :\n",
    "        Maria_df[col_name] = Maria_df[col_name].astype('float64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maria's analysis in Catalonia\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>466</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>7.38</td>\n",
       "      <td>15.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>387</td>\n",
       "      <td>13</td>\n",
       "      <td>6</td>\n",
       "      <td>6.36</td>\n",
       "      <td>13.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>318</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>5.49</td>\n",
       "      <td>11.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>327</td>\n",
       "      <td>19</td>\n",
       "      <td>8</td>\n",
       "      <td>5.67</td>\n",
       "      <td>11.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>267</td>\n",
       "      <td>28</td>\n",
       "      <td>13</td>\n",
       "      <td>4.74</td>\n",
       "      <td>9.83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years  Maria_abs_freq  Maria_total_position  Maria_girls_position  \\\n",
       "0  2018             466                     8                     4   \n",
       "1  2019             387                    13                     6   \n",
       "2  2020             318                    20                    10   \n",
       "3  2021             327                    19                     8   \n",
       "4  2022             267                    28                    13   \n",
       "\n",
       "   Maria_total_percent  Maria_girls_percent  \n",
       "0                 7.38                15.15  \n",
       "1                 6.36                13.00  \n",
       "2                 5.49                11.23  \n",
       "3                 5.67                11.65  \n",
       "4                 4.74                 9.83  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data-frame with the data\n",
    "\n",
    "print('Maria\\'s analysis in Catalonia\\n')\n",
    "display(Maria_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plotting the results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_columns = [x for x in Maria_df.columns if x != 'years']\n",
    "titles = [\"Absolute Frequencies Maria in Catalonia\", \"Ranking: Maria total position in Catalonia\",\n",
    "          \"Ranking: Maria girls position in Catalonia\", \"Maria total % in Catalonia\", \"Maria girls % in Catalonia\"]\n",
    "\n",
    "# Define the number of rows and columns for the matrix plot\n",
    "num_cols = 2  # You can adjust the number of columns as needed\n",
    "num_rows = int(np.ceil(len(selected_columns) / num_cols))\n",
    "\n",
    "# Create a subplot with the specified number of rows and columns\n",
    "fig, axes = plt.subplots(num_rows, num_cols, figsize=(12, 10))\n",
    "\n",
    "# Flatten the axes array to make it easier to iterate\n",
    "axes = axes.flatten()\n",
    "\n",
    "colors = sns.color_palette(\"tab10\", len(selected_columns))\n",
    "\n",
    "# Loop through each 'geo' and create a subplot in the matrix\n",
    "for (i, col_name), color, title in zip(enumerate(selected_columns), colors, titles) :\n",
    "    ax = axes[i]  # Get the current axis\n",
    "    sns.barplot(x=\"years\", y=col_name, data=Maria_df, color=color, ax=ax)\n",
    "    ax.set_title(f\"{title}\", fontsize=13)\n",
    "    xticks_index = np.arange(0, len(Maria_df), 1)\n",
    "    ax.set_xticks(xticks_index)\n",
    "    ax.tick_params(axis='x', rotation=0)\n",
    "    ax.set_xlabel('Year')\n",
    "    ax.set_ylabel('')\n",
    "\n",
    "# Remove any unused subplots in case the number of 'geo' values is less than num_rows * num_cols\n",
    "for j in range(len(selected_columns), num_rows * num_cols):\n",
    "    fig.delaxes(axes[j])\n",
    "\n",
    "plt.suptitle('Maria\\'s born in Catalonia - Statistical information\\n Last five years (2018-2022)', fontsize=15, y=0.98, weight='bold') # Establishing a general tittle for the plot.\n",
    "plt.subplots_adjust(hspace=0.5, wspace=0.25) # Adjust vertical (hspace) and horizontal (wspace) spacing\n",
    "fig.savefig('Marias_Catalonia' + '.jpg', format='jpg', dpi=550)\n",
    "# plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Maria's analysis in Catalonia by city (comarca)**\n",
    "\n",
    "### **Extracting and processing the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maria's analysis in Catalonia by city (comarca)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Maria\\'s analysis in Catalonia by city (comarca)\\n')\n",
    "\n",
    "years = ['2018', '2019', '2020', '2021', '2022']\n",
    "Maria_df_dict = dict()\n",
    "\n",
    "for com_id in range(0, 42): # 42 = len(data_json['onomastica_nadons']['ff']['f']) - 1\n",
    "\n",
    "    Maria_abs_freq, Maria_total_position, Maria_girls_position, Maria_total_percent, Maria_girls_percent = [], [], [], [], []\n",
    "\n",
    "    for year in years :\n",
    "\n",
    "        url = f'https://api.idescat.cat/onomastica/v1/nadons/dades.json?id=40683&class=com&t={year}&lang=es'\n",
    "        response = requests.get(url)\n",
    "        data_json = response.json() \n",
    "\n",
    "        Maria_abs_freq.append(data_json['onomastica_nadons']['ff']['f'][com_id]['pos1']['v']) # abs freq name Maria over the names of childs born in comarca {com_id} in {year}\n",
    "        Maria_total_position.append(data_json['onomastica_nadons']['ff']['f'][com_id]['rank']['total']) # rank of name Maria over the names of childs born in comarca {com_id} in {year}\n",
    "        Maria_girls_position.append(data_json['onomastica_nadons']['ff']['f'][com_id]['rank']['sex']) # rank of name Maria over the names of girls born in comarca {com_id} in {year}\n",
    "        Maria_total_percent.append(data_json['onomastica_nadons']['ff']['f'][com_id]['pos1']['w']['total']) # % of childs born in comarca {com_id} in {year} whose name is Maria\n",
    "        Maria_girls_percent.append(data_json['onomastica_nadons']['ff']['f'][com_id]['pos1']['w']['sex'])  # % of girls born in comarca {com_id} in {year} whose name is Maria\n",
    "\n",
    "    Maria_dict = dict()\n",
    "    Maria_dict['years'] = years\n",
    "    Maria_dict['Maria_abs_freq'] = Maria_abs_freq\n",
    "    Maria_dict['Maria_total_position'] = Maria_total_position\n",
    "    Maria_dict['Maria_girls_position'] = Maria_girls_position\n",
    "    Maria_dict['Maria_total_percent'] = Maria_total_percent\n",
    "    Maria_dict['Maria_girls_percent'] = Maria_girls_percent  \n",
    "    com = data_json['onomastica_nadons']['ff']['f'][com_id]['c']['content']\n",
    "    Maria_df_dict[com] = pd.DataFrame(Maria_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Catalonia city (comarca) with more Maria's born in 2018 --> Barcelonès\n",
      "Catalonia city (comarca) with more Maria's born in 2019 --> Barcelonès\n",
      "Catalonia city (comarca) with more Maria's born in 2020 --> Barcelonès\n",
      "Catalonia city (comarca) with more Maria's born in 2021 --> Barcelonès\n",
      "Catalonia city (comarca) with more Maria's born in 2022 --> Barcelonès\n"
     ]
    }
   ],
   "source": [
    "###  Catalonia city (comarca) with more Maria\\'s born by year\n",
    "\n",
    "Maria_abs_freq_year = dict()\n",
    "\n",
    "for year in ['2018', '2019', '2020', '2021', '2022']  :\n",
    "\n",
    "    Maria_abs_freq_city = dict()\n",
    "\n",
    "    for com in Maria_df_dict.keys() :\n",
    "\n",
    "        value =  Maria_df_dict[com].loc[Maria_df_dict[com]['years'] == year, 'Maria_abs_freq'].iloc[0]\n",
    "\n",
    "        if value != '_' : # To avoid the cities with missing value.\n",
    "        \n",
    "            Maria_abs_freq_city[com] = value\n",
    "\n",
    "    Maria_abs_freq_year[year] = Maria_abs_freq_city\n",
    "\n",
    "\n",
    "Maria_abs_freq_values = dict()\n",
    "Maria_abs_freq_index = dict()\n",
    "city_max_Maria = dict()\n",
    "years =  ['2018', '2019', '2020', '2021', '2022'] \n",
    "\n",
    "for year in years :\n",
    "\n",
    "    Maria_abs_freq_values[year] = np.array([x for x in Maria_abs_freq_year[year].values()], dtype=int)\n",
    "    Maria_abs_freq_index[year] = np.array([x for x in Maria_abs_freq_year[year].keys()])\n",
    "    city_max_Maria[year] = Maria_abs_freq_index[year][np.argmax(Maria_abs_freq_values[year])]\n",
    "    print(f'Catalonia city (comarca) with more Maria\\'s born in {year} -->', city_max_Maria[year])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plotting the results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1300 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the number of rows and columns for the matrix plot\n",
    "num_cols = 3  # You can adjust the number of columns as needed\n",
    "num_rows = int(np.ceil(len(years) / num_cols))\n",
    "\n",
    "# Create a subplot with the specified number of rows and columns\n",
    "fig, axes = plt.subplots(num_rows, num_cols, figsize=(12, 13))\n",
    "\n",
    "# Flatten the axes array to make it easier to iterate\n",
    "axes = axes.flatten()\n",
    "\n",
    "colors = sns.color_palette(\"tab10\", len(years))\n",
    "\n",
    "# Loop through each 'geo' and create a subplot in the matrix\n",
    "for i, color, year in zip(range(0,len(years)), colors, years) :\n",
    "\n",
    "    ax = axes[i]  # Get the current axis\n",
    "    sns.barplot(x=Maria_abs_freq_values[year], y=Maria_abs_freq_index[year], color=color, ax=ax)\n",
    "    ax.set_title(f\"{year}\", fontsize=13)\n",
    "    ax.tick_params(axis='x', rotation=0)\n",
    "    ax.set_xlabel('Count')\n",
    "    ax.set_ylabel('Cities')\n",
    "\n",
    "# Remove any unused subplots in case the number of 'geo' values is less than num_rows * num_cols\n",
    "for j in range(len(years), num_rows * num_cols):\n",
    "    fig.delaxes(axes[j])\n",
    "\n",
    "plt.suptitle('Absolute Frequencies Maria by Catalonia cities (comarcas)\\n Last five years (2018-2022)', fontsize=15, y=0.95, weight='bold') # Establishing a general tittle for the plot.\n",
    "plt.subplots_adjust(hspace=0.25, wspace=0.8) # Adjust vertical (hspace) and horizontal (wspace) spacing\n",
    "# fig.savefig('Marias_Areas_Catalonia' + '.jpg', format='jpg', dpi=550)\n",
    "# plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Gender info for the childs born in Catalonia in the last nine years (2014-2022)**\n",
    "\n",
    "### **Extracting and processing the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def try_float(x):   \n",
    "    try:\n",
    "        return float(x)\n",
    "    except ValueError:\n",
    "        return None\n",
    "\n",
    "url = 'https://www.idescat.cat/indicadors/?id=aec&n=15237&fil=43&lang=en'\n",
    "response = requests.get(url)\n",
    "soup = BeautifulSoup(response.text, 'html.parser')\n",
    "\n",
    "table = soup.find('table')\n",
    "\n",
    "columns = table.find(class_=\"cap\") \n",
    "columns_html = columns.select(\"thead th\")\n",
    "columns_list = []\n",
    "\n",
    "for i in range(1,len(columns_html)) :\n",
    "    columns_list.append(columns.select(\"thead th\")[i].text)\n",
    "\n",
    "columns_list = ['Year'] + columns_list\n",
    "tr_list = table.select('tr')\n",
    "useful_info_index = range(1,(len(tr_list)-3))\n",
    "\n",
    "rows = dict()\n",
    "for i , r in enumerate(useful_info_index) :\n",
    "    text_data = tr_list[r].text\n",
    "    row_data = text_data.replace('\\n', ' ').split()\n",
    "    row_data = [x.replace(',', '.') for x in row_data]\n",
    "    row_data = [try_float(x) for x in row_data]\n",
    "    row_data = [x for x in row_data if x != None]\n",
    "    rows[i] = row_data\n",
    "\n",
    "df = pd.DataFrame(rows)\n",
    "df = df.T\n",
    "df.columns = columns_list\n",
    "df['Year'] = df['Year'].astype('int')\n",
    "df['Boys_prop'] = round(df['Boys'] / df['Total'], 3)\n",
    "df['Girls_prop'] = round(df['Girls'] / df['Total'], 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gender info for the childs born in Catalonia in the last nine years (2014-2022)\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Boys</th>\n",
       "      <th>Girls</th>\n",
       "      <th>Total</th>\n",
       "      <th>Boys_prop</th>\n",
       "      <th>Girls_prop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>29.187</td>\n",
       "      <td>27.195</td>\n",
       "      <td>56.382</td>\n",
       "      <td>0.518</td>\n",
       "      <td>0.482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021</td>\n",
       "      <td>29.604</td>\n",
       "      <td>28.030</td>\n",
       "      <td>57.634</td>\n",
       "      <td>0.514</td>\n",
       "      <td>0.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>29.832</td>\n",
       "      <td>28.632</td>\n",
       "      <td>58.464</td>\n",
       "      <td>0.510</td>\n",
       "      <td>0.490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019</td>\n",
       "      <td>31.453</td>\n",
       "      <td>30.095</td>\n",
       "      <td>61.548</td>\n",
       "      <td>0.511</td>\n",
       "      <td>0.489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>32.623</td>\n",
       "      <td>30.943</td>\n",
       "      <td>63.566</td>\n",
       "      <td>0.513</td>\n",
       "      <td>0.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2017</td>\n",
       "      <td>34.462</td>\n",
       "      <td>32.341</td>\n",
       "      <td>66.803</td>\n",
       "      <td>0.516</td>\n",
       "      <td>0.484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016</td>\n",
       "      <td>35.435</td>\n",
       "      <td>33.539</td>\n",
       "      <td>68.974</td>\n",
       "      <td>0.514</td>\n",
       "      <td>0.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015</td>\n",
       "      <td>36.406</td>\n",
       "      <td>34.044</td>\n",
       "      <td>70.450</td>\n",
       "      <td>0.517</td>\n",
       "      <td>0.483</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year    Boys   Girls   Total  Boys_prop  Girls_prop\n",
       "0  2022  29.187  27.195  56.382      0.518       0.482\n",
       "1  2021  29.604  28.030  57.634      0.514       0.486\n",
       "2  2020  29.832  28.632  58.464      0.510       0.490\n",
       "3  2019  31.453  30.095  61.548      0.511       0.489\n",
       "4  2018  32.623  30.943  63.566      0.513       0.487\n",
       "5  2017  34.462  32.341  66.803      0.516       0.484\n",
       "6  2016  35.435  33.539  68.974      0.514       0.486\n",
       "7  2015  36.406  34.044  70.450      0.517       0.483"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data-frame with the data\n",
    "\n",
    "print('Gender info for the childs born in Catalonia in the last nine years (2014-2022)\\n')\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plotting the results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_columns = [x for x in df.columns if x in ['Boys_prop', 'Girls_prop']]\n",
    "\n",
    "# Define the number of rows and columns for the matrix plot\n",
    "num_cols = 2  # You can adjust the number of columns as needed\n",
    "num_rows = int(np.ceil(len(selected_columns) / num_cols))\n",
    "\n",
    "# Create a subplot with the specified number of rows and columns\n",
    "fig, axes = plt.subplots(num_rows, num_cols, figsize=(8, 3))\n",
    "\n",
    "# Flatten the axes array to make it easier to iterate\n",
    "axes = axes.flatten()\n",
    "\n",
    "colors = sns.color_palette(\"tab10\", len(selected_columns))\n",
    "titles = ['Girls', 'Boys']\n",
    "\n",
    "# Loop through each 'geo' and create a subplot in the matrix\n",
    "for i, color, col_name, title in zip(range(0,len(selected_columns)), colors, selected_columns, titles) :\n",
    "    ax = axes[i]  # Get the current axis\n",
    "    sns.barplot(x=\"Year\", y=col_name, data=df, color=color, ax=ax)\n",
    "    ax.set_title(f\"{title}\", fontsize=11)\n",
    "    xticks_index = np.arange(0, len(df), 1)\n",
    "    ax.set_xticks(xticks_index)\n",
    "    ax.tick_params(axis='x', rotation=0, labelsize=9)\n",
    "    ax.tick_params(axis='y', rotation=0, labelsize=9)\n",
    "    ax.set_xlabel('Year')\n",
    "    ax.set_ylabel(' ')\n",
    "    ax.set_ylim([0.45, 0.54])\n",
    "\n",
    "# Remove any unused subplots in case the number of 'geo' values is less than num_rows * num_cols\n",
    "for j in range(len(selected_columns), num_rows * num_cols):\n",
    "    fig.delaxes(axes[j])\n",
    "\n",
    "plt.suptitle('Relative frequencies of the gender of childs born in Catalonia\\n Last nine years (2014-2022)', fontsize=12, y=1.1, weight='bold') # Establishing a general tittle for the plot.\n",
    "plt.subplots_adjust(hspace=0.6, wspace=0.3) # Adjust vertical (hspace) and horizontal (wspace) spacing\n",
    "# fig.savefig('Gender_born_Catalonia' + '.jpg', format='jpg', dpi=550)\n",
    "# plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Maria's analysis in Catalonia by province**\n",
    "\n",
    "### **Extracting and processing the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "years = ['2018', '2019', '2020', '2021', '2022']\n",
    "Maria_df_dict = dict()\n",
    "\n",
    "for prov_id in range(0, 4): # 4 = len(data_json['onomastica_nadons']['ff']['f']) - 1\n",
    "\n",
    "    Maria_abs_freq, Maria_total_position, Maria_girls_position, Maria_total_percent, Maria_girls_percent = [], [], [], [], []\n",
    "\n",
    "    for year in years :\n",
    "\n",
    "        url = f'https://api.idescat.cat/onomastica/v1/nadons/dades.json?id=40683&class=prov&t={year}&lang=es'\n",
    "        response = requests.get(url)\n",
    "        data_json = response.json() \n",
    "\n",
    "        Maria_abs_freq.append(data_json['onomastica_nadons']['ff']['f'][prov_id]['pos1']['v']) # abs freq name Maria over the names of childs born in province {prov_id} in {year}\n",
    "        Maria_total_position.append(data_json['onomastica_nadons']['ff']['f'][prov_id]['rank']['total']) # rank of name Maria over the names of childs born in province {prov_id} in {year}\n",
    "        Maria_girls_position.append(data_json['onomastica_nadons']['ff']['f'][prov_id]['rank']['sex']) # rank of name Maria over the names of girls born in province {prov_id} in {year}\n",
    "        Maria_total_percent.append(data_json['onomastica_nadons']['ff']['f'][prov_id]['pos1']['w']['total']) # % of childs born in province {prov_id} in {year} whose name is Maria\n",
    "        Maria_girls_percent.append(data_json['onomastica_nadons']['ff']['f'][prov_id]['pos1']['w']['sex'])  # % of girls born in province {prov_id} in {year} whose name is Maria\n",
    "\n",
    "    Maria_dict = dict()\n",
    "    Maria_dict['years'] = years\n",
    "    Maria_dict['Maria_abs_freq'] = Maria_abs_freq\n",
    "    Maria_dict['Maria_total_position'] = Maria_total_position\n",
    "    Maria_dict['Maria_girls_position'] = Maria_girls_position\n",
    "    Maria_dict['Maria_total_percent'] = Maria_total_percent\n",
    "    Maria_dict['Maria_girls_percent'] = Maria_girls_percent  \n",
    "    prov = data_json['onomastica_nadons']['ff']['f'][prov_id]['c']['content']\n",
    "    Maria_df_dict[prov] = pd.DataFrame(Maria_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maria's analysis in Catalonia by province\n",
      "-----------------------------------------------------------------------------------------------\n",
      "Barcelona\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>344</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>7.41</td>\n",
       "      <td>15.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>288</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>6.46</td>\n",
       "      <td>13.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>245</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>5.81</td>\n",
       "      <td>11.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>189</td>\n",
       "      <td>33</td>\n",
       "      <td>14</td>\n",
       "      <td>4.59</td>\n",
       "      <td>9.56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018            344                   11                    5   \n",
       "1  2019            288                   14                    7   \n",
       "2  2020            245                   19                    9   \n",
       "3  2021              _                    _                    _   \n",
       "4  2022            189                   33                   14   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                7.41               15.19  \n",
       "1                6.46               13.17  \n",
       "2                5.81               11.89  \n",
       "3                   _                   _  \n",
       "4                4.59                9.56  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Girona\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>47</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>7.00</td>\n",
       "      <td>14.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>27</td>\n",
       "      <td>31</td>\n",
       "      <td>16</td>\n",
       "      <td>4.21</td>\n",
       "      <td>8.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>33</td>\n",
       "      <td>21</td>\n",
       "      <td>11</td>\n",
       "      <td>5.24</td>\n",
       "      <td>10.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>37</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>6.10</td>\n",
       "      <td>12.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>19</td>\n",
       "      <td>47</td>\n",
       "      <td>22</td>\n",
       "      <td>3.21</td>\n",
       "      <td>6.52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             47                    6                    2   \n",
       "1  2019             27                   31                   16   \n",
       "2  2020             33                   21                   11   \n",
       "3  2021             37                   12                    5   \n",
       "4  2022             19                   47                   22   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                7.00               14.43  \n",
       "1                4.21                8.62  \n",
       "2                5.24               10.79  \n",
       "3                6.10               12.45  \n",
       "4                3.21                6.52  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Lleida\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "      <td>13</td>\n",
       "      <td>4.89</td>\n",
       "      <td>10.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>23</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>6.69</td>\n",
       "      <td>13.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>69</td>\n",
       "      <td>38</td>\n",
       "      <td>2.44</td>\n",
       "      <td>4.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>17</td>\n",
       "      <td>19</td>\n",
       "      <td>7</td>\n",
       "      <td>5.30</td>\n",
       "      <td>11.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>5.89</td>\n",
       "      <td>12.22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             17                   28                   13   \n",
       "1  2019             23                    8                    3   \n",
       "2  2020              8                   69                   38   \n",
       "3  2021             17                   19                    7   \n",
       "4  2022             19                   15                    7   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                4.89               10.15  \n",
       "1                6.69               13.71  \n",
       "2                2.44                4.84  \n",
       "3                5.30               11.06  \n",
       "4                5.89               12.22  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Tarragona\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>58</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>8.81</td>\n",
       "      <td>18.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>49</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>7.60</td>\n",
       "      <td>15.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>32</td>\n",
       "      <td>19</td>\n",
       "      <td>8</td>\n",
       "      <td>5.23</td>\n",
       "      <td>10.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>12</td>\n",
       "      <td>5.00</td>\n",
       "      <td>10.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>6.66</td>\n",
       "      <td>13.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             58                    4                    2   \n",
       "1  2019             49                    6                    4   \n",
       "2  2020             32                   19                    8   \n",
       "3  2021             30                   26                   12   \n",
       "4  2022             40                   10                    5   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                8.81               18.22  \n",
       "1                7.60               15.85  \n",
       "2                5.23               10.62  \n",
       "3                5.00               10.33  \n",
       "4                6.66               13.70  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Maria\\'s analysis in Catalonia by province')\n",
    "\n",
    "for prov in Maria_df_dict.keys():\n",
    "    print('-----------------------------------------------------------------------------------------------')\n",
    "    print(prov)\n",
    "    display(Maria_df_dict[prov])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Catalonia province with more Maria's born in 2022 --> Barcelona\n"
     ]
    }
   ],
   "source": [
    "# Catalonia province with more Maria's born in 2022\n",
    "\n",
    "Maria_abs_freq_2022 = dict()\n",
    "\n",
    "for prov in Maria_df_dict.keys():\n",
    "    Maria_abs_freq_2022[prov] = Maria_df_dict[prov].loc[Maria_df_dict[prov]['years'] == '2022', 'Maria_abs_freq'].iloc[0]\n",
    "\n",
    "Maria_abs_freq_2022_values = np.array([x for x in Maria_abs_freq_2022.values()], dtype=int)\n",
    "Maria_abs_freq_2022_index = np.array([x for x in Maria_abs_freq_2022.keys()])\n",
    "prov_max_Maria_2022 = Maria_abs_freq_2022_index[np.argmax(Maria_abs_freq_2022_values)]\n",
    "print('Catalonia province with more Maria\\'s born in 2022 -->', prov_max_Maria_2022)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plotting the results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Maria_df_dict['Barcelona'] = Maria_df_dict['Barcelona'].drop([3], axis=0)\n",
    "\n",
    "for prov in Maria_df_dict.keys() :\n",
    "    for col_name in Maria_df_dict[prov].columns :\n",
    "        if col_name in ['Maria_abs_freq', 'Maria_total_position', 'Maria_girls_position'] :\n",
    "            Maria_df_dict[prov][col_name] = Maria_df_dict[prov][col_name].astype('int64')\n",
    "        elif col_name in ['Maria_total_percent', 'Maria_girls_percent'] :\n",
    "            Maria_df_dict[prov][col_name] = Maria_df_dict[prov][col_name].astype('float64')\n",
    "\n",
    "provinces = Maria_df_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the number of rows and columns for the matrix plot\n",
    "num_cols = 2  # You can adjust the number of columns as needed\n",
    "num_rows = int(np.ceil(len(provinces) / num_cols))\n",
    "\n",
    "# Create a subplot with the specified number of rows and columns\n",
    "fig, axes = plt.subplots(num_rows, num_cols, figsize=(10, 8))\n",
    "\n",
    "# Flatten the axes array to make it easier to iterate\n",
    "axes = axes.flatten()\n",
    "\n",
    "colors = sns.color_palette(\"tab10\", len(provinces))\n",
    "\n",
    "# Loop through each 'geo' and create a subplot in the matrix\n",
    "for i, color, prov in zip(range(0,len(provinces)), colors, provinces) :\n",
    "    ax = axes[i]  # Get the current axis\n",
    "    sns.barplot(x=\"years\", y='Maria_abs_freq', data=Maria_df_dict[prov], color=color, ax=ax)\n",
    "    ax.set_title(f\"{prov}\", fontsize=12)\n",
    "    xticks_index = np.arange(0, len(Maria_df_dict[prov]), 1)\n",
    "    ax.set_xticks(xticks_index)\n",
    "    ax.tick_params(axis='x', rotation=0)\n",
    "    ax.set_xlabel('Year')\n",
    "    ax.set_ylabel('Count')\n",
    "\n",
    "# Remove any unused subplots in case the number of 'geo' values is less than num_rows * num_cols\n",
    "for j in range(len(provinces), num_rows * num_cols):\n",
    "    fig.delaxes(axes[j])\n",
    "\n",
    "plt.suptitle('Absolute Frequencies Maria by Catalonia provinces\\n Last five years (2018-2022)', fontsize=15, y=0.98, weight='bold') # Establishing a general tittle for the plot.\n",
    "plt.subplots_adjust(hspace=0.3, wspace=0.3) # Adjust vertical (hspace) and horizontal (wspace) spacing\n",
    "# fig.savefig('Marias_Provinces_Catalonia' + '.jpg', format='jpg', dpi=550)\n",
    "# plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Maria's analysis in Catalonia by area (region)**\n",
    "\n",
    "### **Extracting and processing the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "years = ['2018', '2019', '2020', '2021', '2022']\n",
    "Maria_df_dict = dict()\n",
    "\n",
    "for at_id in range(0, 8): # 8 = len(data_json['onomastica_nadons']['ff']['f']) - 1\n",
    "\n",
    "    Maria_abs_freq, Maria_total_position, Maria_girls_position, Maria_total_percent, Maria_girls_percent = [], [], [], [], []\n",
    "\n",
    "    for year in years :\n",
    "\n",
    "        url = f'https://api.idescat.cat/onomastica/v1/nadons/dades.json?id=40683&class=at&t={year}&lang=es'\n",
    "        response = requests.get(url)\n",
    "        data_json = response.json() \n",
    "\n",
    "        Maria_abs_freq.append(data_json['onomastica_nadons']['ff']['f'][at_id]['pos1']['v']) # abs freq name Maria over the names of childs born in comarca {com_id} in {year}\n",
    "        Maria_total_position.append(data_json['onomastica_nadons']['ff']['f'][at_id]['rank']['total']) # rank of name Maria over the names of childs born in comarca {com_id} in {year}\n",
    "        Maria_girls_position.append(data_json['onomastica_nadons']['ff']['f'][at_id]['rank']['sex']) # rank of name Maria over the names of girls born in comarca {com_id} in {year}\n",
    "        Maria_total_percent.append(data_json['onomastica_nadons']['ff']['f'][at_id]['pos1']['w']['total']) # % of childs born in comarca {com_id} in {year} whose name is Maria\n",
    "        Maria_girls_percent.append(data_json['onomastica_nadons']['ff']['f'][at_id]['pos1']['w']['sex'])  # % of girls born in comarca {com_id} in {year} whose name is Maria\n",
    "\n",
    "    Maria_dict = dict()\n",
    "    Maria_dict['years'] = years\n",
    "    Maria_dict['Maria_abs_freq'] = Maria_abs_freq\n",
    "    Maria_dict['Maria_total_position'] = Maria_total_position\n",
    "    Maria_dict['Maria_girls_position'] = Maria_girls_position\n",
    "    Maria_dict['Maria_total_percent'] = Maria_total_percent\n",
    "    Maria_dict['Maria_girls_percent'] = Maria_girls_percent  \n",
    "    at = data_json['onomastica_nadons']['ff']['f'][at_id]['c']['content']\n",
    "    Maria_df_dict[at] = pd.DataFrame(Maria_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maria's analysis in Catalonia by area (region)\n",
      "-----------------------------------------------------------------------------------------------\n",
      "Metropolità\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>308</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>7.67</td>\n",
       "      <td>15.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>246</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>6.38</td>\n",
       "      <td>13.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>210</td>\n",
       "      <td>22</td>\n",
       "      <td>10</td>\n",
       "      <td>5.77</td>\n",
       "      <td>11.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>211</td>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>5.77</td>\n",
       "      <td>11.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>164</td>\n",
       "      <td>30</td>\n",
       "      <td>13</td>\n",
       "      <td>4.63</td>\n",
       "      <td>9.63</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018            308                   10                    5   \n",
       "1  2019            246                   15                    7   \n",
       "2  2020            210                   22                   10   \n",
       "3  2021            211                   20                    8   \n",
       "4  2022            164                   30                   13   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                7.67               15.66  \n",
       "1                6.38               13.01  \n",
       "2                5.77               11.80  \n",
       "3                5.77               11.86  \n",
       "4                4.63                9.63  "
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     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Comarques Gironines\n"
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       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             47                    6                    2   \n",
       "1  2019             27                   31                   16   \n",
       "2  2020             33                   21                   11   \n",
       "3  2021             37                   12                    5   \n",
       "4  2022             19                   44                   20   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                7.11               14.67  \n",
       "1                4.29                8.77  \n",
       "2                5.30               10.90  \n",
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     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Camp de Tarragona\n"
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       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             39                    5                    3   \n",
       "1  2019             35                    3                    2   \n",
       "2  2020             18                   28                   13   \n",
       "3  2021             17                   37                   18   \n",
       "4  2022             30                    5                    3   \n",
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       "0                8.72               18.03  \n",
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     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Terres de l'Ebre\n"
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       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             14                    7                    4   \n",
       "1  2019             11                    9                    6   \n",
       "2  2020              5                   30                   16   \n",
       "3  2021             10                   12                    6   \n",
       "4  2022              5                   37                   15   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0               10.52               21.41  \n",
       "1                8.12               16.69  \n",
       "2                4.13                8.17  \n",
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       "4                4.00                8.35  "
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      "-----------------------------------------------------------------------------------------------\n",
      "Ponent\n"
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       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             14                   31                   13   \n",
       "1  2019             20                    7                    4   \n",
       "2  2020              7                   68                   34   \n",
       "3  2021             16                   15                    5   \n",
       "4  2022             16                   15                    8   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                4.65                9.60  \n",
       "1                6.78               13.93  \n",
       "2                2.46                4.87  \n",
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       "4                5.71               11.85  "
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      "-----------------------------------------------------------------------------------------------\n",
      "Comarques Centrals\n"
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       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             22                   18                    8   \n",
       "1  2019             29                    7                    2   \n",
       "2  2020             17                   19                    7   \n",
       "3  2021             17                   23                   11   \n",
       "4  2022             17                   22                    9   \n",
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       "0                6.46               13.56  \n",
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      "-----------------------------------------------------------------------------------------------\n",
      "Alt Pirineu i Aran\n"
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       "      <td>_</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>0</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "      <td>_</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018              _                    _                    _   \n",
       "1  2019              _                    _                    _   \n",
       "2  2020              _                    _                    _   \n",
       "3  2021              0                    _                    _   \n",
       "4  2022              _                    _                    _   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                   _                   _  \n",
       "1                   _                   _  \n",
       "2                   _                   _  \n",
       "3                0.00                0.00  \n",
       "4                   _                   _  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "Penedès\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>Maria_abs_freq</th>\n",
       "      <th>Maria_total_position</th>\n",
       "      <th>Maria_girls_position</th>\n",
       "      <th>Maria_total_percent</th>\n",
       "      <th>Maria_girls_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>20</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>5.38</td>\n",
       "      <td>11.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>18</td>\n",
       "      <td>24</td>\n",
       "      <td>12</td>\n",
       "      <td>4.85</td>\n",
       "      <td>9.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>7.59</td>\n",
       "      <td>15.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>16</td>\n",
       "      <td>38</td>\n",
       "      <td>16</td>\n",
       "      <td>4.32</td>\n",
       "      <td>9.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>15</td>\n",
       "      <td>38</td>\n",
       "      <td>18</td>\n",
       "      <td>4.26</td>\n",
       "      <td>8.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  years Maria_abs_freq Maria_total_position Maria_girls_position  \\\n",
       "0  2018             20                   23                   12   \n",
       "1  2019             18                   24                   12   \n",
       "2  2020             27                    4                    3   \n",
       "3  2021             16                   38                   16   \n",
       "4  2022             15                   38                   18   \n",
       "\n",
       "  Maria_total_percent Maria_girls_percent  \n",
       "0                5.38               11.22  \n",
       "1                4.85                9.91  \n",
       "2                7.59               15.86  \n",
       "3                4.32                9.09  \n",
       "4                4.26                8.87  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Maria\\'s analysis in Catalonia by area (region)')\n",
    "\n",
    "for at in Maria_df_dict.keys():\n",
    "    print('-----------------------------------------------------------------------------------------------')\n",
    "    print(at)\n",
    "    display(Maria_df_dict[at])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Catalonia area with more Maria's born in 2022 --> Metropolità\n"
     ]
    }
   ],
   "source": [
    "# Catalonia region with more Maria\\'s born in 2022\n",
    "\n",
    "selected_at = [x for x in Maria_df_dict.keys() if x != 'Alt Pirineu i Aran']\n",
    "Maria_abs_freq_2022 = dict()\n",
    "\n",
    "for at in selected_at :\n",
    "    Maria_abs_freq_2022[at] = Maria_df_dict[at].loc[Maria_df_dict[at]['years'] == '2022', 'Maria_abs_freq'].iloc[0]\n",
    "\n",
    "Maria_abs_freq_2022_values = np.array([x for x in Maria_abs_freq_2022.values()], dtype=int)\n",
    "Maria_abs_freq_2022_index = np.array([x for x in Maria_abs_freq_2022.keys()])\n",
    "prov_max_Maria_2022 = Maria_abs_freq_2022_index[np.argmax(Maria_abs_freq_2022_values)]\n",
    "print('Catalonia area with more Maria\\'s born in 2022 -->', prov_max_Maria_2022)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plotting the results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x1000 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for at in selected_at :\n",
    "    for col_name in Maria_df_dict[at].columns :\n",
    "        if col_name in ['Maria_abs_freq', 'Maria_total_position', 'Maria_girls_position'] :\n",
    "            Maria_df_dict[at][col_name] = Maria_df_dict[at][col_name].astype('int64')\n",
    "        elif col_name in ['Maria_total_percent', 'Maria_girls_percent'] :\n",
    "            Maria_df_dict[at][col_name] = Maria_df_dict[at][col_name].astype('float64')\n",
    "\n",
    "# Define the number of rows and columns for the matrix plot\n",
    "num_cols = 2  # You can adjust the number of columns as needed\n",
    "num_rows = int(np.ceil(len(selected_at) / num_cols))\n",
    "\n",
    "# Create a subplot with the specified number of rows and columns\n",
    "fig, axes = plt.subplots(num_rows, num_cols, figsize=(11, 10))\n",
    "\n",
    "# Flatten the axes array to make it easier to iterate\n",
    "axes = axes.flatten()\n",
    "\n",
    "colors = sns.color_palette(\"tab10\", len(selected_at))\n",
    "\n",
    "# Loop through each 'geo' and create a subplot in the matrix\n",
    "for i, color, at in zip(range(0,len(selected_at)), colors, selected_at) :\n",
    "    ax = axes[i]  # Get the current axis\n",
    "    sns.barplot(x=\"years\", y='Maria_abs_freq', data=Maria_df_dict[at], color=color, ax=ax)\n",
    "    ax.set_title(f\"{at}\", fontsize=13)\n",
    "    xticks_index = np.arange(0, len(Maria_df_dict[at]), 1)\n",
    "    ax.set_xticks(xticks_index)\n",
    "    ax.tick_params(axis='x', rotation=0)\n",
    "    ax.set_xlabel('Year')\n",
    "    ax.set_ylabel('Count')\n",
    "\n",
    "# Remove any unused subplots in case the number of 'geo' values is less than num_rows * num_cols\n",
    "for j in range(len(selected_at), num_rows * num_cols):\n",
    "    fig.delaxes(axes[j])\n",
    "\n",
    "plt.suptitle('Absolute Frequencies Maria by Catalonia areas - Last five years (2018-2022)', fontsize=15, y=0.95, weight='bold') # Establishing a general tittle for the plot.\n",
    "plt.subplots_adjust(hspace=0.8, wspace=0.3) # Adjust vertical (hspace) and horizontal (wspace) spacing\n",
    "# fig.savefig('Marias_Areas_Catalonia' + '.jpg', format='jpg', dpi=550)\n",
    "# plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}