add files

Introduction.py

@@ -0,0 +1,9 @@
+import streamlit as st
+from streamlit import session_state as session
+
+from stat_mod import *
+
+st.set_page_config(page_title="EU Data Explorer📊", page_icon="📊")
+
+st.title("EU Data Explorer📊")
+st.markdown(intro_text, unsafe_allow_html=True)

README.md

@@ -1,11 +1,11 @@
 ---
 title: Eudataexplorer
-emoji: 💩
+emoji: 📈
 colorFrom: green
 colorTo: gray
 sdk: streamlit
 sdk_version: 1.17.0
-app_file: app.py
+app_file: Introduction.py
 pinned: false
 license: apache-2.0
 ---

data/create_regional_dataset.ipynb

@@ -0,0 +1,386 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "bc9fba0f",
+   "metadata": {},
+   "source": [
+    "# DataFrame for EU regional data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0e470150",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os, sys\n",
+    "sys.path.insert(1, os.path.abspath('..'))\n",
+    "\n",
+    "from stat_mod import *\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b380d28d-7e6e-4f5b-82e3-e1d9d2ec214a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create dicts with EU NUTS 2 regions\n",
+    "eu_regions = { 'AT': 'Western Europe',\n",
+    "'BE': 'Western Europe', 'FR': 'Western Europe', 'DE': 'Western Europe',\n",
+    "'IE': 'Western Europe', 'LU': 'Western Europe', 'NL': 'Western Europe',\n",
+    "'CY': 'Southern Europe', 'EL': 'Southern Europe', 'IT': 'Southern Europe',\n",
+    "'MT': 'Southern Europe', 'PT': 'Southern Europe', 'ES': 'Southern Europe',\n",
+    "'DK': 'Northern Europe', 'EE': 'Northern Europe', 'FI': 'Northern Europe',\n",
+    "'LV': 'Northern Europe', 'LT': 'Northern Europe', 'SE': 'Northern Europe',\n",
+    "'BG': 'Central and Eastern Europe', 'HR': 'Central and Eastern Europe',\n",
+    "'CZ': 'Central and Eastern Europe', 'RO': 'Central and Eastern Europe',\n",
+    "'SK': 'Central and Eastern Europe', 'SI': 'Central and Eastern Europe',\n",
+    "'PL': 'Central and Eastern Europe', 'HU': 'Central and Eastern Europe' }\n",
+    "\n",
+    "regions = {}\n",
+    "for item in countries.values():\n",
+    "    regions.update(nuts_codes[item])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "dd5d63ab-9317-4aa0-a366-7f412cfd4cf4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Regional \"GDP\"\n",
+    "def get_gdp_region():\n",
+    "    params = {'unit': 'MIO_EUR', 'geo': list(regions.keys()), 'time': 2020}\n",
+    "    df = client.get_dataset('nama_10r_2gdp', params).to_dataframe()\n",
+    "    \n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df['Country'] = df['geo'].str[:2]\n",
+    "    df['EU Region'] = df['Country'].apply(lambda x: eu_regions[x])\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df.rename(columns = {'values': 'GDP'}, inplace = True)\n",
+    "    df['GDP'] = df['GDP'] / 1000\n",
+    "    cols = ['Country', 'EU Region', 'GDP',]\n",
+    "    \n",
+    "    return df[cols]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "ff71efcc-e4a6-4dce-9881-f431ddda628f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Regional \"GDP\" per capita\n",
+    "def get_gdp_capita_region():\n",
+    "    params = {'unit': 'EUR_HAB', 'time': 2020,\n",
+    "              'geo': list(regions.keys())}\n",
+    "    df = client.get_dataset('nama_10r_2gdp', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df.rename(columns = {'values': 'GDP per Capita'}, inplace = True)\n",
+    "    df = df[['GDP per Capita']]\n",
+    "    \n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7c9a96ad-052a-49b0-b364-cea1adb39312",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Regional unemployment\n",
+    "def get_unemployment_region():\n",
+    "    params = {'sex': 'T', 'geo': list(regions.keys()), 'time': 2021,\n",
+    "              'age': 'Y15-74', 'isced11': 'TOTAL'} \n",
+    "    df = client.get_dataset('lfst_r_lfu3rt', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Unemployment %'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Unemployment %']]\n",
+    "    \n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d88a8821-1ff9-4081-90a5-710b11b03e1a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Life expectancy\n",
+    "def get_life_expectancy():\n",
+    "    params = {'sex': 'T', 'geo': list(regions.keys()), 'time': 2020}\n",
+    "    df = client.get_dataset('tgs00101', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Life Expectancy'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Life Expectancy']]\n",
+    "    \n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8d9569f3-7ce7-429e-b22a-4abf7a5032bb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get tertiary Educational attainment\n",
+    "def get_tertiary_education():\n",
+    "    params = {'sex': 'T', 'geo': list(regions.keys()), 'time': 2020}\n",
+    "    df = client.get_dataset('tgs00109', params).to_dataframe()\n",
+    "    \n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Tertiary Educational Attainment %'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Tertiary Educational Attainment %']]\n",
+    "    \n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "2206a2e3-4e77-4725-8bc5-b84978e52dcc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Population density\n",
+    "def get_population_density():\n",
+    "    params = {'geo': list(regions.keys()), 'time': 2019}\n",
+    "    df = client.get_dataset('tgs00024', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Population Density'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Population Density']]\n",
+    "    \n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2eb66c5f-229b-41c4-adf3-db0ed0cb9589",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Poverty Risk\n",
+    "def get_poverty_risk():\n",
+    "    params = {'geo': list(regions.keys()), 'time': 2019}\n",
+    "    df = client.get_dataset('ilc_peps11', params).to_dataframe()\n",
+    "    \n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'People at Risk of Poverty %'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['People at Risk of Poverty %']]\n",
+    "    \n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "757f2be5-2e42-4075-bda1-294d238f5aed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Regional availability of doctors\n",
+    "def get_doctors():\n",
+    "    params = {'geo': list(regions.keys()), 'time': 2019,'unit': 'P_HTHAB',\n",
+    "              'isco08': 'OC221' }\n",
+    "    df = client.get_dataset('hlth_rs_prsrg', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Doctors per 100000'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Doctors per 100000']]\n",
+    "    \n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f8c52f1a-a7ca-4a0c-8b29-fa22ecc32f47",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get deaths in road accidents\n",
+    "def get_fatal_road_accidents():\n",
+    "    params = {'victim': 'KIL', 'geo': list(regions.keys()), 'time': 2020,\n",
+    "              'unit': 'P_MHAB'}\n",
+    "    df = client.get_dataset('tran_r_acci', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Fatal Road Accidents per Million'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Fatal Road Accidents per Million']]\n",
+    "    \n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "efc48ba6-062d-4e0a-86c1-0df22c6238ff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Regular Internet Users\n",
+    "\n",
+    "def get_regular_internet_users():\n",
+    "    params = {'indic_is': 'I_IDAY', 'geo': list(regions.keys()), 'time': 2021,\n",
+    "              'unit': 'PC_IND'}\n",
+    "    df = client.get_dataset('isoc_r_iuse_i', params).to_dataframe()\n",
+    "\n",
+    "    # Remove NAs\n",
+    "    df.dropna(inplace = True)\n",
+    "    df['region_name'] = df['geo'].apply(lambda x: regions[x])\n",
+    "    df.rename(columns = {'values': 'Regular Internet Users %'}, inplace = True)\n",
+    "    df.set_index('region_name', inplace=True) \n",
+    "    df = df[['Regular Internet Users %']]\n",
+    "    \n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "d7b173c5-aa6c-4b21-b1a1-c642b18184ee",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Get all data\n",
+    "df = get_gdp_region()\n",
+    "df = df.join(get_gdp_capita_region())\n",
+    "df = df.join(get_unemployment_region())\n",
+    "df = df.join(get_life_expectancy())\n",
+    "df = df.join(get_doctors())\n",
+    "df = df.join(get_fatal_road_accidents())\n",
+    "df = df.join(get_tertiary_education())\n",
+    "df = df.join(get_population_density())\n",
+    "df = df.join(get_poverty_risk())\n",
+    "df = df.join(get_regular_internet_users())\n",
+    "\n",
+    "# Remove NAs\n",
+    "df.dropna(thresh = 4, inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "478f421c-49e8-4334-ad2d-65cafd5b380f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 242 entries, Abruzzo to Южен централен (Yuzhen tsentralen)\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column                             Non-Null Count  Dtype  \n",
+      "---  ------                             --------------  -----  \n",
+      " 0   Country                            242 non-null    object \n",
+      " 1   EU Region                          242 non-null    object \n",
+      " 2   GDP                                242 non-null    float64\n",
+      " 3   GDP per Capita                     242 non-null    float64\n",
+      " 4   Unemployment %                     238 non-null    float64\n",
+      " 5   Life Expectancy                    238 non-null    float64\n",
+      " 6   Doctors per 100000                 173 non-null    float64\n",
+      " 7   Fatal Road Accidents per Million   239 non-null    float64\n",
+      " 8   Tertiary Educational Attainment %  238 non-null    float64\n",
+      " 9   Population Density                 239 non-null    float64\n",
+      " 10  People at Risk of Poverty %        183 non-null    float64\n",
+      " 11  Regular Internet Users %           169 non-null    float64\n",
+      "dtypes: float64(10), object(2)\n",
+      "memory usage: 24.6+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Check cols\n",
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "9a335ba4-330e-49a4-bec4-bf37dc4c2e50",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Save to CSV\n",
+    "df.to_csv('../data/eu_regional_data.csv',\n",
+    "          float_format = '%.2f', encoding = 'utf-8')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "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": "3.8.5"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "9737f18efb1b9d105cd953add47348769fd82af91ada1884766527cfb8bc009e"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

data/eu_region_data.csv

@@ -0,0 +1,243 @@
+region_name,Country,EU Region,GDP,GDP per Capita,Unemployment %,Life Expectancy,Doctors per 100000,Fatal Road Accidents per Million,Tertiary Educational Attainment %,Population Density,People at Risk of Poverty %,Regular Internet Users %
+Abruzzo,IT,Southern Europe,30.89,24000.00,9.30,82.90,435.45,46.00,21.20,120.50,25.00,78.00
+Alentejo,PT,Southern Europe,12.44,17700.00,6.60,80.20,310.06,135.00,21.40,22.70,22.00,70.00
+Algarve,PT,Southern Europe,8.71,19900.00,8.30,80.30,419.03,75.00,24.40,88.90,23.20,76.00
+Alsace,FR,Western Europe,59.58,31000.00,7.10,81.80,362.21,30.00,39.00,230.60,,75.00
+Andalucía,ES,Southern Europe,150.56,17700.00,21.70,81.70,371.83,30.00,32.50,97.40,37.70,84.00
+Aquitaine,FR,Western Europe,103.98,29600.00,7.40,83.50,363.49,47.00,36.00,83.90,,81.00
+Aragón,ES,Southern Europe,35.29,26500.00,10.20,82.30,502.84,51.00,39.70,27.90,21.10,85.00
+Arnsberg,DE,Western Europe,125.49,35100.00,4.30,80.20,,21.00,25.50,449.10,18.50,
+Auvergne,FR,Western Europe,37.18,27000.00,7.00,82.10,311.28,52.00,31.20,52.60,,68.00
+"Aνατολική Μακεδονία, Θράκη (Anatoliki Makedonia, Thraki)",EL,Southern Europe,6.49,10900.00,18.50,80.00,510.88,47.00,24.40,42.80,35.20,
+Aττική (Attiki),EL,Southern Europe,78.18,20900.00,11.90,81.10,813.51,40.00,41.00,987.50,24.80,
+Basilicata,IT,Southern Europe,11.64,21200.00,8.30,82.80,351.49,33.00,17.60,55.70,34.70,74.00
+Basse-Normandie ,FR,Western Europe,38.75,26400.00,6.40,82.10,303.75,55.00,32.60,82.60,,79.00
+Berlin,DE,Western Europe,155.17,42300.00,5.70,80.90,,14.00,42.90,4322.90,19.30,
+Bourgogne,FR,Western Europe,45.36,27900.00,7.10,81.70,295.55,62.00,35.00,51.30,,77.00
+Brandenburg,DE,Western Europe,74.92,29700.00,3.00,80.60,,56.00,29.20,86.70,17.00,
+Bratislavský kraj,SK,Central and Eastern Europe,26.19,38900.00,2.60,78.80,648.52,36.00,45.60,328.80,7.90,90.00
+Braunschweig,DE,Western Europe,75.52,47400.00,3.80,80.80,,40.00,32.00,197.30,18.10,
+Bremen,DE,Western Europe,31.93,46900.00,6.90,80.00,,21.00,30.80,1744.50,26.50,
+Bretagne,FR,Western Europe,99.65,29400.00,5.80,82.60,325.67,41.00,38.10,122.40,,80.00
+Bucureşti-Ilfov,RO,Central and Eastern Europe,60.31,26000.00,3.50,75.50,617.92,46.00,40.50,1321.90,14.00,77.00
+Budapest,HU,Central and Eastern Europe,50.43,29000.00,2.90,77.90,570.91,19.00,49.80,3433.80,15.60,92.00
+Burgenland,AT,Western Europe,8.92,30200.00,5.10,81.80,434.45,61.00,33.10,77.80,,78.00
+Calabria,IT,Southern Europe,30.90,16500.00,18.00,82.50,388.11,32.00,16.00,126.50,39.80,72.00
+Campania,IT,Southern Europe,102.83,18100.00,19.30,81.20,390.99,31.00,16.30,422.20,49.70,74.00
+Canarias,ES,Southern Europe,39.16,17400.00,23.20,83.40,394.47,22.00,34.40,299.40,35.00,84.00
+Cantabria,ES,Southern Europe,12.87,22100.00,11.50,83.20,515.45,27.00,42.50,110.50,19.40,82.00
+Castilla y León,ES,Southern Europe,55.40,23200.00,11.40,82.40,465.79,52.00,39.00,25.60,16.70,83.00
+Castilla-La Mancha,ES,Southern Europe,39.57,19400.00,15.60,81.10,282.57,47.00,30.80,25.80,30.70,84.00
+Cataluña,ES,Southern Europe,212.93,27800.00,11.60,82.30,489.63,27.00,42.30,238.10,18.80,88.00
+Centre — Val de Loire,FR,Western Europe,71.57,27800.00,7.20,82.40,260.16,43.00,31.90,65.40,,76.00
+Centro (PT),PT,Southern Europe,38.41,17300.00,5.80,81.50,500.38,66.00,26.20,79.20,20.40,72.00
+Centru,RO,Central and Eastern Europe,24.57,10600.00,5.10,74.40,321.08,85.00,17.10,68.20,24.40,72.00
+Champagne-Ardenne,FR,Western Europe,36.66,27800.00,8.90,81.00,289.95,56.00,24.80,51.50,,76.00
+Chemnitz,DE,Western Europe,41.28,29100.00,2.30,80.00,,47.00,27.00,219.90,18.30,
+Ciudad de Ceuta,ES,Southern Europe,1.64,19500.00,26.60,79.80,905.79,24.00,25.70,4222.90,45.90,88.00
+Ciudad de Melilla,ES,Southern Europe,1.51,17900.00,19.80,79.30,,12.00,34.30,6041.50,38.50,87.00
+Comunidad Foral de Navarra,ES,Southern Europe,19.26,29300.00,10.60,83.40,540.39,30.00,48.40,63.10,11.70,86.00
+Comunidad de Madrid,ES,Southern Europe,216.53,32000.00,11.60,82.30,519.84,16.00,50.20,839.70,19.00,90.00
+Comunitat Valenciana ,ES,Southern Europe,104.72,20800.00,15.90,82.60,393.03,26.00,38.00,216.20,27.00,87.00
+Corse,FR,Western Europe,8.82,25500.00,9.10,84.00,301.69,49.00,39.30,39.60,,74.00
+Darmstadt,DE,Western Europe,203.86,50700.00,4.10,81.80,,27.00,32.70,542.20,13.50,
+Detmold,DE,Western Europe,78.67,38300.00,4.10,81.40,,34.00,25.90,316.30,15.50,
+Dolnośląskie,PL,Central and Eastern Europe,43.81,15100.00,4.00,76.20,,58.00,36.10,144.90,14.50,
+Drenthe,NL,Western Europe,15.58,31500.00,3.50,81.60,295.79,59.00,34.60,184.50,14.30,94.00
+Dresden,DE,Western Europe,50.63,31800.00,3.30,80.80,,26.00,32.10,205.60,16.60,
+Dél-Alföld,HU,Central and Eastern Europe,12.62,10300.00,4.50,75.40,358.32,54.00,21.60,68.10,14.90,79.00
+Dél-Dunántúl,HU,Central and Eastern Europe,8.44,9700.00,4.80,75.60,359.37,55.00,18.50,63.70,24.60,82.00
+Düsseldorf,DE,Western Europe,217.05,41700.00,4.50,80.50,,24.00,28.90,1006.70,20.50,
+Eastern and Midland,IE,Western Europe,186.17,75700.00,6.40,82.60,,21.00,53.90,169.80,19.00,95.00
+Eesti,EE,Northern Europe,26.83,20200.00,6.20,78.90,346.90,45.00,40.10,30.50,,85.00
+Emilia-Romagna,IT,Southern Europe,149.36,33600.00,5.50,82.60,425.23,50.00,23.30,201.90,15.50,83.00
+Etelä-Suomi,FI,Northern Europe,43.47,37900.00,7.50,81.90,,42.00,43.50,36.60,16.30,91.00
+Extremadura,ES,Southern Europe,19.39,18300.00,19.50,81.80,306.95,38.00,26.70,26.00,37.70,81.00
+Flevoland,NL,Western Europe,14.63,34300.00,4.60,81.70,126.49,24.00,35.00,292.50,15.80,92.00
+Franche-Comté,FR,Western Europe,30.19,25500.00,7.00,81.60,307.48,54.00,33.80,72.60,,78.00
+Freiburg,DE,Western Europe,86.68,38100.00,3.00,82.20,,34.00,33.60,244.90,13.50,
+Friesland (NL),NL,Western Europe,21.00,32300.00,4.50,81.90,237.36,54.00,34.30,191.00,16.70,91.00
+Friuli-Venezia Giulia,IT,Southern Europe,36.88,30600.00,5.70,82.80,404.61,39.00,21.40,159.90,13.80,82.00
+Galicia,ES,Southern Europe,59.11,21900.00,11.70,83.70,474.96,38.00,40.30,92.00,24.30,81.00
+Gelderland,NL,Western Europe,82.04,39200.00,3.90,81.40,371.53,41.00,38.10,415.80,14.70,90.00
+Gießen,DE,Western Europe,36.12,34400.00,3.50,81.00,,46.00,30.00,194.90,17.10,
+Grad Zagreb,HR,Central and Eastern Europe,17.55,23400.00,5.50,,,,,,,
+Groningen,NL,Western Europe,23.24,39700.00,5.40,81.10,546.22,46.00,40.60,247.90,23.00,90.00
+Guadeloupe,FR,Western Europe,9.29,22600.00,17.10,80.60,277.88,124.00,23.30,247.00,,65.00
+Guyane,FR,Western Europe,4.35,15000.00,14.60,,219.22,115.00,18.70,3.40,,79.00
+Hamburg,DE,Western Europe,119.14,64400.00,4.40,81.40,,8.00,36.70,2597.50,23.70,
+Hannover,DE,Western Europe,84.49,39300.00,2.80,80.90,,43.00,28.30,239.00,17.60,
+Haute-Normandie ,FR,Western Europe,51.35,27600.00,7.60,81.10,274.59,35.00,31.80,151.20,,73.00
+Helsinki-Uusimaa,FI,Northern Europe,93.28,55000.00,7.70,82.30,,27.00,54.90,184.70,10.10,95.00
+Hovedstaden,DK,Northern Europe,128.90,69700.00,5.70,81.50,500.65,15.00,53.10,756.00,17.50,95.00
+Ile-de-France,FR,Western Europe,710.09,57400.00,8.00,82.70,386.90,20.00,54.30,1026.80,,83.00
+Illes Balears,ES,Southern Europe,26.79,22000.00,14.80,83.90,366.83,31.00,34.80,241.20,15.10,89.00
+Jadranska Hrvatska,HR,Central and Eastern Europe,15.41,11500.00,9.50,79.30,327.82,71.00,26.40,56.00,22.00,78.00
+Jihovýchod,CZ,Central and Eastern Europe,31.79,18700.00,2.40,78.80,430.81,58.00,27.70,124.00,12.50,80.00
+Jihozápad,CZ,Central and Eastern Europe,20.98,17000.00,2.40,78.60,377.68,62.00,19.80,71.80,9.60,80.00
+Karlsruhe,DE,Western Europe,123.72,44000.00,3.30,81.80,,33.00,34.50,409.30,14.50,
+Kassel,DE,Western Europe,44.27,36300.00,2.90,80.90,,41.00,28.10,147.50,15.30,
+Koblenz,DE,Western Europe,50.57,33700.00,2.90,81.00,,35.00,27.30,186.70,19.80,
+Kujawsko-pomorskie,PL,Central and Eastern Europe,23.03,11100.00,4.40,76.30,,65.00,26.60,116.80,23.20,
+Kärnten,AT,Western Europe,20.70,36900.00,5.60,81.40,485.10,62.00,32.10,59.90,,75.00
+Köln,DE,Western Europe,193.31,43200.00,4.00,81.30,,21.00,32.20,613.40,19.70,
+Közép-Dunántúl,HU,Central and Eastern Europe,13.46,12700.00,2.10,75.40,244.93,73.00,22.10,99.10,13.50,80.00
+La Rioja,ES,Southern Europe,8.13,25700.00,11.50,82.50,349.48,51.00,38.50,62.60,15.20,82.00
+La Réunion ,FR,Western Europe,19.15,22100.00,17.90,81.90,337.69,50.00,22.90,345.70,,61.00
+Languedoc-Roussillon,FR,Western Europe,74.01,25600.00,11.40,82.70,365.77,48.00,41.00,104.40,,73.00
+Latvija,LV,Northern Europe,29.47,15500.00,7.60,75.50,326.73,73.00,37.80,30.20,,84.00
+Lazio,IT,Southern Europe,186.30,32400.00,10.00,83.10,473.79,45.00,27.00,343.00,24.80,83.00
+Leipzig,DE,Western Europe,34.97,33300.00,4.50,80.80,,39.00,37.00,268.40,20.20,
+Liguria,IT,Southern Europe,46.09,30300.00,8.40,81.90,462.36,39.00,21.80,284.30,17.60,84.00
+Limburg (NL),NL,Western Europe,45.19,40500.00,3.80,80.90,354.09,47.00,34.60,517.70,15.30,88.00
+Limousin,FR,Western Europe,18.08,24800.00,6.30,82.50,337.16,47.00,33.80,42.90,,76.00
+Lombardia,IT,Southern Europe,365.51,36500.00,5.90,81.40,372.88,32.00,21.70,435.80,16.20,82.00
+Lorraine,FR,Western Europe,56.55,24300.00,8.50,81.00,302.64,38.00,32.50,98.60,,77.00
+Lubelskie,PL,Central and Eastern Europe,19.56,9300.00,5.20,76.50,,75.00,33.40,84.00,28.80,
+Lubuskie,PL,Central and Eastern Europe,11.23,11100.00,,75.80,,76.00,27.90,72.60,14.50,
+Luxembourg,LU,Western Europe,64.22,101800.00,5.30,82.20,,42.00,47.10,239.80,,94.00
+Länsi-Suomi,FI,Northern Europe,52.23,37900.00,7.70,82.30,,49.00,45.90,23.70,,93.00
+Lüneburg,DE,Western Europe,49.23,28600.00,3.00,81.00,,51.00,26.90,111.40,16.20,
+Malta,MT,Southern Europe,13.07,25300.00,3.50,82.30,,23.00,30.60,1595.10,,84.00
+Marche,IT,Southern Europe,39.66,26300.00,7.10,83.20,382.59,46.00,21.20,161.90,19.10,80.00
+Martinique ,FR,Western Europe,8.86,24600.00,12.80,81.90,305.98,78.00,27.10,328.60,,68.00
+Mayotte,FR,Western Europe,2.76,9700.00,,73.30,81.01,36.00,,750.80,,
+Mazowiecki regionalny,PL,Central and Eastern Europe,27.11,11600.00,3.80,75.30,,123.00,26.50,79.50,21.30,
+Małopolskie,PL,Central and Eastern Europe,42.61,12500.00,3.20,77.60,,47.00,33.80,224.00,18.50,
+Mecklenburg-Vorpommern,DE,Western Europe,46.59,28900.00,3.80,80.40,,44.00,27.30,71.30,23.20,
+Mellersta Norrland,SE,Northern Europe,14.52,38600.00,6.30,81.40,380.37,48.00,37.00,5.30,23.60,92.00
+Midi-Pyrénées,FR,Western Europe,94.73,30400.00,6.10,83.60,342.55,48.00,43.30,67.80,,77.00
+Midtjylland,DK,Northern Europe,65.33,49200.00,4.80,82.10,407.93,32.00,38.90,103.70,16.30,96.00
+Mittelfranken,DE,Western Europe,79.56,44800.00,3.60,80.90,,29.00,33.80,245.70,18.40,
+Molise,IT,Southern Europe,6.09,20500.00,10.90,82.40,415.35,83.00,18.50,68.20,38.10,72.00
+Moravskoslezsko,CZ,Central and Eastern Europe,18.78,15700.00,4.60,76.80,375.90,36.00,21.10,226.20,14.90,84.00
+Münster,DE,Western Europe,89.38,34100.00,3.40,80.90,,26.00,26.60,380.10,18.40,
+Niederbayern,DE,Western Europe,48.48,38900.00,1.80,80.80,,54.00,24.40,121.00,,
+Niederösterreich,AT,Western Europe,59.52,35300.00,5.10,81.30,471.11,53.00,33.00,88.90,,84.00
+Noord-Brabant,NL,Western Europe,120.73,47000.00,3.20,81.10,265.28,39.00,41.10,514.80,13.90,91.00
+Noord-Holland,NL,Western Europe,171.05,59300.00,4.50,81.70,487.96,30.00,49.90,1041.20,17.00,93.00
+Nord-Est,RO,Central and Eastern Europe,22.81,7200.00,6.80,73.30,255.50,98.00,11.80,87.50,47.10,64.00
+Nord-Pas de Calais,FR,Western Europe,113.78,27900.00,8.80,80.40,319.98,23.00,32.10,327.40,,76.00
+Nord-Vest,RO,Central and Eastern Europe,26.90,10600.00,3.10,74.10,335.01,80.00,20.10,75.00,19.30,75.00
+Nordjylland,DK,Northern Europe,26.33,44600.00,5.00,81.80,346.36,29.00,32.00,76.40,17.70,93.00
+Norra Mellansverige,SE,Northern Europe,31.23,36400.00,9.70,82.20,359.02,31.00,35.30,13.50,18.30,91.00
+Norte,PT,Southern Europe,60.33,16900.00,6.60,81.30,531.76,39.00,24.90,169.30,23.20,70.00
+Northern and Western,IE,Western Europe,26.43,30100.00,5.10,82.90,,38.00,46.40,35.00,25.40,97.00
+Nyugat-Dunántúl,HU,Central and Eastern Europe,13.28,13300.00,2.20,76.00,283.58,49.00,25.00,88.60,16.30,82.00
+Oberbayern,DE,Western Europe,273.50,58000.00,2.70,82.40,,36.00,41.80,273.40,14.80,
+Oberfranken,DE,Western Europe,40.74,38300.00,3.30,80.70,,32.00,27.70,147.80,18.70,
+Oberpfalz,DE,Western Europe,46.41,41700.00,2.50,80.70,,42.00,29.70,115.20,,
+Oberösterreich,AT,Western Europe,65.24,43700.00,3.80,81.70,426.53,45.00,31.10,126.80,,81.00
+Opolskie,PL,Central and Eastern Europe,10.53,10700.00,2.80,76.60,,69.00,27.60,101.40,17.00,
+Overijssel,NL,Western Europe,45.70,39300.00,3.80,81.20,265.13,40.00,37.70,344.90,15.80,90.00
+Panonska Hrvatska,HR,Central and Eastern Europe,9.17,7900.00,9.70,,,,,,,
+Pays de la Loire,FR,Western Europe,116.15,30100.00,6.00,83.20,292.99,42.00,35.90,118.30,,78.00
+País Vasco,ES,Southern Europe,66.56,30400.00,9.80,83.40,563.31,19.00,53.40,303.70,14.40,84.00
+Pest,HU,Central and Eastern Europe,14.60,11200.00,3.00,76.00,258.85,56.00,30.70,205.10,19.10,86.00
+Picardie,FR,Western Europe,47.85,24700.00,9.70,80.40,257.53,50.00,32.60,99.40,,77.00
+Piemonte,IT,Southern Europe,126.20,29400.00,7.30,81.60,370.31,42.00,19.80,172.30,16.70,80.00
+Podkarpackie,PL,Central and Eastern Europe,20.07,9400.00,4.80,77.50,,63.00,29.60,117.80,22.30,
+Podlaskie,PL,Central and Eastern Europe,11.79,10000.00,3.20,77.10,,68.00,31.40,57.50,20.80,
+Pohjois- ja Itä-Suomi,FI,Northern Europe,45.78,35900.00,7.80,81.50,,48.00,42.00,6.30,19.00,91.00
+Poitou-Charentes,FR,Western Europe,50.04,27400.00,8.60,82.80,298.29,56.00,33.40,70.00,,80.00
+Pomorskie,PL,Central and Eastern Europe,30.46,13000.00,2.30,77.20,,73.00,34.90,130.60,15.30,
+Praha,CZ,Central and Eastern Europe,58.04,43700.00,2.30,80.30,736.22,17.00,45.90,2714.30,7.90,88.00
+Principado de Asturias,ES,Southern Europe,21.47,21100.00,12.50,82.20,398.31,22.00,44.20,96.60,24.60,85.00
+Prov. Antwerpen,BE,Western Europe,88.19,47000.00,5.20,82.00,271.16,33.00,41.00,665.80,,86.00
+Prov. Brabant Wallon,BE,Western Europe,22.20,54400.00,6.80,81.90,525.24,47.00,59.70,369.70,,92.00
+Prov. Hainaut,BE,Western Europe,33.11,24500.00,10.30,78.00,253.30,57.00,32.40,354.80,,77.00
+Prov. Limburg (BE),BE,Western Europe,28.07,31800.00,3.40,82.30,256.65,47.00,37.70,367.50,,87.00
+Prov. Liège,BE,Western Europe,30.96,27800.00,9.40,78.60,358.81,56.00,39.70,289.70,,84.00
+Prov. Luxembourg (BE),BE,Western Europe,6.95,23900.00,5.60,79.90,231.48,100.00,42.50,64.60,,85.00
+Prov. Namur,BE,Western Europe,13.18,26400.00,7.60,79.30,351.89,84.00,40.80,135.90,,80.00
+Prov. Oost-Vlaanderen,BE,Western Europe,54.76,35800.00,2.80,81.80,292.63,45.00,44.10,512.30,,90.00
+Prov. Vlaams-Brabant,BE,Western Europe,49.71,42800.00,4.00,82.60,409.53,28.00,51.40,544.70,,91.00
+Prov. West-Vlaanderen,BE,Western Europe,45.61,37900.00,3.60,81.90,262.07,42.00,38.70,380.80,,89.00
+Provence-Alpes-Côte d’Azur,FR,Western Europe,161.29,31500.00,8.10,83.00,404.03,45.00,40.00,162.40,,76.00
+Provincia Autonoma di Bolzano/Bozen,IT,Southern Europe,23.72,44400.00,3.80,82.80,324.38,58.00,17.60,72.20,11.50,82.00
+Provincia Autonoma di Trento,IT,Southern Europe,20.04,36900.00,4.80,82.80,329.25,46.00,22.40,88.20,14.00,83.00
+Puglia,IT,Southern Europe,71.64,18200.00,14.60,82.70,384.75,40.00,15.30,206.80,37.40,70.00
+Região Autónoma da Madeira,PT,Southern Europe,4.46,17600.00,8.00,79.10,442.35,39.00,22.90,318.00,32.20,76.00
+Região Autónoma dos Açores,PT,Southern Europe,4.15,17100.00,7.20,77.90,354.58,70.00,15.80,105.30,36.70,71.00
+Región de Murcia,ES,Southern Europe,29.94,19800.00,14.30,82.40,452.19,26.00,32.80,132.40,31.90,87.00
+Rheinhessen-Pfalz,DE,Western Europe,76.69,37200.00,4.40,81.20,,23.00,32.70,303.20,16.50,
+Rhône-Alpes,FR,Western Europe,231.70,34300.00,7.20,82.80,345.62,39.00,43.20,150.90,,78.00
+Région de Bruxelles-Capitale/ Brussels Hoofdstedelijk Gewest,BE,Western Europe,83.85,68400.00,12.40,79.40,390.38,13.00,49.30,7526.70,,89.00
+Saarland,DE,Western Europe,33.95,34500.00,3.00,80.20,,21.00,26.30,385.50,21.60,
+Sachsen-Anhalt,DE,Western Europe,63.54,29000.00,4.40,79.70,,56.00,22.60,108.70,18.60,
+Salzburg,AT,Western Europe,27.95,49900.00,4.60,82.20,581.16,50.00,32.50,78.90,,81.00
+Sardegna,IT,Southern Europe,32.38,20200.00,13.50,82.80,482.15,59.00,17.70,68.30,28.10,80.00
+Schleswig-Holstein,DE,Western Europe,98.36,33800.00,3.40,81.20,,37.00,26.90,188.20,20.80,
+Schwaben,DE,Western Europe,74.76,39300.00,2.90,81.80,,37.00,32.40,191.50,16.30,
+Severovýchod,CZ,Central and Eastern Europe,25.46,16800.00,2.40,78.70,350.83,53.00,20.50,123.70,12.90,77.00
+Severozápad,CZ,Central and Eastern Europe,15.20,13600.00,4.30,76.40,325.10,56.00,13.70,131.70,21.50,76.00
+Sicilia,IT,Southern Europe,83.33,17200.00,18.70,81.90,441.16,33.00,14.90,192.10,48.70,70.00
+Sjeverna Hrvatska,HR,Central and Eastern Europe,8.06,10000.00,4.60,,,,,,,
+Sjælland,DK,Northern Europe,31.53,37600.00,5.00,80.60,364.26,26.00,30.40,118.30,12.30,94.00
+Småland med öarna,SE,Northern Europe,33.34,38200.00,7.50,82.50,382.98,23.00,37.20,26.20,16.40,90.00
+Sostinės regionas,LT,Northern Europe,21.14,25600.00,4.80,75.80,580.98,50.00,58.60,86.60,21.20,81.00
+Southern,IE,Western Europe,160.27,97500.00,6.50,82.50,,38.00,45.60,55.60,20.40,92.00
+Steiermark,AT,Western Europe,48.59,39000.00,4.30,81.10,521.32,42.00,31.10,76.60,,75.00
+Stockholm,SE,Northern Europe,153.56,64400.00,8.20,82.30,458.82,5.00,53.70,361.80,14.80,94.00
+Stredné Slovensko,SK,Central and Eastern Europe,17.92,13400.00,7.50,76.80,330.86,56.00,23.70,82.70,21.50,79.00
+Stuttgart,DE,Western Europe,215.44,51900.00,3.10,82.30,,24.00,34.70,393.30,13.30,
+Střední Morava,CZ,Central and Eastern Europe,19.96,16500.00,2.20,77.80,380.58,40.00,22.30,133.20,12.90,81.00
+Střední Čechy,CZ,Central and Eastern Europe,25.05,18000.00,2.50,78.50,265.17,62.00,24.20,128.50,9.60,79.00
+Sud-Est,RO,Central and Eastern Europe,21.53,9100.00,6.00,73.70,219.85,95.00,13.10,70.90,40.10,64.00
+Sud-Muntenia,RO,Central and Eastern Europe,24.95,8600.00,7.70,73.70,159.76,99.00,13.10,86.10,36.50,65.00
+Sud-Vest Oltenia,RO,Central and Eastern Europe,16.92,8900.00,9.20,75.00,311.52,90.00,16.70,66.90,38.90,62.00
+Syddanmark,DK,Northern Europe,58.01,47400.00,4.40,81.80,408.18,43.00,33.50,102.00,16.60,94.00
+Sydsverige,SE,Northern Europe,61.75,40000.00,11.20,82.60,434.48,27.00,45.40,110.10,25.40,91.00
+Thüringen,DE,Western Europe,62.22,29300.00,3.30,80.70,,39.00,29.10,132.40,19.30,
+Tirol,AT,Western Europe,33.45,44100.00,4.80,82.40,588.76,34.00,31.90,60.40,,81.00
+Toscana,IT,Southern Europe,111.31,30100.00,7.50,83.40,444.77,41.00,21.10,162.70,18.70,83.00
+Trier,DE,Western Europe,16.30,30500.00,,81.10,,51.00,31.60,108.50,21.40,
+Tübingen,DE,Western Europe,80.71,43300.00,2.90,82.50,,33.00,32.20,214.20,14.10,
+Umbria,IT,Southern Europe,21.45,24700.00,6.60,83.70,456.90,52.00,23.10,105.50,13.30,83.00
+Unterfranken,DE,Western Europe,53.07,40300.00,2.30,82.00,,34.00,31.30,155.10,17.50,
+Utrecht,NL,Western Europe,76.84,58100.00,4.00,81.80,590.14,25.00,55.70,934.60,15.60,93.00
+Valle d’Aosta/Vallée d’Aoste,IT,Southern Europe,4.52,36300.00,7.30,81.40,366.99,0.00,18.90,38.60,8.10,84.00
+Veneto,IT,Southern Europe,151.91,31200.00,5.30,83.10,345.71,47.00,19.80,282.00,11.10,81.00
+Vest,RO,Central and Eastern Europe,20.72,11700.00,3.50,74.00,416.35,81.00,17.00,55.70,21.90,71.00
+Vidurio ir vakarų Lietuvos regionas ,LT,Northern Europe,28.37,14400.00,8.20,74.80,405.84,68.00,37.80,37.20,28.30,76.00
+Vorarlberg,AT,Western Europe,18.21,45700.00,4.10,82.50,432.63,40.00,29.20,156.30,,79.00
+Vzhodna Slovenija,SI,Central and Eastern Europe,20.39,18500.00,5.00,79.50,276.15,41.00,30.80,89.00,17.00,81.00
+Västsverige,SE,Northern Europe,90.35,43800.00,8.40,82.70,420.85,17.00,43.40,70.10,19.20,93.00
+Východné Slovensko,SK,Central and Eastern Europe,19.61,12000.00,10.90,76.60,347.60,27.00,26.60,103.90,21.20,78.00
+Warmińsko-mazurskie,PL,Central and Eastern Europe,13.61,9600.00,3.50,76.10,,82.00,23.60,61.10,24.20,
+Warszawski stołeczny,PL,Central and Eastern Europe,92.91,30000.00,2.10,78.00,,43.00,57.20,510.20,13.40,
+Weser-Ems,DE,Western Europe,90.85,35800.00,3.40,80.80,,50.00,25.00,169.80,17.10,
+Wielkopolskie,PL,Central and Eastern Europe,52.16,14900.00,2.20,76.60,,62.00,29.30,117.90,17.50,
+Wien,AT,Western Europe,96.59,50400.00,12.10,80.20,686.75,6.00,42.70,4808.90,,86.00
+Zachodniopomorskie,PL,Central and Eastern Europe,19.32,11400.00,3.50,76.20,,60.00,29.60,76.60,17.10,
+Zahodna Slovenija,SI,Central and Eastern Europe,26.53,26500.00,4.50,81.80,381.57,35.00,41.60,126.90,11.50,89.00
+Zeeland,NL,Western Europe,13.99,36400.00,3.60,82.40,165.16,57.00,31.80,212.60,14.30,97.00
+Zuid-Holland,NL,Western Europe,168.99,45000.00,5.10,81.30,369.44,22.00,44.20,1292.20,19.40,92.00
+Západné Slovensko,SK,Central and Eastern Europe,28.36,15600.00,4.70,77.10,277.43,57.00,22.40,123.00,11.30,79.00
+Área Metropolitana de Lisboa,PT,Southern Europe,71.43,24900.00,6.80,81.40,652.83,33.00,38.00,1015.90,17.80,83.00
+Åland,FI,Northern Europe,1.17,38900.00,,83.30,,0.00,41.60,19.20,,
+Észak-Alföld,HU,Central and Eastern Europe,13.23,9200.00,7.10,74.80,326.17,46.00,19.20,83.10,24.20,76.00
+Észak-Magyarország,HU,Central and Eastern Europe,10.56,9500.00,6.20,73.80,240.10,42.00,16.80,84.40,23.90,76.00
+Östra Mellansverige,SE,Northern Europe,66.87,38600.00,9.80,82.30,449.97,22.00,42.80,44.70,18.70,92.00
+Övre Norrland,SE,Northern Europe,23.81,45600.00,6.10,82.20,457.75,23.00,40.00,3.40,16.60,87.00
+Łódzkie,PL,Central and Eastern Europe,32.43,13200.00,4.40,75.30,,90.00,30.20,135.20,16.50,
+Śląskie,PL,Central and Eastern Europe,60.97,13500.00,2.90,76.10,,42.00,30.70,368.80,13.80,
+Świętokrzyskie,PL,Central and Eastern Europe,12.08,9800.00,4.40,76.10,,79.00,31.90,105.10,20.70,
+Ήπειρος (Ipeiros),EL,Southern Europe,3.72,11200.00,15.10,83.80,666.61,75.00,31.60,36.80,27.60,
+Βόρειο Αιγαίο (Voreio Aigaio),EL,Southern Europe,2.33,10100.00,13.90,82.60,320.01,52.00,29.30,59.30,35.50,
+Δυτική Ελλάδα (Dytiki Ellada),EL,Southern Europe,7.40,11400.00,17.50,81.70,494.85,89.00,25.00,59.20,40.90,
+Δυτική Μακεδονία (Dytiki Makedonia),EL,Southern Europe,3.32,12600.00,19.80,81.70,343.82,38.00,26.60,28.80,34.80,
+Θεσσαλία (Thessalia),EL,Southern Europe,8.71,12200.00,16.70,81.50,531.19,56.00,30.30,51.40,28.00,
+Ιόνια Νησιά (Ionia Nisia),EL,Southern Europe,2.81,13800.00,13.20,81.50,525.28,44.00,23.70,89.40,25.70,
+Κεντρική Μακεδονία (Kentriki Makedonia),EL,Southern Europe,22.70,12100.00,16.10,80.50,613.53,55.00,32.20,101.20,31.70,
+Κρήτη (Kriti),EL,Southern Europe,8.19,12800.00,16.30,82.60,610.65,44.00,28.00,76.50,31.60,
+Κύπρος (Kypros),CY,Southern Europe,21.55,24200.00,7.50,82.40,427.23,54.00,44.90,95.70,,89.00
+Νότιο Αιγαίο (Notio Aigaio),EL,Southern Europe,5.45,15600.00,18.80,82.60,370.19,86.00,22.50,66.10,34.50,
+Πελοπόννησος (Peloponnisos),EL,Southern Europe,7.65,13400.00,12.70,82.10,385.66,75.00,23.90,37.10,36.40,
+Στερεά Ελλάδα (Sterea Ellada),EL,Southern Europe,8.38,15100.00,17.20,82.30,312.24,86.00,25.20,36.10,29.50,
+Северен централен (Severen tsentralen),BG,Central and Eastern Europe,4.59,6000.00,6.70,72.80,333.20,81.00,26.50,53.10,35.90,70.00
+Северозападен (Severozapaden),BG,Central and Eastern Europe,4.19,5800.00,11.10,72.10,448.70,98.00,20.70,39.00,41.30,62.00
+Североизточен (Severoiztochen),BG,Central and Eastern Europe,6.19,6700.00,6.10,73.50,397.76,72.00,23.30,63.70,34.70,71.00
+Югозападен (Yugozapaden),BG,Central and Eastern Europe,31.01,14800.00,3.50,74.50,444.85,45.00,43.40,103.70,22.70,71.00
+Югоизточен (Yugoiztochen),BG,Central and Eastern Europe,6.36,6200.00,5.60,73.30,341.89,88.00,22.90,52.50,36.60,65.00
+Южен централен (Yuzhen tsentralen),BG,Central and Eastern Europe,8.99,6400.00,4.00,73.90,403.78,55.00,21.90,63.70,37.70,63.00

pages/2_Analyses.py

@@ -0,0 +1,99 @@
+import os
+import sys
+
+sys.path.insert(1, os.path.abspath(".."))
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import pandas as pd
+import plotly.express as px
+import streamlit as st
+from statsmodels.stats.descriptivestats import describe
+
+from stat_mod import *
+
+# Set style of plots
+plt.style.use("seaborn-whitegrid")
+
+# Set plot resolution
+mpl.rcParams["figure.dpi"] = 300
+
+# Configure Streamlit page properties
+st.set_page_config(page_title="Analyses📊", page_icon="📊")
+
+# Page title
+st.title("Statistical Analyses📊")
+st.markdown(analysis_text, unsafe_allow_html=True)
+
+# Read data CSV file
+df = pd.read_csv("data/eu_region_data.csv")
+num_cols = list(df.columns[3:])
+
+# Define tabs on page
+tab_str = [
+    "Descriptive Stats",
+    "Regression Model",
+]
+tab1, tab2 = st.tabs(tab_str)
+
+with tab1:
+    st.markdown("##### Descriptive Stats for NUTS 2 Regional Data")
+
+    with st.expander("View NUTS 2 Regional Data"):
+        st.dataframe(df.style.format(precision=2))
+        st.write("This custom dataset was obtained using the EuroStat API.")
+        st.download_button(
+            "Download Dataset (CSV)",
+            df.to_csv(index=False, float_format="%.2f").encode("utf-8"),
+            "nuts2_dataset.csv",
+            "text/csv",
+            key="download-csv",
+        )
+
+    with st.expander("Summary Stats for NUTS 2 Regional Data"):
+        df_desc = describe(df, percentiles=[25, 75])
+        st.dataframe(df_desc.style.format(precision=2))
+
+    with st.expander("Distribution Plot for NUTS 2 Regional Data", expanded=True):
+
+        desc_cont = st.container()
+        col1, col2 = st.columns(2)
+        variable = col1.selectbox("Choose Variable: ", options=num_cols, index=1)
+        plot_type = col2.selectbox(
+            "Choose Plot: ", options=["Kernel Distribution Estimation Plot", "Box Plot"]
+        )
+
+        with desc_cont:
+            if plot_type == "Kernel Distribution Estimation Plot":
+                fig1 = kde_plt(df, variable)
+                st.pyplot(fig1)
+
+            elif plot_type == "Box Plot":
+                fig1 = box_plt(df, variable)
+                st.plotly_chart(fig1, use_container_width=True)
+
+    with st.expander("Correlation Heat Map for NUTS 2 Regional Data"):
+        fig = corr_heatmap(df)
+        st.pyplot(fig)
+
+with tab2:
+    st.markdown("##### Regression Modelling for NUTS 2 Regional Data")
+
+    lin_reg_cont = st.container()
+
+    col3, col4 = st.columns(2)
+    col5, col6 = st.columns(2)
+    iv = col3.selectbox("Choose X: ", options=num_cols, index=1)
+    dv = col4.selectbox("Choose Y: ", options=num_cols, index=3)
+    model_dict = {"Linear Regression": "ols", "LOWESS": "lowess"}
+    model = col5.radio("Choose Model: ", options=model_dict.keys(), horizontal=True)
+
+    if model == "Linear Regression":
+        show_res = col6.checkbox("View Model Summary", value=False)
+
+    with lin_reg_cont:
+        fig2 = lin_reg_plt(df, iv, dv, model_dict[model])
+        st.plotly_chart(fig2, use_container_width=True)
+
+        if "show_res" in globals() and show_res == True:
+            summary = px.get_trendline_results(fig2).px_fit_results.iloc[0].summary()
+            st.write(summary)

requirements.txt

@@ -0,0 +1,10 @@
+eurostatapiclient==0.2.7
+plotly==5.7.0
+streamlit==1.11.1
+pandas==1.3.5
+matplotlib==3.6.2
+seaborn==0.11.1
+statsmodels==0.12.2
+patsy==0.5.1
+numpy==1.22.4
+scipy==1.6.2

stat_mod/__init__.py

@@ -0,0 +1,6 @@
+from stat_mod.data_opt import *
+from stat_mod.datasets import *
+from stat_mod.definitions import *
+from stat_mod.figures import *
+from stat_mod.text import *
+from stat_mod.utils import *

stat_mod/definitions.py

@@ -0,0 +1,480 @@
+countries = {
+    "Austria": "AT",
+    "Belgium": "BE",
+    "Bulgaria": "BG",
+    "Croatia": "HR",
+    "Cyprus": "CY",
+    "Czechia": "CZ",
+    "Denmark": "DK",
+    "Estonia": "EE",
+    "Finland": "FI",
+    "France": "FR",
+    "Germany": "DE",
+    "Greece": "EL",
+    "Hungary": "HU",
+    "Ireland": "IE",
+    "Italy": "IT",
+    "Latvia": "LV",
+    "Lithuania": "LT",
+    "Luxembourg": "LU",
+    "Malta": "MT",
+    "Netherlands": "NL",
+    "Poland": "PL",
+    "Portugal": "PT",
+    "Romania": "RO",
+    "Slovakia": "SK",
+    "Slovenia": "SI",
+    "Spain": "ES",
+    "Sweden": "SE",
+}
+
+countries_ISO3 = {
+    "AUT": " Austria",
+    "BEL": " Belgium",
+    "BGR": " Bulgaria",
+    "HRV": " Croatia",
+    "CYP": " Cyprus",
+    "CZE": " Czech Republic",
+    "DNK": " Denmark",
+    "EST": " Estonia",
+    "FIN": " Finland",
+    "FRA": " France",
+    "DEU": " Germany",
+    "GRC": " Greece",
+    "HUN": " Hungary",
+    "IRL": " Ireland",
+    "ITA": " Italy",
+    "LVA": " Latvia",
+    "LTU": " Lithuania",
+    "LUX": " Luxembourg",
+    "MLT": " Malta",
+    "NLD": " Netherlands",
+    "POL": " Poland",
+    "PRT": " Portugal",
+    "ROU": " Romania",
+    "SVK": " Slovakia",
+    "SVN": " Slovenia",
+    "ESP": " Spain",
+    "SWE": " Sweden",
+}
+
+nuts_codes = {
+    "AL": {
+        "AL01": "Veri",
+        "AL02": "Qender",
+        "AL03": "Jug",
+        "ALZZ": "Extra-Regio NUTS 2",
+    },
+    "AT": {
+        "AT11": "Burgenland",
+        "AT12": "Niederösterreich",
+        "AT13": "Wien",
+        "AT21": "Kärnten",
+        "AT22": "Steiermark",
+        "AT31": "Oberösterreich",
+        "AT32": "Salzburg",
+        "AT33": "Tirol",
+        "AT34": "Vorarlberg",
+        "ATZZ": "Extra-Regio NUTS 2",
+    },
+    "BE": {
+        "BE10": "Région de Bruxelles-Capitale/ Brussels Hoofdstedelijk Gewest",
+        "BE21": "Prov. Antwerpen",
+        "BE22": "Prov. Limburg (BE)",
+        "BE23": "Prov. Oost-Vlaanderen",
+        "BE24": "Prov. Vlaams-Brabant",
+        "BE25": "Prov. West-Vlaanderen",
+        "BE31": "Prov. Brabant Wallon",
+        "BE32": "Prov. Hainaut",
+        "BE33": "Prov. Liège",
+        "BE34": "Prov. Luxembourg (BE)",
+        "BE35": "Prov. Namur",
+        "BEZZ": "Extra-Regio NUTS 2",
+    },
+    "BG": {
+        "BG31": "Северозападен (Severozapaden)",
+        "BG32": "Северен централен (Severen tsentralen)",
+        "BG33": "Североизточен (Severoiztochen)",
+        "BG34": "Югоизточен (Yugoiztochen)",
+        "BG41": "Югозападен (Yugozapaden)",
+        "BG42": "Южен централен (Yuzhen tsentralen)",
+        "BGZZ": "Extra-Regio NUTS 2",
+    },
+    "CH": {
+        "CH01": "Région lémanique",
+        "CH02": "Espace Mittelland",
+        "CH03": "Nordwestschweiz",
+        "CH04": "Zürich",
+        "CH05": "Ostschweiz",
+        "CH06": "Zentralschweiz",
+        "CH07": "Ticino",
+        "CHZZ": "Extra-Regio NUTS 2",
+    },
+    "CY": {"CY00": "Κύπρος (Kypros)", "CYZZ": "Extra-Regio NUTS 2"},
+    "CZ": {
+        "CZ01": "Praha",
+        "CZ02": "Střední Čechy",
+        "CZ03": "Jihozápad",
+        "CZ04": "Severozápad",
+        "CZ05": "Severovýchod",
+        "CZ06": "Jihovýchod",
+        "CZ07": "Střední Morava",
+        "CZ08": "Moravskoslezsko",
+        "CZZZ": "Extra-Regio NUTS 2",
+    },
+    "DE": {
+        "DE11": "Stuttgart",
+        "DE12": "Karlsruhe",
+        "DE13": "Freiburg",
+        "DE14": "Tübingen",
+        "DE21": "Oberbayern",
+        "DE22": "Niederbayern",
+        "DE23": "Oberpfalz",
+        "DE24": "Oberfranken",
+        "DE25": "Mittelfranken",
+        "DE26": "Unterfranken",
+        "DE27": "Schwaben",
+        "DE30": "Berlin",
+        "DE40": "Brandenburg",
+        "DE50": "Bremen",
+        "DE60": "Hamburg",
+        "DE71": "Darmstadt",
+        "DE72": "Gießen",
+        "DE73": "Kassel",
+        "DE80": "Mecklenburg-Vorpommern",
+        "DE91": "Braunschweig",
+        "DE92": "Hannover",
+        "DE93": "Lüneburg",
+        "DE94": "Weser-Ems",
+        "DEA1": "Düsseldorf",
+        "DEA2": "Köln",
+        "DEA3": "Münster",
+        "DEA4": "Detmold",
+        "DEA5": "Arnsberg",
+        "DEB1": "Koblenz",
+        "DEB2": "Trier",
+        "DEB3": "Rheinhessen-Pfalz",
+        "DEC0": "Saarland",
+        "DED2": "Dresden",
+        "DED4": "Chemnitz",
+        "DED5": "Leipzig",
+        "DEE0": "Sachsen-Anhalt",
+        "DEF0": "Schleswig-Holstein",
+        "DEG0": "Thüringen",
+        "DEZZ": "Extra-Regio NUTS 2",
+    },
+    "DK": {
+        "DK01": "Hovedstaden",
+        "DK02": "Sjælland",
+        "DK03": "Syddanmark",
+        "DK04": "Midtjylland",
+        "DK05": "Nordjylland",
+        "DKZZ": "Extra-Regio NUTS 2",
+    },
+    "EE": {"EE00": "Eesti", "EEZZ": "Extra-Regio NUTS 2"},
+    "EL": {
+        "EL30": "Aττική (Attiki)",
+        "EL41": "Βόρειο Αιγαίο (Voreio Aigaio)",
+        "EL42": "Νότιο Αιγαίο (Notio Aigaio)",
+        "EL43": "Κρήτη (Kriti)",
+        "EL51": "Aνατολική Μακεδονία, Θράκη (Anatoliki Makedonia, Thraki)",
+        "EL52": "Κεντρική Μακεδονία (Kentriki Makedonia)",
+        "EL53": "Δυτική Μακεδονία (Dytiki Makedonia)",
+        "EL54": "Ήπειρος (Ipeiros)",
+        "EL61": "Θεσσαλία (Thessalia)",
+        "EL62": "Ιόνια Νησιά (Ionia Nisia)",
+        "EL63": "Δυτική Ελλάδα (Dytiki Ellada)",
+        "EL64": "Στερεά Ελλάδα (Sterea Ellada)",
+        "EL65": "Πελοπόννησος (Peloponnisos)",
+        "ELZZ": "Extra-Regio NUTS 2",
+    },
+    "ES": {
+        "ES11": "Galicia",
+        "ES12": "Principado de Asturias",
+        "ES13": "Cantabria",
+        "ES21": "País Vasco",
+        "ES22": "Comunidad Foral de Navarra",
+        "ES23": "La Rioja",
+        "ES24": "Aragón",
+        "ES30": "Comunidad de Madrid",
+        "ES41": "Castilla y León",
+        "ES42": "Castilla-La Mancha",
+        "ES43": "Extremadura",
+        "ES51": "Cataluña",
+        "ES52": "Comunitat Valenciana ",
+        "ES53": "Illes Balears",
+        "ES61": "Andalucía",
+        "ES62": "Región de Murcia",
+        "ES63": "Ciudad de Ceuta",
+        "ES64": "Ciudad de Melilla",
+        "ES70": "Canarias",
+        "ESZZ": "Extra-Regio NUTS 2",
+    },
+    "FI": {
+        "FI19": "Länsi-Suomi",
+        "FI1B": "Helsinki-Uusimaa",
+        "FI1C": "Etelä-Suomi",
+        "FI1D": "Pohjois- ja Itä-Suomi",
+        "FI20": "Åland",
+        "FIZZ": "Extra-Regio NUTS 2",
+    },
+    "FR": {
+        "FR10": "Ile-de-France",
+        "FRB0": "Centre — Val de Loire",
+        "FRC1": "Bourgogne",
+        "FRC2": "Franche-Comté",
+        "FRD1": "Basse-Normandie ",
+        "FRD2": "Haute-Normandie ",
+        "FRE1": "Nord-Pas de Calais",
+        "FRE2": "Picardie",
+        "FRF1": "Alsace",
+        "FRF2": "Champagne-Ardenne",
+        "FRF3": "Lorraine",
+        "FRG0": "Pays de la Loire",
+        "FRH0": "Bretagne",
+        "FRI1": "Aquitaine",
+        "FRI2": "Limousin",
+        "FRI3": "Poitou-Charentes",
+        "FRJ1": "Languedoc-Roussillon",
+        "FRJ2": "Midi-Pyrénées",
+        "FRK1": "Auvergne",
+        "FRK2": "Rhône-Alpes",
+        "FRL0": "Provence-Alpes-Côte d’Azur",
+        "FRM0": "Corse",
+        "FRY1": "Guadeloupe",
+        "FRY2": "Martinique ",
+        "FRY3": "Guyane",
+        "FRY4": "La Réunion ",
+        "FRY5": "Mayotte",
+        "FRZZ": "Extra-Regio NUTS 2",
+    },
+    "HR": {
+        "HR02": "Panonska Hrvatska",
+        "HR03": "Jadranska Hrvatska",
+        "HR05": "Grad Zagreb",
+        "HR06": "Sjeverna Hrvatska",
+        "HRZZ": "Extra-Regio NUTS 2",
+    },
+    "HU": {
+        "HU11": "Budapest",
+        "HU12": "Pest",
+        "HU21": "Közép-Dunántúl",
+        "HU22": "Nyugat-Dunántúl",
+        "HU23": "Dél-Dunántúl",
+        "HU31": "Észak-Magyarország",
+        "HU32": "Észak-Alföld",
+        "HU33": "Dél-Alföld",
+        "HUZZ": "Extra-Regio NUTS 2",
+    },
+    "IE": {
+        "IE04": "Northern and Western",
+        "IE05": "Southern",
+        "IE06": "Eastern and Midland",
+        "IEZZ": "Extra-Regio NUTS 2",
+    },
+    "IS": {"IS00": "Ísland", "ISZZ": "Extra-Regio NUTS 2"},
+    "IT": {
+        "ITC1": "Piemonte",
+        "ITC2": "Valle d’Aosta/Vallée d’Aoste",
+        "ITC3": "Liguria",
+        "ITC4": "Lombardia",
+        "ITF1": "Abruzzo",
+        "ITF2": "Molise",
+        "ITF3": "Campania",
+        "ITF4": "Puglia",
+        "ITF5": "Basilicata",
+        "ITF6": "Calabria",
+        "ITG1": "Sicilia",
+        "ITG2": "Sardegna",
+        "ITH1": "Provincia Autonoma di Bolzano/Bozen",
+        "ITH2": "Provincia Autonoma di Trento",
+        "ITH3": "Veneto",
+        "ITH4": "Friuli-Venezia Giulia",
+        "ITH5": "Emilia-Romagna",
+        "ITI1": "Toscana",
+        "ITI2": "Umbria",
+        "ITI3": "Marche",
+        "ITI4": "Lazio",
+        "ITZZ": "Extra-Regio NUTS 2",
+    },
+    "LI": {"LI00": "Liechtenstein", "LIZZ": "Extra-Regio NUTS 2"},
+    "LT": {
+        "LT01": "Sostinės regionas",
+        "LT02": "Vidurio ir vakarų Lietuvos regionas ",
+        "LTZZ": "Extra-Regio NUTS 2",
+    },
+    "LU": {"LU00": "Luxembourg", "LUZZ": "Extra-Regio NUTS 2"},
+    "LV": {"LV00": "Latvija", "LVZZ": "Extra-Regio NUTS 2"},
+    "ME": {"ME00": "Црна Гора", "MEZZ": "Extra-Regio NUTS 2"},
+    "MK": {"MK00": "Северна Македонија", "MKZZ": "Extra-Regio NUTS 2"},
+    "MT": {"MT00": "Malta", "MTZZ": "Extra-Regio NUTS 2"},
+    "NL": {
+        "NL11": "Groningen",
+        "NL12": "Friesland (NL)",
+        "NL13": "Drenthe",
+        "NL21": "Overijssel",
+        "NL22": "Gelderland",
+        "NL23": "Flevoland",
+        "NL31": "Utrecht",
+        "NL32": "Noord-Holland",
+        "NL33": "Zuid-Holland",
+        "NL34": "Zeeland",
+        "NL41": "Noord-Brabant",
+        "NL42": "Limburg (NL)",
+        "NLZZ": "Extra-Regio NUTS 2",
+    },
+    "NO": {
+        "NO02": "Innlandet",
+        "NO06": "Trøndelag",
+        "NO07": "Nord-Norge",
+        "NO08": "Oslo og Viken",
+        "NO09": "Agder og Sør-Østlandet",
+        "NO0A": "Vestlandet",
+        "NO0B": "Jan Mayen and Svalbard",
+        "NOZZ": "Extra-Regio NUTS 2",
+    },
+    "PL": {
+        "PL21": "Małopolskie",
+        "PL22": "Śląskie",
+        "PL41": "Wielkopolskie",
+        "PL42": "Zachodniopomorskie",
+        "PL43": "Lubuskie",
+        "PL51": "Dolnośląskie",
+        "PL52": "Opolskie",
+        "PL61": "Kujawsko-pomorskie",
+        "PL62": "Warmińsko-mazurskie",
+        "PL63": "Pomorskie",
+        "PL71": "Łódzkie",
+        "PL72": "Świętokrzyskie",
+        "PL81": "Lubelskie",
+        "PL82": "Podkarpackie",
+        "PL84": "Podlaskie",
+        "PL91": "Warszawski stołeczny",
+        "PL92": "Mazowiecki regionalny",
+        "PLZZ": "Extra-Regio NUTS 2",
+    },
+    "PT": {
+        "PT11": "Norte",
+        "PT15": "Algarve",
+        "PT16": "Centro (PT)",
+        "PT17": "Área Metropolitana de Lisboa",
+        "PT18": "Alentejo",
+        "PT20": "Região Autónoma dos Açores",
+        "PT30": "Região Autónoma da Madeira",
+        "PTZZ": "Extra-Regio NUTS 2",
+    },
+    "RO": {
+        "RO11": "Nord-Vest",
+        "RO12": "Centru",
+        "RO21": "Nord-Est",
+        "RO22": "Sud-Est",
+        "RO31": "Sud-Muntenia",
+        "RO32": "Bucureşti-Ilfov",
+        "RO41": "Sud-Vest Oltenia",
+        "RO42": "Vest",
+        "ROZZ": "Extra-Regio NUTS 2",
+    },
+    "RS": {
+        "RS11": "Београдски регион",
+        "RS12": "Регион Војводине",
+        "RS21": "Регион Шумадије и Западне Србије",
+        "RS22": "Регион Јужне и Источне Србије",
+        "RSZZ": "Extra-Regio NUTS 2",
+    },
+    "SE": {
+        "SE11": "Stockholm",
+        "SE12": "Östra Mellansverige",
+        "SE21": "Småland med öarna",
+        "SE22": "Sydsverige",
+        "SE23": "Västsverige",
+        "SE31": "Norra Mellansverige",
+        "SE32": "Mellersta Norrland",
+        "SE33": "Övre Norrland",
+        "SEZZ": "Extra-Regio NUTS 2",
+    },
+    "SI": {
+        "SI03": "Vzhodna Slovenija",
+        "SI04": "Zahodna Slovenija",
+        "SIZZ": "Extra-Regio NUTS 2",
+    },
+    "SK": {
+        "SK01": "Bratislavský kraj",
+        "SK02": "Západné Slovensko",
+        "SK03": "Stredné Slovensko",
+        "SK04": "Východné Slovensko",
+        "SKZZ": "Extra-Regio NUTS 2",
+    },
+    "TR": {
+        "TR10 ": "İstanbul",
+        "TR21": "Tekirdağ, Edirne, Kırklareli",
+        "TR22": "Balıkesir, Çanakkale",
+        "TR31": "İzmir",
+        "TR32": "Aydın, Denizli, Muğla",
+        "TR33": "Manisa, Afyonkarahisar, Kütahya, Uşak",
+        "TR41": "Bursa, Eskişehir, Bilecik",
+        "TR42": "Kocaeli, Sakarya, Düzce, Bolu, Yalova",
+        "TR51": "Ankara",
+        "TR52": "Konya, Karaman",
+        "TR61": "Antalya, Isparta, Burdur",
+        "TR62": "Adana, Mersin",
+        "TR63": "Hatay, Kahramanmaraş, Osmaniye",
+        "TR71": "Kırıkkale, Aksaray, Niğde, Nevşehir, Kırşehir",
+        "TR72": "Kayseri, Sivas, Yozgat",
+        "TR81": "Zonguldak, Karabük, Bartın",
+        "TR82": "Kastamonu, Çankırı, Sinop",
+        "TR83": "Samsun, Tokat, Çorum, Amasya",
+        "TR90 ": "Trabzon, Ordu, Giresun, Rize, Artvin, Gümüşhane",
+        "TRA1": "Erzurum, Erzincan, Bayburt",
+        "TRA2": "Ağrı, Kars, Iğdır, Ardahan",
+        "TRB1": "Malatya, Elazığ, Bingöl, Tunceli",
+        "TRB2": "Van, Muş, Bitlis, Hakkari",
+        "TRC1": "Gaziantep, Adıyaman, Kilis",
+        "TRC2": "Şanlıurfa, Diyarbakır",
+        "TRC3": "Mardin, Batman, Şırnak, Siirt",
+        "TRZZ": "Extra-Regio NUTS 2",
+    },
+    "UK": {
+        "UKC1": "Tees Valley and Durham",
+        "UKC2": "Northumberland and Tyne and Wear",
+        "UKD1": "Cumbria",
+        "UKD3": "Greater Manchester",
+        "UKD4": "Lancashire",
+        "UKD6": "Cheshire",
+        "UKD7": "Merseyside",
+        "UKE1": "East Yorkshire and Northern Lincolnshire",
+        "UKE2": "North Yorkshire",
+        "UKE3": "South Yorkshire",
+        "UKE4": "West Yorkshire",
+        "UKF1": "Derbyshire and Nottinghamshire",
+        "UKF2": "Leicestershire, Rutland and Northamptonshire",
+        "UKF3": "Lincolnshire",
+        "UKG1": "Herefordshire, Worcestershire and Warwickshire",
+        "UKG2": "Shropshire and Staffordshire",
+        "UKG3": "West Midlands",
+        "UKH1": "East Anglia",
+        "UKH2": "Bedfordshire and Hertfordshire",
+        "UKH3": "Essex",
+        "UKI3": "Inner London — West",
+        "UKI4": "Inner London — East",
+        "UKI5": "Outer London — East and North East",
+        "UKI6": "Outer London — South",
+        "UKI7": "Outer London — West and North West",
+        "UKJ1": "Berkshire, Buckinghamshire and Oxfordshire",
+        "UKJ2": "Surrey, East and West Sussex",
+        "UKJ3": "Hampshire and Isle of Wight",
+        "UKJ4": "Kent",
+        "UKK1": "Gloucestershire, Wiltshire and Bristol/Bath area",
+        "UKK2": "Dorset and Somerset",
+        "UKK3": "Cornwall and Isles of Scilly",
+        "UKK4": "Devon",
+        "UKL1": "West Wales and The Valleys",
+        "UKL2": "East Wales",
+        "UKM5": "North Eastern Scotland",
+        "UKM6": "Highlands and Islands",
+        "UKM7": "Eastern Scotland",
+        "UKM8": "West Central Scotland",
+        "UKM9": "Southern Scotland",
+        "UKN0": "Northern Ireland",
+        "UKZZ": "Extra-Regio NUTS 2",
+    },
+}

stat_mod/figures.py

@@ -0,0 +1,96 @@
+import matplotlib.pyplot as plt
+import plotly.express as px
+import seaborn as sns
+
+from .definitions import *
+
+## Functions for plotting ##
+def lin_reg_plt(df, x, y, model):
+    """Create linear regression plot.
+
+    Returns:
+        plotly.graph_objects
+    """
+    if model == "lowess":
+        trendline_options = dict(frac=0.6)
+    else:
+        trendline_options = None
+
+    # Plotly scatter plot for the data points
+    fig = px.scatter(
+        df,
+        x=x,
+        y=y,
+        trendline=model,
+        height=400,
+        trendline_options=trendline_options,
+        hover_data=["region_name"],
+        trendline_color_override=px.colors.qualitative.D3[3],
+        color_discrete_sequence=px.colors.qualitative.D3,
+    )
+
+    fig.update_layout(
+        plot_bgcolor="white",
+        legend=dict(orientation="h", title=""),
+        margin=dict(l=1, r=1, t=18, b=1, pad=1),
+    )
+
+    return fig
+
+
+def box_plt(df, variable):
+    """Create Plotly box plot.
+
+    Returns:
+        plotly.graph_objects
+    """
+    fig = px.box(
+        df,
+        x="EU Region",
+        y=variable,
+        points="all",
+        color_discrete_sequence=px.colors.qualitative.D3,
+        hover_data=["region_name"],
+        notched=True,
+        title="",
+        color="EU Region",
+        height=400,
+    )
+
+    fig.update_layout(
+        margin=dict(l=1, r=1, t=23, b=1, pad=1),
+        plot_bgcolor="white",
+        showlegend=False,
+        yaxis_title="",
+        xaxis_title="",
+    )
+    return fig
+
+
+def kde_plt(df, variable):
+    """Create kernel density estimation plot.
+
+    Returns:
+        plotly.graph_objects
+    """
+    fig, ax = plt.subplots(figsize=(10, 6))
+
+    ax.grid(False)
+    ax.spines["top"].set_visible(False)
+    ax.spines["right"].set_visible(False)
+    ax.spines["bottom"].set_visible(False)
+    ax.spines["left"].set_visible(False)
+    ax.get_yaxis().set_ticks([])
+
+    sns.kdeplot(data=df, x=variable, fill=True, alpha=0.15, hue="EU Region", ax=ax)
+
+    return fig
+
+
+def corr_heatmap(df):
+    """Create correlation heat map."""
+    fig, ax = plt.subplots(figsize=(10, 8))
+
+    sns.heatmap(df.corr().round(decimals=2), annot=True, ax=ax)
+
+    return fig

stat_mod/text.py

@@ -0,0 +1,10 @@
+intro_text = """Welcome to the EU Data Explorer. This is a small dashboard app displaying data for EU countries sourced from [EuroStat](https://ec.europa.eu/eurostat/web/nuts/background). Statistical analyses and simple regression modelling is showcased in the Analyses page."""
+
+
+analysis_text = """ 
+The app page presents statistical analyses of data for administrative regions in
+EU countries ([NUTS 2](https://ec.europa.eu/eurostat/web/nuts/background) level).
+The **Descriptive Stats** tab includes the dataset, summary statistics and visualizations. 
+Additionally, the **Regression Model** tab provides linear regression or [LOWESS](https://blogs.sas.com/content/iml/2016/10/17/what-is-loess-regression.html) modelling
+by selecting the variables of your preference.
+"""