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| # -*- coding: utf-8 -*- | |
| """borgarlina3_leaflet.ipynb | |
| Automatically generated by Colab. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1gxzQen-P5wRoyODWRkWWGomLytSMWTsW | |
| """ | |
| """ | |
| !pip install contextily | |
| !pip install osmnx | |
| !pip install ipyleaflet | |
| !pip install geopandas matplotlib | |
| !pip install folium | |
| """ | |
| from IPython import get_ipython | |
| from IPython.display import display | |
| #import contextily | |
| #import osmnx | |
| import ipyleaflet | |
| import geopandas as gpd | |
| import pandas as pd | |
| import folium | |
| def load_and_preprocess_data(geojson_file, pop_file, smallarea_file, dwellings_file): | |
| lina1 = gpd.read_file(geojson_file) | |
| pop = pd.read_csv(pop_file) | |
| smallarea = gpd.read_file(smallarea_file) | |
| dwellings = pd.read_csv(dwellings_file) | |
| # Pad 'smasvaedi' column with leading zeros | |
| pop['smasvaedi'] = pop['smasvaedi'].astype(str).str.zfill(4) | |
| # Transform to WGS84 | |
| smallarea_wgs84 = smallarea.to_crs(epsg=4326) | |
| lina1_wgs84 = lina1.to_crs(epsg=4326) | |
| # Filter data | |
| pop2024 = pop[(pop['ar'] == 2024) & (pop['aldursflokkur'] == "0-4 ára") & (pop['kyn'] == 1)] | |
| all_dwellings = dwellings[dwellings['framvinda'] == "Fullbúið"].groupby('smasvaedi')['Fjöldi'].sum().reset_index() | |
| # Join dataframes | |
| pop2024_smallarea = smallarea_wgs84.merge(pop2024, left_on='smsv', right_on='smasvaedi', how='left') | |
| all_dwellings_smallarea = smallarea_wgs84.merge(all_dwellings, left_on='fid', right_on='smasvaedi', how='left') | |
| return lina1_wgs84, pop2024_smallarea, all_dwellings_smallarea | |
| def create_map(lina1_wgs84, all_dwellings_smallarea): | |
| m = folium.Map() | |
| # The 'dagsetning' column does not exist in all_dwellings_smallarea | |
| #all_dwellings_smallarea['dagsetning'] = all_dwellings_smallarea['dagsetning'].astype(str) | |
| print(all_dwellings_smallarea.dtypes) | |
| # Add polygons to the map | |
| all_dwellings_smallarea['pubdate'] = all_dwellings_smallarea['pubdate'].astype(str) | |
| folium.Choropleth( | |
| geo_data=all_dwellings_smallarea[all_dwellings_smallarea['nuts3'] == '001'].to_json(), | |
| name="choropleth", | |
| data=all_dwellings_smallarea, | |
| columns=["smasvaedi", "Fjöldi"], | |
| key_on="feature.properties.smasvaedi", | |
| fill_color="YlGn", | |
| fill_opacity=0.7, | |
| line_opacity=0.2, | |
| legend_name="Dwellings" | |
| ).add_to(m) | |
| # Add markers for lina1_wgs84 | |
| for _, r in lina1_wgs84.iterrows(): | |
| folium.Marker(location=[r.geometry.y, r.geometry.x]).add_to(m) | |
| # Display the map | |
| return m | |
| def main(): | |
| geojson_file = "../given_data/cityline_geojson/cityline_2030.geojson" | |
| pop_file = "../given_data/ibuafjoldi.csv" | |
| smallarea_file = "../given_data/smasvaedi_2021.json" | |
| dwellings_file = "../given_data/ibudir.csv" | |
| lina1_wgs84, pop2024_smallarea, all_dwellings_smallarea = load_and_preprocess_data(geojson_file, pop_file, smallarea_file, dwellings_file) | |
| create_map(lina1_wgs84, all_dwellings_smallarea) # Call the function to create the map | |
| if __name__ == "__main__": | |
| main() | |