| """ | |
| Cannabis Licenses | License Mao | |
| Copyright (c) 2022-2023 Cannlytics | |
| Authors: | |
| Keegan Skeate <https://github.com/keeganskeate> | |
| Candace O'Sullivan-Sutherland <https://github.com/candy-o> | |
| Created: 9/22/2022 | |
| Updated: 9/19/2023 | |
| License: <https://github.com/cannlytics/cannabis-data-science/blob/main/LICENSE> | |
| Description: | |
| Map the adult-use cannabis retailers permitted in the United States: | |
| ✓ Alaska | |
| ✓ Arizona | |
| ✓ California | |
| ✓ Colorado | |
| ✓ Connecticut | |
| ✓ Delaware | |
| ✓ Illinois | |
| ✓ Maine | |
| ✓ Massachusetts | |
| ✓ Michigan | |
| ✓ Missouri | |
| ✓ Montana | |
| ✓ Nevada | |
| ✓ New Jersey | |
| X New York (Under development) | |
| ✓ New Mexico | |
| ✓ Oregon | |
| ✓ Rhode Island | |
| ✓ Vermont | |
| X Virginia (Expected 2024) | |
| ✓ Washington | |
| """ | |
| # External imports. | |
| import folium | |
| import pandas as pd | |
| def create_retailer_map( | |
| df, | |
| color='crimson', | |
| filename=None, | |
| lat='premise_latitude', | |
| long='premise_longitude', | |
| ): | |
| """Create a map of licensed retailers.""" | |
| m = folium.Map( | |
| location=[39.8283, -98.5795], | |
| zoom_start=3, | |
| control_scale=True, | |
| ) | |
| for _, row in df.iterrows(): | |
| folium.Circle( | |
| radius=5, | |
| location=[row[lat], row[long]], | |
| color=color, | |
| ).add_to(m) | |
| if filename: | |
| m.save(filename) | |
| return m | |
| # === Test === | |
| if __name__ == '__main__': | |
| # Read all licenses. | |
| data = pd.read_csv('../data/all/licenses-all-latest.csv') | |
| data = data.loc[ | |
| (~data['premise_latitude'].isnull()) & | |
| (~data['premise_longitude'].isnull()) | |
| ] | |
| # Create a map of all licenses. | |
| map_file = '../analysis/figures/cannabis-licenses-map.html' | |
| m = create_retailer_map(data, filename=map_file) | |
| print('Saved map to', map_file) | |
| # FIXME: Create a PNG image of the map. | |
| # import io | |
| # from PIL import Image | |
| # img_data = m._to_png(30) | |
| # img = Image.open(io.BytesIO(img_data)) | |
| # img.save('../analysis/figures/cannabis-licenses-map.png') | |