""" Cannabis Licenses | Get Missouri Licenses Copyright (c) 2023 Cannlytics Authors: Keegan Skeate <https://github.com/keeganskeate> Candace O'Sullivan-Sutherland <https://github.com/candy-o> Created: 4/26/2023 Updated: 8/13/2023 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE> Description: Collect Missouri cannabis license data. Requirements: The script leverages Google Maps to attempt to geocode license addresses. Ensure that you have a `.env` file with a valid Google Maps API specified as `GOOGLE_MAPS_API_KEY`. Command-line Usage: python get_licenses_mo.py --data_dir <DATA_DIR> --env <ENV_FILE> Data Source: - Missouri Medical Cannabis Licenses URL: <https://health.mo.gov/safety/medical-marijuana/licensed-facilities.php> """ # Standard imports: from datetime import datetime import os import re from typing import Optional # External imports: from bs4 import BeautifulSoup from cannlytics.data.gis import geocode_addresses from dotenv import dotenv_values import numpy as np import pandas as pd import requests import zipcodes # Specify where your data lives. DATA_DIR = '../data/mo' ENV_FILE = '../../../.env' # Specify state-specific constants. STATE = 'MO' MISSOURI = { 'licensing_authority_id': 'MDHSS', 'licensing_authority': 'Missouri Department of Health and Senior Services', 'licenses_url': 'https://health.mo.gov/safety/cannabis/licensed-facilities.php', 'columns': { 'Medical': 'medical', 'Comprehensive': 'adult_use', 'Approved to Operate': 'license_status', 'License \nNumber': 'license_number', 'Entity Name': 'business_legal_name', 'City': 'premise_city', 'State': 'premise_state', 'Postal Code': 'premise_zip_code', ' Contact \nInformation 1': 'first_name', 'Contact \nInformation 1': 'first_name', 'Contact \nInformation 2': 'last_name', 'Contact \nPhone': 'business_phone' }, 'drop': ['first_name', 'last_name'], } def format_phone_number(x): """Format phone numbers as ###-###-####.""" digits = re.sub(r'\D', '', x) return '{}-{}-{}'.format(digits[:3], digits[3:6], digits[6:]) def get_gis_data(df: pd.DataFrame, api_key: str) -> pd.DataFrame: """Get GIS data.""" drop_cols = ['state', 'state_name', 'address', 'formatted_address'] rename_cols = { 'county': 'premise_county', 'latitude': 'premise_latitude', 'longitude': 'premise_longitude' } df = geocode_addresses(df, api_key=api_key, address_field='address') get_city = lambda x: x.split(', ')[1].split(',')[0] if STATE in str(x) else x df['premise_city'] = df['formatted_address'].apply(get_city) df.drop(columns=drop_cols, inplace=True) return df.rename(columns=rename_cols) def get_licenses_mo( data_dir: Optional[str] = None, env_file: Optional[str] = '.env', ): """Get Missouri cannabis license data.""" # Load the environment variables. config = dotenv_values(env_file) google_maps_api_key = config.get('GOOGLE_MAPS_API_KEY') if google_maps_api_key is None: print('Proceeding without `GOOGLE_MAPS_API_KEY`.') # Create the download directory if it doesn't exist. download_dir = os.path.join(data_dir, '.datasets') if not os.path.exists(download_dir): os.makedirs(download_dir) # Get the licenses website content. url = MISSOURI['licenses_url'] response = requests.get(url) soup = BeautifulSoup(response.content, 'html.parser') # Find all workbook links on the website. links = soup.find_all('a') xlsx_links = [x for x in links if x.get('href').endswith('.xlsx')] # Download the files to the download directory. datafiles = [] base = 'https://health.mo.gov/safety/cannabis/xls/' for link in xlsx_links: file_url = base + link.get('href').split('/')[-1] file_name = os.path.join(download_dir, os.path.basename(file_url)) with open(file_name, 'wb') as file: response = requests.get(file_url) file.write(response.content) datafiles.append(file_name) # Open each datafile and extract the data. licenses = [] for datafile in datafiles: # Get the license type from the filename. license_type = datafile.split('\\')[-1].replace('.xlsx', '') \ .replace('licensed-', '') \ .replace('-facilities', '') # Open the workbook. data = pd.read_excel(datafile, skiprows=1) # Rename columns. data.rename(columns=MISSOURI['columns'], inplace=True) # Replace non-NaN columns with True and NaN columns with False. data['license_status'] = data['license_status'].notna() \ .map({True: 'Active', False: 'Inactive'}) # Combine medical / adult_use into `license_designation`. try: data['medical'] = data['medical'].notna().map({True: True, False: False}) data['adult_use'] = data['adult_use'].notna().map({True: True, False: False}) conditions = [ (data['medical'] & data['adult_use']), (data['medical']), (data['adult_use']) ] choices = [ 'medical and adult-use', 'medical', 'adult-use' ] data['license_designation'] = np.select(conditions, choices, default=None) except KeyError: data['license_designation'] = 'adult-use' # Combine owner name columns. data['business_owner_name'] = data['first_name'].str.cat( data['last_name'], sep=' ', ) # Clean the phone numbers. data['business_phone'] = data['business_phone'].apply(str).apply(format_phone_number) # Drop unused columns. unnamed = [x for x in data.columns if re.match('^Unnamed', x)] to_drop = MISSOURI['drop'] + unnamed data.drop(to_drop, axis=1, inplace=True) # Augment GIS data. data['address'] = data['business_legal_name'] + ', ' + data['premise_city'] + ', ' + data['premise_state'] + ' ' + data['premise_zip_code'].astype(str) data = get_gis_data(data, google_maps_api_key) # Get the county. get_county = lambda x: zipcodes.matching(x)[0]['county'] data['county'] = data['premise_zip_code'].astype(str).apply(get_county) # Standardize the license data. data = data.assign( id=data['license_number'].astype(str), business_dba_name=data['business_legal_name'], licensing_authority_id=MISSOURI['licensing_authority_id'], licensing_authority=MISSOURI['licensing_authority'], premise_state=STATE, license_status_date=None, license_type=license_type, license_term=None, issue_date=None, expiration_date=None, business_structure=None, activity=None, parcel_number=None, business_image_url=None, ) # Define metadata. data['data_refreshed_date'] = datetime.now().isoformat() # Sort the columns in alphabetical order data.sort_index(axis=1, inplace=True) # Save the data. if data_dir is not None: if not os.path.exists(data_dir): os.makedirs(data_dir) date = datetime.now().isoformat()[:10] outfile = f'{data_dir}/{license_type}-{STATE.lower()}-{date}.csv' data.to_csv(outfile, index=False) # Record the licenses. licenses.append(data) # Save all of the licenses. licenses = pd.concat(licenses) if data_dir is not None: date = datetime.now().isoformat()[:10] licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{date}.csv', index=False) licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-latest.csv', index=False) # Return the licenses. return licenses # === Test === # [✓] Tested: 2023-08-13 by Keegan Skeate <keegan@cannlytics> if __name__ == '__main__': # Support command line usage. import argparse try: arg_parser = argparse.ArgumentParser() arg_parser.add_argument('--d', dest='data_dir', type=str) arg_parser.add_argument('--data_dir', dest='data_dir', type=str) arg_parser.add_argument('--env', dest='env_file', type=str) args = arg_parser.parse_args() except SystemExit: args = {'data_dir': DATA_DIR, 'env_file': ENV_FILE} # Get licenses, saving them to the specified directory. data_dir = args.get('d', args.get('data_dir')) env_file = args.get('env_file') data = get_licenses_mo(data_dir, env_file=env_file)