zyn_iowa.py

import requests
import pandas as pd


def get_coordinates_for_iowa_cities(csv_file_path):
    # Read the CSV file into a DataFrame
    df = pd.read_csv(csv_file_path)

    # Filter rows where admin_name is 'Iowa'
    iowa_df = df[df["admin_name"] == "Iowa"]

    # Select only the 'city', 'lat', and 'lng' columns, and rename them
    iowa_cities = iowa_df[["city", "lat", "lng"]].rename(
        columns={"city": "name", "lat": "lat", "lng": "long"}
    )

    # Convert the DataFrame to a list of dictionaries
    iowa_cities_list = iowa_cities.to_dict("records")

    return iowa_cities_list


def convert_data(lat, long, city_name):
    # Store finder API URL
    url = f"https://us.zyn.com/find-a-store/GetStores/?lat={lat}&lng={long}"
    r = requests.get(url)
    data = r.json()
    df = pd.DataFrame(data["Data"])
    df["City"] = city_name  # Add a new column for the city name
    return df


if __name__ == "__main__":
    dfs = []
    cities = get_coordinates_for_iowa_cities(
        "~/Downloads/simplemaps_worldcities_basicv1/worldcities.csv"
    )
    for city in cities:
        df = convert_data(city["lat"], city["long"], city["name"])
        dfs.append(df)

    # Concatenate all DataFrames into a single DataFrame
    final_df = pd.concat(dfs, ignore_index=True)

    # Check for duplicate addresses
    duplicate_addresses = final_df.duplicated(subset=["Address1"], keep=False)

    if duplicate_addresses.any():
        print("Duplicate addresses found:")
        print(final_df[duplicate_addresses])
    else:
        print("No duplicate addresses found.")

    # Save the final DataFrame to a CSV file
    final_df.to_csv("zyn_data_iowa.csv", index=False)