I used Python, geonames and folium to create a heatmap of the FARTers who have made orders around the country.

farters-heatmp20220317.py

"""
I used Python, geonames and folium to create a heatmap of the FARTers who have made orders around the country. 
I used Mike Cunha's excellent example to aid in creation on the map. https://github.com/mikecunha/pygeo_heatmap

https://python-visualization.github.io/folium/
https://www.geonames.org/ 
"""
import csv, os
from geopy.geocoders import Nominatim
import pandas as pd 
import folium
from folium.plugins import HeatMap

geolocator = Nominatim(user_agent="fart")
loc_hr_dict = {}
loc_dict = {}

with open("FartEtsySoldOrders2022.csv") as orders:
    next(orders)
    read = csv.reader(orders, delimiter=',')
    n_cities = 0
    for row in read:
        city = row[2].lower()
        order_loc = f"{city}, {row[3]} {row[4]}"
        print(order_loc)
        geo_loc = geolocator.geocode(order_loc)
        if city not in loc_hr_dict:
            loc_dict[geo_loc.latitude, geo_loc.longitude] = 1
            loc_hr_dict[city] = 1
            n_cities += 1
        else:
            num = loc_hr_dict.get(city)
            loc_hr_dict[city] = num + 1
            loc_dict[geo_loc.latitude, geo_loc.longitude] = num +1
            print(num + 1)

with open('lat-long.csv', 'w') as f:
    f.write("lat, lon, Total \n")
    for key in loc_dict.keys():
        loc = ', '.join(str(lat_long) for lat_long in key)
        f.write(f"{loc}, {loc_dict[key]}\n")

for_map = pd.read_csv('lat-long.csv', sep=', ', engine='python')
max_amount = for_map['Total'].max()

hmap = folium.Map(location=[35.539, -82.518], zoom_start=7, )

hm_wide = HeatMap( list(zip((for_map.lat.values).tolist(), (for_map.lon.values).tolist(), (for_map.Total.values).tolist())),
                   min_opacity=0.2,
                   radius=17, blur=15, 
                   max_zoom=1, 
                 )

hmap.add_child(hm_wide)
hmap.save(os.path.join('heatmap.html'))