how do I make a chloropleth map zip code to column in folium

Question

I am trying to create a chloropleth by mapping zip codes to a cluster column on a data frame playing with stuff I've found on the folium site and tutorials, but I am new to this library.

Using this currently as a tutorial: https://www.roelpeters.be/plot-choropleth-map-geopandas-folium/

I've created a geopandas json file from census zip code data, and get zip code outlines on my folium map, but the zip codes are not coloring to the cluster data. I end up with the entire map in grey, though I know there is data there (due to the locations of businesses and my starting gps coordinates from the iterrowsenter image description here

Any assistance on what steps I'm missing would be greatly appreciated. Do I need the cluster column in the geopandas file?

'''' import pandas as pd import numpy as np import folium import geopandas as gpd

df = pd.read_excel('folliumsample.xlsx')

df.head()

#census shape file from zip code data 2020 https://www.census.gov/geographies/mapping- 
files/time-series/geo/cartographic-boundary.2020.html ZIP Code Tabulation Areas (ZCTAs)
path = "cb_2020_us_zcta520_500k.shp"
geo = gpd.read_file(path)
geojson = geo.to_crs("EPSG:4326")

geojson.rename(columns={'GEOID20':'Zipcode'}, inplace=True) #rename 
zip code to same as my df
df['Zipcode']=df['Zipcode'].astype(int) #change to type int
geojson['Zipcode']=geojson['Zipcode'].astype(int)
df_merged = df.merge(geojson, on=['Zipcode']) #merge both 

df_merged.head()

geo = gpd.GeoSeries(df_merged.set_index('Zipcode') 
['geometry']).to_json() #convert to a json file


mymap = folium.Map(location=[39.6563, -104.7638],
           width = 950, 
           height = 550,
           zoom_start=12,
           tiles='openstreetmap')

folium.Choropleth(
geo_data = geo,
name = 'Choropleth',
data = df_merged,
columns = ['Zipcode','Cluster'],
key_on = 'feature.id',
fill_color = 'YlGnBu',
fill_opacity = 0.5,
line_opacity = 1,
legend_name = 'cluster data',
smooth_factor=  0
).add_to(mymap)

for index, location_info in df.iterrows():
    folium.Marker([location_info["Lat"], location_info["Long"]], 
              popup=location_info["Company_name"], #display 
 business name
              fill_color="#3db7e4" #color businesses
             ).add_to(mymap)''''

Sample data:

Company_name Zipcode City State Lat Long Cluster 0 Comp1 80013 Aurora CO 39.6563 -104.7638 1 1 Comp2 80219 Denver CO 39.6962 -105.0382 0 2 Comp3 80015 Aurora CO 39.6288 -104.7813 2 3 Comp4 80134 Parker CO 39.4626 -104.7754 3 4 Comp5 80634 Greeley CO 40.3963 -104.7871 1 5 Comp6 80016 Aurora CO 39.5815 -104.7171 2 6 Comp7 80525 Fort Collins CO 40.5418 -105.0441 1 7 Comp8 80631 Greeley CO 40.4398 -104.6821 3 8 Comp9 80229 Denver CO 39.8581 -104.9564 1 9 Comp10 80504 Longmont CO 40.1573 -105.0090 1

This is what my geofile looks like for properties:

'{"type": "FeatureCollection", "features": [{"id": "80013", "type": "Feature", "properties": {}, "geometry": {"type": "Polygon", "coordinates": [[[-104.81019612119022, 39.642137465196676], [-104.81014812414129, 39.64442046722674], [-104.81002113260413, 39.65098747304646], [-104.80995013541128, 39.65315147502026], [-104.80995914474724, 39.66050848125328], [-104.80995114870088, 39.663617483909924], [-104.80994615153455, 39.66584648581322], [-104.80993815539817, 39.66888548841048], [-104.80993315769658, 39.67069348995617], [-104.80992815958469, 39.672178491227456], [-104.80992716062626, 39.67299849192606], [-104.80992316292868, 39.67481049347325], [-104.80990417213638, 39.682057499667195], [-104.80759217310714, 39.68207750417318], [-104.8022311753691, 39.68213751463363], [-104.80106317585147, 39.68214251690581], [-104.79099417991726, 39.68210053642], [-104.790141180085, 39.68191953791836], [-104.78154718376396, 39.68208555474938], [-104.77236218749071, 39.682048572550094]

Edit: Added updates to the code. I merged the DF and the geo file, but still same issue. Everything that is fenced is black.

Answer 1

The reason why it was not painted on the map correctly is that first of all both zip codes need to be strings, so I changed them to string format. Also, the association key is feature.properties.Zipcode in the case of a gdf file loaded by geopandas. I don't think there is a color fill for default markers, so I have disabled it. The attached image works with the sample data and is limited to the gdf (geojson) data.

import pandas as pd
import numpy as np
import folium
import geopandas as gpd
import io

# df = pd.read_excel('folliumsample.xlsx')
# df.head()

data = '''
Company_name Zipcode City State Lat Long Cluster
0 Comp1 80013 Aurora CO 39.6563 -104.7638 1 
1 Comp2 80219 Denver CO 39.6962 -105.0382 0 
2 Comp3 80015 Aurora CO 39.6288 -104.7813 2 
3 Comp4 80134 Parker CO 39.4626 -104.7754 3 
4 Comp5 80634 Greeley CO 40.3963 -104.7871 1 
5 Comp6 80016 Aurora CO 39.5815 -104.7171 2 
6 Comp7 80525 "Fort Collins" CO 40.5418 -105.0441 1 
7 Comp8 80631 Greeley CO 40.4398 -104.6821 3 
8 Comp9 80229 Denver CO 39.8581 -104.9564 1 
9 Comp10 80504 Longmont CO 40.1573 -105.0090 1
'''

df = pd.read_csv(io.StringIO(data), delim_whitespace=True)

#census shape file from zip code data 2020 https://www.census.gov/geographies/mapping- 
#files/time-series/geo/cartographic-boundary.2020.html ZIP Code Tabulation Areas (ZCTAs)
path = "/content/cb_2020_us_zcta520_500k.shp"
geo = gpd.read_file(path)
geojson = geo.to_crs("EPSG:4326")

geojson.rename(columns={'GEOID20':'Zipcode'}, inplace=True) #rename 
#zip code to same as my df
df['Zipcode']=df['Zipcode'].astype(str) #change to type int
geojson['Zipcode']=geojson['Zipcode'].astype(str)
df_merged = df.merge(geojson, on=['Zipcode']) #merge both 

df_merged.head()
# sample data sync
geojson = geojson[geojson['Zipcode'].isin(df['Zipcode'])]

mymap = folium.Map(location=[39.6563, -104.7638],
                   #width = 950,
                   #height = 550,
                   zoom_start=10,
                   tiles='openstreetmap')

folium.Choropleth(
    geo_data = geojson,
    name = 'Choropleth',
    data = df_merged,
    columns = ['Zipcode','Cluster'],
    key_on = 'feature.properties.Zipcode',
    fill_color = 'YlGnBu',
    fill_opacity = 0.5,
    line_opacity = 1,
    legend_name = 'cluster data',
    smooth_factor=  0
).add_to(mymap)

for index, location_info in df.iterrows():
    folium.Marker([location_info["Lat"], location_info["Long"]],
                  popup=location_info["Company_name"], #display business name
                  #fill_color="#3db7e4" #color businesses
             ).add_to(mymap)
mymap

I couldn't get the data at the URL in the question, so I got the data from the following site.