How to draw a zip-code level Choropleth map

Question

I have a Pandas dataframe df that looks as follows:

user_id   zip_code    city              county        state
0001      10021       New York          New York      NY
0002      10003       New York          New York      NY
0003      06831       Greenwich         Fairfield     CT
0004      33172       Miami             Miami-Dade    FL
0005      07417       Franklin Lakes    Bergen        NJ

I'm trying to plot a zip-code level choropleth using the following:

from urllib.request import urlopen
import json
import requests

with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)


fig = px.choropleth(df,
                    geojson= counties,
                    locations='fips', 
                    locationmode="USA-states", 
                    scope="usa",
                    color='user_id',
                    color_continuous_scale="blues",
                    )

fig.show()

But, the map is rendering as blank.

How do I render a zip-code level choropleth?

Answer 1

The reason it is not displayed is because the geojson file you are using does not have the zip code data. Therefore, it is necessary to prepare a geojson file with zip codes. As an example, I created a graph with sample data from here. Depending on your data, if you want to handle zip codes for the entire US, the number of data will be huge and will affect the performance.

from urllib.request import urlopen
import json
import requests

# Nevada Zip code
url = 'https://raw.githubusercontent.com/OpenDataDE/State-zip-code-GeoJSON/master/nv_nevada_zip_codes_geo.min.json'
with urlopen(url) as response:
    nv_zip_json = json.load(response)

zip_code = []
for i in range(len(nv_zip_json['features'])):
    code = nv_zip_json['features'][i]['properties']['ZCTA5CE10']
    zip_code.append(code)

import pandas as pd
import numpy as np
df = pd.DataFrame({'zip_code': zip_code, 'value': np.random.randint(0,30, len(nv_zip_json['features']))})
df['zip_code'] = df['zip_code'].astype(str)

import plotly.express as px

fig = px.choropleth(df,
                    geojson= nv_zip_json,
                    locations='zip_code',
                    featureidkey="properties.ZCTA5CE10",
                    color='value',
                    color_continuous_scale="blues",
                    projection="mercator",
                    )

fig.update_geos(fitbounds="locations", visible=False)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})

fig.show()

To draw a map by county using the current data, the following code can be used.

import plotly.express as px

fig = px.choropleth(df,
                    geojson= counties,
                    locations='county',
                    featureidkey="properties.NAME",
                    scope="usa",
                    color='user_id',
                    color_continuous_scale="blues",
                    )

fig.show()