Plotly

• https://plotly.com/python
• https://plotly.com/python/maps/
• https://plotly.com/python/choropleth-maps/
• https://plotly.com/python/county-choropleth/

Zip Code to State

• https://www.kaggle.com/datasets/danofer/zipcodes-county-fips-crosswalk

PUMAs

• https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas/2020pumas.html

ZCTA

• zip-code tabulated area
• https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
• https://catalog.data.gov/dataset/zip-code-tabulation-areas-census-2000

Zip-Code County

• https://www.huduser.gov/portal/datasets/usps_crosswalk.html

• https://data.world/nrippner/fips-to-zip-code-crosswalk

• https://opendata.stackexchange.com/questions/4335/mapping-counties-to-zip-codes

• Summary: The Geospatial Data Abstraction Library (GDAL)

• https://gdal.org/download.html

• https://opensourceoptions.com/blog/how-to-install-gdal-with-anaconda/

• https://github.com/fitnr/get-tiger

• https://github.com/fitnr/censusgeocode

• https://github.com/OpenDataDE/State-zip-code-GeoJSON

• https://www.census.gov/cgi-bin/geo/shapefiles2010/main

import json
from urllib.request import urlopen

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

import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
                   dtype={"fips": str})

import plotly.express as px

fig = px.choropleth_mapbox(df,
                           geojson=counties,
                           locations='fips',
                           color='unemp',
                           color_continuous_scale="Viridis",
                           range_color=(0, 12),
                           mapbox_style="carto-positron",
                           zoom=3,
                           center = {"lat": 37.0902, "lon": -95.7129},
                           opacity=0.5,
                           labels={'unemp':'unemployment rate'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()