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Home ยป Plot a Choropleth Map with Folium and GeoPandas

Plot a Choropleth Map with Folium and GeoPandas

In this blog post, we’ll use GeoPandas and Folium in Python to plot a choropleth map of New York’s unemployment rate per borough. Not because it’s extremely interesting, but because it took me a while to get all the elements in order, and I want to help you save some time.

  • First, I load all necessary packages.
  • Next, I load the ‘nybb’ example dataset.
  • Set to WGS projection (EPSG:4326)
  • Add a column with unemployment numbers (August 2021).
  • Change the column type of BoroCode to string.
import folium
import pandas as pd
import geopandas as gpd

path = gpd.datasets.get_path('nybb')
df = gpd.read_file(path)
df = df.to_crs(epsg = 4326)
df['unemployment'] = pd.Series([4.0, 4.6, 4.5, 4.2, 9.1])
df['BoroCode'] = df['BoroCode'].apply(lambda x: str(x))

This is the resulting table:

Next, we’ll turn our geometry column into a GeoJSON.

  • Because you’ll want to join your unemployment data on the JSON, make sure you set it as the index!
  • Equally important, make sure you converted it to a string in the previous step, otherwise your join won’t work.
geo = gpd.GeoSeries(df.set_index('BoroCode')['geometry']).to_json()

Next, create the Choropleth.

  • We have a GeoJSON that contains the geographical data. It is passed to the geo_data parameter.
  • We have our DataFrame that contains the unemployment data (columns ‘BoroCode’ and ‘unemployment’), passed to the data parameter. We join it on the GeoJSON’s ‘’ key.
m = folium.Map(location = [40.70, -73.94], zoom_start = 10)
    geo_data = geo,
    name = 'Choropleth',
    data = df,
    columns = ['BoroCode','unemployment'],
    key_on = '',
    fill_color = 'YlGnBu',
    fill_opacity = 0.5,
    line_opacity = 1,
    legend_name = 'Unemployment (%)',
    smooth_factor=  0

Finally, render the map. Due to the complexity of the polygons, you might want to use the following method instead of simply printing the map if you’re using Jupyter.

def embed_map(m):
    from IPython.display import IFrame'index.html')
    return IFrame('index.html', width='100%', height='750px')

And there we go:

Choropleth using Folium and GeoPandas

Say thanks, ask questions or give feedback

Technologies get updated, syntax changes and honestly… I make mistakes too. If something is incorrect, incomplete or doesn’t work, let me know in the comments below and help thousands of visitors.

5 thoughts on “Plot a Choropleth Map with Folium and GeoPandas”

  1. Thanks for this!
    -I tried using a smoothing factor to see if would render inline, but it wouldn’t even with it very high. I wonder if it’s the transparency.
    -The embed code doesn’t need to be wrapped in a function
    -I tried this with some data of mine and it plotted with every polygon in gray even though the legend showed the appropriate colors and range. Any ideas?

  2. Solved ๐Ÿ™‚
    The index shared between the DataFrame and the GeoSeries converted to JSON has to be a string, it can’t be e.g. an integer!

  3. Hey there,

    This has been super helpful – thanks so much! Just one question – do you know what classification scheme this uses by default? And I know geopandas with matplotlib allows changing the classification scheme by using ‘scheme = …’ – how would the scheme be changed in folium? I cannot seem to find this online!

    Thanks again for this highly useful page!

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