| CARVIEW |
Select Language
HTTP/2 200
accept-ranges: bytes
access-control-allow-origin: *
age: 0
cache-control: max-age=600
content-encoding: gzip
content-type: text/html; charset=utf-8
date: Wed, 30 Jul 2025 21:22:03 GMT
etag: W/"687e6266-319718"
expires: Wed, 30 Jul 2025 21:32:02 GMT
last-modified: Mon, 21 Jul 2025 15:53:10 GMT
server: Vercel
strict-transport-security: max-age=63072000
vary: Accept-Encoding
via: 1.1 varnish
x-cache: MISS
x-cache-hits: 0
x-fastly-request-id: 3ca2dcf71759fb548d0f20eb9c8cf69d948d93d6
x-github-request-id: 32BF:1EF9A9:3E70:5670:688A8CF9
x-origin-cache: HIT
x-proxy-cache: MISS
x-robots-tag: index
x-served-by: cache-bom-vanm7210093-BOM
x-timer: S1753910522.469253,VS0,VE613
x-vercel-cache: MISS
x-vercel-id: bom1::7pqj7-1753910522437-a7b604fcae56
content-length: 973898
Usa county choropleth maps in Python
conda install plotly
conda install geopandas
USA County Choropleth Maps in Python
How to create colormaped representations of USA counties by FIPS values in Python.
Plotly Studio: Transform any dataset into an interactive data application in minutes with AI. Sign up for early access now.
Deprecation warning¶
This page describes a legacy "figure factory" method for creating map-like figures using self-filled scatter traces. This is no longer the recommended way to make county-level choropleth maps, instead we recommend using a GeoJSON-based approach to making outline choropleth maps or the alternative tile-based choropleth maps.
Required Packages¶
plotly_geo, geopandas, pyshp and shapely must be installed for this figure factory to run.
Run the following commands to install the correct versions of the following modules:
In [1]:
!pip install plotly-geo==1.0.0
!pip install geopandas==0.8.1
!pip install pyshp==2.1.2
!pip install shapely==1.7.1
Collecting plotly-geo==1.0.0 Downloading plotly_geo-1.0.0-py3-none-any.whl.metadata (834 bytes) Downloading plotly_geo-1.0.0-py3-none-any.whl (23.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 81.6 MB/s eta 0:00:00 Installing collected packages: plotly-geo Successfully installed plotly-geo-1.0.0 Collecting geopandas==0.8.1 Downloading geopandas-0.8.1-py2.py3-none-any.whl.metadata (892 bytes) Collecting pandas>=0.23.0 (from geopandas==0.8.1) Downloading pandas-2.3.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (91 kB) Collecting shapely (from geopandas==0.8.1) Downloading shapely-2.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.8 kB) Collecting fiona (from geopandas==0.8.1) Downloading fiona-1.10.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (56 kB) Collecting pyproj>=2.2.0 (from geopandas==0.8.1) Downloading pyproj-3.6.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (31 kB) Collecting numpy>=1.22.4 (from pandas>=0.23.0->geopandas==0.8.1) Downloading numpy-2.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (60 kB) Collecting python-dateutil>=2.8.2 (from pandas>=0.23.0->geopandas==0.8.1) Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl.metadata (8.4 kB) Collecting pytz>=2020.1 (from pandas>=0.23.0->geopandas==0.8.1) Downloading pytz-2025.2-py2.py3-none-any.whl.metadata (22 kB) Collecting tzdata>=2022.7 (from pandas>=0.23.0->geopandas==0.8.1) Downloading tzdata-2025.2-py2.py3-none-any.whl.metadata (1.4 kB) Requirement already satisfied: certifi in /home/circleci/.pyenv/versions/3.9.23/lib/python3.9/site-packages (from pyproj>=2.2.0->geopandas==0.8.1) (2025.4.26) Collecting six>=1.5 (from python-dateutil>=2.8.2->pandas>=0.23.0->geopandas==0.8.1) Downloading six-1.17.0-py2.py3-none-any.whl.metadata (1.7 kB) Collecting attrs>=19.2.0 (from fiona->geopandas==0.8.1) Downloading attrs-25.3.0-py3-none-any.whl.metadata (10 kB) Requirement already satisfied: click~=8.0 in /home/circleci/.local/lib/python3.9/site-packages (from fiona->geopandas==0.8.1) (8.1.8) Collecting click-plugins>=1.0 (from fiona->geopandas==0.8.1) Downloading click_plugins-1.1.1.2-py2.py3-none-any.whl.metadata (6.5 kB) Collecting cligj>=0.5 (from fiona->geopandas==0.8.1) Downloading cligj-0.7.2-py3-none-any.whl.metadata (5.0 kB) Collecting importlib-metadata (from fiona->geopandas==0.8.1) Downloading importlib_metadata-8.7.0-py3-none-any.whl.metadata (4.8 kB) Collecting zipp>=3.20 (from importlib-metadata->fiona->geopandas==0.8.1) Downloading zipp-3.23.0-py3-none-any.whl.metadata (3.6 kB) Downloading geopandas-0.8.1-py2.py3-none-any.whl (962 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 962.8/962.8 kB 135.7 MB/s eta 0:00:00 Downloading pandas-2.3.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.4/12.4 MB 70.1 MB/s eta 0:00:00 Downloading numpy-2.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (19.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.5/19.5 MB 63.8 MB/s eta 0:00:00 Downloading pyproj-3.6.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.3/8.3 MB 56.1 MB/s eta 0:00:00 Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl (229 kB) Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) Downloading six-1.17.0-py2.py3-none-any.whl (11 kB) Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) Downloading fiona-1.10.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 17.3/17.3 MB 68.1 MB/s eta 0:00:00 Downloading attrs-25.3.0-py3-none-any.whl (63 kB) Downloading click_plugins-1.1.1.2-py2.py3-none-any.whl (11 kB) Downloading cligj-0.7.2-py3-none-any.whl (7.1 kB) Downloading importlib_metadata-8.7.0-py3-none-any.whl (27 kB) Downloading zipp-3.23.0-py3-none-any.whl (10 kB) Downloading shapely-2.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.5/2.5 MB 61.3 MB/s eta 0:00:00 Installing collected packages: pytz, zipp, tzdata, six, pyproj, numpy, cligj, click-plugins, attrs, shapely, python-dateutil, importlib-metadata, pandas, fiona, geopandas ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15/15 [geopandas] Successfully installed attrs-25.3.0 click-plugins-1.1.1.2 cligj-0.7.2 fiona-1.10.1 geopandas-0.8.1 importlib-metadata-8.7.0 numpy-2.0.2 pandas-2.3.1 pyproj-3.6.1 python-dateutil-2.9.0.post0 pytz-2025.2 shapely-2.0.7 six-1.17.0 tzdata-2025.2 zipp-3.23.0 Collecting pyshp==2.1.2 Downloading pyshp-2.1.2.tar.gz (217 kB) Preparing metadata (setup.py) ... - done Building wheels for collected packages: pyshp DEPRECATION: Building 'pyshp' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'pyshp'. Discussion can be found at https://github.com/pypa/pip/issues/6334 Building wheel for pyshp (setup.py) ... - done Created wheel for pyshp: filename=pyshp-2.1.2-py3-none-any.whl size=36357 sha256=c199926e34569aded8e2518232f75cfa920f3cf8c8ebf89c9ee9f64ba7fbba65 Stored in directory: /home/circleci/.cache/pip/wheels/f6/71/55/8728cf20a761b0fbca9ea511b37197287c1fff00f02b74fc1f Successfully built pyshp Installing collected packages: pyshp Successfully installed pyshp-2.1.2 Collecting shapely==1.7.1 Downloading Shapely-1.7.1-1-cp39-cp39-manylinux1_x86_64.whl.metadata (34 kB) Downloading Shapely-1.7.1-1-cp39-cp39-manylinux1_x86_64.whl (1.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.0/1.0 MB 63.6 MB/s eta 0:00:00 Installing collected packages: shapely Attempting uninstall: shapely Found existing installation: shapely 2.0.7 Uninstalling shapely-2.0.7: Successfully uninstalled shapely-2.0.7 Successfully installed shapely-1.7.1
If you are using Windows, follow this post to properly install geopandas and dependencies: https://geoffboeing.com/2014/09/using-geopandas-windows/. If you are using Anaconda, do not use PIP to install the packages above. Instead use conda to install them:
FIPS and Values¶
Every US state and county has an assigned ID regulated by the US Federal Government under the term FIPS (Federal Information Processing Standards) codes. There are state codes and county codes: the 2016 state and county FIPS codes can be found at the US Census Website.
Combine a state FIPS code (eg. 06 for California) with a county FIPS code of the state (eg. 059 for Orange county) and this new state-county FIPS code (06059) uniquely refers to the specified state and county.
ff.create_choropleth only needs a list of FIPS codes and a list of values. Each FIPS code points to one county and each corresponding value in values determines the color of the county.
Simple Example¶
A simple example of this is a choropleth a few counties in California:
In [2]:
import plotly.figure_factory as ff
fips = ['06021', '06023', '06027',
'06029', '06033', '06059',
'06047', '06049', '06051',
'06055', '06061']
values = range(len(fips))
fig = ff.create_choropleth(fips=fips, values=values)
fig.layout.template = None
fig.show()
/home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:774: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:330: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:847: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:852: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.
Change the Scope¶
Even if your FIPS values belong to a single state, the scope defaults to the entire United States as displayed in the example above. Changing the scope of the choropleth shifts the zoom and position of the USA map. You can define the scope with a list of state names and the zoom will automatically adjust to include the state outlines of the selected states.
By default scope is set to ['USA'] which the API treats as identical to passing a list of all 50 state names:
['AK', 'AL', 'CA', ...]
State abbreviations (eg. CA) or the proper names (eg. California) as strings are accepted. If the state name is not recognized, the API will throw a Warning and indicate which FIPS values were ignored.
Another param used in the example below is binning_endpoints. If your values is a list of numbers, you can bin your values into half-open intervals on the real line.
In [3]:
import plotly.figure_factory as ff
import numpy as np
import pandas as pd
df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv')
df_sample_r = df_sample[df_sample['STNAME'] == 'California']
values = df_sample_r['TOT_POP'].tolist()
fips = df_sample_r['FIPS'].tolist()
colorscale = [
'rgb(193, 193, 193)',
'rgb(239,239,239)',
'rgb(195, 196, 222)',
'rgb(144,148,194)',
'rgb(101,104,168)',
'rgb(65, 53, 132)'
]
fig = ff.create_choropleth(
fips=fips, values=values, scope=['CA', 'AZ', 'Nevada', 'Oregon', ' Idaho'],
binning_endpoints=[14348, 63983, 134827, 426762, 2081313], colorscale=colorscale,
county_outline={'color': 'rgb(255,255,255)', 'width': 0.5}, round_legend_values=True,
legend=dict(
title=dict(
text='Population by County'
)
),
title=dict(
text='California and Nearby States'
)
)
fig.layout.template = None
fig.show()
/home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:808: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:330: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:357: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:847: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:852: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.
Single State¶
In [4]:
import plotly.figure_factory as ff
import numpy as np
import pandas as pd
df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv')
df_sample_r = df_sample[df_sample['STNAME'] == 'Florida']
values = df_sample_r['TOT_POP'].tolist()
fips = df_sample_r['FIPS'].tolist()
endpts = list(np.mgrid[min(values):max(values):4j])
colorscale = ["#030512","#1d1d3b","#323268","#3d4b94","#3e6ab0",
"#4989bc","#60a7c7","#85c5d3","#b7e0e4","#eafcfd"]
fig = ff.create_choropleth(
fips=fips, values=values, scope=['Florida'], show_state_data=True,
colorscale=colorscale, binning_endpoints=endpts, round_legend_values=True,
plot_bgcolor='rgb(229,229,229)',
paper_bgcolor='rgb(229,229,229)',
legend_title='Population by County',
county_outline={'color': 'rgb(255,255,255)', 'width': 0.5},
exponent_format=True,
)
fig.layout.template = None
fig.show()
/home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:808: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:330: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:357: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:847: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:852: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.
Multiple States¶
In [5]:
import plotly.figure_factory as ff
import pandas as pd
NE_states = ['Connecticut', 'Maine', 'Massachusetts', 'New Hampshire', 'Rhode Island', 'Vermont']
df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv')
df_sample_r = df_sample[df_sample['STNAME'].isin(NE_states)]
values = df_sample_r['TOT_POP'].tolist()
fips = df_sample_r['FIPS'].tolist()
colorscale = [
'rgb(68.0, 1.0, 84.0)',
'rgb(66.0, 64.0, 134.0)',
'rgb(38.0, 130.0, 142.0)',
'rgb(63.0, 188.0, 115.0)',
'rgb(216.0, 226.0, 25.0)'
]
fig = ff.create_choropleth(
fips=fips, values=values,
scope=NE_states, county_outline={'color': 'rgb(255,255,255)', 'width': 0.5},
legend_title='Population per county'
)
fig.update_layout(
legend_x = 0,
annotations = {'x': -0.12, 'xanchor': 'left'}
)
fig.layout.template = None
fig.show()
/home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:774: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:330: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:357: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:847: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:852: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.
Simplify County, State Lines¶
Below is a choropleth that uses several other parameters. For a full list of all available params call help(ff.create_choropleth)
simplify_countydetermines the simplification factor for the counties. The larger the number, the fewer vertices and edges each polygon has. See https://toblerity.org/shapely/manual.html#object.simplify for more information.simplify_statesimplifies the state outline polygon. See the documentation for more information. Default for bothsimplify_countyandsimplify_stateis 0.02
Note: This choropleth uses a divergent categorical colorscale. See https://react-colorscales.getforge.io/ for other cool colorscales.
In [6]:
import plotly.figure_factory as ff
import pandas as pd
scope = ['Oregon']
df_sample = pd.read_csv(
'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv'
)
df_sample_r = df_sample[df_sample['STNAME'].isin(scope)]
values = df_sample_r['TOT_POP'].tolist()
fips = df_sample_r['FIPS'].tolist()
colorscale = ["#8dd3c7", "#ffffb3", "#bebada", "#fb8072",
"#80b1d3", "#fdb462", "#b3de69", "#fccde5",
"#d9d9d9", "#bc80bd", "#ccebc5", "#ffed6f",
"#8dd3c7", "#ffffb3", "#bebada", "#fb8072",
"#80b1d3", "#fdb462", "#b3de69", "#fccde5",
"#d9d9d9", "#bc80bd", "#ccebc5", "#ffed6f",
"#8dd3c7", "#ffffb3", "#bebada", "#fb8072",
"#80b1d3", "#fdb462", "#b3de69", "#fccde5",
"#d9d9d9", "#bc80bd", "#ccebc5", "#ffed6f"]
fig = ff.create_choropleth(
fips=fips, values=values, scope=scope,
colorscale=colorscale, round_legend_values=True,
simplify_county=0, simplify_state=0,
county_outline={'color': 'rgb(15, 15, 55)', 'width': 0.5},
state_outline={'width': 1},
legend_title='pop. per county',
title='Oregon'
)
fig.layout.template = None
fig.show()
/home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:774: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:330: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:357: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:847: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:852: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.
The Entire USA¶
In [7]:
import plotly.figure_factory as ff
import numpy as np
import pandas as pd
df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/laucnty16.csv')
df_sample['State FIPS Code'] = df_sample['State FIPS Code'].apply(lambda x: str(x).zfill(2))
df_sample['County FIPS Code'] = df_sample['County FIPS Code'].apply(lambda x: str(x).zfill(3))
df_sample['FIPS'] = df_sample['State FIPS Code'] + df_sample['County FIPS Code']
colorscale = ["#f7fbff","#ebf3fb","#deebf7","#d2e3f3","#c6dbef","#b3d2e9","#9ecae1",
"#85bcdb","#6baed6","#57a0ce","#4292c6","#3082be","#2171b5","#1361a9",
"#08519c","#0b4083","#08306b"]
endpts = list(np.linspace(1, 12, len(colorscale) - 1))
fips = df_sample['FIPS'].tolist()
values = df_sample['Unemployment Rate (%)'].tolist()
fig = ff.create_choropleth(
fips=fips, values=values,
binning_endpoints=endpts,
colorscale=colorscale,
show_state_data=False,
show_hover=True, centroid_marker={'opacity': 0},
asp=2.9, title='USA by Unemployment %',
legend_title='% unemployed'
)
fig.layout.template = None
fig.show()
/home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:808: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:330: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:357: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:847: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead. /home/circleci/project/doc/.venv/lib/python3.9/site-packages/plotly/figure_factory/_county_choropleth.py:852: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.
Also see tile county choropleths made in Python: https://plotly.com/python/tile-county-choropleth/
Reference¶
For more info on ff.create_choropleth(), see the full function reference
What About Dash?¶
Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash at https://dash.plot.ly/installation.
Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:
import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )
from dash import Dash, dcc, html
app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])
app.run(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter