I have a value associated with each US state (let's pretend it's the average temperature in January for each state). I want to display this data as a heat map of the United States. To be clear, it would be a map of the US with each state having a color from a color gradient that corresponds to a quantitative value. I don't know what this plot type is called, so I'm having trouble figuring out how to do this in MATLAB or another program, but does anyone know an easy way to do this? I have a vector of data (of length 50) and just need to make a US map plot.


Plotly in Python provides a nice solution:

import plotly.plotly as py
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')

for col in df.columns:
    df[col] = df[col].astype(str)

scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
            [0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]

df['text'] = df['state'] + '<br>' +\
    'Beef '+df['beef']+' Dairy '+df['dairy']+'<br>'+\
    'Fruits '+df['total fruits']+' Veggies ' + df['total veggies']+'<br>'+\
    'Wheat '+df['wheat']+' Corn '+df['corn']

data = [ dict(
        colorscale = scl,
        autocolorscale = False,
        locations = df['code'],
        z = df['total exports'].astype(float),
        locationmode = 'USA-states',
        text = df['text'],
        marker = dict(
            line = dict (
                color = 'rgb(255,255,255)',
                width = 2
        colorbar = dict(
            title = "Millions USD"
    ) ]

layout = dict(
        title = '2011 US Agriculture Exports by State<br>(Hover for breakdown)',
        geo = dict(
            projection=dict( type='albers usa' ),
            showlakes = True,
            lakecolor = 'rgb(255, 255, 255)',

fig = dict( data=data, layout=layout )

url = py.plot( fig, filename='d3-cloropleth-map' )

enter image description here


There are many ways to plot choropleth maps in R. Here's another one that uses the popular grammar of graphics library ggplot:

choro <- left_join(
  USArrests %>% 
    add_rownames("region") %>% 
ggplot(choro, aes(long, lat)) +
  geom_polygon(aes(group = group, fill = Assault)) + 

enter image description here

  • $\begingroup$ Great solution, any way to add Alaska and Hawaii though? $\endgroup$ – Igor Filippov Dec 14 '16 at 21:47
  • $\begingroup$ Hmm like ggplot() + borders("world", region = "usa") + borders("state") + coord_quickmap()? $\endgroup$ – lukeA Dec 14 '16 at 22:45

R, with googlevis package, also provides great solution (interactive html map):

states <- data.frame(state.name, state.x77)
GeoStates <- gvisGeoChart(states, "state.name", "Illiteracy",
                                       width=600, height=400))

enter image description here


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.