Combine choropleth map and histogram in Python

About

A choropleth map is a map combined where colors are proportional to values in each region.

This chart has been created by Joseph Barbier, thanks to him for sharing his work here!

Libraries

First, we need to load the following libraries:

import matplotlib.pyplot as plt
import geopandas as gpd
import pandas as pd
from pyfonts import load_google_font
from pypalettes import load_cmap

Dataset

Here we need to load 2 datasets:

one with map data (shape of each state)
one with data for each state

And then we merge them:

path = "https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/refs/heads/master/static/data/usa-salary.csv"
path = "../../static/data/usa-salary.csv"
df_salary = pd.read_csv(path)

path = "https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/refs/heads/master/static/data/us.geojson"
path = "../../static/data/us.geojson"
gdf = gpd.read_file(path).merge(df_salary, on="state")

gdf = gdf[gdf["salary"] < 100]  # remove district of columbia
gdf = gdf[gdf["state"] != "Alaska"]
gdf = gdf[gdf["state"] != "Hawaii"]
gdf.head()

	state	geometry	salary
0	Alabama	MULTIPOLYGON (((-87.41958 30.4796, -87.42683 3...	59.605
2	Arizona	POLYGON ((-111.00627 31.32718, -111.06712 31.3...	66.340
3	Arkansas	POLYGON ((-90.30422 35.00008, -90.30124 34.995...	54.658
4	California	MULTIPOLYGON (((-114.72428 32.71284, -114.7645...	74.819
5	Colorado	POLYGON ((-109.04633 40.99983, -108.88932 40.9...	77.331

We add a centroid column (approximation of the center of the state) that will be used later to add individual state labels:

gdf_projected = gdf.to_crs(epsg=3035)
gdf_projected["centroid"] = gdf_projected.geometry.centroid
gdf["centroid"] = gdf_projected["centroid"].to_crs(gdf.crs)
gdf.head()

	state	geometry	salary	centroid
0	Alabama	MULTIPOLYGON (((-87.41958 30.4796, -87.42683 3...	59.605	POINT (-86.81841 32.78448)
2	Arizona	POLYGON ((-111.00627 31.32718, -111.06712 31.3...	66.340	POINT (-111.63132 34.30186)
3	Arkansas	POLYGON ((-90.30422 35.00008, -90.30124 34.995...	54.658	POINT (-92.43851 34.90643)
4	California	MULTIPOLYGON (((-114.72428 32.71284, -114.7645...	74.819	POINT (-119.36883 37.27561)
5	Colorado	POLYGON ((-109.04633 40.99983, -108.88932 40.9...	77.331	POINT (-105.52816 39.02442)

Basic choropleth map

The key steps here are:

create a colormap (cmap) with the color range we want
create a matplotlib Figure with fig, ax = plt.subplots()
plot the choropleth map with gdf.plot()

Combine choropleth map and histogram in Python: Basic choropleth map

cmap = load_cmap("enara", cmap_type="continuous", reverse=True)
edgecolor = "white"
linewidth = 0

fig, ax = plt.subplots(figsize=(8, 8), dpi=300)

ax.set_xlim(-130, -65)
ax.set_ylim(20, 50)

gdf.plot(ax=ax, column="salary", cmap=cmap, edgecolor=edgecolor, linewidth=linewidth)

fig.tight_layout()

Add barplot

In order to add the barplot, we use the ax.inset_axes() function to create a subplot (smaller) that will contain our barplot.

If you're not familiar with complex layouts in Matplotlib, please check this dedicated lesson where we explain the concept in depth!

Then we customize it a bit so that it uses the right color scale and looks nice.

Combine choropleth map and histogram in Python: Add barplot

cmap = load_cmap("enara", cmap_type="continuous", reverse=True)
edgecolor = "white"
linewidth = 0

fig, ax = plt.subplots(figsize=(8, 8), dpi=300)

gdf.plot(ax=ax, column="salary", cmap=cmap, edgecolor=edgecolor, linewidth=linewidth)

ax.set_xlim(-130, -65)
ax.set_ylim(20, 50)

bar_ax = ax.inset_axes(bounds=[0.05, -0.05, 0.5, 0.4], zorder=-1)
n, bins, _ = bar_ax.hist(gdf["salary"], bins=15, alpha=0)
colors = [cmap((val - min(bins)) / (max(bins) - min(bins))) for val in bins]
bar_ax.bar(
    bins[:-1], n, color=colors, width=2, edgecolor=edgecolor, linewidth=linewidth
)

fig.tight_layout()

Clean the Axes of map and barplot

Here we remove all spines (border of each plot) and clean up the labels in the histogram.

Combine choropleth map and histogram in Python: Clean the Axes of map and barplot

cmap = load_cmap("enara", cmap_type="continuous", reverse=True)
edgecolor = "white"
linewidth = 0

fig, ax = plt.subplots(figsize=(8, 8), dpi=300)

gdf.plot(ax=ax, column="salary", cmap=cmap, edgecolor=edgecolor, linewidth=linewidth)

ax.set_xlim(-130, -65)
ax.set_ylim(20, 50)
ax.axis("off")

bar_ax = ax.inset_axes(bounds=[0.05, -0.05, 0.5, 0.4], zorder=-1)
n, bins, _ = bar_ax.hist(gdf["salary"], bins=15, alpha=0)
colors = [cmap((val - min(bins)) / (max(bins) - min(bins))) for val in bins]
bar_ax.bar(
    bins[:-1], n, color=colors, width=2, edgecolor=edgecolor, linewidth=linewidth
)
bar_ax.spines[["top", "left", "right"]].set_visible(False)
bar_ax.set_yticks([])
x_ticks = list(range(50, 90, 10))
x_tick_labels = [f"{val}k" for val in x_ticks]
bar_ax.set_xticks(x_ticks, labels=x_tick_labels, size=8)
bar_ax.tick_params(axis="x", length=0, pad=5)

fig.tight_layout()

Add individual state labels

The easiest way to find the center of each country is to use the centroid attribute of the geometry column in the geo dataframe. These coordinates can then be used to add annotations to the map.

Since the default font isn't very attractive, we load a font for the annotations. We can then use the load_google_font() function from pyfonts to load the fonts from Google font.

Just before adding the annotations, we define an adjustment dictionary to help us improve the approximate position of the annotations. This is necessary because centroids aren't always ideally positioned for annotations.

Combine choropleth map and histogram in Python: Add individual state labels

font2 = load_google_font("Ubuntu")
cmap = load_cmap("enara", cmap_type="continuous", reverse=True)
edgecolor = "white"
linewidth = 0
text_color = "white"

fig, ax = plt.subplots(figsize=(8, 8), dpi=300)

gdf.plot(ax=ax, column="salary", cmap=cmap, edgecolor=edgecolor, linewidth=linewidth)

ax.set_xlim(-130, -65)
ax.set_ylim(20, 50)
ax.axis("off")

bar_ax = ax.inset_axes(bounds=[0.05, -0.05, 0.5, 0.4], zorder=-1)
n, bins, _ = bar_ax.hist(gdf["salary"], bins=15, alpha=0)
colors = [cmap((val - min(bins)) / (max(bins) - min(bins))) for val in bins]
bar_ax.bar(
    bins[:-1], n, color=colors, width=2, edgecolor=edgecolor, linewidth=linewidth
)
bar_ax.spines[["top", "left", "right"]].set_visible(False)
bar_ax.set_yticks([])
x_ticks = list(range(50, 90, 10))
x_tick_labels = [f"{val}k" for val in x_ticks]
bar_ax.set_xticks(x_ticks, labels=x_tick_labels, size=8, font=font2)
bar_ax.tick_params(axis="x", length=0, pad=5)

exclude = {
    "Indiana",
    "Michigan",
    "Mississippi",
    "Florida",
    "New Jersey",
    "West Virginia",
    "South Carolina",
    "Louisiana",
    "Massachusetts",
    "Vermont",
    "Connedgecolorticut",
    "Maryland",
    "Delaware",
    "Rhode Island",
    "New Hampshire",
}
states_to_annotate = [state for state in gdf.state.to_list() if state not in exclude]

adjustments = {
    "California": (0, -1),
    "Kentucky": (0, -0.2),
    "Washington": (0.5, -0.4),
    "Virginia": (0, -0.2),
    "Idaho": (0, -0.4),
    "New York": (0, -0.2),
}

for state in states_to_annotate:
    centroid = gdf.loc[gdf["state"] == state, "centroid"].values[0]
    x_val, y_val = centroid.coords[0]
    try:
        x_val += adjustments[state][0]
        y_val += adjustments[state][1]
    except KeyError:
        pass
    value = gdf.loc[gdf["state"] == state, "salary"].values[0]
    if value <= 65:
        color_text = "black"
    else:
        color_text = text_color
    ax.text(
        x=x_val,
        y=y_val,
        s=f"{state.upper()}\n${value:.0f}k",
        fontsize=5,
        font=font2,
        color=color_text,
        ha="center",
        va="center",
    )

fig.tight_layout()

Add last annotations

The title, credit and source annotations are added via the fig.text() function at the end:

Combine choropleth map and histogram in Python: Add last annotations

font1 = load_google_font("Ubuntu", italic=True)
font2 = load_google_font("Ubuntu")
cmap = load_cmap("enara", cmap_type="continuous", reverse=True)
edgecolor = "white"
linewidth = 0
text_color = "white"

fig, ax = plt.subplots(figsize=(8, 8), dpi=300)

gdf.plot(ax=ax, column="salary", cmap=cmap, edgecolor=edgecolor, linewidth=linewidth)

ax.set_xlim(-130, -65)
ax.set_ylim(20, 50)
ax.axis("off")

bar_ax = ax.inset_axes(bounds=[0.05, -0.05, 0.5, 0.4], zorder=-1)
n, bins, _ = bar_ax.hist(gdf["salary"], bins=15, alpha=0)
colors = [cmap((val - min(bins)) / (max(bins) - min(bins))) for val in bins]
bar_ax.bar(
    bins[:-1], n, color=colors, width=2, edgecolor=edgecolor, linewidth=linewidth
)
bar_ax.spines[["top", "left", "right"]].set_visible(False)
bar_ax.set_yticks([])
x_ticks = list(range(50, 90, 10))
x_tick_labels = [f"{val}k" for val in x_ticks]
bar_ax.set_xticks(x_ticks, labels=x_tick_labels, size=8, font=font2)
bar_ax.tick_params(axis="x", length=0, pad=5)

exclude = {
    "Indiana",
    "Michigan",
    "Mississippi",
    "Florida",
    "New Jersey",
    "West Virginia",
    "South Carolina",
    "Louisiana",
    "Massachusetts",
    "Vermont",
    "Connedgecolorticut",
    "Maryland",
    "Delaware",
    "Rhode Island",
    "New Hampshire",
}
states_to_annotate = [state for state in gdf.state.to_list() if state not in exclude]

adjustments = {
    "California": (0, -1),
    "Kentucky": (0, -0.2),
    "Washington": (0.5, -0.4),
    "Virginia": (0, -0.2),
    "Idaho": (0, -0.4),
    "New York": (0, -0.2),
}

for state in states_to_annotate:
    centroid = gdf.loc[gdf["state"] == state, "centroid"].values[0]
    x_val, y_val = centroid.coords[0]
    try:
        x_val += adjustments[state][0]
        y_val += adjustments[state][1]
    except KeyError:
        pass
    value = gdf.loc[gdf["state"] == state, "salary"].values[0]
    if value <= 65:
        color_text = "black"
    else:
        color_text = text_color
    ax.text(
        x=x_val,
        y=y_val,
        s=f"{state.upper()}\n${value:.0f}k",
        fontsize=5,
        font=font2,
        color=color_text,
        ha="center",
        va="center",
    )

fig.text(
    x=0.5,
    y=0.8,
    s="Average salary in the United States in 2025",
    ha="center",
    size=22,
    font=load_google_font("Roboto Slab"),
)

credit_params = dict(x=0.9, ha="right", size=7, font=font1, va="bottom")
fig.text(y=0.24, s="Graphic: Joseph Barbier", **credit_params)
fig.text(y=0.22, s="Data from Forbes and the U.S. Census Bureau", **credit_params)
fig.text(y=0.2, s="Data do not include District of Columbia", **credit_params)

fig.tight_layout()

fig.savefig(
    "../../static/graph/web-choropleth-map-with-histogram.png",
    dpi=300,
    bbox_inches="tight",
)

Combine choropleth map and histogram in Python

About

Libraries

Dataset

Basic choropleth map

Add barplot

Clean the Axes of map and barplot

Add individual state labels

Add last annotations

Going further

💡 Out of dataviz inspiration?

Combine choropleth map and histogram in Python

About

Libraries

Dataset

Basic choropleth map

Add barplot

Clean the Axes of map and barplot

Add individual state labels

Add last annotations

Going further

Related posts

Related chart types

💡 Out of dataviz inspiration?