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Treemaps with python and matplotlib
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import squarify
# qualtities plotted
# squarre area is the town surface area (superf)
# color scale is the town population in 2011 (p11_pop)
# read data from csv file
# data from CAPP opendata http://opendata.agglo-pau.fr/index.php/fiche?idQ=27
df = pd.read_csv("Evolution_et_structure_de_la_population/Evolution_structure_population.csv", sep=";")
df = df.set_index("libgeo")
df = df[["superf", "p11_pop"]]
df2 = df.sort_values(by="superf", ascending=False)
# treemap parameters
x = 0.
y = 0.
width = 100.
height = 100.
cmap = matplotlib.cm.viridis
# color scale on the population
# min and max values without Pau
mini, maxi = df2.drop("PAU").p11_pop.min(), df2.drop("PAU").p11_pop.max()
norm = matplotlib.colors.Normalize(vmin=mini, vmax=maxi)
colors = [cmap(norm(value)) for value in df2.p11_pop]
colors[1] = "#FBFCFE"
# labels for squares
labels = ["%s\n%d km2\n%d hab" % (label) for label in zip(df2.index, df2.superf, df2.p11_pop)]
labels[11] = "MAZERES-\nLEZONS\n%d km2\n%d hab" % (df2["superf"]["MAZERES-LEZONS"], df2["p11_pop"]["MAZERES-LEZONS"])
# make plot
fig = plt.figure(figsize=(12, 10))
fig.suptitle("Population et superficie des communes de la CAPP", fontsize=20)
ax = fig.add_subplot(111, aspect="equal")
ax = squarify.plot(df2.superf, color=colors, label=labels, ax=ax, alpha=.7)
ax.set_xticks([])
ax.set_yticks([])
ax.set_title("L'aire de chaque carré est proportionnelle à la superficie de la commune\n", fontsize=14)
# color bar
# create dummy invisible image with a color map
img = plt.imshow([df2.p11_pop], cmap=cmap)
img.set_visible(False)
fig.colorbar(img, orientation="vertical", shrink=.96)
fig.text(.76, .9, "Population", fontsize=14)
fig.text(.5, 0.1,
"Superficie totale %d km2, Population de la CAPP : %d hab" % (df2.superf.sum(), df2.p11_pop.sum()),
fontsize=14,
ha="center")
fig.text(.5, 0.07,
"Source : http://opendata.agglo-pau.fr/",
fontsize=14,
ha="center")
plt.show()
@gVallverdu

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gVallverdu commented Jul 18, 2016

This is the output :
treemap_capp_pau

@scienceML

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scienceML commented Jan 17, 2017

Hi there, could you tell what version of python, matplotlib did you use? It does not render like you have on your webpage.

@Michael-E-Rose

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Michael-E-Rose commented Feb 22, 2017

Without knowledge of how the data looks like this example is pretty useless.

@hiramf

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hiramf commented Jun 9, 2017

@Michael-E-Rose
I disagree, I've been looking for way to plot treemaps and I find it very helpful. You can look at the data yourself here:
Evolution et structure de la population de 1968 à 2012 sur la CAPP

@smxzehvb

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smxzehvb commented Aug 22, 2017

You probably want to also scale the colorbar without PAU. Line 46 should probably be:

img = plt.imshow([df2.drop("PAU").p11_pop], cmap=cmap)

@yngstr

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yngstr commented Sep 28, 2017

I've tried replicating your example with the data from the link, code runs fine but the treemap has overlapping rectangles and labels, and is generally unreadable/not useful. Mind sharing your versions? using python 2.7 and matplotlib 2.0.2
treemapwut

@natngmk

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natngmk commented Sep 30, 2017

Hi, this is some thing useful. However, learning from your example, my boxes in the plot doesn't have any border. Did I miss something?

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