python treemap_Python中的Treemap可视化

你可以使用Pygal库，这很简单

另一个解决方案是你可以使用squarify库，这是我使用的代码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_excel("Customer Success New.xlsx")

df = df.set_index("location_id")

df = df[["user_id", "company_id"]]

df2 = df.sort_values(by="user_id", 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.company_id.min(), df2.company_id.max()

norm = matplotlib.colors.Normalize(vmin=mini, vmax=maxi)

colors = [cmap(norm(value)) for value in df2.company_id]

colors[1] = "#FBFCFE"

# labels for squares

#labels = ["hab" % (label) for label in zip(df2.index, df2.user_id), df2.company_id)]

#labels[11] = "MAZERES" % (df2["user_id"]["MAZERES-LEZONS"], df2["company_id"]["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()