使用 squarify.plot 在标签上显示多列值

Question

我有一个数据框，我想用 squarify 绘制树图。我想通过编辑 labels 参数在图表上显示 country_name 和 counts，但它似乎只取一个值。

示例数据

import squarify
import pandas as pd
from matplotlib import pyplot as plt
d = {'country_name':['USA', 'UK', 'Germany'], 'counts':[100, 200, 300]}
dd = pd.DataFrame(data=d)

fig = plt.gcf()
ax = fig.add_subplot()
fig.set_size_inches(16, 4.5)
norm = matplotlib.colors.Normalize(vmin=min(dd.counts), vmax=max(dd.counts))
colors = [matplotlib.cm.Blues(norm(value)) for value in dd.counts]
squarify.plot(label=dd.country_name, sizes=dd.counts, alpha=.7, color=colors)
plt.axis('off')
plt.show()

预期输出将在图表上显示 counts 和 country_name。

Answer 1

您可以通过同时遍历两列并组合字符串来创建标签列表。例如：


import squarify
import pandas as pd
from matplotlib import pyplot as plt
import matplotlib

d = {'country_name': ['USA', 'UK', 'Germany'], 'counts': [100, 200, 300]}
dd = pd.DataFrame(data=d)
labels = [f'{country}\n{count}' for country, count in zip(dd.country_name, dd.counts)]
fig = plt.gcf()
ax = fig.add_subplot()
fig.set_size_inches(16, 4.5)
norm = matplotlib.colors.Normalize(vmin=min(dd.counts), vmax=max(dd.counts))
colors = [matplotlib.cm.Blues(norm(value)) for value in dd.counts]
squarify.plot(label=labels, sizes=dd.counts, alpha=.7, color=colors)
plt.axis('off')
plt.show()

使用 squarify.plot 在标签上显示多列值

Show multiple columns values on labels with squarify.plot

pandas

matplotlib

squarify