问题描述
我有一个数据框,我想用 squarify
绘制树状图。我想通过编辑 country_name
参数在图表上显示 counts
和 labels
,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同时包含 counts
和 country_name
。
解决方法
您可以通过同时循环遍历两列并组合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()