the pie chart example on pandas plotting tutorial http://pandas.pydata.org/pandas-docs/version/0.15.0/visualization.html generates the following figure:
pandas plotting教程http://pandas.pydata.org/pandas-docs/version/0.15.0/visualization.html上的饼图示例生成下图:
with this code:
使用此代码:
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
np.random.seed(123456)
import pandas as pd
df = pd.DataFrame(3 * np.random.rand(4, 2), index=['a', 'b', 'c', 'd'], columns=['x', 'y'])
f, axes = plt.subplots(1,2, figsize=(10,5))
for ax, col in zip(axes, df.columns):
df[col].plot(kind='pie', autopct='%.2f', labels=df.index, ax=ax, title=col, fontsize=10)
ax.legend(loc=3)
plt.show()
I want to remove the text label (a,b,c,d) from both subplots, because for my application those label are long, so I only want to show them in legend.
我想从两个子图中删除文本标签(a,b,c,d),因为对于我的应用程序,这些标签很长,所以我只想在图例中显示它们。
After read this: How to add a legend to matplotlib pie chart?, I figure out an way with matplotlib.pyplot.pie
but the figure is not as fancy even if i am still using ggplot.
看完之后:如何在matplotlib饼图中添加一个图例?,我找到了matplotlib.pyplot.pie的方法,但即使我还在使用ggplot,这个数字并不像花哨一样。
f, axes = plt.subplots(1,2, figsize=(10,5))
for ax, col in zip(axes, df.columns):
patches, text, _ = ax.pie(df[col].values, autopct='%.2f')
ax.legend(patches, labels=df.index, loc='best')
My question is, is there a way that can combine the things I want from both side? to be clear, I want the fanciness from pandas, but remove the text from the wedges.
我的问题是,有没有办法可以将我想要的东西从两边结合起来?要清楚,我想要大熊猫的幻想,但要从楔子中删除文字。
Thank you
1 个解决方案
#1
You can turn off the labels in the chart, and then define them within the call to legend
:
您可以关闭图表中的标签,然后在图例调用中定义它们:
df[col].plot(kind='pie', autopct='%.2f', labels=['','','',''], ax=ax, title=col, fontsize=10)
ax.legend(loc=3, labels=df.index)
or
... labels=None ...
#1
You can turn off the labels in the chart, and then define them within the call to legend
:
您可以关闭图表中的标签,然后在图例调用中定义它们:
df[col].plot(kind='pie', autopct='%.2f', labels=['','','',''], ax=ax, title=col, fontsize=10)
ax.legend(loc=3, labels=df.index)
or
... labels=None ...