使用secondary_y轴绘制分组数据

Question

I would like to plot 12 graphs (one graph per month) including columns 'A' and 'B' on the left y axis and column 'C' on the right.

Code below plots everything on the left side.

import pandas as pd
index=pd.date_range('2011-1-1 00:00:00', '2011-12-31 23:50:00', freq='1h')
df=pd.DataFrame(np.random.rand(len(index),3),columns=['A','B','C'],index=index)

df2 = df.groupby(lambda x: x.month)
for key, group in df2:
    group.plot()

How to separate columns and use something like this: group.plot({'A','B':style='g'},{'C':secondary_y=True}) ?

Answer 1

You can capture the axes which the Pandas plot() command returns and use it again to plot C specifically on the right axis.

index=pd.date_range('2011-1-1 00:00:00', '2011-12-31 23:50:00', freq='1h')
df=pd.DataFrame(np.random.randn(len(index),3).cumsum(axis=0),columns=['A','B','C'],index=index)

df2 = df.groupby(lambda x: x.month)
for key, group in df2:
    ax = group[['A', 'B']].plot()
    group[['C']].plot(secondary_y=True, ax=ax)

To get all lines in a single legend see: Legend only shows one label when plotting with pandas