If I have two dataframes, then since pandas 1.1.0 I can compare them along axis 1 as follows:
import pandas as pd
df1 = pd.DataFrame([[1,2,3,4], [1,2,3,4]], index=['A', 'B'])
df2 = pd.DataFrame([[1,2,5,4], [5,2,3,1]], index=['A', 'B'])
df1.compare(df2, align_axis=1)
I would like to rename the self/other labels to something more descriptive.
I am aware of this answer for the align_axis=0 case:
df1.compare(df2, align_axis=0).rename(index={'self': 'left', 'other': 'right'}, level=-1)
But that doesn’t work for align_axis=1:
df1.compare(df2, align_axis=1).rename(index={'self': 'left', 'other': 'right'}, level=-1)
(I also tried with level=0).
I am also aware of this open pull request that would add a suffixes argument to pd.compare that would allow you to do:
df1.compare(df2, align_axis=1, suffixes=["left", "right"])
but until that pull request gets merged, what is the way to currently do this in pandas?
>Solution :
When is axis 1 you should change index to columns in rename
df1.compare(df2, align_axis=1).rename(columns={'self': 'left', 'other': 'right'}, level=-1)
Out[56]:
0 2 3
left right left right left right
A NaN NaN 3.0 5.0 NaN NaN
B 1.0 5.0 NaN NaN 4.0 1.0