Reindex on both index and columns at the same time

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I often need to reindex dataframe on both the index and columns of another dataframe, i.e.

df_out = df2.reindex(df1.index).reindex(df1.columns,axis='columns')

Is there a more efficient way to do this? As in quicker execution. Or less verbose.

pandas dataframe indexing python
1 Answers

reindex setting index and columns in one call

reindex can take both index and columns parameters in one call to do exactly that:

df2.reindex(index=df1.index, columns=df1.columns)

reindex_like to reindex just like another dataframe (both axes):

df2.reindex_like(df1)

Let's check with the same example from the docs:

print(df)
           http_status  response_time
Firefox            200           0.04
Chrome             200           0.02
Safari             404           0.07
IE10               404           0.08
Konqueror          301           1.00

new_index = ['Safari', 'Iceweasel', 'Comodo Dragon', 'IE10','Chrome']
new_columns = ['http_status', 'some_other_col']
df.reindex(index=new_index, columns=new_columns)

                  http_status  some_other_col
Safari               404.0             NaN
Iceweasel              NaN             NaN
Comodo Dragon          NaN             NaN
IE10                 404.0             NaN
Chrome               200.0             NaN
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