Pivot table on mutiple pandas dataframe

Question

I have large data splitted into 5 dataframes with exactly same rows. Just wondering, if there any efficient way to merge the pivot tables and to process them in parallel.

Process that would like to do is :

df1 --> df1_pivot   ---> Merge(df1_pivot, df2_pivot) ---> df1_df2_pivot
df1 --> df2_pivot

Goal is to process dataframe in parallel and merge them. (using multi-processing).

EDIT: Pivot can be multi-index, like this.

pd.pivot_table(df1, index= ['col4', 'col3' ], columns=[ 'col1', 'col2' ],  
                          values='val_tosum', aggfunc='sum' )

Answer 1

使用pd.concat

pd.concat([df1, df2, df3, df4, df5], axis=1)