Panda multiply dataframes using dictionary to map columns

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I am looking to multiply element-wise two dataframes with matching indices, using a dictionary to map which columns to multiply together. I can only come up with convoluted ways to do it and I am sure there is a better way, really appreciate the help! thx!

df1:

Index ABC DEF XYZ
01/01/2004 1 2 3
05/01/2004 4 7 2

df2:

Index Echo Epsilon
01/01/2004 5 10
05/01/2004 -1 -2

Dictionary d = {'ABC': 'Echo', 'DEF': 'Echo', 'XYZ': 'Epsilon'}

Expected result:

Index ABC DEF XYZ
01/01/2004 5 10 30
05/01/2004 -4 -7 -4
pandas python
1 Answers

You can use:

# only if not already the index 
df1 = df1.set_index('Index')
df2 = df2.set_index('Index')

df1.mul(df2[df1.columns.map(d)].set_axis(df1.columns, axis=1))

or:

df1.mul(df2.loc[df1.index, df1.columns.map(d)].values)

output:

            ABC  DEF  XYZ
Index                    
01/01/2004    5   10   30
05/01/2004   -4   -7   -4
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