Reputation: 411
I am reading in two files into Python, both with the form:
0.00902317 0.0270695 0.0451159 0.0631622 \
0000010 6.962980e-05 7.063750e-05 7.165970e-05 7.269680e-05
1000010 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
2000010 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
The first row is an ID number, and the columns are different ages. The two files have different ages comprising them, and only a few common ID#s.
Ultimately I am combining the two dataframes to find the common ID#s. But I want the resulting dataframe
File 1 File 2
0.00902317 0.0270695 0.0675493 0.1091622 \
0000010 6.962980e-05 7.063750e-05 0.000000e+00 0.000000e+00
1000010 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
2000010 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
Is there a way to make a dataframe that looks like this, multiindexing columns?
Apologies if this is a simple question, I am new to working with dataframes.
Upvotes: 2
Views: 103
Reputation: 863711
I think you can use concat
:
print (pd.concat([df1, df2], axis=1, keys=['File 1','File 2']))
File 1 File 2
0.00902317 0.0270695 0.0451159 0.0631622 0.0675493 0.1091622
0000010 0.00007 0.000071 0.000072 0.000073 0.0 0.0
1000010 0.00000 0.000000 0.000000 0.000000 0.0 0.0
2000010 0.00000 0.000000 0.000000 0.000000 0.0 0.0
Upvotes: 2