Columns to row in python

Question

Do we have sas equivalent of proc transpose. i have the following variables

 a b c d e f g
 1 3 4 5 3 2 2
 2 3 3 3 2 4 2

i want to transpose, across columns a and b , dummy out put below:

 a b tranposed_columns transposed_value
 1 3 c                 4
 1 3 d                 5
 1 3 e                 3
 1 3 f                 2
 1 3 g                 2
 2 3 c                 3
 2 3 d                 3
 2 3 e                 2
 2 3 f                 4
 2 3 g                 2

How can i do this in python, in sas i would have written

 proc transpose data=Dummy_data 
 out=ouput_data (rename=(col1=transposed_value _name_=tranposed_columns));
 by a b;
 run;

i tried dummy_data.T , but it tranposes all the data, also tried hands with pivot data, but its not repeating the rows.

dummy_data.pivot_table(index=['a','b'],values=['c','d','e','f','g'], aggfunc='sum', fill_value=0)

@unutbu: right, I missed this was about Pandas; the question title and first paragraph led me to the canonical duplicate. — Martijn Pieters
– Martijn Pieters, Commented Sep 10, 2016 at 11:52

unutbu · Accepted Answer · 2016-09-10 11:52:56Z

2

Use pd.melt to coalesce columns into a single column. Use the id_vars parameter to "protect" certain columns from participating in the melt:

In [11]: pd.melt(df, id_vars=['a','b'], var_name='transposed_columns', value_name='transposed_value')
Out[11]: 
   a  b transposed_columns  transposed_value
0  1  3                  c                 4
1  2  3                  c                 3
2  1  3                  d                 5
3  2  3                  d                 3
4  1  3                  e                 3
5  2  3                  e                 2
6  1  3                  f                 2
7  2  3                  f                 4
8  1  3                  g                 2
9  2  3                  g                 2

answered Sep 10, 2016 at 11:52

unutbu

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1 Comment

Mukul Over a year ago

thanks a lot for de-duplicating it . also this works perfectly fine. simple and elegant solution.

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