How do I transpose a dataframe after groupby?

I have this table

I would like to group based on ‘port’ and then have them as columns in a new dataframe that has valueA as rows, like this:

How do I do this?

>Solution :

Example

import pandas as pd
data1 = {'port': [1, 2, 3, 4, 1, 2, 3, 4], 
         'valueA': [3.1, 3.09, 3.09, 3.11, 3.1, 3.1, 3.08, 3.09], 
         'valueB': [58.2, 58.3, 58.15, 58.2, 58.25, 58.25, 58.15, 58.1], 
         'valueC': [0.09, 0.1, 0.09, 0.1, 0.09, 0.09, 0.09, 0.09]}
df = pd.DataFrame(data1)

Code

grp = df.groupby('port').cumcount()
df.set_index([grp, 'port'])['valueA'].unstack().rename_axis('', axis=1)

output:

    1       2       3       4
0   3.1     3.09    3.09    3.11
1   3.1     3.10    3.08    3.09

Intermediate

df & grp:

df                                      grp
    port    valueA  valueB  valueC      
0   1       3.10    58.20   0.09        0
1   2       3.09    58.30   0.10        0
2   3       3.09    58.15   0.09        0
3   4       3.11    58.20   0.10        0
4   1       3.10    58.25   0.09        1
5   2       3.10    58.25   0.09        1
6   3       3.08    58.15   0.09        1
7   4       3.09    58.10   0.09        1