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i have a dataframe that looks like this,

    A            C
0   tcmb    2.730000e+00
1   ntot    1.359208e+17
2   tex     3.524790e+02
3   fwhm    5.622522e+00
4   vlsr    -1.138359e+01
5   size    6.216793e-01
0   tcmb    2.730000e+00
1   ntot    2.408878e+17
2   tex     1.217280e+01
3   fwhm    1.022482e+00

and would like to have a data like this;

tcmb    ntot            tex          fwhm          vlsr            size
2.73    1.359208e+17n   3.524790e+02 5.622522e+00  -1.138359e+01  6.216793e-01  
2.73    2.408878e+17    2.408878e+17 1.022482e+00   2.800713e+01  5.535814e-01

this is what I have used but I am getting something else;

df_pivoted = df.pivot_table(index='A', columns='A', values='C', aggfunc='first')
humblefool_9
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    Use `df = df.assign(g = df.groupby('A').cumcount()).pivot(index='g', columns='A', values='C')` – jezrael May 03 '22 at 12:00

0 Answers0