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- Col1 Col2 Col3
- 0 123.0 33.0 ABC
- 1 345.0 39.0 ABC
- 2 567.0 100.0 ABC
- 3 123.0 82.0 PQR
- 4 345.0 10.0 PQR
- 5 789.0 38.0 PQR
- 6 890.0 97.0 XYZ
- 7 345.0 96.0 XYZ
- Col1 ABC PQR XYZ
- 0 123.0 33.0 82.0 NaN
- 1 345.0 39.0 10.0 96.0
- 2 567.0 100.0 NaN NaN
- 3 789.0 NaN 38.0 NaN
- 4 890.0 NaN NaN 97.0
- print (df.pivot(index='Col1', columns='Col3', values='Col2'))
- Col3 ABC PQR XYZ
- Col1
- 123.0 33.0 82.0 NaN
- 345.0 39.0 10.0 96.0
- 567.0 100.0 NaN NaN
- 789.0 NaN 38.0 NaN
- 890.0 NaN NaN 97.0
- print (df.set_index(['Col1','Col3'])['Col2'].unstack())
- Col3 ABC PQR XYZ
- Col1
- 123.0 33.0 82.0 NaN
- 345.0 39.0 10.0 96.0
- 567.0 100.0 NaN NaN
- 789.0 NaN 38.0 NaN
- 890.0 NaN NaN 97.0
- print (df.pivot_table(index='Col1', columns='Col3', values='Col2'))
- Col3 ABC PQR XYZ
- Col1
- 123.0 33.0 82.0 NaN
- 345.0 39.0 10.0 96.0
- 567.0 100.0 NaN NaN
- 789.0 NaN 38.0 NaN
- 890.0 NaN NaN 97.0
- print (df.groupby(['Col1','Col3']).mean().squeeze().unstack())
- Col3 ABC PQR XYZ
- Col1
- 123.0 33.0 82.0 NaN
- 345.0 39.0 10.0 96.0
- 567.0 100.0 NaN NaN
- 789.0 NaN 38.0 NaN
- 890.0 NaN NaN 97.0
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