Think of transposition as turning a table on its side: pandas exchanges its rows and columns, changing how the same values are organized for analysis. section 7.6
Use transposition when the current shape makes a comparison, calculation, or presentation easier in the opposite orientation:
- Call df.transpose() or its shorter equivalent df.T. section 7.6
- Transpose a grouped result to place income brackets along one axis and years along the other. section 7.6
- Continue chaining operations after transposition, such as pct_change(), a second transpose, mean(), sort_values(), and head(). section 7.6
Compare income brackets across years
After grouping SAT math scores by Year and calculating means, transpose the selected family-income columns so the income brackets become rows: df.groupby('Year')[['income<20k', '20k<income<40k', '40k<income<60k', '60k<income<80k', '80k<income<100k', 'income>100k']].mean().T. The same pattern appears when grouped tuition statistics are transposed with .transpose() or .T. section 7.6 section 13.3
df.groupby('Year')[['income<20k',
'20k<income<40k',
'40k<income<60k',
'60k<income<80k',
'80k<income<100k',
'income>100k']].mean().T
Inspect the complete grouped-mean expression that uses T to reorient family-income results by year. section 7.6
