Examples

import numpy as np
import pandas as pd

df = pd.DataFrame([[2, 3, 4],
                   [5, 6, 7],
                   [8, 9, 10],
                   [np.nan, np.nan, np.nan]],
                  columns=['P', 'Q', 'R'])

Aggregate 'sum' and 'min' functions over the rows:

df.agg(['sum', 'min'])

	P	Q	R
sum	15.0	18.0	21.0
min	2.0	3.0	4.0

Different aggregations per column:

df.agg({'P' : ['sum', 'min'], 'Q' : ['min', 'max']})

	P	Q
max	NaN	9.0
min	2.0	3.0
sum	15.0	NaN

Aggregate over the columns:

df.agg("mean", axis="columns")

0    3.0
1    6.0
2    9.0
3    NaN
dtype: float64