Pandas DataFrame Aggregate: agg() function

Dataframe.aggregate() function is used to  perform aggregation using one or more operation along the desired axis.
It uses callable, string, dict, or list of string/callables. It can take a string, a function, or a list thereof, and compute all the aggregates at once. 

Syntax

DataFrame.aggregate(func, axis=0, *args, **kwargs)

Parameter

• func: It is a callable function, string, dict or list. It is used for aggression of data.
• axis:By Default 0.{0 or ‘index’, 1 or ‘columns’}
• *args: It is a Positional arguments to pass to function.
• **kwargs: It is a keyword arguments to pass to a function.

Return

It returns aggregated DataFrame.

Example

import pandas as pd
import numpy as np

Physics_marks=[44,np.NaN,47,28,39]
Chemistry_marks=[45,46,np.NaN,40,30]
Maths_marks=[35,38,29,30,np.NaN]

Students_marks=pd.DataFrame({'Physics':Physics_marks,
                             'Chemistry':Chemistry_marks,
                             'Maths':Maths_marks})

Students_marks

Output

1. Along Rows

Students_marks.aggregate(['sum','max'], axis=0)

Output

2. Along Columns

Students_marks.aggregate(['sum','max'], axis=1)

Output