The Pandas Series function agg() used to aggregate using one or more operations over the specified axis. It returns either scalar, Series or DataFrame object.
1 Series.agg(func = None, axis = 0, *args, **kwargs)
2
3 Series.aggregate(func = None, axis = 0, *args, **kwargs)
func : It is a function, string, list or dict that used to for aggregating the data. If a function, it must either work when passed a Series or when passed to Series.apply().
axis : It is either string or an integer that specifies the axis for the function to applied. It can be either 0 or 'index' and not specified the default value will be 0.
args It specifies the positional argument passed to func after the series value.
**kwargs : It specifies the additional keyword arguments passed to func.
1 import pandas as pd
2
3 ser = pd.Series([2, 3, 5, 7])
4 res = ser.agg(min)
5
6 print('The aggregated min of Series object is :')
7 print(res)
In the above example, a Series object is created by passing an array. A agg() function is called by passing pandas min() function that find the minimum value and assign to the variable that will be printed on console.
1 The aggregated min of Series object is :
2 2
agg() with list
1 import pandas as pd
2
3 ser = pd.Series([2, 3, 5, 7])
4 res = ser.agg(['min', 'max'])
5
6 print('The aggregated min of Series object is :')
7 print(res)
In the above example, a agg() function is called by passing a list of functions. It perform specified operations and returns the DataFrame object. The result is assigned to the variable that will be printed on console.
1 The aggregated min of Series object is :
2 min 2
3 max 7
4 dtype: int64
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