GroupBy

The GroupBy object is returned by calls to .groupby() on a Series or DataFrame. The .groupby() function reassembles the data into distinct groups, often for aggregation.

Example

The following example produces a GroupBy object from a DataFrame and uses it to produce some aggregate results.

import pandas as pd
df = pd.DataFrame({'Key' : ['A', 'A', 'A', 'B', 'B', 'C'],
'Value' : [15., 23., 17., 5., 8., 12.]})
print(df, end='\n\n')
group = df.groupby(['Key'], as_index=False)
print(group.count(), end='\n\n')
print(group.sum(), end='\n\n')
print(group.mean())

This produces the following output:

Key Value
0 A 15.0
1 A 23.0
2 A 17.0
3 B 5.0
4 B 8.0
5 C 12.0
Key Value
0 A 3
1 B 2
2 C 1
Key Value
0 A 55.0
1 B 13.0
2 C 12.0
Key Value
0 A 18.333333
1 B 6.500000
2 C 12.000000

Selected methods of the GroupBy object are listed below:

GroupBy

.count()
Produces a new Series or DataFrame with counts of the values for each group in a GroupBy object.
.max()
Produces a new Series or DataFrame with maximum values for the groups in a GroupBy object.
.mean()
Produces a new Series or DataFrame with aggregate mean values for the groups in a GroupBy object.
.min()
Produces a new Series or DataFrame with minimum values for the groups in a GroupBy object.
.sum()
Produces a new Series or DataFrame with aggregate sums for the groups in a GroupBy object.

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