groupby

df.groupby(column_name) or df.groupby([column_names])

Groups all DataFrame rows with the same value in column_name or list of column_names.

A groupby operation groups large amounts of data based on the column name(s).

Input:

column_name : string

Groups by the column specified. The column becomes the index.

column_names : list (of strings)

Groups by all listed columns, starting with the first one in the list. The columns become the indices.

Returns:

A new DataFrame with the parameter column(s) as the index and all other columns grouped.

Return Type:

DataFrame

Note:

A groupby() is usually followed by an aggregate method. A groupby() without an aggregate method will return a DataFrameGroupBy object rather than a DataFrame.

Aggregate Methods
.mean()   .median()   .count()   .max()   .min()   .sum()

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pets

Index	Species	Color	Weight	Age
0	dog	black	40	5
1	cat	golden	15	8
2	cat	black	20	9
3	dog	white	80	2
4	dog	black	25	0.5
5	hamster	black	1	3
6	hamster	golden	0.25	0.2

.groupby() with one column

pets.groupby('Species').count()

Index	ID	Color	Weight	Age
cat	2	2	2	2
dog	3	3	3	3
hamster	2	2	2	2

.groupby() with multiple columns

pets.groupby(['Species', 'Color']).count().reset_index()

Index	Species	Color	ID	Weight	Age	Is_Cat	Owner_Comment
0	cat	black	2	2	2	2	2
1	cat	golden	1	1	1	1	1
2	dog	black	2	2	2	2	2
3	dog	white	1	1	1	1	1
4	hamster	black	1	1	1	1	1
5	hamster	golden	1	1	1	1	1