Pandas DataFrame: groupby() function

Last update on August 19 2022 21:50:52 (UTC/GMT +8 hours)

DataFrame - groupby() function

The groupby() function is used to group DataFrame or Series using a mapper or by a Series of columns.

A groupby operation involves some combination of splitting the object, applying a function, and combining the results. This can be used to group large amounts of data and compute operations on these groups.

Syntax:

DataFrame.groupby(self, by=None, axis=0, level=None, as_index=True, sort=True, group_keys=True, squeeze=False, observed=False, **kwargs)

Parameters:

Name	Description	Type/Default Value	Required / Optional
by	Used to determine the groups for the groupby. If by is a function, it’s called on each value of the object’s index. If a dict or Series is passed, the Series or dict VALUES will be used to determine the groups (the Series’ values are first aligned; see .align() method). If an ndarray is passed, the values are used as-is determine the groups. A label or list of labels may be passed to group by the columns in self. Notice that a tuple is interpreted as a (single) key.	mapping, function, label, or list of labels	Required
axis	Split along rows (0) or columns (1).	{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required
level	If the axis is a MultiIndex (hierarchical), group by a particular level or levels.	int, level name, or sequence of such, Default Value: None	Required
as_index	For aggregated output, return object with group labels as the index. Only relevant for DataFrame input. as_index=False is effectively “SQL-style” grouped output.	bool Default Value: True	Required
sort	Sort group keys. Get better performance by turning this off. Note this does not influence the order of observations within each group. Groupby preserves the order of rows within each group.	bool Default Value: True	Required
group_keys	When calling apply, add group keys to index to identify pieces.	bool Default Value: True	Required
squeeze	Reduce the dimensionality of the return type if possible, otherwise return a consistent type.	bool Default Value: False	Required
observed	This only applies if any of the groupers are Categoricals. If True: only show observed values for categorical groupers. If False: show all values for categorical groupers.	bool Default Value: False	Required
**kwargs	Optional, only accepts keyword argument 'mutated' and is passed to groupby.		Optional

Returns: DataFrameGroupBy or SeriesGroupBy
Depends on the calling object and returns groupby object that contains information about the groups.

Example:

Download the Pandas DataFrame Notebooks from here.

Previous: DataFrame - transform() function
Next: DataFrame - rolling() function