pandas.Grouper

class pandas.Grouper(key=None, level=None, freq=None, axis=0, sort=False) [source]

A Grouper allows the user to specify a groupby instruction for a target object

This specification will select a column via the key parameter, or if the level and/or axis parameters are given, a level of the index of the target object.

These are local specifications and will override ‘global’ settings, that is the parameters axis and level which are passed to the groupby itself.

Parameters:

key : string, defaults to None groupby key, which selects the grouping column of the target level : name/number, defaults to None the level for the target index freq : string / frequency object, defaults to None This will groupby the specified frequency if the target selection (via key or level) is a datetime-like object. For full specification of available frequencies, please see here. axis : number/name of the axis, defaults to 0 sort : boolean, default to False whether to sort the resulting labels additional kwargs to control time-like groupers (when `freq` is passed) closed : closed end of interval; ‘left’ or ‘right’ label : interval boundary to use for labeling; ‘left’ or ‘right’ convention : {‘start’, ‘end’, ‘e’, ‘s’} If grouper is PeriodIndex base, loffset

Returns:

A specification for a groupby instruction

Examples

Syntactic sugar for df.groupby('A')

>>> df.groupby(Grouper(key='A'))

Specify a resample operation on the column ‘date’

>>> df.groupby(Grouper(key='date', freq='60s'))

Specify a resample operation on the level ‘date’ on the columns axis with a frequency of 60s

>>> df.groupby(Grouper(level='date', freq='60s', axis=1))

Attributes

ax
groups