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.

If axis and/or level are passed as keywords to both Grouper and groupby, the values passed to Grouper take precedence.

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 closed : {‘left’ or ‘right’} Closed end of interval. Only when freq parameter is passed. label : {‘left’ or ‘right’} Interval boundary to use for labeling. Only when freq parameter is passed. convention : {‘start’, ‘end’, ‘e’, ‘s’} If grouper is PeriodIndex and freq parameter is passed. base : int, default 0 Only when freq parameter is passed. loffset : string, DateOffset, timedelta object Only when freq parameter is passed.

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