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