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
- 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