pandas.core.window.rolling.Rolling.rank#
- Rolling.rank(method='average', ascending=True, pct=False, **kwargs)[source]#
Calculate the rolling rank.
New in version 1.4.0.
- Parameters
- method{‘average’, ‘min’, ‘max’}, default ‘average’
How to rank the group of records that have the same value (i.e. ties):
average: average rank of the group
min: lowest rank in the group
max: highest rank in the group
- ascendingbool, default True
Whether or not the elements should be ranked in ascending order.
- pctbool, default False
Whether or not to display the returned rankings in percentile form.
- **kwargs
For NumPy compatibility and will not have an effect on the result.
- Returns
- Series or DataFrame
Return type is the same as the original object with
np.float64dtype.
See also
pandas.Series.rollingCalling rolling with Series data.
pandas.DataFrame.rollingCalling rolling with DataFrames.
pandas.Series.rankAggregating rank for Series.
pandas.DataFrame.rankAggregating rank for DataFrame.
Examples
>>> s = pd.Series([1, 4, 2, 3, 5, 3]) >>> s.rolling(3).rank() 0 NaN 1 NaN 2 2.0 3 2.0 4 3.0 5 1.5 dtype: float64
>>> s.rolling(3).rank(method="max") 0 NaN 1 NaN 2 2.0 3 2.0 4 3.0 5 2.0 dtype: float64
>>> s.rolling(3).rank(method="min") 0 NaN 1 NaN 2 2.0 3 2.0 4 3.0 5 1.0 dtype: float64