pandas.core.window.rolling.Rolling.rank#
- Rolling.rank(method='average', ascending=True, pct=False, numeric_only=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. 
- numeric_onlybool, default False
- Include only float, int, boolean columns. - New in version 1.5.0. 
- **kwargs
- For NumPy compatibility and will not have an effect on the result. - Deprecated since version 1.5.0. 
 
- Returns
- Series or DataFrame
- Return type is the same as the original object with - np.float64dtype.
 
 - See also - pandas.Series.rolling
- Calling rolling with Series data. 
- pandas.DataFrame.rolling
- Calling rolling with DataFrames. 
- pandas.Series.rank
- Aggregating rank for Series. 
- pandas.DataFrame.rank
- Aggregating 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