pandas.core.window.expanding.Expanding.rank¶
- Expanding.rank(method='average', ascending=True, pct=False, **kwargs)[source]¶
Calculate the expanding 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.float64
dtype.
See also
pandas.Series.expanding
Calling expanding with Series data.
pandas.DataFrame.expanding
Calling expanding 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.expanding().rank() 0 1.0 1 2.0 2 2.0 3 3.0 4 5.0 5 3.5 dtype: float64
>>> s.expanding().rank(method="max") 0 1.0 1 2.0 2 2.0 3 3.0 4 5.0 5 4.0 dtype: float64
>>> s.expanding().rank(method="min") 0 1.0 1 2.0 2 2.0 3 3.0 4 5.0 5 3.0 dtype: float64