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# pandas.api.typing.Rolling.rank

Rolling.rank(method='average', ascending=True, pct=False, numeric_only=False)

  Calculate the rolling rank.

  Compute the rank of each value within each rolling window. Ties are resolved using the `method` parameter.

  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

    ascending bool, default True

      Whether or not the elements should be ranked in ascending order.

    pct bool, default False

      Whether or not to display the returned rankings in percentile form.

    numeric_only bool, default False

      Include only float, int, boolean columns.

  Returns:
    Series or DataFrame

      Return type is the same as the original object with `np.float64` dtype.

  See also

  `Series.rolling`

    Calling rolling with Series data.

  `DataFrame.rolling`

    Calling rolling with DataFrames.

  `Series.rank`

    Aggregating rank for Series.

  `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