pandas.core.window.rolling.Rolling.quantile#

Rolling.quantile(quantile, interpolation='linear', **kwargs)[source]#

Calculate the rolling quantile.

Parameters

quantilefloat

Quantile to compute. 0 <= quantile <= 1.

interpolation{‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}

This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:

linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j.

lower: i.

higher: j.

nearest: i or j whichever is nearest.

midpoint: (i + j) / 2.

**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.rolling: Calling rolling with Series data.
pandas.DataFrame.rolling: Calling rolling with DataFrames.
pandas.Series.quantile: Aggregating quantile for Series.
pandas.DataFrame.quantile: Aggregating quantile for DataFrame.

Examples

>>> s = pd.Series([1, 2, 3, 4])
>>> s.rolling(2).quantile(.4, interpolation='lower')
0    NaN
1    1.0
2    2.0
3    3.0
dtype: float64

>>> s.rolling(2).quantile(.4, interpolation='midpoint')
0    NaN
1    1.5
2    2.5
3    3.5
dtype: float64

pandas.core.window.rolling.Rolling.aggregate

pandas.core.window.rolling.Rolling.sem