mars.dataframe.Series.quantile#

Series.quantile(q=0.5, interpolation='linear')#

Return value at the given quantile.

Parameters

  • q (float or array-like, default 0.5 (50% quantile)) – 0 <= q <= 1, the quantile(s) to compute.

  • 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.

Returns

If q is an array or a tensor, a Series will be returned where the index is q and the values are the quantiles, otherwise a float will be returned.

Return type

float or Series

See also

core.window.Rolling.quantile, numpy.percentile

Examples

>>> import mars.dataframe as md
>>> s = md.Series([1, 2, 3, 4])
>>> s.quantile(.5).execute()
2.5
>>> s.quantile([.25, .5, .75]).execute()
0.25    1.75
0.50    2.50
0.75    3.25
dtype: float64