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cudf.DataFrame.quantile#

DataFrame.quantile(
q=0.5,
axis=0,
numeric_only=False,
interpolation=None,
method='single',
columns=None,
exact=True,
)[source]#

Return values at the given quantile.

Parameters:
qfloat or array-like

0 <= q <= 1, the quantile(s) to compute

axisint

axis is a NON-FUNCTIONAL parameter

numeric_onlybool, default False

If True, compute the quantile only over numeric columns.

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

This parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j. Default is 'linear' for method="single", and 'nearest' for method="table".

  • 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.

method{‘single’, ‘table’}, default ‘single’

Whether to compute quantiles per-column (‘single’) or over all columns (‘table’). When ‘table’, the only allowed interpolation methods are ‘nearest’, ‘lower’, and ‘higher’.

columnslist of str

List of column names to include.

exactboolean

Whether to use approximate or exact quantile algorithm.

Returns:
Series or DataFrame

If q is an array, a DataFrame will be returned where the index is q, the columns are the columns of self, and the values are the quantiles.

If q is a float, a Series will be returned where the index is the columns of self and the values are the quantiles.

Examples

>>> import cupy as cp
>>> import cudf
>>> df = cudf.DataFrame(cp.array([[1, 1], [2, 10], [3, 100], [4, 100]]),
...                   columns=['a', 'b'])
>>> df
   a    b
0  1    1
1  2   10
2  3  100
3  4  100
>>> df.quantile(0.1)
a    1.3
b    3.7
Name: 0.1, dtype: float64
>>> df.quantile([.1, .5])
       a     b
0.1  1.3   3.7
0.5  2.5  55.0

Pandas Compatibility Note

pandas.DataFrame.quantile()

When q is a scalar and the columns do not share a common dtype (for example a mix of datetime and numeric columns), pandas returns an object-dtype Series. cuDF does not support mixed types under a Series and raises a MixedTypeError instead.

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