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Pandas DataFrame quantile() Method

❮ DataFrame Reference


Example

Return the values at the 0.2 quantile for each column:

import pandas as pd

data = [[1, 1, 2], [6, 4, 2], [4, 2, 1], [4, 2, 3]]

df = pd.DataFrame(data)

print(df.quantile(0.2))
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Definition and Usage

The quantile() method calculates the quantile of the values in a given axis. Default axis is row.

By specifying the column axis (axis='columns'), the quantile() method calculates the quantile column-wise and returns the mean value for each row.


Syntax

dataframe.quantile(q, axis, numeric_only, unterpolation)

Parameters

The q, axis, numeric_only parameters are keyword arguments.

Parameter Value Description
q Float
Array
Optional, Default 0.5. Specifies the quantile to calculate.
axis 0
1
'index'
'columns'
Optional, Which axis to check, default 0.
numeric_only True
False
Optional. Specify whether to only check numeric values. Default True
interpolation 'higher'
'linear'
'lower'
'midpoint'
'nearest'
Optional. Specifies the interpolation method to use.

 Return Value

A Series or a DataFrame object with the quantiles.

If the q argument is a Float, the return value will be a Series object.

If the q argument is an Array, the return value will be a DataFrame object.

This function does NOT make changes to the original DataFrame object.


❮ DataFrame Reference