Pandas DataFrame quantile() Method

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))

Try it Yourself »

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