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 |
Optional, Which axis to check, default 0. |
| numeric_only | True |
Optional. Specify whether to only check numeric values. Default True |
| interpolation | 'higher' |
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.
