Pandas DataFrame quantile() Method – Be on the Right Side of Change

Preparation

Before any data manipulation can occur, two (2) new libraries will require installation.

The Pandas library enables access to/from a DataFrame.
The NumPy library supports multi-dimensional arrays and matrices in addition to a collection of mathematical functions.

To install these libraries, navigate to an IDE terminal. At the command prompt ($), execute the code below. For the terminal used in this example, the command prompt is a dollar sign ($). Your terminal prompt may be different.

$ pip install pandas

Hit the <Enter> key on the keyboard to start the installation process.

$ pip install numpy

Hit the <Enter> key on the keyboard to start the installation process.

If the installations were successful, a message displays in the terminal indicating the same.

Feel free to view the PyCharm installation guide for the required libraries.

Add the following code to the top of each code snippet. This snippet will allow the code in this article to run error-free.

import pandas as pd
import numpy as np

DataFrame quantile()

The quantile() method returns the values from a DataFrame/Series at the specified quantile and axis.

The syntax for this method is as follows:

DataFrame.quantile(q=0.5, axis=0, numeric_only=True, interpolation='linear')

Parameter	Description
`q`	This is a value `0 <= q <= 1` and is the quantile(s) to calculate.
`axis`	If zero (0) or index is selected, apply to each column. Default 0. If one (1) apply to each row.
`numeric_only`	Only include columns that contain integers, floats, or boolean values.
`interpolation`	Calculates the estimated median or quartiles for the DataFrame/Series.

To fully understand the interpolation parameter from a mathematical point of view, feel free to check out this tutorial:

This example uses the same stock DataFrame as noted above to determine the quantile(s).

df = pd.DataFrame({'ASL':   [18.93, 17.03, 14.87],
                   'DBL':   [39.91, 41.46, 40.99],
                   'UXL':   [44.01, 43.67, 41.98]})

result = df.quantile(0.15)
print(result)

Line [1] creates a DataFrame from a dictionary of lists and saves it to df.
Line [2] uses the quantile() method to calculate by setting the q (quantile) parameter to 0.15. This output saves to the result variable.
Line [3] outputs the result to the terminal.

Output

ASL	15.518
DBL	40.234
USL	42.487
Name: 0.15, dtype: float64

More Pandas DataFrame Methods

Feel free to learn more about the previous and next pandas DataFrame methods (alphabetically) here:

👈 df.prod()

df.rank() 👉

Also, check out the full cheat sheet overview of all Pandas DataFrame methods.