NumPy np.quantile()

May 28, 2022 | by Arround The Web | No comments

As the name suggests, the quantile() function in NumPy allows you to calculate the qth quantile of the specified array along a set axis. When working with normal distributions, quantiles and percentiles are very fundamental concepts.

Let us explore NumPy’s quantile function.

Function Syntax

The function syntax is as shown below:

numpy.quantile(a, q, axis=None, out=None, overwrite_input=False, method='linear', keepdims=False, *, interpolation=None)

Function Parameters

The function accepts the parameters as follows:

a – the input array or array_like object.
q – your target quantile to calculate. You can also pass an inclusive sequence of quantiles ranging from 0 to 1.
axis – defines along which axis to calculate the quantile. By default, this value is set to None. Hence, the function will flatten the array and calculate the specified quantile.
out – sets an output array for the result.
overwrite_input – this parameter allows the function to modify the input array.
method – specifies the method used in estimating the quantile. Check the docs to discover the accepted values.

Function Return Value

The function returns the q^th quantile of the specified array along the set axis.

Example #1

The example shown below calculates a single quantile of a specified array.

# import numpy
import numpy as np
arr = np.array([10,20,30,40,50])
print(f".5 quantile: {np.quantile(arr, 0.5)}")

The code above should return the .5 quantile of the values in the provided array. The resulting output is:

.5 quantile: 30.0

Example #2

To calculate multiple quantiles of a given array, we can do:

arr = np.array([10,20,30,40,50])
print(np.quantile(arr, [0.25, 0.25, 0.50]))

The above code calculates the quantiles as specified in the sequence.

The resulting values are as shown below:

[20. 20. 30.]

Example #3

To calculate the quantile of a 2D array along a specific axis:

arr = np.array([[9,5,3], [4,7,1]])
print(np.quantile(arr, .25, axis=0))

For example, we calculate the .25th quantile along axis 0 of the input array in the code above.

The output is as shown:

[5.25 5.5 1.5 ]

Example #4

You can also change the interpolation method as shown in the example below:

arr = np.array([[9,5,3], [4,7,1]])
print(np.quantile(arr, .25, axis=0, interpolation='nearest'))

This results in the following array:

[4 5 1]

Conclusion

Using this article, you should be familiar with the NumPy quantile function and how to use it to calculate the q^th quantiles of a given array along a specified axis.

See you at the next one!!!

Source: linuxhint.com