numpy.percentile() in python

numpy.percentile() compute the q-th percentile of data along the specified axis. A percentile is a measure indicating the value below which a given percentage of observations in a group falls. Example:

import numpy as np
a = np.array([1, 3, 5, 7, 9])
res = np.percentile(a, 50)
print(res)

5.0

Syntax

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

Parameters:

Returns: The q-th percentile(s) of the array elements. If q is a list, it returns multiple percentiles.

Examples

Example 1: In this example, we compute the 25th, 50th and 75th percentiles of a 1D array.

import numpy as np
a = np.array([10, 20, 30, 40, 50])
res = np.percentile(a, [25, 50, 75])
print(res)

[20. 30. 40.]

Example 2: In this example, we compute the 50th percentile (median) along each row of a 2D array using the axis parameter.

import numpy as np
a = np.array([[10, 7, 4], [3, 2, 1]])
res = np.percentile(a, 50, axis=1)
print(res)

[7. 2.]

Example 3: In this example, we compute the 50th percentile (median) using the method='lower' option.

import numpy as np
a = np.array([1, 2, 3, 4])
res = np.percentile(a, 50, method='lower')
print(res)

2

Example 4: In this example, we compute the 50th percentile (median) along each row of a 2D array and use keepdims=True to preserve the original dimensions.

import numpy as np
a = np.array([[10, 20, 30], [40, 50, 60]])
res = np.percentile(a, 50, axis=1, keepdims=True)
print(res)

[[20.]
 [50.]]