NumPy median()

import numpy as np

# create an array
array1 = np.array([0, 1, 2, 3, 4, 5, 6, 7])

# calculate the median of the array
median1 = np.median(array1)

print(median1)

# Output: 3.5

median() Syntax

The syntax of the numpy.median() method is:

numpy.median(array, axis = None, out = None, overwrite_input = False, keepdims = <no value>)

median() Arguments

The numpy.median() method takes following arguments:

• array - array containing numbers whose median we need to compute (can be array_like)
• axis (optional) - axis or axes along which the medians are computed (int or tuple of int)
• out (optional) - output array in which to place the result (ndarray)
• override_input (optional) - bool value that determines if intermediate calculations can modify an array
• keepdims (optional) - specifies whether to preserve the shape of the original array (bool)

median() Return Value

The numpy.median() method returns the median of the array.

Example 1: Find the median of a ndArray

import numpy as np

# create an array
array1 = np.array([[[0, 1], 
                    [2, 3]],                     
                    [[4, 5], 
                    [6, 7]]])

# find the median of the entire array
median1 = np.median(array1)

# find the median across axis 0
median2 = np.median(array1, 0)

# find the median across axis 0 and 1
median3 = np.median(array1, (0, 1))

print('\nmedian of the entire array:', median1)
print('\nmedian across axis 0:\n', median2)
print('\nmedian across axis 0 and 1', median3)

Output

median of the entire array: 3.5

median across axis 0:
 [[2. 3.]
 [4. 5.]]

median across axis 0 and 1 [3. 4.]

Example 2: Using Optional keepdims Argument

If keepdims is set to True, the resultant median array is of the same number of dimensions as the original array.

import numpy as np

array1 = np.array([[1, 2, 3],
                [4, 5, 6]])

# keepdims defaults to False
result1 = np.median(array1, axis = 0)

# pass keepdims as True
result2 = np.median(array1, axis = 0, keepdims = True)

print('Dimensions in original array:', array1.ndim)
print('Without keepdims:', result1, 'with dimensions', result1.ndim)
print('With keepdims:', result2, 'with dimensions', result2.ndim)

Output

Dimensions in original array: 2
Without keepdims: [2.5 3.5 4.5] with dimensions 1
With keepdims: [[2.5 3.5 4.5]] with dimensions 2

Example 3: Using Optional out Argument

The out parameter allows to specify an output array where the result will be stored.

import numpy as np

array1 = np.array([[1, 2, 3],
                [4, 5, 6]])

# create an output array
output = np.zeros(3)

# compute median and store the result in the output array
np.median(array1, out = output, axis = 0)

print('median:', output)

Output

median: [2.5 3.5 4.5]