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]