The numpy.median()
method computes the median along an array's specified axis.
Example
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 bearray_like
)axis
(optional) - axis or axes along which the medians are computed (int
ortuple 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 arraykeepdims
(optional) - specifies whether to preserve the shape of the original array (bool
)
Notes: The default values of numpy.median()
have the following implications:
axis = None
- the median of the entire array is taken.- By default,
keepdims
will not be passed.
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]