Although numpy.ndarray has a mean, max, std etc. method, it does not have a median method. For a list of all methods available for an ndarray, see the numpy documentation for ndarray.
It is available as a function that takes the array as an argument:
>>> import numpy as np
>>> a = np.array([1,2,3,4,5,6,7,8,9,10])
>>> np.median(a)
5.5
As you will see in the documentation for ndarray.mean, ndarray.mean and np.mean are "equivalent functions," so this is just a matter of semantics.
NumPy
numpy.org › doc › stable › reference › generated › numpy.median.html
numpy.median — NumPy v2.4 Manual
Returns the median of the array elements.
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Programiz
programiz.com › python-programming › numpy › methods › median
NumPy median()
axis = None - the median of the entire array is taken. By default, keepdims will not be passed. The numpy.median() method returns the median of the array.
NumPy
numpy.org › doc › stable › reference › generated › numpy.ma.median.html
numpy.ma.median — NumPy v2.4 Manual
Returns the median of the array elements.
NumPy
numpy.org › doc › 2.0 › reference › generated › numpy.median.html
numpy.median — NumPy v2.0 Manual
Returns the median of the array elements.
NumPy
numpy.org › doc › 2.3 › reference › generated › numpy.median.html
numpy.median — NumPy v2.3 Manual
Returns the median of the array elements.
GeeksforGeeks
geeksforgeeks.org › numpy-median-in-python
numpy.median() in Python - GeeksforGeeks
November 28, 2018 - Otherwise, it will consider arr to be flattened(works on all the axis). axis = 0 means along the column and axis = 1 means working along the row. out : [ndarray, optional] Different array in which we want to place the result. The array must have the same dimensions as expected output. dtype : [data-type, optional]Type we desire while computing median. Results : Median of the array (a scalar value if axis is none) or array with median values along specified axis. Code #1: ... # Python Program illustrating # numpy.median() method import numpy as np # 1D array arr = [20, 2, 7, 1, 34] print("arr : ", arr) print("median of arr : ", np.median(arr)) Output :
NumPy
numpy.org › devdocs › reference › generated › numpy.median.html
numpy.median — NumPy v2.5.dev0 Manual
Returns the median of the array elements.
NumPy
numpy.org › doc › 2.1 › reference › generated › numpy.ma.median.html
numpy.ma.median — NumPy v2.1 Manual
Returns the median of the array elements.
NumPy
numpy.org › doc › 2.1 › reference › generated › numpy.median.html
numpy.median — NumPy v2.1 Manual
Returns the median of the array elements.
Codecademy
codecademy.com › docs › python:numpy › built-in functions › .median()
Python:NumPy | Built-in Functions | .median() | Codecademy
May 1, 2024 - numpy.median(a, axis=None, out=None, overwrite_input=False, keepdims=False) a: The array of elements to calculate the median from. axis: The axis or axes along which to calculate the median.
NumPy
numpy.org › doc › 2.2 › reference › generated › numpy.ma.median.html
numpy.ma.median — NumPy v2.2 Manual
Returns the median of the array elements.
NumPy
numpy.org › devdocs › reference › generated › numpy.ma.median.html
numpy.ma.median — NumPy v2.5.dev0 Manual
Returns the median of the array elements.
Studytonight
studytonight.com › numpy › numpy-median-function
NumPy median() function - Studytonight
The Input Array is : [26, 2, 73, 13, 34] The median of 1D array is : 26.0 · Now we will apply this method on two-dimensional array and will check the output: import numpy as np inp = [[1, 17, 19, 33, 49], [14, 6, 87, 8, 19], [34, 2, 54, 4, 7]] print("\nThe median of array when axis = None : ") print(np.median(inp)) # calculating median along the axis = 0 print("\nThe median of array when axis = 0 : ") print(np.median(inp, axis = 0)) #calculating median along the axis = 1 print("\nThe median of array when axis = 1 : ") print(np.median(inp, axis = 1))