numpy.median() in Python (original) (raw)

Last Updated : 28 Nov, 2018

numpy.median(arr, axis = None) : Compute the median of the given data (array elements) along the specified axis.

How to calculate median?

• Given data points.
• Arrange them in ascending order
• Median = middle term if total no. of terms are odd.
• Median = Average of the terms in the middle (if total no. of terms are even)

Parameters :
arr : [array_like]input array.
axis : [int or tuples of int]axis along which we want to calculate the median. 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:

import numpy as np

arr = [ 20 , 2 , 7 , 1 , 34 ]

print ( "arr : " , arr)

print ( "median of arr : " , np.median(arr))

Output :

arr : [20, 2, 7, 1, 34] median of arr : 7.0

Code #2:

import numpy as np

arr = [[ 14 , 17 , 12 , 33 , 44 ],

`` [ 15 , 6 , 27 , 8 , 19 ],

`` [ 23 , 2 , 54 , 1 , 4 , ]]

print ( "\nmedian of arr, axis = None : " , np.median(arr))

print ( "\nmedian of arr, axis = 0 : " , np.median(arr, axis = 0 ))

print ( "\nmedian of arr, axis = 1 : " , np.median(arr, axis = 1 ))

out_arr = np.arange( 3 )

print ( "\nout_arr : " , out_arr)

print ( "median of arr, axis = 1 : " ,

`` np.median(arr, axis = 1 , out = out_arr))

Output :

median of arr, axis = None : 15.0

median of arr, axis = 0 : [15. 6. 27. 8. 19.]

median of arr, axis = 1 : [17. 15. 4.]

out_arr : [0 1 2] median of arr, axis = 1 : [17 15 4]