numpy.median () in Python



How to calculate the median?

  • Point data is given.
  • Arrange them in ascending order
  • Median = medium term if everything is not there. the conditions are weird.
  • Median = Average in terms in the middle (if the total number of terms is 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:

# 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:

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

Code # 2:

# Python program illustrating
# numpy.median () method

import numpy as np

 
# 2D array

arr = [[ 14 , 17 , 12 , 33 , 44 ], 

  [ 15 , 6 , 27 , 8 , 19 ], 

[ 23 , 2 , 54 , 1 , 4 ,]] 

 
# median of a flattened array

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

  
# axis median = 0

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

 
# median axes = 1

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

  

out_arr = np.arange ( 3 )

print ( "out_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]