numpy.median() in Python
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))
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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))
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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]
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