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:
# 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
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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 the flattened array print("\nmedian of arr, axis = None : ", np.median(arr))     # median along the axis = 0 print("\nmedian of arr, axis = 0 : ", np.median(arr, axis = 0))    # median along the axis = 1 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]
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