numpy.mean() in Python
numpy.mean(arr, axis = None) : Compute the arithmetic mean (average) of the given data (array elements) along the specified axis.
arr : [array_like]input array.
axis : [int or tuples of int]axis along which we want to calculate the arithmetic mean. 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 mean.
Results : Arithmetic mean of the array (a scalar value if axis is none) or array with mean values along specified axis.
arr : [20, 2, 7, 1, 34] mean of arr : 12.8
mean of arr, axis = None : 18.6 mean of arr, axis = 0 : [17.33333333 8.33333333 31. 14. 22.33333333] mean of arr, axis = 1 : [24. 15. 16.8] out_arr : [0 1 2] mean of arr, axis = 1 : [24 15 16]
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