numpy.sum(arr, axis, dtype, out) : This function returns the sum of array elements over the specified axis.
Parameters :
arr : input array.
axis : axis along which we want to calculate the sum value. 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 : Different array in which we want to place the result. The array must have same dimensions as expected output. Default is None.
initial : [scalar, optional] Starting value of the sum.Return : Sum of the array elements (a scalar value if axis is none) or array with sum values along the specified axis.
Code #1:
# Python Program illustrating # numpy.sum() methodimport numpy as np # 1D array arr = [20, 2, .2, 10, 4] print("\nSum of arr : ", np.sum(arr)) print("Sum of arr(uint8) : ", np.sum(arr, dtype = np.uint8)) print("Sum of arr(float32) : ", np.sum(arr, dtype = np.float32)) print ("\nIs np.sum(arr).dtype == np.uint : ", np.sum(arr).dtype == np.uint) print ("Is np.sum(arr).dtype == np.float : ", np.sum(arr).dtype == np.float) |
Output:
Sum of arr : 36.2 Sum of arr(uint8) : 36 Sum of arr(float32) : 36.2 Is np.sum(arr).dtype == np.uint : False Is np.sum(arr).dtype == np.uint : True
Code #2:
# Python Program illustrating # numpy.sum() methodimport numpy as np # 2D array arr = [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4,]] print("\nSum of arr : ", np.sum(arr)) print("Sum of arr(uint8) : ", np.sum(arr, dtype = np.uint8)) print("Sum of arr(float32) : ", np.sum(arr, dtype = np.float32)) print ("\nIs np.sum(arr).dtype == np.uint : ", np.sum(arr).dtype == np.uint) print ("Is np.sum(arr).dtype == np.uint : ", np.sum(arr).dtype == np.float) |
Output:
Sum of arr : 279 Sum of arr(uint8) : 23 Sum of arr(float32) : 279.0 Is np.sum(arr).dtype == np.uint : False Is np.sum(arr).dtype == np.uint : False
Code #3:
# Python Program illustrating # numpy.sum() method import numpy as np # 2D array arr = [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4,]] print("\nSum of arr : ", np.sum(arr)) print("Sum of arr(axis = 0) : ", np.sum(arr, axis = 0)) print("Sum of arr(axis = 1) : ", np.sum(arr, axis = 1)) print("\nSum of arr (keepdimension is True): \n", np.sum(arr, axis = 1, keepdims = True)) |
Output:
Sum of arr : 279 Sum of arr(axis = 0) : [52 25 93 42 67] Sum of arr(axis = 1) : [120 75 84] Sum of arr (keepdimension is True): [[120] [ 75] [ 84]]
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