numpy.sum() in Python

numpy.sum() is a NumPy function used to calculate the sum of array elements. It can sum values across the entire array or along a specific axis. It also allows controlling the output data type, initial value, and shape of the result.

Example: This example shows the use of numpy.sum() to find the total of a 1D numeric array.

import numpy as np
arr = np.array([5, 10, 15])
print(np.sum(arr))

30

Explanation: np.sum(arr) adds all elements (5 + 10 + 15) and returns the total.

Syntax

numpy.sum(arr, axis=None, dtype=None, out=None, initial=0, keepdims=False)

Parameters:

• arr: Input array whose elements are to be summed.
• axis: Axis along which the sum is computed. 0 -> column-wise, 1 -> row-wise and None -> entire array
• dtype: Data type of the returned sum.
• out: Output array to store the result.
• initial: Starting value of the sum.
• keepdims: Keeps the reduced axis as dimension in result.

Examples

Example 1: This example shows how numpy.sum() works on a 1D array and how changing the dtype affects the result.

import numpy as np

arr = np.array([20, 2, 0.2, 10, 4])

print(np.sum(arr))
print(np.sum(arr, dtype=np.uint8))
print(np.sum(arr, dtype=np.float32))

36.2
36
36.2

Explanation:

• np.sum(arr) sums all values normally.
• np.sum(arr, dtype=np.uint8) result is converted into uint8, causing decimal removal.
• np.sum(arr, dtype=np.float32) keeps decimal since it's a float type.

Example 2: This example calculates the sum of a 2D array and shows how using different data types changes the output.

import numpy as np

arr = np.array([ [14, 17, 12, 33, 44],
               [15,  6, 27,  8, 19],
               [23,  2, 54,  1,  4] ])

print(np.sum(arr))
print(np.sum(arr, dtype=np.uint8))
print(np.sum(arr, dtype=np.float32))

279
23
279.0

Example 3: This example demonstrates summing a 2D array along rows, columns, and using keepdims=True.

import numpy as np

arr = np.array([ [14, 17, 12, 33, 44],
               [15,  6, 27,  8, 19],
               [23,  2, 54,  1,  4] ])

print(np.sum(arr))
print(np.sum(arr, axis=0))
print(np.sum(arr, axis=1))
print(np.sum(arr, axis=1, keepdims=True))

279
[52 25 93 42 67]
[120  75  84]
[[120]
 [ 75]
 [ 84]]

Explanation:

• np.sum(arr, axis=0) column-wise sum.
• np.sum(arr, axis=1) row-wise sum.
• np.sum(arr, axis=1, keepdims=True) keeps each row's sum in a column format.