Python numpy sum() function is used to get the sum of array elements over a given axis.
Python NumPy sum() method syntax is:
sum(array, axis, dtype, out, keepdims, initial)
Let’s look at some of the examples of numpy sum() function.
If we pass only the array in the sum() function, it’s flattened and the sum of all the elements is returned.
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4],
[5, 6]])
total = np.sum(array1)
print(f'Sum of all the elements is {total}')
Output: Sum of all the elements is 21
If we specify the axis value, the sum of elements along that axis is returned. If the array shape is (X, Y) then the sum along 0-axis will be of shape (1, Y). The sum along 1-axis will be of shape (1, X).
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4],
[5, 6]])
total_0_axis = np.sum(array1, axis=0)
print(f'Sum of elements at 0-axis is {total_0_axis}')
total_1_axis = np.sum(array1, axis=1)
print(f'Sum of elements at 1-axis is {total_1_axis}')
Output:
Sum of elements at 0-axis is [ 9 12]
Sum of elements at 1-axis is [ 3 7 11]
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4]])
total_1_axis = np.sum(array1, axis=1, dtype=float)
print(f'Sum of elements at 1-axis is {total_1_axis}')
Output: Sum of elements at 1-axis is [3. 7.]
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4]])
total_1_axis = np.sum(array1, axis=1, initial=10)
print(f'Sum of elements at 1-axis is {total_1_axis}')
Output: Sum of elements at 1-axis is [13 17]
Reference: API Doc
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Dear Pankaj, I only want to sum some of the values not all. what should I do in that case? Imagine that It is an array including 0 and 1s and I would like to sum 1s before each zero not to sum all the 1s. I appreciate if you could help me.
- Mona
Hi Pankaj What mean when use “axis=-1” in sum function Thanks…
- Elaf Ali