Example 1: python get a vector of row sums from an array
np.sum(your_array, axis=1).tolist()
import numpy as np
your_array = np.array([range(0,4),range(3,7),range(1,5),range(2,6)])
print(your_array)
--> [[0 1 2 3]
[3 4 5 6]
[1 2 3 4]
[2 3 4 5]]
np.sum(your_array, axis=0).tolist()
--> [6, 10, 14, 18]
np.sum(your_array, axis=1).tolist()
--> [6, 18, 10, 14]
Example 2: sum axis in python
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]
Example 3: sum along axis python
import numpy as np
matrix=np.ones((10,10))
print(matrix.sum(axis=0))
print(matrix.sum(axis=1))
Example 4: python sum of list axes
>>> np.sum([[0, 1], [0, 5]])
6
>>> np.sum([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.sum([[0, 1], [0, 5]], axis=1)
array([1, 5])
Example 5: python np.sum
npsum = np.sum(array)
Example 6: np sum
>>> np.sum([0.5, 1.5])
2.0
>>> np.sum([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
1
>>> np.sum([[0, 1], [0, 5]])
6
>>> np.sum([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.sum([[0, 1], [0, 5]], axis=1)
array([1, 5])
>>> np.sum([[0, 1], [np.nan, 5]], where=[False, True], axis=1)
array([1., 5.])