Examples of how to calculate the sum along an axis with numpy in python:

### Create a random matrix with numpy

Let's create a random matrix with numpy of size = (3,3):

`import numpy as np`

`data = np.random.randint(0,5,size=(3,3))`

returns for example

`array([[4, 1, 2],`

`[2, 1, 1],`

`[4, 0, 1]])`

### Sum along the first axis (axis=0)

To sum along a given axis of a matrix with numpy, a solution is to use numpy.sum with the parameter "axis":

`data.sum(axis=0)`

gives

`array([10, 2, 4])`

### Sum along the second axis (axis=1)

Another example along the axis=1

`data.sum(axis=1)`

gives

`array([7, 4, 5])`

### Sum all elements of a matrix with numpy

Note: to sum all elements of a matrix with numpy:

`data.sum()`

gives here

`16`

### Another example with more than 2 dimensions

Another example with a matrix of size = (3,3,3)

`import numpy as np`

`data = np.random.randint(0,5,size=(3,3,3))`

gives gor example

`array([[[4, 2, 4],`

`[3, 3, 1],`

`[0, 4, 1]],`

`[[3, 4, 0],`

`[3, 1, 3],`

`[4, 4, 2]],`

`[[2, 0, 2],`

`[2, 4, 1],`

`[3, 3, 4]]])`

Sum along axis=0

`data.sum(axis=0)`

gives

`array([[ 9, 6, 6],`

`[ 8, 8, 5],`

`[ 7, 11, 7]])`

Sum along axis=1

`data.sum(axis=1)`

gives

`array([[ 7, 9, 6],`

`[10, 9, 5],`

`[ 7, 7, 7]])`

Sum along axis=2

`data.sum(axis=2)`

gives

`array([[10, 7, 5],`

`[ 7, 7, 10],`

`[ 4, 7, 10]])`