The `numpy.mean() `

function calculates the arithmetic mean of the numpy array.

**Example**

```
import numpy as np
arr = [5,2,6,21,63]
print("Our array: ", arr)
print("mean of our array : ", np.mean(arr))
```

We can also calculate the mean across different axis such as rows or columns by specifying the axis parameter. Specifying axis = 0 means the mean will be calculated along the column and axis = 1 specifies to find the mean across the rows.

**Example**

```
import numpy as np
arr = [[1, 17, 12, 12, 36],
[78, 16, 27, 70, 21],
[98, 45, 42, 11, 45, ]]
# mean along the columns
print("mean of our array along the columns by setting axis = 0 : ", np.mean(arr, axis = 0))
# mean along the rows
print("mean of our array along the rows by setting axis = 1 : ", np.mean(arr, axis = 1))
```