The `numpy.std() `

function calculates the standard deviation of the numpy array or list along a given axis.

**Example**

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

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

**Example**

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