How do I calculate the standard deviation of a NumPy array?

How do I calculate the standard deviation of a NumPy array?

You can use the numpy.std() function to calculate the standard deviation of a NumPy array. Just pass your array as an argument.

Can you show me an example?

Sure! Here's a simple example:

import numpy as np

array = np.array([1, 2, 3, 4, 5])
std_dev = np.std(array)
print(std_dev)

This will output the standard deviation of the array.

What if I have a 2D array?

For a 2D array, you can specify the axis parameter. For example:

array_2d = np.array([[1, 2, 3], [4, 5, 6]])
std_dev_axis0 = np.std(array_2d, axis=0)  # Standard deviation for each column
std_dev_axis1 = np.std(array_2d, axis=1)  # Standard deviation for each row

This will give you the standard deviation along the specified axis.