Mastering Numerical Computing with NumPy

NumPy array operations

This section will guide you through the creation and manipulation of numerical data with NumPy. Let's start by creating a NumPy array from the list:

In [17]: my_list = [2, 14, 6, 8]         my_array = np.asarray(my_list)         type(my_array)Out[17]: numpy.ndarray

Let's do some addition, subtraction, multiplication, and division with scalar values:

In [18]: my_array + 2Out[18]: array([ 4, 16, 8, 10])In [19]: my_array - 1Out[19]: array([ 1, 13, 5, 7])In [20]: my_array * 2Out[20]: array([ 4, 28, 12, 16, 8])In [21]: my_array / 2Out[21]: array([ 1. , 7. , 3. , 4. ])

It's much harder to do the same operations in a list because the list does not support vectorized operations and you need to iterate its elements. There are many ways to create ...