Learn how to create, index, slice, reshape, and perform arithmetic operations on arrays using NumPy, the most popular Python library for data science.

This post shows you how to use arrays in Python and why this data structure is so useful. A foundational skill for data science, coding, and more!

So, it can be easily said that the index range of a list in Python will be 0 to n-1, where n is the total items in the list. In the above example, the index range will be 0 to 2 (3-1). Negative ...

The Python array is designed to emulate the behavior of an array in C, and it’s meant chiefly to allow Python to work with C arrays. The array type is useful in those cases, but in almost every ...

For example, if a loop is designed to run five times but the list has only three items, the loop would try to access two non-existent indices. In such a situation, the programmer needs to check their ...

NumPy is known for being fast, but there's always room for improvement. Learn how to use Cython to iterate over NumPy arrays at the speed of C.