A Professional’s Tutorial to Python Numpy

Lists • arrays Compare + contrast fundamental Python data types

Adam Ross Nelson

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For an overview of these tutorials, click here (or click the image).

Welcome to tenth, in a series of tutorials that teach beginner Python specifically for aspiring data scientists. For an overview of these tutorials, click here.

Introduction

So you might be tempted to ask yourself why is Python so popular for data science? There are a variety of reasons for that. And as discussed in the introductory article on this tutorial series popularity is also a mixed blessing.

So yeah, Python’s rise in data science has been meteoric. Python owes much this rise to its simplicity and expansive library repertoire. At the forefront of these libraries stands NumPy, which offers nearly unparalleled capabilities for handling arrays and intricate numerical computations.

White background with black numbers strewn across the image. Many small and large numbers.
Image Credit: Author’s illustration created in Canva.com.

Earlier tutorials in this series introduced readers to Python lists.

After having studied more rudimentary data types, such as lists, it is also important to study arrays and matrices which are not native to Python. One of the best ways to learn about arrays is to focus on the data…

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