Data Visualization in Python with Matplotlib and Pandas - Installation and Setup

Installation and Setup

David Landup
David Landup

We'll be working with several tools throughout the course. Dabbling in Python almost warrants that you've already used some of these before, if not most, since these are fairly popular libraries present in a large amount of projects. Namely, we'll be using:

We'll rely on Numpy sparingly, so if you haven't worked with it before - there's no need to worry. Even though Matplotlib uses Numpy Arrays under the hood, even without prior experience with it, you'll be able to follow the course without a problem given the intuitive API and little need to use it manually.

Assuming no prior knowledge of Pandas, we'll first be jumping into Lesson 3 - Getting Started with Pandas. It's extensively used with Matplotlib, and we'll be using it throughout the course to pre-process and wrangle data into the formats most fit for our visualization needs. We'll start at the foundations and building blocks of Pandas to common tasks and operations you'll be performing as well as data reshaping, giving you an solid introduction to the library and how we'll be using it in the course.

In the case you don't already have these tools installed on your local machine, let's quickly set them up.

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