/Try-Pandas

In this series, we're going to learn the fundamentals of the popular Python data science tool called Pandas.

Primary LanguageJupyter NotebookMIT LicenseMIT

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Try Pandas

Pandas is a great tool for doing analysis on spreadsheets.

It's easy to say that but let's actually learn why by doing something real.

We're going to be analyzing NBA data to help understand why Pandas should be a tool in your data science toolkit.

But more importantly, doing something practical will help you better understand the need for a tool like Pandas.

To help us work with Pandas in a practical way, we've teamed up with Deepnote. Deepnote is a service that makes it easy to run interactive notebooks (also known as Juptyer Notebooks). These notebooks allow us to run Python & Pandas in a highly visual and highly interactive manner.

What's better, notebooks, especially on Deepnote, allow non-technical team members to participate in a code-heavy document (as we'll see how).

To get started, sign up for Deepnote using this link (This link will unlock pro features).

Once you sign up, you can automagically copy all the code in this repo with the following button: