Why Python for Data Analysis?

This is part of the “Intro to Data Analysis with Python” series of posts, with content from the Enki app. If you stumbled upon this, you could start from the beginning.

Most people choose Python when working with data. Whether it's for analysis, visualization, or manipulation of data, Python is very flexible.

There are several good reasons for this.

Python closely resembles the English language, which makes it quick to get started with, especially for beginners.

It has a mature ecosystem of tools for extracting and manipulating data.

These tools usually come from an ever-expanding collection of libraries, many of which are community-driven.

New libraries or updates to existing libraries arrive often.

Many of these libraries are created for specific tasks like analysis, visualization, array manipulation, and more.

💡 We will dive into the different libraries Python has to offer in the next post.

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