Why Python for Data Analysis?

Learn to Code Today!

Learn 10x faster: coding, no-code and data skills. Join millions of users mastering new tech skills and accelerating their career with Enki.
Get started

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.

About Enki

  • Fully personalized online up-skilling
  • Unlimited AI coaching
  • Designed by Silicon Valley experts

More articles

Meet your AI-enabled coach

Professional athletes have a coach for every aspect of their performance. Why can’t you for your work? Enki’s AI-powered coaching on-demand - combined with state of the art, structured learning content - makes this a reality.
1
1:1 AI Coaching
How do I remove duplicate emails?
Convert the list to a set and back to a list. Sets automatically remove duplicates.
2
Personalized Exercises
3
Interactive practice

Unlock full access to all skills on Enki with a 7-day free trial

Get started