Course Outline

Data wrangling is a core skill that everyone who works with data should be familiar with since so much of the world's data isn't clean. Though this course is geared towards those who use Python to analyze data, the high-level concepts can be applied in all programming languages and software applications for data analysis.

Lesson 1: The Walkthrough

In the first lesson of this course, we'll walk through an example of data wrangling so you get a feel for the full process . We'll introduce gathering data, then download a file from the web and import it into a Jupyter Notebook. We'll then introduce assessing data and assess the dataset we just downloaded both visually and programmatically. We'll be looking for quality and structural issues. Finally, we'll introduce cleaning data and use code to clean a few of the issues we identified while assessing.

The goal of this walkthrough is awareness rather than mastery, so you'll be able to start wrangling your own data even after just this first lesson.

Lessons 2-4: Gathering, Assessing, and Cleaning Data (in Detail)

In the following lessons, you'll master gathering , assessing , and cleaning data. We'll cover the full data wrangling process with real datasets too, so think of this course as a series of wrangling journeys. You'll learn by doing and leave each lesson with tangible skills.

Your Instructors

More Information

There will be things that we refer to in videos that you won't be 100% familiar with and aren't necessary to succeed in this course. For these topics, we've handpicked resources and linked to them in the notes at the bottom of each page under a More Information heading (just like it is here). You don't need to check these out, but if you want to, they are there to help you. Links to any websites, external videos, etc. that we use in the lesson material will be linked in this section as well.

When these types of resources are referenced in a reading concept, a link will be provided directly in that text, rather than at the bottom of the page.