Data analysts and data scientists alike report that while there are definitely “sexier” parts of the job, most of their time is spent on data preparation and cleaning.

In our data cleaning and analysis course, you’ll learn how to supercharge your data analysis workflow with cleaning and analytical techniques from the Python pandas library that will make you a data analysis superstar.

You'll learn concepts such as groupby objects to solve split-apply-combine problems faster. You'll also learn how to use pandas to create pivot tables, concatenate data, and merge data to solve complex data problems as well as look at your data in a completely different way.

Then you’ll dive into string manipulation with string accessors and regular expressions (also called regex), a more refined way to do string manipulation.

You’ll also learn how to handle missing values in your data, a critical part of almost every data analysis project.

At the end of this course, you will be able to complete a guided project cleaning and analyze employee exit surveys. When you’re finished, you’ll have a real-world example of your data analysis abilities with genuine business value that you can show to potential employers to prove you’ve got the skills they need.

By the end of this course, you'll be able to:

  • Use different data aggregation techniques.
  • Combine data sets.
  • Transform and reshape data.
  • Clean strings and handle missing data.

Learn Python Data Cleaning and Analyze Data Using Pandas

Data Aggregation

Learn how to aggregate data with pandas.

Combining Data with Pandas

Learn how to combine data with pandas.

Transforming Data with Pandas

Learn how to transform data with pandas.

Working with Strings in Pandas

Learn how to work with strings in pandas.

Working with Missing and Duplicate Data

Learn how to work with missing and duplicate data in pandas.

Clean And Analyze Employee Exit Surveys

Practice data cleaning using pandas.