Create and Alter DataFrame Indexes
In this course, you'll dive into DataFrame indexing with pandas. Follow Abby, a marketing analyst, as she navigates her marketing dataset. You'll learn reindexing, .loc, .iloc, data filtering techniques, and more through interactive demos.
What you'll learn
This course will focus on skills needed to clean data using pandas DataFrames in Python. You'll follow Abby the marketing analyst while she explores customer data as she gets ready for a marketing campaign for her company, MadeUp Inc.
In this course, Create and Alter DataFrame Indexes, you’ll gain the ability to reference data in a pandas DataFrame using indexes, which is useful when you're trying to access or filter data in a DataFrame for data exploration and cleansing.
First, you’ll explore pandas DataFrames and indexes.
Next, you’ll discover how to create and recreate indexes on DataFrames.
Then, you’ll see how to access rows of a DataFrame with different syntaxes.
Finally, you’ll learn how to filter DataFrames for rows that match or contain certain string values.
When you’re finished with this course, you’ll have the skills and knowledge of creating and altering DataFrame indexes needed to access and filter data in DataFrames for data exploration and cleansing.
Table of contents
- .Loc vs. .Iloc 3m
- Access Rows with .Loc 1m
- Demo: Using .Loc 2m
- Access Rows with .Iloc 1m
- Demo: Using .Iloc 3m
- Access Rows with Bracket Index 2m
- Demo: Using Brackets to Access Rows 2m
- Filtering Data with Matching Strings 1m
- Demo: Using .Loc to Match Strings 2m
- Filtering Data Containing a String 1m
- Demo: Filtering Data Containing Strings 1m
- Demo: Putting It All Together 1m
- Summary 1m
About the author
Matt Stenzel is a Data and AI Cloud Solution Architect at Microsoft. He has 15+ years of experience in the data and analytics industry working in various roles including a software developer, data engineer, DW developer, DBA and integration architect. He has spent the last 8 years working at Microsoft helping companies across the US successfully implement Azure solutions that provide business value.