Data Cleaning Basics

Learn how to clean messy data using pandas.


  • Learn about different encodings.
  • Learn how to extract and convert numeric values from string values.
  • Learn how to work with missing values.

Mission Outline

1. Reading CSV Files with Encodings
2. Cleaning Column Names
3. Converting String Columns to Numeric
4. Practicing Converting String Columns to Numeric
5. Extracting Values from the Start of Strings
6. Extracting Values from the End of Strings
7. Correcting Bad Values
8. Dropping Missing Values
9. Filling Missing Values
10. Challenge: Extracting Storage Information
11. Reordering Columns and Exporting Cleaned Data
12. Next Steps
13. Takeaways

Course Info:

Pandas and NumPy Fundamentals


The average completion time for this course is 10-hours.This course requires a basic subscription and includes five missions and one guided project.  It is the 3rd course in the Data Analyst in Python path and Data Scientist in Python path.


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