Congrulations! Now you know how to clean data using pandas and NumPy. Cleaning data can be a major undertaking, but it’s vital to any data science project. You’ve practiced the necessary skills on three different datasets, all while bulding a reusable data cleaning script.
In this video course, you learned how to:
- Drop unnecessary columns in a
- Change the index of a
.str()methods to clean columns
- Rename columns to a more recognizable set of labels
- Skip unnecessary rows in a CSV file
Check out the links below to find additional resources that’ll help you on your Python data science journey:
- The Pandas documentation
- The NumPy documentation
- Python for Data Analysis by Wes McKinney, the creator of Pandas
- Pandas Cookbook by Ted Petrou, a data science trainer and consultant
Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.