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Data Cleaning With pandas and NumPy (Summary)

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 DataFrame
  • Change the index of a DataFrame
  • Use .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:

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Sample Code (.zip)

965.9 KB

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Course Slides (.pdf)

608.2 KB

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