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Data Cleaning

via Kaggle

Overview

Master efficient workflows for cleaning real-world, messy data.
  • Drop missing values, or fill them in with an automated workflow.
  • Transform numeric variables to have helpful properties.
  • Help Python recognize dates as composed of day, month, and year.
  • Avoid UnicoodeDecodeErrors when loading CSV files.
  • Efficiently fix typos in your data.

Syllabus

  • Handling Missing Values
  • Scaling and Normalization
  • Parsing Dates
  • Character Encodings
  • Inconsistent Data Entry

Taught by

Rachael Tatman

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