Data Cleaning

Data cleaning is the process of finding and fixing inaccurate, duplicate, incomplete, or incorrectly formatted data.

Core Steps in Data Cleaning

  • Check Quality: Look over your file first. Find out what errors exist, such as wrong text types or blank cells.
  • Remove Duplicates: Erase repeat rows so each piece of data is counted only one time.
  • Fix Structure: Make text and numbers uniform. Change all dates to the same format, fix typos, and make capital letters match.
  • Handle Missing Info: Fill in blank spots using average values, or delete the rows if too much info is missing.
  • Manage Outliers: Drop extreme values that fall too far outside normal ranges if they ruin your general math or averages.
  • Validate Data: Test the final set against basic rules to make sure everything looks correct and makes sense

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