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    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

    What Our Clients Say

    Our Latest Insights

    iWeb Scraping eliminates manual data entry with AI-powered extraction for businesses worldwide.

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