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Data Wrangling with Python

Tips and Tools to Make Your Life Easier

by Jacqueline Kazil Author · Katharine Jarmul Author


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How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that's initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started.

Through various step-by-step exercises, you'll learn how to acquire, clean, analyze, and present data efficiently. You'll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain.

  • Quickly learn basic Python syntax, data types, and language concepts
  • Work with both machine-readable and human-consumable data
  • Scrape websites and APIs to find a bounty of useful information
  • Clean and format data to eliminate duplicates and errors in your datasets
  • Learn when to standardize data and when to test and script data cleanup
  • Explore and analyze your datasets with new Python libraries and techniques
  • Use Python solutions to automate your entire data-wrangling process
  • Publication Details

    O'Reilly Media
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    • Kindle Book
    • OverDrive Read 5.9 MB
    • Adobe PDF eBook 9 MB
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    Jacqueline Kazil (Author)

    Jacqueline Kazil is a data lover. In her career, she has worked in technology focusing in finance, government, and journalism. Most notably, she is a former Presidential Innovation Fellow and co-founded a technology organization in government call...

    More about Jacqueline Kazil

    Katharine Jarmul (Author)

    Katharine Jarmul is a Python developer who enjoys data analysis and acquisition, web scraping, teaching Python and all things Unix. She has worked at small and large start ups before starting her consulting career overseas. Originally from Los Ang...

    More about Katharine Jarmul
    Data Wrangling with Python
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