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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
About the 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 called 18F. Her career has consisted of many data science and wrangling projects including Geoq, an open source mapping workflow tool, Congress.gov remake, and Top Secret America. She is active in the Python and data related communities -- Python Software Foundation, PyLadies, Women Data Science DC, and more. She teaches Python in Washington, D.C. at meetups, conferences, and mini bootcamps. She often pair programs with her sidekick, Ellie (@ellie_the_brave). You can find her on Twitter @jackiekazil or follow her blog, The coderSnorts (https://medium.com/coder-snorts).
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 Angeles, she learned Python while working at the Washington Post in 2008. As one of the founders of PyLadies (http://pyladies.org/), Katharine hopes to promote diversity in Python and other open source languages through education and training. She has led numerous workshops and tutorials ranging from beginner to advanced topics in Python. For more information on upcoming trainings, reach out to her on Twitter (http://twitter.com/kjam) or her her web site (http://kjamistan.com/).
Summary
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.
