Data Wrangling with Python

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

Table of Contents

Chapter 1. Introduction to Python

Chapter 2. Python Basics

Chapter 3. Data Meant to Be Read by Machines

Chapter 4. Working with Excel Files

Chapter 5. PDFs and Problem Solving in Python

Chapter 6. Acquiring and Storing Data

Chapter 7. Data Cleanup: Investigation, Matching, and Formatting

Chapter 8. Data Cleanup: Standardizing and Scripting

Chapter 9. Data Exploration and Analysis

Chapter 10. Presenting Your Data

Chapter 11. Web Scraping: Acquiring and Storing Data from the Web

Chapter 12. Advanced Web Scraping: Screen Scrapers and Spiders Chapter 13. APIs

Chapter 14. Automation and Scaling

Chapter 15. Conclusion

About The Authors

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 cofounded 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; a Congress.gov remake; and Top Secret America. She is active in Python and data communities-Python Software Found on, PyLadies, Women Data Science DC, and more. She teaches Python in Washin http://projects.washingtonpost.com/top-secret-america/ /camps. She often pairs pro- grams with her sidekick, Ellie (@ellie_the_brave). You can find her on Twitter @jack- iekazil or follow her blog, The coderSnorts.

Katharine Jarmul is a Python developer who enjoys data analysis and acquisition, web scraping, teaching Python, and all things Unix. She worked at small and large startups 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, Katharine hopes to promote diversity in Python and other open source languages through education and training. She has led numerous work- shops and tutorials ranging from beginner to advanced topics in Python. For more information on upcoming trainings, reach out to her on Twitter (@kjam) or her web- site.