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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
- Sales Rank: #64834 in Books
- Published on: 2016-02-20
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 1.10" w x 6.90" l, .0 pounds
- Binding: Paperback
- 508 pages
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/).
Most helpful customer reviews
12 of 13 people found the following review helpful.
A Great Mentor for the Beginning Wrangler
By ronb
I pre-ordered this book a couple of months ago and anxiously waited for it to arrive. Data wrangling is the largest part of most any inquiry, the actual data analysis is usually nothing compared to getting the data into a usable form. I was really looking forward to having a reference, and at first I was disappointed with this book. It is directed at the non-programmer and begins with the simplest python skills. It does not use any of the advanced data structures or modules that I have used in the past. Even though I just did not get much out of it, I still had to give it five stars!
First and foremost, it is well written: the grammar and punctuation are correct, the example code and explanations are clear and insightful. Most computer books are agonizing to read, but this was a joy. Although it does not provide comprehensive examples of all the modules and data structures, which one might use in data wrangling, it does provide an example for each type of data you might want to import: CSV, JSON, XML, Excel and PDF. Plus there are chapters on using web scraping, APIs, and both Relational and NoSQL databases. Moreover, each example is explained with a step-by-step narrative, that shows the beginner not just how to do it, but how to think about working through the process. This is why I recommended the book to colleague, who is an atmospheric scientist learning to program with python.
7 of 8 people found the following review helpful.
Barely includes anything on NumPy, nothing on Pandas - doesn't seem like it would be useful for actually 'wrangling data'
By science_mom
I bought this book expecting that it would at least contain some information on NumPy and Pandas - but these aren't covered in detail at all. I'm not sure why you would try to 'wrangle data' with python without using NumPy. There is a very similar book (with almost the same title) published by O'reilly that is written by the author of Pandas (Wes McKinney). I assumed that this was an update to that book because the titles were so similar - but that wasn't the case at all. The other book covers both NumPy and Pandas. Returning this one...
5 of 6 people found the following review helpful.
One of the few books that should be on every learner's bookshelf. Concise, understandable, & practical.
By gnomic
There is a lot of great information and examples in this book. What makes it stand out is that they are understandable. You won't get lost in the details like some books. This is all the work that we do every day, laid out in plain language.
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