Top 8 resources for learning data analysis with pandas

轉載來自Top 8 resources for learning data analysis with pandas

I recently launched a video series about "pandas", a popular Python library for data analysis, manipulation, and visualization. But for those of you who want to learn pandas and prefer the written word, Ive compiled my list ofrecommended resources:

1. Intro to pandas data structures: This is the first post in Greg Redas classic three-part pandas tutorial (part 2, part 3). Its highly readable, presents the "right" level of detail for a pandas beginner, and includes lots of useful examples.

2. Introduction to Pandas / Data Wrangling with Pandas / Plotting with Pandas: Three extremely long (but well-written) Jupyter notebooks from Chris Fonnesbecks Advanced Statistical Computing course at Vanderbilt University (my alma mater!). If you want to go deep into the details and learn about many powerful pandas features, these notebooks are for you.

3. Python for Data Analysis: This book was written by the creator of pandas, Wes McKinney, back in 2012. It covers IPython, NumPy, and pandas, and also includes an excellent appendix of "Python Language Essentials". Its still probably the best pandas book out there, though it might be worth waiting to buy until early 2017 when the second edition is released. (Wes is currently accepting suggestions for the book!)

4. Common Excel Tasks Demonstrated in Pandas: If youre coming from an Excel background, this post (and part 2) may help you to build a mental model for how pandas "thinks". Its from Chris Moffitts excellent blog, Practical Business Python.

5. Translating SQL to pandas: This Jupyter notebook from Greg Reda may be helpful if you are transitioning from SQL to pandas. (Heres the related video presentation.)

6. Modern Pandas: This is a recent seven-part series by Tom Augspurger, a contributor to pandas, primarily targetingintermediate pandas users who want to make their code more modern and idiomatic.

7. If you prefer reading code snippets (rather than articles or books) to learn a language, you might like Mark Graphs 10-page Cheat sheet to the pandas DataFrame object or Chris Albons Data Wrangling code samples.

8. All of the code from my pandas video series is available for you to browse, in a well-commented Jupyter notebook.

What excellent pandas resources did I miss? Let me know in the comments section below!

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