4 ms·
Would just throw an extra plug for Python for Data Analysis. Though the title might sound a little bland, it's a good, practical summary of how to use pandas fo
by rcar 10y ago
Would just throw an extra plug for Python for Data Analysis. Though the title might sound a little bland, it's a good, practical summary of how to use pandas for the sorts of data analysis you often have to do in data science work.
- kyleschiller 10y agoVery strong third. The appendix alone taught me most of what I know about python, and it's a great departure from the mass of online materials that focus on ML without getting into the tools you'll need for cleaning and managing data. Plus, it's free online: http://www3.canisius.edu/~yany/python/Python4DataAnalysis.pdf http://www3.canisius.edu/~yany/python/Python4DataAnalysis.pd...
- zvikara 10y agoLinked pdf looks like a pirated copy from it-ebooks.info
- clumsysmurf 10y ago2E is in the works http://shop.oreilly.com/product/0636920050896.do http://shop.oreilly.com/product/0636920050896.do
- ploika 10y agoI'd add the disclaimer that while Python for Data Analysis is a great resource for learning pandas, which itself is invaluable for data science in Python, the book doesn't cover machine learning or statistical inference in any great detail. That's not a criticism, it's just (mostly) beyond the scope of the book.
- rcar 10y agoA fair point for sure, which is actually one of the reasons why I do tend to recommend the book. ML and stats are generally the more flashy and well-known parts of data science, and so I've found that people new to the field often don't have major difficulties finding resources for learning them or finding the self motivation to dive into them. The data cleanup, on the other hand, is often the more important work to be done on projects while simultaneously being seen as the less enjoyable part. Learning how to do it well makes it a more interesting process, and pandas and this book lay a good foundation for that.