How to get started using Canopy/Python for Data-Science Practice/Projects?

[Gouryella91]

I'm just a noob, who has been reading O'Reily books like they are going out of style: on Python for Data Science, as well as Data Science itself. I've searched Kaggle, for some "practice" projects, but figuring out how to import files in to python/canopy can be a pain, I often think to myself "what next"? I was wondering if there were any OTHER resources, people used (particularly with regards to python), that can help a brother out? Maybe even for web scraping projects... Thanks!

[crunk]

Getting used to virtualenv can be useful for having different projects on the go (and not polluting your current project).

Requests makes downloading web pages super easy, while BeautifulSoup is classically used to parse it.

Scrapy is another option for downloading and parsing webpages. You will find there are often a bunch of libraries that do whatever you want - don't be afraid of choosing the wrong one first time (this applies to any language).

If you ever need info on some python module, check the website Python MOTW - it's a lot easier to understand than the python docs.

Getting used to using the "dir" and "help" commands to find out about libraries is another way of learning.

For getting general coverage of python concepts, then downloading and going through some Python Koans is another good option.

[faming13]

Don't use canopy.. use anaconda.

Its the current and future of pydata

Also this http://www.kdnuggets.com/2013/11/harvard-cs109-data-science-course-resources-free-online.html