(My partner Bryan Senseman is co-author of this blog.)

Over the last month or so, I've assembled a few scripts to showcase the web-scraping capabilities of R and python. The tasks are generally pretty simple, involving web data that looks like tables and  ultimately resides in either R or python/Pandas dataframes. Not surprisingly, the supporting community-developed libraries generally work well, combining with the power of  the languages to deliver painless programming solutions for the tasks at hand.

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