Developers vs Data Scientists – Different Approaches to a Common Goal

(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.For the most part……Perhaps one in every five times I run the scripts, they fail to connect to the scrapesites or are otherwise unsuccessful returning data. I could have invested additional programming effort handling the exceptions, but didn’t, satisfied that I could always make them work by hand. Alas, I got “caught” with the errors…


Link to Full Article: Developers vs Data Scientists – Different Approaches to a Common Goal

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