I recall being completely stumped during my undergraduate years when given a dataset that contained longitude and latitude. My youthful brain simply could not fathom the utility of coordinates. Perhaps it was the insurmountable backlog of assignments and assessments that was clouding my mind. Fast forward a couple of years and I’m now ready to wring out every last drop of value these variables have to offer.
Eliminating confounding factors to protect experimental accuracy.
Whether for work or for fun, web scraping is a critical skill that every data scientist should have in their arsenal. It opens the door to an immeasurable amount of data beyond the restrictions of what you can find on Kaggle or other open data websites. But the best part is that when you gain the ability to scrape efficiently and autonomously at a small scale, you will easily be able to translate that to larger scraping projects.
Using these tips, I’ve gone from scraping ~1000 Amazon reviews for sentiment analysis to scraping ~30,000 COVID-19 news articles for a study…
The full code can be found on my GitHub.
Those already acquainted with the sport would know how critical it is to wear a pair of rock climbing shoes that fit perfectly. Ill-fitting shoes can spell disaster in so many ways. Being a niche sport, buying a good-fitting pair is not as easy as walking into the store and trying it on. Depending on one’s country of residence, shops selling climbing shoes could be far and few. That is why many resort to purchasing it online.
However, buying a pair is no easy feat and combing through hundreds of reviews…
Food. Analytics. Sports. In that order.