This RShiny app pulls the latest COVID 19 data from NY Times and displays interactive maps and plots highlighting the progression of new cases/deaths in a given state.
This RShiny app uses AP exit poll data scraped from NY Times to simulate how the 2020 US election would turn out if only a certain group voted
Last month, Strava rolled out a simple, but fun new feature to its subscribers called #statmaps. Strava subscribers can now use a hashtag to enhance the map style of a given activity. The activity’s polyline is then displayed as a gradient of color based on the chosen attribute.
I think this is pretty neat, but I’m not a Strava premium subscriber. So, naturally, I wondered if I could replicate this in R for free with my raw Garmin data.
Over the summer, ProPublica obtained and released police records from New York City’s Civilian Complaint Review Board (CCRB). The data set offers yet another glimpse into the scale and pervasiveness of racial bias that underpins delinquent police behavior.
The records spanning September 1985 to January 2020 include over 33K closed cases of 3,300 NYPD officers who had at least one misconduct allegation filed against them.
Whenever this quarantine situation lifts, I plan to move out to San Francisco and continue my full-time job in person. Since I hate the process of manually filtering through Craigslist for apartments, I figured I could apply some of my recently-acquired R skills to do the heavy lifting.
In this article, we’ll walk through how to use R to scrape Craigslist posts, clean data, and do some basic visualization.
In 2020, I picked up R and started finding interesting opportunities to tell stories with data and educate beginners on how to do it themselves. My work has been featured by the largest publications on Medium including Towards Data Science and The Startup.
