It’s a lot easier than you think, and there’s some questionable Seventies music too!
An introduction into tidy databases in R with dbplyr
Learn about R’s scraping capabilities and write a simple function to grab a US music chart from any date in the past
Explore the all time best teams of English football and learn how to make one of those race bar charts that have become popular
R is full of useful stuff. Here are a few things that I use a lot which others may not know about.
By writing a function to analyze Star Wars characters, learn the powerful abstraction capabilities of R
How to test your server side output and stop unnecessary red error messages of death appearing in your user interface
Constantly manually executing SQL queries for your clients? Here’s a way to get them to help themselves.
It is now possible to build Shiny apps that can update themselves on a regular basis, pulling in refreshed data so that people are always looking at the most up to date analysis. So with one up front development sprint, an analyst can reduce their ongoing analytic workload on a particular topic by close to 100%.
As data scientists, we are all familiar with what happens when a process, package or application breaks. We dive into it with interest to try to diagnose where the unanticipated error occurred. Did something unexpected occur in the raw data? Did our code not anticipate a particular permutation of inputs?