The rate at which data is being generated by business and the world at large is rapidly exceeding the speed at which leaders are equipping themselves to work with data.
The more coding I do, the more sensitive I become to inefficiency. Here are ten hacks I use regularly to try to minimize distractions and keep up my production pace.
The reticulate package allows R and Python to work together — here’s a tutorial
I struggled to keep it to ten last time, so here’s ten more for you
With so many people jumping on the data science bandwagon, how can you tell a great R coder from the rest?
By writing a function to analyze Star Wars characters, learn the powerful abstraction capabilities of R
Constantly manually executing SQL queries for your clients? Here’s a way to get them to help themselves.
I build R Shiny apps quite a lot, and one of the common uses is to allow dynamic filtering of the underlying data, so that you can adjust a chart or a table based on some particular subset of interest.