I found a new dataset about UK broadband speeds and I started analysing it in R. However, after cleaning the data, I thought that creating a dashboard with Shiny would take me too much time so I moved to Tableau. I wanted to keep my analyses in one place so I embedded the dashboard into the output html document (see below).
Initially I thought that RMarkdown can’t generate embedded Tableau visualizations because the iframe in my report seemed blank after knitting the report. I had to open the generated in the browser to see the iframe filled with Tableau dashboard.
RMarkdown file is available here.
Kaggle released new data set which I thought would be perfect to try interactive visualizations from qtlcharts, ggvis, and radarchart packages.
The html report generated with RMarkdown and the latest version uploaded to Kaggle (kernel) is here.
Kaggle released another interesting data set. This time it’s a loan book of a P2P lender – Lending Club.
I had a stab at analysing it and here are some teaser charts that were created, but more can be found here.
Kaggle publishes many interesting datasets and one of them was including various world university rankings.
I decided to run a quick analysis of the CWUR data and create a map in R using rworldmap package.
The initial results are here:
USA and China outnumber other countries by the number of universities in the CWUR data.
The map shows that USA by far outnumbers other countries in the top 100 universities according to CWUR.
Here’s the gist:
My latest script for this analysis can be found on Kaggle.