Analyzing US Drought data

Series: R Tidy Tuesday

The data this week comes from the U.S. Drought Monitor.

Analyzing Survivor TV Show data

The data this week comes from the survivorR R package by way of Daniel Oehm. survivoR is a collection of data sets detailing events across all 40 seasons of the US Survivor, including castaway information, vote history, immunity and reward challenge winners and jury votes.

Analyzing CEO depatures

Series: R Tidy Tuesday

The data this week comes from Gentry et al. by way of DataIsPlural. It contains the reasons for CEO departure in S&P 1500 firms from 2000 through 2018.

R Tidy Tuesday analysis

I consider data analysis just like a sport: to become or stay good at it regular training is required. In this series, I analyze interesting data sets provided by the great R Tidy Tuesday data project as a mean “to stay in shape”.

(Self-inflicted) rules: I give myself roughly 90 minutes for the analysis and an extra 30 minutes for documenting.

Needless to say, the analysis and the documentation are not meant to be exhaustive and perfect in this case.

I try to write one or two of these analysis per month.

Tidy Tuesday was born out of the R4DS (R for data science) Online Learning Community and the R for Data Science textbook written by Hadley Wickham and Garrett Grolemund. Every week a “tamed” new data set (i.e. data is partly preprocessed but not completely tidy) alongside an article or a source is posted on the Tidy Tuesday GitHub repository.

The goal is to explore this data set using data wrangling and summarizing techniques and (lots of) insightful visualizations.

Written by Manuel Rademaker