# Boxplots and Day of Week Effects

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

THIS BLOG DOES NOT CONSTITUTE INVESTMENT ADVICE. ACTING ON IT WILL MOST LIKELY BE DETRIMENTAL TO YOUR FINANCIAL HEALTH.**MarginTale**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

After following some R-related quant finance blogs like Timely Portfolio, Systematic Investor or Quantitative thoughts– to name some of my favourites – I decided to start my own. I’ll first focus on R snippets which come in handy, and will potentially expand to quant trading and backtesting as time allows.

I’ll start with a simple graphical boxplot analysis of “days of the week effects” with two R snippet/tidbits regarding:

- How do you adapt the ggplot2 plotting of boxplots to a mundane 50%-box 95%-line 5%-dots view?
- How do you subdivide your days in weekdays easily and robustly?

Lets jump directly into the code which can be downloaded at https://gist.github.com/1974563:

Running the code, we get following output:

From MarginTale |

These boxplots now show 50% of the observations in the box, the vertical lines cover 95% and the dots 2.5%. I find this easier to communicate than the standard definition. This is implemented in the functions myBoxPlotSummary and myBoxPlotOutliers which are in turn called from stat_summary in ggplot.

A second issue I tripped over is the sorting of days in the above boxplot. If one uses the obvious way and just defines a factor as “weekdays(index(…))” then the plot function will alphabetically sort the days – not exactly what you want. If you then try to order the factors, your solution will depend on how locale (the language you use) specifies the abbreviations of the weekdays. A robust solution shown in the code is to use the function .indexwday from the package xts.

To

**leave a comment**for the author, please follow the link and comment on their blog:**MarginTale**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.