First Steps With ExPanDaR

Each day, Mara Averick (@dataandme) (link) shares some excellent R advice and links on Twitter. For a while, I bookmarked all her suggestions but there were so many of them that I did not manage to return to them. Even allocating them to bookmark folders did not improve my follow up rate.

For the past month or so, I have been creating R scripts in RStudio each day to try out the coding of some of her suggestions. This was the case today with her link to Joachim Gassen’s ExPanDaR 0.4.0 package (link).

I have a GitHub repository for this exploration to share my csv files and code (link). Like most of my efforts it is just a start … and an attempt to share sport examples.

However, I am really interested in the package’s potential for me to have a first look at data, and if appropriate to work through it with coaches to develop their data dashboard … if they think it can be of help to them.

I used the ExPanDaR’s functions to create: a descriptive table (of all variables); a scatter plot; a quantile_trend_graph (distributions of one variable over time); and a list of the 5 most extreme observations in the data frame. I particularly liked the Shiny opportunities I had to plot variables. I am still trying to work out the tooltip functionality for my descriptive table.

My visualisation examples are:

I am looking forward to exploring these functions and other visualisation functions available in ExPanDaR.

#AsianCup2019 after 12 games: a look at fouls, yellow cards, goals and referees

Twelve games have been played in the 2019 Asian Cup football tournament (link). I am using the official AFC website for some secondary data analysis.

In this post, I look at some of the data relating to fouls penalised, yellow cards, goals scored and the referees involved.

I have used ggplot2 (link) and ggrepel (link) for some very basic visualisations: