With a bunch of data about the best performances in different running events, I wanted to learn how to produce meaningful plots and inside with R and ggplot. The data is originally taken from http://www.alltime-athletics.com/men.htm a website by Peter Larsson. I did a lot of postprocessing to be able to handle the data more easily. I also wanted to learn how to work with R and data frames. Most of the source code was taken from StackOverflow or other sides. Especially helpful was also the ggplot documentation. The data set, together with the source code that produces the figures below can be downloaded from Github.
I consider data for the male running events: 100m, 200m, 400m, 800m, 1.500m, 5.000m, 10.000m and the marathon. For each event, there are hundreds to thousands of results. These results are sorted by best performance. I.e., this might be the 1000 best marathon performances. For each of these performances, we have the associated rank that comes along with that performance. But also data like the name, date of birth and nationality of the athlete. Some typical lines in the original data file look like this:
1, 2:02:57 , Dennis Kimetto , KEN , 22.04.84 ,1, Berlin , 28.09.2014
2, 2:03:02 , Geoffrey Mutai , KEN , 07.10.81 ,1, Boston , 18.04.2011
3, 2:03:03 , Kenenisa Bekele , ETH , 13.06.82 ,1, Berlin , 25.09.2016
Meaning that Dennis Kimetto from Kenya ran the marathon world record in Berlin in 2014 with a time of 2:2:57h. The second best performance all-time was from Geoggrey Mutai and the third best performance from Kenenisa Bekele. The data was obtained in July 2018, so there might be some changes in the future.