Week 11 Tutorial Worksheet
AY23/24 Semester 1
No submission required
Question 1
In this tutorial, we continue to work with the Olympics data from TidyTuesday. We will use
the following two data sets:
• olympics.csv contains information on Olympic games from 1896 to 2016.
• regions.csv maps the 3-digit NOC codes to the country/region names.
1. Create a graph on the number of nations and events in each Summer Olympics from 1896
to 2016 using ggplot2 plotting. Your graph can be similar to the following.
Number of Events and Nations in Summer Olympics
300
Events
200
Nations
100
0
1890
1920
1950
1980
2010
2. Which five countries won the most gold medals in 2016? Use your dplyr skills answer this
question.
After that, extract the names (in noc) of the top five countries as a vector named
summer_top_5. The vector should take the following value:
1
summer_top_5
## [1] "USA" "GBR" "CHN" "RUS" "GER"
3. Compute the number of gold medals received for the summer_top_5 countries since the
year of 2000. Use it to re-create the plot below, as closely as you can.
Gold medals received for selected countries, by year
50
Number of golds received
USA
40
30
UK
China
20
Russia
Germany
10
2000
2004
2008
2012
2016
4. Instead of the total number of golds, let us now examine the countries’ rankings in golds
received across years. Prepare the data to obtain the rankings in golds received for the
summer_top_5 countries from 2000 to 2016. Save your resulting data frame as an object
named ranks_top_5.
Hint: Ranking functions in R vary in how they handle tied values. dplyr provides two
handy functions: min_rank() and dense_rank(). For sports data, the former is typically
the conventional choice. More information is available in their documentation.
5. Use ranks_top_5 to re-create, as much as you can, the plot below.
2
Rankings of golds received, by year
for countries that won the most golds in 2016
1
USA
2
UK
3
China
4
Russia
5
Germany
6
7
8
9
2000
2004
2008
2012
2016
Note: dplyr::min_rank() was used to compute country rankings
Requirements
• You code should generate a vector named summer_top_5 and a data frame named
ranks_top_5.
• The knitted HTML should contain three plots, one each for Question 1.1, Question 1.3,
and Question 1.5.
3