An edited barplot

Let’s do a better plot, ordering the bars, plotting each winner’s continent and presenting the countries with their flags. To do so, I’ve:

• Obtained the iso2 code and continent of each country.
• As England is missing in the table, I am replacing its values, and picking a file with the English flag from the internet with england_link.

winners <- winners %>%
  mutate(iso2 = countrycode(winner, "country.name", "iso2c"),
         continent = countrycode(winner, "country.name", "continent"))

winners <- winners %>%
  mutate(iso2 = replace(iso2, is.na(iso2), "EN"),
         continent = replace(continent, is.na(continent), "Europe"))

england_link <- "https://upload.wikimedia.org/wikipedia/en/thumb/b/be/Flag_of_England.svg/800px-Flag_of_England.svg.png"

Here is the new version of the visualization of the World Cup winners:

• Define the plot as a bar plot, with fill color defined by continent of each country.
• Set the limits of y axis with ylim so that I can set the flags on the left hand side.
• Placing country flags in y = -0.5 with geom_flag. England flag is missing as it is not included in this geom.
• Placing the English flag with geom_image.
• Placing the number of World Cups won of each country with geom_text for better readability. This will allow removing the y axis later.
• Flip axis with coord_flip and remove axis and background with theme_void.
• Set an image title with ggtitle.
• Tune colors and legend labels with scale_fill_manual. Legend size is tuned with legend.* parameters in the theme.
• Change title size with plot.title in theme.

winners %>%
  mutate(winner = fct_reorder(winner, n)) %>%
  ggplot(aes(winner, n, fill = continent)) +
  geom_bar(stat = "identity") +
  ylim(-1, 5) +
  geom_flag(y = -0.5, aes(image = iso2), size = 0.12) +
  geom_image(aes(x = "England", y = -0.5, image = england_link), size = 0.12) +
  geom_text(aes(label = n), hjust = -1, size = 5) +
  coord_flip() +
  theme_void() +
  ggtitle("Winners of the World Cup until 2018") +
  scale_fill_manual(values = c("#9E66AB", "#599AD3"), label = c("America", "Europe")) +
  theme(legend.position = c(0.7, 0.2),
        legend.key.size = unit(1, 'cm'),
        legend.text = element_text(size = 12),
        legend.title = element_text(size = 15),
        plot.title = element_text(size = 20))

The resulting barplot is hopefully more informative than the default plot.

A World Cup winners timeline

I have also done a timeline plot presenting where has won the World Cups each of the winners. For doing that, I need to obtain World Cup winners ordered with non-increasing order of Cups won l_winners:

l_winners <- winners %>%
  arrange(n) %>%
  pull(winner)

I also need a the url address of a World Cup icon:

world_cup_icon <- "https://upload.wikimedia.org/wikipedia/commons/thumb/b/ba/FIFA_World_Cup_Icon_%28Campionato_mondiale_di_calcio%29.svg/94px-FIFA_World_Cup_Icon_%28Campionato_mondiale_di_calcio%29.svg.png"

Here is the plot. Let’s see how I have done it:

• I am retrieving the iso2 country codes in worldcups to set the flags later.
• The plot has year in the x axis, and winner in the y axis.
• In every year a country has won a World Cup I am placing a World Cup icon with geom_image.
• I am placing country flags on the left-hand size like in the previous plot. Let’s remember that first World Cup was celebrated in 1930. I am using geom_flag and geom_image in the same was as in the previous plot.
• I am changing the default labels of the years axis with scale_x_continuous.
• I am using theme_minimal to maintain the grid lines in a white background. In theme I am removing all elements of the y axis.

worldcups %>%
  mutate(winner = factor(winner, levels = l_winners),
         iso2 = countrycode(winner, "country.name", "iso2c")) %>%
  mutate(iso2 = replace(iso2, is.na(iso2), "EN")) %>%
  ggplot(aes(year, winner)) +
  geom_image(image = world_cup_icon, size = 0.03) +
  geom_flag(x = 1920, aes(image = iso2)) +
  geom_image(aes(y = "England", x = 1920, image = england_link)) +
  scale_x_continuous(limits = c(1920, 2018), breaks = seq(1930, 2018, 8), name = element_blank()) +
  theme_minimal() +
  theme(axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        axis.title.y = element_blank())

We observe here that Uruguay won its two World Cups in the first editions of the competition. We also see how Argentina, France and Spain have started to win World Cups recently.

With these two visualizations, I have presented some of the functionalities of ggplot2 to customize plots. I have also introduced ggimage package, that allows placing any image in plots done with ggplot2 with geom_image and geom_flag.

References

• FIFA World Cup dataset from Kaggle in tidytuesday repository: https://github.com/rfordatascience/tidytuesday/tree/master/data/2022/2022-11-29
• The first visualization was largely inspired by Paula’s blog R Functions and Packages for Political Science Analysis: https://rforpoliticalscience.com/2020/12/22/add-flags-to-graphs-with-ggimage-package-in-r/
• I have selected barplot colors inspired by this post compiled by R bloggers: https://www.r-bloggers.com/2012/05/bar-graph-colours-that-work-well/

Session info

## R version 4.2.2 Patched (2022-11-10 r83330)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Linux Mint 19.2
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
## 
## locale:
##  [1] LC_CTYPE=es_ES.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=es_ES.UTF-8    
##  [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=es_ES.UTF-8   
##  [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] countrycode_1.4.0  tidytuesdayR_1.0.2 kableExtra_1.3.4   ggimage_0.3.1     
##  [5] forcats_0.5.2      stringr_1.4.1      dplyr_1.0.10       purrr_0.3.5       
##  [9] readr_2.1.3        tidyr_1.2.1        tibble_3.1.8       ggplot2_3.4.0     
## [13] tidyverse_1.3.1   
## 
## loaded via a namespace (and not attached):
##  [1] httr_1.4.4         sass_0.4.1         jsonlite_1.8.3     viridisLite_0.4.1 
##  [5] modelr_0.1.10      bslib_0.3.1        assertthat_0.2.1   highr_0.9         
##  [9] yulab.utils_0.0.5  cellranger_1.1.0   yaml_2.3.6         pillar_1.8.1      
## [13] backports_1.4.1    glue_1.6.2         digest_0.6.30      rvest_1.0.3       
## [17] colorspace_2.0-3   ggfun_0.0.9        htmltools_0.5.3    pkgconfig_2.0.3   
## [21] broom_1.0.1        haven_2.5.1        magick_2.7.3       bookdown_0.26     
## [25] scales_1.2.1       webshot_0.5.3      ggplotify_0.1.0    svglite_2.1.0     
## [29] tzdb_0.3.0         timechange_0.1.1   farver_2.1.1       generics_0.1.2    
## [33] usethis_2.1.5      ellipsis_0.3.2     withr_2.5.0        cli_3.4.1         
## [37] magrittr_2.0.3     crayon_1.5.2       readxl_1.4.1       evaluate_0.17     
## [41] fs_1.5.2           fansi_1.0.3        xml2_1.3.3         blogdown_1.9      
## [45] tools_4.2.2        hms_1.1.2          lifecycle_1.0.3    munsell_0.5.0     
## [49] reprex_2.0.2       compiler_4.2.2     jquerylib_0.1.4    gridGraphics_0.5-1
## [53] systemfonts_1.0.4  rlang_1.0.6        grid_4.2.2         rstudioapi_0.13   
## [57] labeling_0.4.2     rmarkdown_2.14     gtable_0.3.0       DBI_1.1.2         
## [61] curl_4.3.2         R6_2.5.1           lubridate_1.9.0    knitr_1.40        
## [65] fastmap_1.1.0      utf8_1.2.2         stringi_1.7.8      Rcpp_1.0.9        
## [69] vctrs_0.5.0        dbplyr_2.2.1       tidyselect_1.1.2   xfun_0.34