Eurovision Grand Finale Rankings
Jim Gruman
May 17, 2022
Last updated: 2022-05-17
Checks: 7 0
Knit directory: myTidyTuesday/
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For #TidyTuesday 2022 week 20, Bob Rudis and Tanya Shapiro built a nice sample dataset of Eurovision grand finale rankings from 2004 to 2022.
I am going to attempt to build on Lee Olney’s submission to twitter. Reference https://github.com/leeolney3/TidyTuesday/blob/main/2022/week_20/
#TidyTuesday week 20, Eurovision grand finale rankings from 2004 to 2022. Data from Eurovision, credits to Tanya Shapiro and Bob Rudis.#rstats code: https://t.co/TJNXMGcXg2 pic.twitter.com/xdw1M8bTnx
— Lee Olney (@leeolney3) May 17, 2022
First, let’s load the packages:
suppressPackageStartupMessages({
library(tidyverse)
library(cowplot)
})Second, let’s load the data and a helper function to glue the counts of countries onto the country labels:
withfreq <- function(string, width = 20) {
dplyr::pull(
dplyr::mutate(
dplyr::add_count(tibble::tibble(string), string),
string = glue::glue("{ stringr::str_wrap(string, width = width) } ({ n })")
),
string
)
}
eurovision <- tidytuesdayR::tt_load("2022-05-17")$eurovision |> mutate(artist_country = withfreq(artist_country))--- Compiling #TidyTuesday Information for 2022-05-17 ------- There are 2 files available ------ Starting Download ---
Downloading file 1 of 2: `eurovision.csv`
Downloading file 2 of 2: `eurovision-votes.csv`--- Download complete ---# h/t to Priyanka Mehta @Priyank79286307 for the suggestion to order country by which countries participated most and which won the most
eurovision_by_country <- eurovision |>
filter(section == "grand-final", year != 2020) |>
group_by(year) |>
mutate(rank_label = case_when(
rank %in% c(1, 2, 3) ~ as.character(rank),
rank == max(rank) ~ "last",
TRUE ~ NA_character_
)) |>
ungroup(year) |>
mutate(
artist_country = factor(artist_country,
levels =
eurovision |>
group_by(artist_country) |>
summarise(
highest_rank = min(rank),
n = n_distinct(year),
.groups = "drop"
) |>
arrange(n, desc(highest_rank)) |>
pull(artist_country)
)
)eurovision_by_country |>
ggplot(aes(x = year, y = artist_country)) +
geom_line(size = .3, color = "grey70") +
geom_point(shape = 21, size = 2.5, fill = "white") +
geom_point(
data = eurovision_by_country |> filter(!is.na(rank_label)),
aes(fill = rank_label),
size = 2.5,
shape = 21
) +
scale_fill_manual(
values = c("#F50405", "#F7C83A", "#1CB4EB", "#4F5251"),
guide = guide_legend(order = 1)
) +
scale_x_continuous(
position = "top",
breaks = seq(2005, 2020, 5),
expand = expansion(mult = c(.02, NA))
) +
coord_cartesian(clip = "off") +
cowplot::theme_minimal_vgrid(12) +
theme(
legend.title = element_blank(),
axis.title = element_blank(),
axis.line = element_blank(),
axis.ticks.y = element_blank(),
legend.position = "top",
plot.margin = margin(.4, 1.4, .3, .4, unit = "cm"),
plot.title.position = "plot",
plot.title = element_text(size = 13),
plot.caption.position = "plot",
plot.caption = element_text(
hjust = 0,
color = "grey20",
margin = margin(t = 13),
size = 9
)
) +
labs(
title = "Eurovision Grand Final Rankings",
subtitle = "From 2004 to 2022, arranged in order of artist country number of appearances (in parens)",
caption = "#TidyTuesday week 20 | Data from Eurovision, credits to Tanya Shapiro and Bob Rudis and Lee Olney"
)
Thank you to
- Lee Olney for the head start
- Bob Rudis and Tanya Shapiro
sessionInfo()R version 4.1.3 (2022-03-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22000)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] cowplot_1.1.1 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9
[5] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.7
[9] ggplot2_3.3.6 tidyverse_1.3.1 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] fs_1.5.2 usethis_2.1.5 lubridate_1.8.0 bit64_4.0.5
[5] httr_1.4.3 rprojroot_2.0.3 R.cache_0.15.0 tools_4.1.3
[9] backports_1.4.1 bslib_0.3.1 utf8_1.2.2 R6_2.5.1
[13] DBI_1.1.2 colorspace_2.0-3 withr_2.5.0 tidyselect_1.1.2
[17] processx_3.5.3 bit_4.0.4 curl_4.3.2 compiler_4.1.3
[21] git2r_0.30.1 cli_3.2.0 tweetrmd_0.0.9 rvest_1.0.2
[25] xml2_1.3.3 sass_0.4.1 scales_1.2.0 callr_3.7.0
[29] digest_0.6.29 rmarkdown_2.14 R.utils_2.11.0 tidytuesdayR_1.0.2
[33] pkgconfig_2.0.3 htmltools_0.5.2 styler_1.7.0 highr_0.9
[37] dbplyr_2.1.1 fastmap_1.1.0 rlang_1.0.2 readxl_1.4.0
[41] rstudioapi_0.13 farver_2.1.0 jquerylib_0.1.4 generics_0.1.2
[45] jsonlite_1.8.0 vroom_1.5.7 R.oo_1.24.0 magrittr_2.0.3
[49] Rcpp_1.0.8.3 munsell_0.5.0 fansi_1.0.3 lifecycle_1.0.1
[53] R.methodsS3_1.8.1 stringi_1.7.6 whisker_0.4 yaml_2.3.5
[57] grid_4.1.3 parallel_4.1.3 promises_1.2.0.1 crayon_1.5.1
[61] haven_2.5.0 hms_1.1.1 knitr_1.39 ps_1.7.0
[65] pillar_1.7.0 reprex_2.0.1 glue_1.6.2 evaluate_0.15
[69] getPass_0.2-2 modelr_0.1.8 vctrs_0.4.1 tzdb_0.3.0
[73] httpuv_1.6.5 selectr_0.4-2 cellranger_1.1.0 gtable_0.3.0
[77] rematch2_2.1.2 assertthat_0.2.1 xfun_0.31 broom_0.8.0
[81] later_1.3.0 ellipsis_0.3.2