Eurovision: Sweden and Ireland Lead with the Most Wins

Tracking Eurovision Wins by Country from 1956 to 2024

#SWDchallenge

Author

Steven Ponce

Published

November 1, 2024

Original

The goal of this month’s #SWDchallenge is to make a good graph. For my submission, I decided to revisit a #dataviz from early in my journey. The chart below was my submission for the 2022 #TidyTuesday week 20 challenge. The goal back then was to visualize the countries with more than three Eurovision wins.

Additional information about this month’s #SWDchallenge can be found HERE

Makeover

Figure 2: Line chart showing cumulative Eurovision wins by country from 1956 to 2024. Sweden and Ireland lead with 7 wins each, with Ireland’s most recent win in 1996 and Sweden’s in 2023. Other countries have fewer wins, depicted in gray.

Steps to Create this Graphic

1. Load Packages & Setup

Code

if (!require("pacman")) install.packages("pacman")
pacman::p_load(
  tidyverse,         # Easily Install and Load the 'Tidyverse'
  ggtext,            # Improved Text Rendering Support for 'ggplot2'
  showtext,          # Using Fonts More Easily in R Graphs
  janitor,           # Simple Tools for Examining and Cleaning Dirty Data
  skimr,             # Compact and Flexible Summaries of Data
  scales,            # Scale Functions for Visualization
  glue,              # Interpreted String Literals
  here,              # A Simpler Way to Find Your Files
  tidytuesdayR,      # Access the Weekly 'TidyTuesday' Project Dataset
  ggrepel            # Automatically Position Non-Overlapping Text Labels with 'ggplot2'
) 

### |- figure size ---- 
camcorder::gg_record( 
  dir    = here::here("temp_plots"), 
  device = "png",
  width  = 10,
  height = 8,
  units  = "in",
  dpi    = 320)

### |- resolution ---- 
showtext_opts(dpi = 320, regular.wt = 300, bold.wt = 800)

2. Read in the Data

Code

eurovision <- tidytuesdayR::tt_load(2022, week = 20)$eurovision %>% 
  clean_names()

3. Examine the Data

Code

glimpse(eurovision)
skim(eurovision)
colnames(eurovision)

4. Tidy Data

Code

# Winners from 1956 to 2003
winners_1956_2003_tbl <- eurovision |> 
  filter(year < 2004,
         section == 'final',
         winner == TRUE) |> 
  select(year, host_city, artist_country, total_points, winner) |> 
  arrange(desc(year)) |> 
  drop_na()

# Winners from 2004 to 2022
winners_2004_2022_tbl <- eurovision |> 
  filter(section == 'grand-final',
         winner == TRUE) |> 
  select(year, host_city, artist_country, total_points, winner) |> 
  arrange(desc(year)) |> 
  drop_na()

# Winners for 2023 and 2024
winners_2023_2024_tbl <- tibble(
  year = c(2023, 2024),
  host_city = c("Liverpool", "Malmö"),  
  artist_country = c("Sweden", "Switzerland"),
  total_points = c(583, 591),  # Placeholder points, adjust based on real data if available
  winner = TRUE
)
 
# Combine all winners
winners_combined_tbl <- bind_rows(winners_1956_2003_tbl, winners_2004_2022_tbl, winners_2023_2024_tbl) |>
  arrange(year) |>
  drop_na()

# Calculate cumulative wins by year
cumulative_data <- winners_combined_tbl |>
  group_by(year, artist_country) |>
  summarise(total_points = sum(total_points), .groups = "drop") |>
  arrange(year) |>
  group_by(artist_country) |>
  mutate(cumulative_wins = row_number()) |>
  ungroup()

# Define key countries to highlight
key_countries <- c("Sweden", "Ireland")

# Get the most recent year for each key country
latest_year_data <- cumulative_data |> 
  filter(artist_country %in% key_countries) |> 
  group_by(artist_country) |> 
  filter(year == max(year)) |> 
  ungroup()

5. Visualization Parameters

Code

### |- plot aesthetics ---- 
bkg_col      <- "#f5f5f2"  
title_col    <- "gray20"           
subtitle_col <- "gray20"     
caption_col  <- "gray30"   
text_col     <- "gray20"    
col_palette  <- c("#FF007F", "#004080")

### |-  titles and caption ----
# icons
tt <- str_glue("#SWDchallenge: Nov 2024 &bull; Source: TidyTuesday 2023 week 20<br>")
li <- str_glue("<span style='font-family:fa6-brands'>&#xf08c;</span>")
gh <- str_glue("<span style='font-family:fa6-brands'>&#xf09b;</span>")
bs <- str_glue("<span style='font-family:fa6-brands'>&#xe671; </span>")

title_text    <- str_glue("Eurovision: Sweden and Ukraine Lead with the Most Wins")
subtitle_text <- str_glue("Tracking Eurovision Wins by Country from 1956 to 2024<br><br>
                          **Total Wins Since Inception**")
caption_text  <- str_glue("{tt} {li} stevenponce &bull; {bs} sponce1 &bull; {gh} poncest &bull; #rstats #ggplot2")

# |- fonts ----
font_add('fa6-brands', here::here("fonts/6.6.0/Font Awesome 6 Brands-Regular-400.otf"))
font_add_google("Oswald", regular.wt = 400, family = "title")                 
font_add_google("Merriweather Sans", regular.wt = 400, family = "subtitle")
font_add_google("Merriweather Sans", regular.wt = 400, family = "text")   
font_add_google("Noto Sans", regular.wt = 400,family = "caption")
showtext_auto(enable = TRUE)  

### |-  plot theme ----
theme_set(theme_minimal(base_size = 14, base_family = "text"))                

theme_update(
  plot.title.position   = "plot",
  plot.caption.position = "plot",
  legend.position       = "plot",
  plot.background       = element_rect(fill = bkg_col, color = bkg_col),
  panel.background      = element_rect(fill = bkg_col, color = bkg_col),
  plot.margin           = margin(t = 10, r = 20, b = 10, l = 20),
  axis.title.x          = element_text(margin = margin(10, 0, 0, 0), size = rel(1.1), 
                                       color = text_col, family = "text", face = "bold", hjust = 0.5),
  axis.title.y          = element_text(margin = margin(0, 10, 0, 0), size = rel(1.1), 
                                       color = text_col, family = "text", face = "bold", hjust = 0.5),
  axis.text             = element_text(size = rel(0.8), color = text_col, family = "text"),
  axis.line.x           = element_line(color = "#252525", linewidth = .3),
  axis.ticks.x          = element_line(color = text_col),  
  axis.title            = element_text(face = "bold"),
  panel.grid.minor      = element_blank(),
  panel.grid.major      = element_blank(),
  panel.grid.major.y    = element_line(color = "grey85", linewidth = .4),
)

6. Plot

Code

#  Line Chart 
cumulative_line_chart <-
  # Geoms
  ggplot(
    cumulative_data,
    aes(x = year, y = cumulative_wins, group = artist_country, color = artist_country)
  ) +
  geom_line(
    data = cumulative_data |> filter(!artist_country %in% key_countries),
    linewidth = 0.25, color = "gray20", alpha = 0.3, linetype = "solid"
  ) +
  geom_line(
    data = cumulative_data |> filter(artist_country %in% key_countries),
    linewidth = 1.2
  ) +
  geom_point(
    data = latest_year_data,
    aes(color = artist_country), size = 4, shape = 21, fill = "white", stroke = 2
  ) +
  geom_text(
    data = latest_year_data,
    aes(label = str_glue("{artist_country} ({cumulative_wins})\n{year}")),
    vjust = -0.5,
    hjust = 0.2, nudge_x = 1, size = 4, fontface = "bold", lineheight = 1
  ) +

  # Scales
  scale_x_continuous(
    breaks = pretty_breaks(n = 5),
    limits = c(min(cumulative_data$year), max(cumulative_data$year) + 5)
  ) +
  scale_y_continuous(
    breaks = seq(0, 8, by = 2),
    limits = c(0, 8)
  )+
  scale_color_manual(values = col_palette) +
  coord_cartesian(clip = "off") +
  
  # Labs
  labs(
    x = "Year",
    y = "",
    color = "Country",
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text
  ) +
  
  # Theme
  theme(
    plot.title = element_text(
      size = rel(1.8),
      family = "title",
      face = "bold",
      color = title_col,
      lineheight = 1.1,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(1.1),
      family = "subtitle",
      color = subtitle_col,
      lineheight = 1.1,
      margin = margin(t = 5, b = 20)
    ),
    plot.caption = element_markdown(
      size = rel(0.65),
      family = "caption",
      color = caption_col,
      lineheight = 1.1,
      hjust = 0.5,
      halign = 1,
      margin = margin(t = 15, b = 5)
    )
  )


# Show plot
cumulative_line_chart

7. Save

Code

### |-  plot image ----  

# Save the plot again
ggsave(
  filename = here::here("data_visualizations/SWD Challenge/2024/swd_2024_11.png"),
  plot   = cumulative_line_chart,
  width  =  10,
  height =  8,
  units  = "in",
  dpi    = 320
)
 
### |-  plot thumbnail----  
magick::image_read(here::here("data_visualizations/SWD Challenge/2024/swd_2024_11.png")) |> 
  magick::image_resize(geometry = "400") |> 
  magick::image_write(here::here("data_visualizations/SWD Challenge/2024/thumbnails/swd_2024_11.png"))

8. Session Info

Expand for Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

loaded via a namespace (and not attached):
 [1] htmlwidgets_1.6.4 compiler_4.4.0    fastmap_1.2.0     cli_3.6.3        
 [5] htmltools_0.5.8.1 tools_4.4.0       rstudioapi_0.16.0 yaml_2.3.10      
 [9] rmarkdown_2.28    knitr_1.48        jsonlite_1.8.8    xfun_0.47        
[13] digest_0.6.37     rlang_1.1.4       renv_1.0.3        evaluate_0.24.0

9. GitHub Repository

Expand for GitHub Repo

Access the GitHub repository here

--- title: "Eurovision: Sweden and Ireland Lead with the Most Wins" subtitle: "Tracking Eurovision Wins by Country from 1956 to 2024" author: "Steven Ponce" date: "2024-11-01" categories: - "#SWDchallenge" image: "thumbnails/swd_2024_11.png" format: html: toc: true toc-depth: 5 code-link: true code-fold: true code-tools: true editor_options: chunk_output_type: console execute: error: false message: false warning: false eval: false share: permalink: "https://stevenponce.netlify.app/data_visualizations.html" linkedin: true twitter: true email: true --- ### Original The goal of this month's #SWDchallenge is to _make a good graph_. For my submission, I decided to revisit a #dataviz from early in my journey. The chart below was my submission for the 2022 #TidyTuesday week 20 challenge. The goal back then was to visualize the countries with more than three Eurovision wins. ![Original chart](https://raw.githubusercontent.com/poncest/tidytuesday/main/2022/Week_20/2022_20_eurovision.png){#fig-1} Additional information about this month's #SWDchallenge can be found [HERE](https://community.storytellingwithdata.com/challenges/nov-2024-make-a-good-graph) ### Makeover ![Line chart showing cumulative Eurovision wins by country from 1956 to 2024. Sweden and Ireland lead with 7 wins each, with Ireland's most recent win in 1996 and Sweden's in 2023. Other countries have fewer wins, depicted in gray.](swd_2024_11.png){#fig-1} ### __Steps to Create this Graphic__ #### 1. Load Packages & Setup ```{r} #| label: load if (!require("pacman")) install.packages("pacman") pacman::p_load( tidyverse, # Easily Install and Load the 'Tidyverse' ggtext, # Improved Text Rendering Support for 'ggplot2' showtext, # Using Fonts More Easily in R Graphs janitor, # Simple Tools for Examining and Cleaning Dirty Data skimr, # Compact and Flexible Summaries of Data scales, # Scale Functions for Visualization glue, # Interpreted String Literals here, # A Simpler Way to Find Your Files tidytuesdayR, # Access the Weekly 'TidyTuesday' Project Dataset ggrepel # Automatically Position Non-Overlapping Text Labels with 'ggplot2' ) ### |- figure size ---- camcorder::gg_record( dir = here::here("temp_plots"), device = "png", width = 10, height = 8, units = "in", dpi = 320) ### |- resolution ---- showtext_opts(dpi = 320, regular.wt = 300, bold.wt = 800) ``` #### 2. Read in the Data ```{r} #| label: read eurovision <- tidytuesdayR::tt_load(2022, week = 20)$eurovision %>% clean_names() ``` #### 3. Examine the Data ```{r} #| label: examine glimpse(eurovision) skim(eurovision) colnames(eurovision) ``` #### 4. Tidy Data ```{r} #| label: tidy # Winners from 1956 to 2003 winners_1956_2003_tbl <- eurovision |> filter(year < 2004, section == 'final', winner == TRUE) |> select(year, host_city, artist_country, total_points, winner) |> arrange(desc(year)) |> drop_na() # Winners from 2004 to 2022 winners_2004_2022_tbl <- eurovision |> filter(section == 'grand-final', winner == TRUE) |> select(year, host_city, artist_country, total_points, winner) |> arrange(desc(year)) |> drop_na() # Winners for 2023 and 2024 winners_2023_2024_tbl <- tibble( year = c(2023, 2024), host_city = c("Liverpool", "Malmö"), artist_country = c("Sweden", "Switzerland"), total_points = c(583, 591), # Placeholder points, adjust based on real data if available winner = TRUE ) # Combine all winners winners_combined_tbl <- bind_rows(winners_1956_2003_tbl, winners_2004_2022_tbl, winners_2023_2024_tbl) |> arrange(year) |> drop_na() # Calculate cumulative wins by year cumulative_data <- winners_combined_tbl |> group_by(year, artist_country) |> summarise(total_points = sum(total_points), .groups = "drop") |> arrange(year) |> group_by(artist_country) |> mutate(cumulative_wins = row_number()) |> ungroup() # Define key countries to highlight key_countries <- c("Sweden", "Ireland") # Get the most recent year for each key country latest_year_data <- cumulative_data |> filter(artist_country %in% key_countries) |> group_by(artist_country) |> filter(year == max(year)) |> ungroup() ``` #### 5. Visualization Parameters ```{r} #| label: params ### |- plot aesthetics ---- bkg_col <- "#f5f5f2" title_col <- "gray20" subtitle_col <- "gray20" caption_col <- "gray30" text_col <- "gray20" col_palette <- c("#FF007F", "#004080") ### |- titles and caption ---- # icons tt <- str_glue("#SWDchallenge: Nov 2024 • Source: TidyTuesday 2023 week 20 ") li <- str_glue("") gh <- str_glue("") bs <- str_glue(" ") title_text <- str_glue("Eurovision: Sweden and Ukraine Lead with the Most Wins") subtitle_text <- str_glue("Tracking Eurovision Wins by Country from 1956 to 2024 **Total Wins Since Inception**") caption_text <- str_glue("{tt} {li} stevenponce • {bs} sponce1 • {gh} poncest • #rstats #ggplot2") # |- fonts ---- font_add('fa6-brands', here::here("fonts/6.6.0/Font Awesome 6 Brands-Regular-400.otf")) font_add_google("Oswald", regular.wt = 400, family = "title") font_add_google("Merriweather Sans", regular.wt = 400, family = "subtitle") font_add_google("Merriweather Sans", regular.wt = 400, family = "text") font_add_google("Noto Sans", regular.wt = 400,family = "caption") showtext_auto(enable = TRUE) ### |- plot theme ---- theme_set(theme_minimal(base_size = 14, base_family = "text")) theme_update( plot.title.position = "plot", plot.caption.position = "plot", legend.position = "plot", plot.background = element_rect(fill = bkg_col, color = bkg_col), panel.background = element_rect(fill = bkg_col, color = bkg_col), plot.margin = margin(t = 10, r = 20, b = 10, l = 20), axis.title.x = element_text(margin = margin(10, 0, 0, 0), size = rel(1.1), color = text_col, family = "text", face = "bold", hjust = 0.5), axis.title.y = element_text(margin = margin(0, 10, 0, 0), size = rel(1.1), color = text_col, family = "text", face = "bold", hjust = 0.5), axis.text = element_text(size = rel(0.8), color = text_col, family = "text"), axis.line.x = element_line(color = "#252525", linewidth = .3), axis.ticks.x = element_line(color = text_col), axis.title = element_text(face = "bold"), panel.grid.minor = element_blank(), panel.grid.major = element_blank(), panel.grid.major.y = element_line(color = "grey85", linewidth = .4), ) ``` #### 6. Plot ```{r} #| label: plot # Line Chart cumulative_line_chart <- # Geoms ggplot( cumulative_data, aes(x = year, y = cumulative_wins, group = artist_country, color = artist_country) ) + geom_line( data = cumulative_data |> filter(!artist_country %in% key_countries), linewidth = 0.25, color = "gray20", alpha = 0.3, linetype = "solid" ) + geom_line( data = cumulative_data |> filter(artist_country %in% key_countries), linewidth = 1.2 ) + geom_point( data = latest_year_data, aes(color = artist_country), size = 4, shape = 21, fill = "white", stroke = 2 ) + geom_text( data = latest_year_data, aes(label = str_glue("{artist_country} ({cumulative_wins})\n{year}")), vjust = -0.5, hjust = 0.2, nudge_x = 1, size = 4, fontface = "bold", lineheight = 1 ) + # Scales scale_x_continuous( breaks = pretty_breaks(n = 5), limits = c(min(cumulative_data$year), max(cumulative_data$year) + 5) ) + scale_y_continuous( breaks = seq(0, 8, by = 2), limits = c(0, 8) )+ scale_color_manual(values = col_palette) + coord_cartesian(clip = "off") + # Labs labs( x = "Year", y = "", color = "Country", title = title_text, subtitle = subtitle_text, caption = caption_text ) + # Theme theme( plot.title = element_text( size = rel(1.8), family = "title", face = "bold", color = title_col, lineheight = 1.1, margin = margin(t = 5, b = 5) ), plot.subtitle = element_markdown( size = rel(1.1), family = "subtitle", color = subtitle_col, lineheight = 1.1, margin = margin(t = 5, b = 20) ), plot.caption = element_markdown( size = rel(0.65), family = "caption", color = caption_col, lineheight = 1.1, hjust = 0.5, halign = 1, margin = margin(t = 15, b = 5) ) ) # Show plot cumulative_line_chart ``` #### 7. Save ```{r} #| label: save ### |- plot image ---- # Save the plot again ggsave( filename = here::here("data_visualizations/SWD Challenge/2024/swd_2024_11.png"), plot = cumulative_line_chart, width = 10, height = 8, units = "in", dpi = 320 ) ### |- plot thumbnail---- magick::image_read(here::here("data_visualizations/SWD Challenge/2024/swd_2024_11.png")) |> magick::image_resize(geometry = "400") |> magick::image_write(here::here("data_visualizations/SWD Challenge/2024/thumbnails/swd_2024_11.png")) ``` #### 8. Session Info ::: {.callout-tip collapse="true"} ##### Expand for Session Info ```{r, echo = FALSE} #| eval: true sessionInfo() ``` ::: #### 9. GitHub Repository ::: {.callout-tip collapse="true"} ##### Expand for GitHub Repo [Access the GitHub repository here](https://github.com/poncest/personal-website/) :::