Eurovision: Sweden and Ireland Lead with the Most Wins

Tracking Eurovision Wins by Country from 1956 to 2024

SWDchallenge

2024

Eurovision wins by country from 1956 to 2024, led by Sweden and Ireland. Built in R.

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

```{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

Code

```{r}
#| label: read

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

3. Examine the Data

Code

```{r}
#| label: examine

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

4. Tidy Data

Code

```{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

Code

```{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 &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

```{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

Code

```{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

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_3.6.4        
 [5] htmltools_0.5.8.1 tools_4.4.0       rstudioapi_0.17.1 yaml_2.3.10      
 [9] rmarkdown_2.29    knitr_1.49        jsonlite_1.8.9    xfun_0.49        
[13] digest_0.6.37     rlang_1.1.6       renv_1.0.3        evaluate_1.0.1

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" description: "Eurovision wins by country from 1956 to 2024, led by Sweden and Ireland. Built in R." date: "2024-11-01" categories: ["SWDchallenge", "2024"] 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: freeze: true 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/) :::