juliasilge/eurovision.md

## eurovision.md

      
    Raw
  

              eurovision.md
            
          
    library(tidyverse)
library(widyr)
library(maps)
#> 
#> Attaching package: 'maps'
#> The following object is masked from 'package:purrr':
#> 
#>     map
eurovision_votes <- read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-05-17/eurovision-votes.csv')
#> Rows: 56312 Columns: 8
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (6): semi_final, edition, jury_or_televoting, from_country, to_country, ...
#> dbl (2): year, points
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

set.seed(234)
eurovision_clusters <-
    eurovision_votes %>%
    widely_svd(from_country, to_country, points, nv = 24) %>%
    widely_kmeans(from_country, dimension, value, k = 4)

eurovision_clusters %>% 
    group_by(cluster) %>% 
    summarise(from_country = paste(from_country, collapse = ", ")) %>% 
    knitr::kable()


cluster
from_country


1
Belarus, Belgium, Bosnia & Herzegovina, Bulgaria, Estonia, Greece, Israel, Latvia, Lithuania, Poland, Romania, Russia, San Marino, Slovakia, United Kingdom


2
Albania, Armenia, Austria, Azerbaijan, Croatia, Czech Republic, F.Y.R. Macedonia, Finland, France, Georgia, Germany, Luxembourg, Macedonia, Malta, Monaco, Montenegro, North Macedonia, Norway, Portugal, Serbia, Serbia & Montenegro, Slovenia, Spain, Sweden, Switzerland, Yugoslavia


3
Andorra, Cyprus, Denmark, Ireland, Italy, Morocco, Netherlands, The Netherlands


4
Australia, Hungary, Iceland, Moldova, Turkey, Ukraine


map_data("world") %>%
    filter(region %in% eurovision_clusters$from_country) %>%
    left_join(eurovision_clusters, by = c("region" = "from_country")) %>%
    ggplot(aes(long, lat, group = group, fill = cluster)) +
    geom_polygon(alpha = 0.8) +
    coord_map() +
    scale_fill_brewer(palette = "Dark2") +
    silgelib::theme_plex() +
    labs(title = "Which countries vote similarly for Eurovision?",
         subtitle = "Clusters identified with SVD and K-means")

^{Created on 2022-05-26 by the reprex package (v2.0.1)}
cluster	from_country
1	Belarus, Belgium, Bosnia & Herzegovina, Bulgaria, Estonia, Greece, Israel, Latvia, Lithuania, Poland, Romania, Russia, San Marino, Slovakia, United Kingdom
2	Albania, Armenia, Austria, Azerbaijan, Croatia, Czech Republic, F.Y.R. Macedonia, Finland, France, Georgia, Germany, Luxembourg, Macedonia, Malta, Monaco, Montenegro, North Macedonia, Norway, Portugal, Serbia, Serbia & Montenegro, Slovenia, Spain, Sweden, Switzerland, Yugoslavia
3	Andorra, Cyprus, Denmark, Ireland, Italy, Morocco, Netherlands, The Netherlands
4	Australia, Hungary, Iceland, Moldova, Turkey, Ukraine