richarddmorey/eurovision2019.csv

## eurovision2019.csv

          
            To.country
            Jury
            Televoting

            
              Netherlands
              231
              261

            
              Italy
              212
              253

            
              Russia
              125
              244

            
              Switzerland
              148
              212

            
              Norway
              47
              291

            
              Sweden
              239
              93

            
              Azerbaijan
              197
              100

            
              North Macedonia
              237
              58

            
              Australia
              154
              131

            
              Iceland
              48
              186

            
              Czech Republic
              150
              7

            
              Denmark
              69
              51

            
              Slovenia
              46
              59

            
              France
              67
              38

            
              Cyprus
              69
              32

            
              Malta
              75
              20

            
              Serbia
              38
              54

            
              Albania
              43
              47

            
              Estonia
              38
              48

            
              San Marino
              16
              65

            
              Greece
              47
              24

            
              Spain
              7
              53

            
              Israel
              12
              35

            
              Germany
              32
              0

            
              Belarus
              18
              13

            
              United Kingdom
              13
              3

## jury_vs_televoting.R
## Eurovision analysis, May 2019
## Richard D. Morey
## 2016-2018 Data available from https://data.world/datagraver/eurovision-song-contest-scores-1975-2018

library(dplyr)
library(tidyr)
library(ggplot2)
library(purrr)
library(openxlsx)
library(RCurl)

## Read in 2019 data
e2019_csv <- RCurl::getURL("https://gist.githubusercontent.com/richarddmorey/4bf962a8c80154228ff1b896a77951c0/raw/f267c99db693e5c1d27ef10518b43a40b0e9df6c/eurovision2019.csv")
e2019 <-read.csv(text = e2019_csv)
e2019$Year <- 2019

## Read in 2016-2018 data
openxlsx::read.xlsx("eurovision_song_contest_1975_2018v2.xlsx") %>%
  mutate(Edition2 = substr(Edition, 5, 10),
         Jury.or.Televoting = factor(Jury.or.Televoting, levels = c("J","T"), labels = c("Jury", "Televoting"))) %>%
  filter(Year > 2015, Edition2 == "f" ) %>%
  group_by(Year, To.country, Jury.or.Televoting) %>%
  summarise(Points = sum(Points)) %>%
  spread(Jury.or.Televoting, Points) %>%
  ungroup() %>%
  split(.$Year) -> x

## Combine data
x[["2019"]] <- as_tibble(e2019)

x %>% map_dbl( ~ cor(.$Jury, .$Televoting, method = "k")) -> cors
x %>% map( ~  ggplot(., aes(x = Jury, y = Televoting, label=To.country)) +
             geom_point() +
             geom_abline(size = .5) +
             geom_text(aes(label=To.country),hjust=0, vjust=0) +
             coord_trans(x = "sqrt", y = "sqrt") +
             expand_limits(y=0, x=0) +
             ggtitle(label = paste0(.$Year[1],
                                    ", Kendall correlation: ",
                                    round(cors[as.character(.$Year[1])], 3)))
) -> year_plots

year_plots %>% map(print)
To.country	Jury	Televoting
Netherlands	231	261
Italy	212	253
Russia	125	244
Switzerland	148	212
Norway	47	291
Sweden	239	93
Azerbaijan	197	100
North Macedonia	237	58
Australia	154	131
Iceland	48	186
Czech Republic	150	7
Denmark	69	51
Slovenia	46	59
France	67	38
Cyprus	69	32
Malta	75	20
Serbia	38	54
Albania	43	47
Estonia	38	48
San Marino	16	65
Greece	47	24
Spain	7	53
Israel	12	35
Germany	32	0
Belarus	18	13
United Kingdom	13	3
	## Eurovision analysis, May 2019
	## Richard D. Morey
	## 2016-2018 Data available from https://data.world/datagraver/eurovision-song-contest-scores-1975-2018

	library(dplyr)
	library(tidyr)
	library(ggplot2)
	library(purrr)
	library(openxlsx)
	library(RCurl)

	## Read in 2019 data
	e2019_csv <- RCurl::getURL("https://gist.githubusercontent.com/richarddmorey/4bf962a8c80154228ff1b896a77951c0/raw/f267c99db693e5c1d27ef10518b43a40b0e9df6c/eurovision2019.csv")
	e2019 <-read.csv(text = e2019_csv)
	e2019$Year <- 2019

	## Read in 2016-2018 data
	openxlsx::read.xlsx("eurovision_song_contest_1975_2018v2.xlsx") %>%
	mutate(Edition2 = substr(Edition, 5, 10),
	Jury.or.Televoting = factor(Jury.or.Televoting, levels = c("J","T"), labels = c("Jury", "Televoting"))) %>%
	filter(Year > 2015, Edition2 == "f" ) %>%
	group_by(Year, To.country, Jury.or.Televoting) %>%
	summarise(Points = sum(Points)) %>%
	spread(Jury.or.Televoting, Points) %>%
	ungroup() %>%
	split(.$Year) -> x

	## Combine data
	x[["2019"]] <- as_tibble(e2019)

	x %>% map_dbl( ~ cor(.$Jury, .$Televoting, method = "k")) -> cors
	x %>% map( ~ ggplot(., aes(x = Jury, y = Televoting, label=To.country)) +
	geom_point() +
	geom_abline(size = .5) +
	geom_text(aes(label=To.country),hjust=0, vjust=0) +
	coord_trans(x = "sqrt", y = "sqrt") +
	expand_limits(y=0, x=0) +
	ggtitle(label = paste0(.$Year[1],
	", Kendall correlation: ",
	round(cors[as.character(.$Year[1])], 3)))
	) -> year_plots

	year_plots %>% map(print)