Societal Violence Scale Scores: 2013-2014
Sydney Nazloo
dat <- read.csv("/users/sydneynazloo/desktop/POLS396/SVSscores2.csv")
library(ggplot2)
aa <- as.data.frame(dat[1:20,], drop = FALSE)
ggplot(data = aa, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
bb <- as.data.frame(dat[21:40,], drop = FALSE)
ggplot(data = bb, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 1 rows containing missing values (geom_bar).## Warning: Removed 1 rows containing missing values (geom_text).
cc <- as.data.frame(dat[41:61,], drop = FALSE)
ggplot(data = cc, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
dd <- as.data.frame(dat[62:83,], drop = FALSE)
ggplot(data = dd, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 4 rows containing missing values (geom_bar).## Warning: Removed 4 rows containing missing values (geom_text).
ee <- as.data.frame(dat[84:105,], drop = FALSE)
ggplot(data = ee, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 2 rows containing missing values (geom_bar).## Warning: Removed 2 rows containing missing values (geom_text).
ff <- as.data.frame(dat[106:127,], drop = FALSE)
ggplot(data = ff, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 1 rows containing missing values (geom_bar).## Warning: Removed 1 rows containing missing values (geom_text).
gg <- as.data.frame(dat[128:149,], drop = FALSE)
ggplot(data = gg, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
hh <- as.data.frame(dat[150:171,], drop = FALSE)
ggplot(data = hh, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
ii <- as.data.frame(dat[172:193,], drop = FALSE)
ggplot(data = ii, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 2 rows containing missing values (geom_bar).## Warning: Removed 2 rows containing missing values (geom_text).
jj <- as.data.frame(dat[194:205,], drop = FALSE)
ggplot(data = jj, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
kk <- as.data.frame(dat[206:227,], drop = FALSE)
ggplot(data = kk, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
ll <- as.data.frame(dat[228:269,], drop = FALSE)
ggplot(data = ll, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 1 rows containing missing values (geom_bar).## Warning: Removed 1 rows containing missing values (geom_text).
mm <- as.data.frame(dat[270:291,], drop = FALSE)
ggplot(data = mm, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
nn <- as.data.frame(dat[292:313,], drop = FALSE)
ggplot(data = nn, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
oo <- as.data.frame(dat[314:333,], drop = FALSE)
ggplot(data = oo, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
pp <- as.data.frame(dat[334:353,], drop = FALSE)
ggplot(data = pp, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
qq <- as.data.frame(dat[354:373,], drop = FALSE)
ggplot(data = qq, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 2 rows containing missing values (geom_bar).## Warning: Removed 2 rows containing missing values (geom_text).
rr <- as.data.frame(dat[374:393,], drop = FALSE)
ggplot(data = rr, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")
ss <- as.data.frame(dat[394:403,], drop = FALSE)
ggplot(data = ss, aes(x = Country, y = Score, fill = factor(Year))) +
geom_bar(position = position_dodge(), stat = "identity") +
geom_text(aes(label = Year), color = "black", position = position_dodge(0.9), size = 3.5) +
labs(x = "Country", y = "Score", title = "Societal Violence Scale Scores: 2013-2014")## Warning: Removed 3 rows containing missing values (geom_bar).## Warning: Removed 3 rows containing missing values (geom_text).
This graph attempts to show any changes in Societal Violence Scale score between the years 2013 and 2014. Countries are scored on the severity and scope of physical integrity rights abuses committed non-state actors in that country. A score of 5 indicates egregious and widespread societal violence, while a score of 1 indicates no significant reports of societal violence. An overall asterisk indicates that that the report was not comprehensive enough to score. In this visualization, I mapped the the score for each country for both years in order to examine which countries had a change in score. This is intended to visualize the how dynamic or stagnant the state of human rights globally is. Based on the graphics I produced, it is evident that most countries had the same score both years. Most of the change, however, was for the worse. Of the countries that have had score changes, most scores went up.