In ablaette/learningR: Slides and Supplementary Material to Get Started with R

***Datensatz vom Server runterladen

install.packages("car")

library(car) library(ess)

data(ess6) names(ess6) View(ess6)

Datensatz erstellen

stf <- ess6 [, c("idno", "cntry", "stfgov", "stfdem")] stf2 <- na.omit(stf) # Listenweise Fallausschluss countries <- levels(stf$cntry)

stfgov2 <- recode(stf2$stfgov, "'Extremely dissatisfied'='0'; '1'='1'; '2'='2'; '3'='3'; '4'='4'; '5'='5'; '6'='6'; '7'='7'; '8'='8'; '9'='9'; 'Extremely satisfied'='10'; else=NA", as.factor.result=TRUE) stfdem2 <- recode(stf2$stfdem, "'Extremely dissatisfied'='0'; '1'='1'; '2'='2'; '3'='3'; '4'='4'; '5'='5'; '6'='6'; '7'='7'; '8'='8'; '9'='9'; 'Extremely satisfied'='10'; else=NA", as.factor.result=TRUE)

View(stf2) View(stfgov2) View(stfdem2)

stfgov2 <- as.numeric(as.factor(stfgov2)) stfdem2 <- as.numeric(as.factor(stfdem2))

tapply(stfdem2, stf2$cntry, mean)

meanDem <- tapply(stfdem2, stf2$cntry, mean) meanGov <- tapply(stfgov2, stf2$cntry, mean)

View(meanDem) View(meanGov)

plot(meanDem, meanGov, main= "Scatterplott: Mean Satisfaction with Democracy vs. Mean Satisfaction with Government (0-10)", xlab= "Mean Satisfaction with Democracy", ylab= "Mean Satisfaction with Government", col= "red", pch = 19, cex = 1, lty = "solid", lwd = 1, xlim=c(0,10), ylim=c(0,10), cex.axis="0.7", text(meanDem, meanGov, labels=countries, cex= 0.7, pos=1) )

barplot(meanDem, main= "MW Satisfaction with Democracy (0-10)", xlab= "Countries", ylab= "Satisfaction with Democracy (0-10)", ylim=c(0,10), border="purple", col="darkblue", , cex.axis="0.7", space=0.5, las=2 )

barplot(meanGov, main= "MW Satisfaction with Government (0-10)", xlab= "Countries", ylab= "Satisfaction with Government (0-10)", ylim=c(0,10), border="purple", col="red", , cex.axis="0.7", space=0.5)

mergeDemGov <- data.frame(meanGov, meanDem)

par(mar=c(2,2,1,1,)) barplot(height=t(as.matrix(mergeDemGov)), beside=T, las=2)

install.packages("ggplot2") library(ggplot2)

ggplot(mergeDemGov, aes(meanGov,), meanDem, fill = countries)) + geom_bar(stat="identity", position = "dodge") + scale_fill_brewer(palette = "Set1")

regression <- lm(yMean~xMean, data=as.data.frame(plotTab1)) abline(regression)

ablaette/learningR documentation built on July 1, 2023, 1:11 a.m.