#### Hope burial data exercise

hope<-read.csv("HOPE Date Order-Table 1.csv",header=TRUE)
burial<-as.Date(hope$Burial.date, "%m/%d/%y")
burial[1:11]<-gsub("20","19", burial[1:11])
data<-data.frame(burial,hope$Sex,hope$Age)
year<-format(as.Date(data$burial, format="%d/%m/%Y"),"%Y")

####### Answer to exercise

births<-data$Year-data$hope.Age
males<-which(data$hope.Sex=="m")
females<-which(data$hope.Sex=="f")
before1923<-which(births<1923)
after1922<-which(births>1922)
maleANDbefore<-intersect(males,before1923)
maleANDafter<-intersect(males,after1922)
femaleANDbefore<-intersect(females,before1923)
femaleANDafter<-intersect(females,after1922)

par(mfrow=c(2,2))
br<-seq(0,110,10)
hist(hope$Age[maleANDbefore],breaks=br,col="blue")
hist(hope$Age[maleANDafter],breaks=br,col="lightblue3")
hist(hope$Age[femaleANDbefore],breaks=br,col="red")
hist(hope$Age[femaleANDafter],breaks=br,col="pink3")

# with %in% you would use something like maleANDafter<-males[which(males %in% after1922)]