func <- function(x1,x2,x3,x4,x5,x6,x7,x8){
return(x1*0.02+x2*0.02+x3*0.02+x4*0.02+x5*0.04+x6*0.15+x7*0.56+x8*1)
}
length_graph <- length(seq(as.Date("2020-03-20"),Sys.Date(),by='days'))
w <- read.csv("~/R/R2/covid/tokyo.csv")
y <- as.xts(as.numeric(substr(w[,9],1,2)),as.Date(w[,5]))
# apply.daily(as.xts(rep(1,length(y[y[,1] == 10])),as.Date(index(y[y[,1] == 10]))),sum)
# v <- c()
# seq(as.Date(w[1,5]),Sys.Date(),by='days')
v <- as.xts(rep(1,length( seq(as.Date(w[1,5]),Sys.Date(),by='days') )), seq(as.Date(w[1,5]),Sys.Date(),by='days'))
for(i in seq(10,80,10)){
if(i < 80){
v<- merge(v, apply.daily(as.xts(rep(1,length(y[y[,1] == i])),as.Date(index(y[y[,1] == i]))),sum))
}else{ # for the case the sample is more than 80 yrs old.
v<- merge(v, apply.daily(as.xts(rep(1,length(y[y[,1] >= i])),as.Date(index(y[y[,1] >= i]))),sum))
}
}
# v<- merge(v, apply.daily(as.xts(rep(1,length(y[y[,1] > 80 ])),as.Date(index(y[y[,1] >80]))),sum))
v <- v[,-1]
for(i in seq(1,8,1)){
colnames(v)[i] <- as.character(i*10)
}
# replace NA with ZERO.
for( i in seq(1,length(colnames(v)),1)) {
for(j in seq(1,length(index(v)),1)) {
if(is.na(v[j,i])){ v[j,i] <- 0}
}
# print(v[,i])
}
# for( i in length(colnames(v))){
# replace(v[,i], which(is.na(v[,i])), 0)
# }
# apply(v[,c(6,7,8)],1,sum)
w <- merge(as.xts(apply(v[,c(1,2,3,4,5)],1,sum) ,index(v)),as.vector(apply(v[,c(6,7,8)],1,sum) ))
colnames(w)[1] <- "lessthan60"
colnames(w)[2] <- "over60"
df <- data.frame(t=last(index(w),length_graph),
# o=last(diff(all[,1]-all[,3],t=all[,3]),length_graph),
o=last(w[,1],length_graph),
k=last(w[,2],length_graph)
# or=last(all[,2],length_graph)*multi,
# kr=last(all[,2],length_graph)*multi
)
# df.melt <- melt(data=df, id.vars="t", measure.vars=c("lessthan60", "over60"))
df.melt <- melt(data=df, id.vars="t", measure.vars=c(colnames(w)[1],colnames(w)[2]))
# head(df.melt)
df <- df.melt
# g <- ggplot(x, aes(x = t, y = value, fill = variable))
# # g <- ggplot(x, aes(x = t, y = d))
# g <- g + geom_bar(stat = "identity")
# # g <- g + scale_fill_nejm()
g <- ggplot(df, aes(x = t, y = value, fill = variable))
g <- g + geom_bar(stat = "identity")
# plot(g)
df <- data.frame(t=last(index(v),length_graph),
# o=last(diff(all[,1]-all[,3],t=all[,3]),length_graph),
a=last(v[,1],length_graph),
b=last(v[,2],length_graph),
c=last(v[,3],length_graph),
d=last(v[,4],length_graph),
e=last(v[,5],length_graph),
f=last(v[,6],length_graph),
g=last(v[,7],length_graph),
h=last(v[,8],length_graph)
# or=last(all[,2],length_graph)*multi,
# kr=last(all[,2],length_graph)*multi
)
for(i in seq(1,8,1)){
colnames(df)[i+1] <- as.character(i*10)
}
# df.melt <- melt(data=df, id.vars="t", measure.vars=c("X10", "X20", "X30", "X40", "X50", "X60", "X70", "X80"))
df.melt <- melt(data=df, id.vars="t", measure.vars=c("10", "20", "30", "40", "50", "60", "70", "80"))
# head(df.melt)
df <- df.melt
# in order to overlayer graph use ggplot(NULL) to create base object.
g <- ggplot(NULL)
# g <- ggplot(df, aes(x = t, y = value, fill = variable))
g <- g + scale_fill_brewer(palette="Spectral",na.value = "black",name = "age group", direction=-1,labels = c("=<19",">=20",">=30",">=40",">=50",">=60",">=70",">=80"))
g <- g + geom_bar(data=df,aes(x = t, y = value, fill = variable),stat = "identity")
# prepare the second layer.
df <- data.frame(t=last(index(v),length_graph),
value=last(mapply(func,v[,1],v[,2],v[,3],v[,4],v[,5],v[,6],v[,7],v[,8]),length_graph)
)
df <- df[-length(df[,1]),] # cut off the last entry.
# g <- ggplot(df, aes(x = t, y = value))
g <- g+geom_line(data=df, aes(x = t, y = value))
# plot(g)
png("~/Dropbox/R-script/covid/05tokyo_age.png", width = 1200, height = 800)
plot(g)
dev.off()
