Data<-data.frame("Date"=as.Date(16200:16499),"Total"=rnorm(300,4500,50))
Mean<-mean(Data$Total)
SD1<-Mean-sd(Data$Total)
SD2<-Mean+sd(Data$Total)

TotalDay <- ggplot(data = Data, aes(x=Date, y=Total,colour=Legend)) +
  geom_line(aes(y=Total, colour="Total Tweets"))

TotalDay + ggtitle("Tweets per Day") +labs(x="Date",y="Tweets") +
  theme(plot.title = element_text(color="#666666", face="bold", size=18, hjust=0)) +
  theme(axis.title = element_text(color="#666666", face="bold", size=13)) +
  geom_hline(aes(yintercept =Mean,colour="Mean")) +
  geom_hline(aes(yintercept =(SD1),
                 colour="Standard Deviation"))+
  geom_hline(aes(yintercept =(SD2),
                 colour="Standard Deviation"))

TotalDay + scale_color_manual(name="Legend",
                              values=c("Total Tweets"="#f04546","Mean"="#3591d1","Standard Deviation"="#62c76b"))

library(stringr)
library(dplyr)
library(Ryacas)
library(quantmod)
library(data.table)
library(tm)
library(lubridate)
library(ggplot2)
library(extrafont)