# set working directory
setwd("~/Desktop")

# read data
dat <- read.csv("plot_sample.csv")

# change table
#install.packages("reshape")
library(reshape)
melted <- melt(dat, id = c("treatment", "time"))

# plot
#install.packages("ggplot2")
library(ggplot2)
#box plot
ggplot(melted, aes(x=as.factor(time), y=value))+
       geom_boxplot(aes(fill=treatment),position= position_dodge(0.9))+
       labs(x="Time(hr)", y="Concentration (mg/ml)")



#+++++++++++++++++++++++++
# Function to calculate the mean and the standard deviation
  # for each group
#+++++++++++++++++++++++++
# data : a data frame
# varname : the name of a column containing the variable
  #to be summariezed
# groupnames : vector of column names to be used as
  # grouping variables
data_summary <- function(data, varname, groupnames){
  require(plyr)
  summary_func <- function(x, col){
    c(mean = mean(x[[col]], na.rm=TRUE),
      sd = sd(x[[col]], na.rm=TRUE))
  }
  data_sum<-ddply(data, groupnames, .fun=summary_func,
                  varname)
  data_sum <- rename(data_sum, c("mean" = varname))
 return(data_sum)
}

df <- data_summary(melted, varname="value", 
                 groupnames=c("treatment", "time"))


p <- ggplot(df, aes(x=time, y=value, fill=treatment)) + 
   geom_bar(stat="identity", position=position_dodge()) +
  geom_errorbar(aes(ymin=value-sd, ymax=value+sd), width=.2,
                 position=position_dodge(.9))
plot(p)