**For df1 plot**

# Group data by when and site
grouped_df1<-group_by(df1,site)
#summarise grouped data and calculate mean and standard error using function mean and std.error(from plotrix)
summarised_df1<-summarise_each(grouped_df1,funs(mean=mean,std_error=std.error))
# Define the top and bottom of the errorbars
limits <- aes(ymax = mean + std_error, ymin=mean-std_error)
#Begin your ggplot
#Here we are plotting site vs mean and filling by another factor variable when
g<-ggplot(summarised_df1,aes(site,mean))
#Creating bar to show the factor variable position_dodge
#ensures side by side creation of factor bars
g<-g+geom_bar(stat = "identity",position = position_dodge())
#creation of error bar
g<-g+geom_errorbar(limits,width=0.25,position = position_dodge(width = 0.9))
#print graph
g

**For df2 plot**

# Group data by when and site
grouped_df2<-group_by(df2,when,site)
#summarise grouped data and calculate mean and standard error using function mean and std.error
summarised_df2<-summarise_each(grouped_df2,funs(mean=mean,std_error=std.error))
# Define the top and bottom of the errorbars
limits <- aes(ymax = mean + std_error, ymin=mean-std_error)
#Begin your ggplot
#Here we are plotting site vs mean and filling by another factor variable when
g<-ggplot(summarised_df2,aes(site,mean,fill=when))
#Creating bar to show the factor variable position_dodge
#ensures side by side creation of factor bars
g<-g+geom_bar(stat = "identity",position = position_dodge())
#creation of error bar
g<-g+geom_errorbar(limits,width=0.25,position = position_dodge(width = 0.9))
#print graph
g