Shery Shery - 7 days ago 4
R Question

ggplot2: add line for average per group (Error: No stat called StatHline.)

I recently updated

ggplot2
package and running into major issues drawing horizontal lines for averages per group using
facets
.
I believe this post is no longer valid?

I am creating a time series graph using the following code:

ggplot(p2p_dt_SKILL_A,aes(x=Date,y=Prod_DL)) +
geom_line(aes(colour="red"),lwd=1.3) +
geom_smooth() +
geom_line(stat = "hline", yintercept = "mean")+
scale_x_date(labels=date_format("%b-%y"),breaks ="2 month")+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-09-18"]))+

geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-10-02"]))+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-10-23"]))+
ylab("DL Prod for All Skills")+
ggtitle("BVG1 DL Prod for All Skills 2014-2015")+
theme(axis.title.y = element_text(size = 15,face="bold",color="red"),
plot.title = element_text(size = 15,lineheight = .8,face="bold",color="red"),
axis.title.x = element_blank(),
legend.position="none")+
facet_wrap(~Patch)


The number 1 issue is that I can no longer use the
stat = "hline"
in the
geom_line(stat = "hline", yintercept = "mean")
because it gives the following error:
Error: No stat called StatHline
.
so therefore I changed it to:

ggplot(p2p_dt_SKILL_A,aes(x=Date,y=Prod_DL)) +
geom_line(aes(colour="red"),lwd=1.3) +
geom_smooth() +
geom_hline(yintercept = mean(p2p_dt_SKILL_A$Prod_DL))+
scale_x_date(labels=date_format("%b-%y"),date_breaks ="2 month")+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-09-18"]))+

geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-10-02"]))+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-10-23"]))+
ylab("DL Prod for All Skills")+
ggtitle("BVG1 DL Prod for All Skills 2014-2015")+
theme(axis.title.y = element_text(size = 15,face="bold",color="red"),
plot.title = element_text(size = 15,lineheight = .8,face="bold",color="red"),
axis.title.x = element_blank(),
legend.position="none")+
facet_wrap(~Patch)


But this doesn't draw the horizontal line at means per Patch. It just takes the overall mean for
Prod_DL

See below:
enter image description here

Are there any new ways now to calculate mean per group and draw horizontal lines?

Thanks

UPDATE

Here is what I did:

#first create a dataframe which holds patch and mean values for prod dl, this will then be used in geom_hline()
mean_Prod_DL <- p2p_dt_SKILL_A%>%
group_by(Patch)%>%
summarise(mean_Prod_DL_per_patch = mean(Prod_DL))


ggplot(p2p_dt_SKILL_A,aes(x=Date,y=Prod_DL)) +
scale_x_date(labels=date_format("%b-%y"),date_breaks ="2 months")+
geom_line(aes(colour="red"),lwd=1.3) +
geom_smooth() +
geom_hline(data = mean_Prod_DL,aes(yintercept = mean_Prod_DL_per_patch),lty=2)+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-09-18"]))+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-10-02"]))+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-10-23"]))+
geom_vline(xintercept = as.numeric(p2p_dt_SKILL_A$Date[p2p_dt_SKILL_A$Date=="2015-12-04"]))+
ylab("DL Prod for All Skills")+
ggtitle("BVG1 DL Prod for All Skills 2014-2016")+
theme(axis.title.y = element_text(size = 15,face="bold",color="red"),
plot.title = element_text(size = 15,lineheight = .8,face="bold",color="red"),
axis.title.x = element_blank(),
legend.position="none")+
facet_wrap(~Patch)


enter image description here

Answer

I agree with @MLavoie that just calculating the quantity of interest is the simplest solution. Not sure in what way you are looking for something 'better'.

Example:

# sample data
my_df <- data.frame(x=rep(1:100, 4),
                    y=cumsum(rnorm(400)),
                    category=rep(letters[1:4], each=100))

# calculate the hline data in one line with data.table
library(data.table)
setDT(my_df)[, cat_mean := mean(y), by=category]

# plot
ggplot(my_df, aes(x=x, y=y, group=category)) +
  geom_line(color='red') +
  geom_smooth(color='blue') +
  geom_hline(aes(yintercept=cat_mean)) +
  facet_wrap(~category)

Result:

enter image description here

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