How do I add x category means to a plot?

Question

I'm creating a plot of rainfall means by month and year in R. The following plot is what I created using these columns: Year, Numbered_Months, Rainfall(mm/month)

My Plot

What I now want to do is add another line that shows the mean value for each month across years. Is there a way to do this with ggplot based on what I've already got plotted, rather than working out a new column into the dataframe and adding it as another 'year' category?

Providing your data as reproducible example and your code could help others to solve your problem, please check https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example — knytt, Aug 02 '20 at 16:51

Marco_CH · Answer 1 · 2021-12-11T00:20:12.643

You could try this:

library(data.table)
library(ggplot2)

dt_a = data.table(year=c(2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2018,2019,2019,2019,2019,2019,2019,2019,2019,2019,2019,2019,2019),
                month=c(1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12),
                value=runif(24, 10, 30))

ggplot(
  data=dt_a, aes(x=month, y=value)
) + geom_line(
  aes(color=factor(year))
) + stat_summary(
  fun = mean, geom="line"
)

score 1 · Answer 2 · answered Aug 02 '20 at 20:20

We can recreate your plot quite well with the following data and plotting code (it's always better to include this in your question)

df <- data.frame(Year = rep(2017:2019, each = 12),
                 Numbered_Months = rep(1:12, 3),
                 `Rainfall(mm/month)` = c(0.2, 0.25, 2.5, 4.9, 2.1, 1.2, 0.6, 
                                          0.3, 0.4, 0.6, 0.65, 0.75, 0.25, 0.15, 
                                          0.35, 0.55, 0.6, 0.8, 0.6, 0.55, 0.5, 
                                          3.4, 2.9, 2.1, 0.45, 0.4, 0.25, 0.8, 
                                          1.4, 0.15, 0.8, 0.85, 0.65, 1.4, 2.3, 
                                          0.3))

library(ggplot2)

original <- ggplot(df, aes(Numbered_Months, Rainfall.mm.month.)) +
  geom_line(aes(colour = factor(Year))) +
  scale_color_manual(values = c("red", "darkblue", "forestgreen")) +
  scale_y_continuous(breaks = 1:5) +
  scale_x_continuous(breaks = 1:12) +
  theme(axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        axis.text.x = element_text(angle = 90),
        panel.grid.minor = element_blank(),
        axis.title.y = element_blank(),
        legend.position = "none")

original

We can either use the stat_summary function or just work out what we want to plot and pass that data to ggplot. In this example I have created a little summary data frame to add the monthly means along with the standard error:

library(dplyr)

group_means <- df %>% 
  group_by(Numbered_Months) %>% 
  summarize(mean = mean(Rainfall.mm.month.), 
            sem_low = mean- sd(Rainfall.mm.month.)/sqrt(3), 
            sem_high = mean + sd(Rainfall.mm.month.)/sqrt(3))
#> `summarise()` ungrouping output (override with `.groups` argument)

original +   
  geom_ribbon(data = group_means, 
              aes(y = mean, ymin = sem_low, ymax = sem_high),
              alpha = 0.1) +
  geom_line(data = group_means, aes(y = mean), linetype = 2, size = 1)

^{Created on 2020-08-02 by the reprex package (v0.3.0)}

How do I add x category means to a plot?

2 Answers2