Displaying stat_summary within each group, by aesthetic mapping, in ggplot

I am close to plotting what I wanted, but haven't quite figured out whether stat_summary is the right way to display the desired plot.

stat_summary

The desired output is the scatter plot with a median line for each year, within each category. For example, in the plot below, I would want a median line for the values in 1999, 2000, and 2001 in Category A (i.e., 3 lines by color) and then the same in Category B (so 6 median lines total).

I looked here, but this didn't seem to get at what I wanted since it was using facets.

My plot looks like it is drawing a line between the medians of each category. Can stat_summary just draw a median line within each category, or do I need to use a different approach (like calculating the medians and adding each line to the plot by category?

stat_summary

Reproducible simple example

library(tidyverse)
library(lubridate)

# Sample data
Date <- sort(sample(seq(as.Date("1999-01-01"), as.Date("2002-01-01"), by = "day"), 500))
Category <- rep(c("A", "B"), 250)
Value <- sample(100:500, 500, replace = TRUE)

# Create data frame
mydata <- data.frame(Date, Category, Value)

# Plot by category and color by year
p <- ggplot(mydata, aes(x = Category, y = Value,
color = factor(year(Date))
)
) +
geom_jitter()
p


# Now add median values of each year for each group
p <- p +
stat_summary(fun.y = median,
geom = "line",
aes(color = factor(year(Date))),
group = 1,
size = 2
)
p


Category

Category

geom_line

2 Answers
2

Here is another possibility using geom_errorbar (instead of stat_summary)

geom_errorbar

stat_summary

# Sample data
set.seed(2017);
Date <- sort(sample(seq(as.Date("1999-01-01"), as.Date("2002-01-01"), by = "day"), 500))
Category <- rep(c("A", "B"), 250)
Value <- sample(100:500, 500, replace = TRUE)
mydata <- data.frame(Date, Category, Value)

mydata %>%
mutate(colour = factor(year(Date))) %>%
group_by(Category, year(Date)) %>%
mutate(Median = median(Value)) %>%
ggplot(aes(Category, Value, colour = colour)) +
geom_jitter() +
geom_errorbar(
aes(ymin = Median, ymax = Median))


Explanation: We pre-compute median values per Category per year(Date) and draw median lines using geom_errorbar.

Category

year(Date)

geom_errorbar

In response to your comment, if you wanted to use summarise to pre-compute median values you could store median values in a separate data.frame

summarise

data.frame

df <- mydata %>%
mutate(Year = as.factor(year(Date))) %>%
group_by(Category, Year) %>%
summarise(Median = median(Value))

ggplot(mydata, aes(Category, Value, colour = factor(year(Date)))) +
geom_jitter() +
geom_errorbar(
data = df,
aes(x = Category, y = Median, colour = Year, ymin = Median, ymax = Median))


It's not quite as clean as the first solution (since you need to specify all aesthetics in geom_errorbar) but the resulting plot is the same.

geom_errorbar

What you're looking for is actually a point, even though it looks like a line, because you don't want to connect observations (what a line does), you just want to show a discrete value (what a point does).

One way, very similar to the post you linked, is to do your stat_summary and use a shape that is essentially a large dash. I turned down the alpha and size of the jittered points to distinguish them from the medians better. For the medians, I kept the color assignment the same but set the group to the interaction between year and category, so there would be six distinct medians calculated.

stat_summary

Note that I set a seed for random number generation and changed the end date to 12/31/2001 instead of 1/1/2002, since you said you expected 3 years but during one generation I got a few observations of 1/1/2002.

library(tidyverse)
library(lubridate)

set.seed(987)
Date <- sort(sample(seq(as.Date("1999-01-01"), as.Date("2001-12-31"), by = "day"), 500))
Category <- rep(c("A", "B"), 250)
Value <- sample(100:500, 500, replace = TRUE)

# Create data frame
mydata <- data.frame(Date, Category, Value)

mydata <- mydata %>%
mutate(year = year(Date) %>% as.factor())

ggplot(mydata, aes(x = Category, y = Value, color = year)) +
geom_jitter(size = 0.6, alpha = 0.6) +
stat_summary(fun.y = median,
geom = "point",
aes(group = interaction(Category, year)),
shape = 95, size = 12, show.legend = F)


Created on 2018-07-01 by the reprex package (v0.2.0).

By clicking "Post Your Answer", you acknowledge that you have read our updated terms of service, privacy policy and cookie policy, and that your continued use of the website is subject to these policies.