与 ggarrange 相同的 y 轴比例

Question

I would like to use ggarrange to combine two plots into a single one, and use the same scaling for the y-axis to make it easier to compare the values, in my case, temperature calculations. This is my sample data:

    Sample  Group   Temperature_A   Temperature_B
1   Sample01    A   20  34
2   Sample02    B   21  31
3   Sample03    A   25  35
4   Sample04    A   18  27
5   Sample05    B   19  29
6   Sample06    A   22  32
7   Sample07    B   23  33
8   Sample08    B   17  28
9   Sample09    A   15  26
10  Sample10    B   28  39

Using the following code, I get the following plot:

p1 <- ggplot(df, aes(Group, Temperature_A)) +
 geom_boxplot()

p2 <- ggplot(df, aes(Group, Temperature_B)) +
 geom_boxplot()

plate <- ggarrange(p1, p2, align = "hv")

plate

What I would like to have is for them to share their y-axis so that I can easily compare the two temperature calculation methods. I can do this manually with + scale_y_continuous(limits = c(a,b)) where I set the appropriate values for a and b, however, I have a lot of different dataframes with different temperature ranges. Ideally, I would use the lowest value (+ some space) from both plots, and the highest value (+ some space) from both plots for the limits of both plots. Is there a way to achieve this?

My manual approach and the desired output:

p1 <- ggplot(df, aes(Group, Temperature_A)) +
 geom_boxplot() + 
 scale_y_continuous(limits = c(10, 40))

p2 <- ggplot(df, aes(Group, Temperature_B)) +
 geom_boxplot() + 
 scale_y_continuous(limits = c(10, 40))

plate <- ggarrange(p1, p2, align = "hv")

plate

Answer 1

This is just to illustrate how you could use facets. Because you have two columns for temperature, this is called the 'wide format'. If you reshape the data to the long format, you can easily use facets.

library(ggplot2)

df <- read.table(text = "    Sample  Group   Temperature_A   Temperature_B
1   Sample01    A   20  34
2   Sample02    B   21  31
3   Sample03    A   25  35
4   Sample04    A   18  27
5   Sample05    B   19  29
6   Sample06    A   22  32
7   Sample07    B   23  33
8   Sample08    B   17  28
9   Sample09    A   15  26
10  Sample10    B   28  39", header = TRUE)

# Reshape
long <- tidyr::pivot_longer(
  df, c("Temperature_A", "Temperature_B"), 
  values_to = "Temperature", names_to = "Temp_name"
)

# Example of facets
ggplot(long) +
  geom_boxplot(aes(Group, Temperature)) +
  facet_wrap(~ Temp_name)

^{Created on 2021-07-27 by the reprex package (v1.0.0)}

Answer 2

I agree with teunbrand. Here is an slightly modified approach:

1. bring data in long format
2. ignore outlieres outlier.shape = NA
3. adapt ylim and
4. facet_wrap

library(tidyverse)
df1 <- df %>% 
    pivot_longer(
        cols = starts_with("Temperature"), 
        names_to = "Temperature",
        values_to = "values"
    ) 


ggplot(df1, aes(Group, values)) +
    geom_boxplot(outlier.shape = NA) +
    coord_cartesian(ylim = c(10, 40)) +
    facet_wrap(~Temperature) + 
    theme_bw()