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I'm trying to create a facet_wrap() where the unit of measure remains identical across the different plots, while allowing to slide across the y axis.

To clearify with I mean, I have created a dataset df:

library(tidyverse)



df <- tibble(

  Year = c(2010,2011,2012,2010,2011,2012),

  Category=c("A","A","A","B","B","B"),

  Value=c(1.50, 1.70, 1.60, 4.50, 4.60, 4.55)

)

with df, we can create the following plot using facet_wrap:

ggplot(data = df, aes(x=Year, y=Value)) + geom_line() + facet_wrap(.~ Category)

Plot 1

To clarify the differences between both plots, one can use scale = "free_y":

ggplot(data = df, aes(x=Year, y=Value)) + geom_line() 

 + facet_wrap(.~ Category, scale="free_y")

Plot 2

Although it's more clear, the scale on the y-axis in plot A isequal to 0.025, while being 0.0125 in B. This could be misleading to someone who's comparing A & B next to each other.

So my question right now is to know whether there exist an elegant way of plotting something like the graph below (with y-scale = 0.025) without having to plot two seperate plots into a grid?

Thanks

Desired result:

Code for the grid:

# Grid

## Plot A

df_A <- df %>%

  filter(Category == "A") 

plot_A <- ggplot(data = df_A, aes(x=Year, y=Value)) + geom_line() +  coord_cartesian(ylim = c(1.5,1.7)) + ggtitle("A")



## Plot B

df_B <- df %>%

  filter(Category == "B") 

plot_B <- ggplot(data = df_B, aes(x=Year, y=Value)) + geom_line()  + coord_cartesian(ylim = c(4.4,4.6)) + ggtitle("B")



grid.arrange(plot_A, plot_B, nrow=1)

Based on the info at Setting individual y axis limits with facet wrap NOT with scales free_y you can you use geom_blank() and manually specified y-limits by Category:

# df from above code

df2 <- tibble(

  Category = c("A", "B"),

  y_min = c(1.5, 4.4),

  y_max = c(1.7, 4.6)

)



df <- full_join(df, df2, by = "Category")



ggplot(data = df, aes(x=Year, y=Value)) + geom_line() + 

  facet_wrap(.~ Category, scales = "free_y") +

  geom_blank(aes(y = y_min)) +

  geom_blank(aes(y = y_max))