What's the Difference Between Facet_Wrap() and Facet_Grid() in Ggplot2

What's the difference between facet_wrap() and facet_grid() in ggplot2?

The answer below refers to the case when you have 2 arguments in facet_grid() or facet_wrap().

facet_grid(x ~ y) will display x*y plots even if some plots are empty.
Ex:

library(ggplot2)
g <- ggplot(mpg, aes(displ, hwy))

There are 4 distinct cyl and 7 distinct class values.

g + geom_point(alpha=1/3) + facet_grid(cyl~class)

The above displays 4 * 7 = 28 plots, even if some are empty (because some classes do not have corresponding cylinder values, like rows with class="midsize" doesn't have any corresponding cyl="5" value )
facet_wrap(x ~ y) on the other hand, displays only the plots having actual values.

g + geom_point(alpha=1/3) + facet_wrap(cyl~class)

There are 19 plots displayed now, one for every combination of cyl and class.

Plot two lines on one graph on left panel and their difference on the right panel using facet_wrap or facet_grid in R

For easier handling, I would create the x - y column before melt. Then we need to create a column (in my code group) for facet_grid. The factor operation sets the position of the facet, so that x and y would be on the left hand side of x - y. Finally, set colors with scale_color_manual.

library(ggplot2)
library(dplyr)
library(reshape2)

df1 <- data.frame(a= c(1:10), x= c(0.1, 0.5, 0.2, 0.1, 0, 0.23, 0.25, 0.4, 0.01, 0.2),
                  y= c(0.3,0.01, 0.8, 0.2, 0.02, 0.14, 0.47, 0.35, 0, 0.32), name="L1")
df2 <- data.frame(a= c(1:10), x= c(0.2, 0.25, 0.2, 0.1, 0, 0.23, 0.25, 0.4, 0.01, 0.2),
                  y= c(0.76,0.81, 0.18, 0.52, 0.02, 0.14, 0.47, 0.35, 0, 0.32), name="L2")

rbind(df1, df2) %>% 
  mutate(`x - y` = x - y) %>% 
  melt(id = c("a", "name")) %>% 
  mutate(group = if_else(variable %in% c("x", "y"), "x and y", "x - y"),
         group = factor(group, levels = c("x and y", "x - y"))) %>% 
  ggplot(aes(a, value, col = variable)) + 
  geom_line() + 
  facet_grid(name ~ group) +
  scale_color_manual(values = c("x" = "red", "y" = "black", "x - y" = "green"))

^{Created on 2022-05-01 by the reprex package (v2.0.1)}

Varying geom_hline for each facet_wrap plot

You have made things a bit more difficult for yourself by leaving value as an array outside of the data frame (notice that although you include it when making df, as an array it just creates a bunch of columns called X1, X2, etc). You can solve the problem like this:

ggplot(df, aes(landmark, value, color = method)) +
  geom_line(alpha = 0.5)+
  geom_point(shape = 19, alpha = 0.5) +
  geom_blank() +
  geom_hline(data = df[df$landmark == 0.65,],
             aes(yintercept = value[df$landmark == 0.65], color = method)) +
  scale_x_continuous(name = paste("True Landmark PFS at", pt, "Months"), 
                     breaks = seq(true_landmark[1], 
                                  true_landmark[length(true_landmark)], 0.1)) +
  ylab(label="Probability of Go") +
  geom_vline(xintercept = theta, color = "black", linetype = "dashed") +
  facet_grid(n~type,labeller = label_parsed)+
  guides(color = guide_legend(title = "Method")) +
  theme(plot.caption = element_text(hjust = 0)) +
  labs(caption = paste("Go: Posterior prob (True PFS/RMST at", pt, 
                      "month > target|data)", ">",
                      "\nDashed line indicates target landmark PFS/RMST value"))

Looking to solve problem with facet_wrap/facet_grid that isn't resolved with space = free

You can get this easily with lemon::facet_rep_grid(repeat.tick.labels = T) instead of ggplot2::facet_grid().

library(tidyverse)
library(lemon)

b <- structure(list(Race = c("Asian", "Asian", "Asian", "Asian", "Asian", "Asian", "Asian", "Asian", "Asian", "Asian", "Black", "Black", "Black", "Black", "Black", "Black", "Black", "Black", "Black", "Black"), Symptom = structure(c(10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 10L, 9L,  8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L), .Label = c("Symptom10", "Symptom9", "Symptom8", "Symptom7", "Symptom6", "Symptom5", "Symptom4", "Symptom3", "Symptom2", "Symptom1"), class = "factor"), Percentage = c(60L, 50L, 20L, 70L, 90L, 100L, 10L, 30L, 40L, 60L, 40L, 20L, 50L, 50L, 85L, 30L, 30L, 20L, 80L, 40L), Group = c("Benign", "Benign", "Warning", "Warning", "Warning", "Fatal", "Fatal",  "Fatal", "Fatal", "Fatal", "Benign", "Benign", "Warning", "Warning", "Warning", "Fatal", "Fatal", "Fatal", "Fatal", "Fatal")), row.names = c(NA, -20L), class = c("tbl_df", "tbl", "data.frame"))

ggplot(data=b, aes(x=Percentage, y= Symptom, fill = Race)) +
  geom_bar(stat="identity", position=position_dodge()) +
  facet_rep_grid(Group~., scales = "free", space = "free", repeat.tick.labels = T)

^{Created on 2022-01-18 by the reprex package (v2.0.1)}

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