Facet_Wrap Add Geom_Hline

facet_wrap add geom_hline

Minimal example using mtcars - you have to create a data frame with mean for each gear (in your case it's Name).

library(tidyverse)
dMean <- mtcars %>%
    group_by(gear) %>%
    summarise(MN = mean(cyl))
ggplot(mtcars) +
    geom_point(aes(mpg, cyl)) +
    geom_hline(data = dMean, aes(yintercept = MN)) +
    facet_wrap(~ gear)

For your case this should work:

library(tidyverse)
dMean <- UKWinners %>%
    group_by(Name) %>%
    summarise(MN = mean(TE.Contr.))
ggplot(UKWinners) +
    geom_point(aes(Pcode, TE.Contr.)) +
    geom_hline(data = dMean, aes(yintercept = MN)) +
    facet_wrap(~ Name)

Different `geom_hline()` for each facet of ggplot

If you have the value you wish to use for each facet as a column in the data frame, and that value is unique within each facet, then you can use geom_hline(aes(yintercept=column)), which will then plot a horizontal line for each of the facets

geom_hline with multiple points and facet_wrap

You can treat it like any other geom_*. Just create a new column with the value of ratio1 at which you want to plot the horizontal line. I do this by sub setting the the data by those where iterations = 0 (note SA has 2 of these) and joining the ratio1 column onto the original dataframe. This column can then be passed to the aesthetics call in geom_hline().

library(tidyverse)

df %>% 
  left_join(df %>% 
              filter(iterations == 0) %>% 
              select(axis, intercept = ratio1)) %>% 

  ggplot(aes(x = equivalent_iterations, y = ratio1, 
             color = equivalent_iterations)) +
  geom_point() + 
  geom_hline(aes(yintercept = intercept)) +
  facet_wrap(~axis) + 
  expand_limits(x = 0, y = 0) 

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"))

How to add different lines for facets

Make sure that the variable species is identical in both datasets. If it a factor in one on them, then it must be a factor in the other too

library(ggplot2)
dummy1 <- expand.grid(X = factor(c("A", "B")), Y = rnorm(10))
dummy1$D <- rnorm(nrow(dummy1))
dummy2 <- data.frame(X = c("A", "B"), Z = c(1, 0))
ggplot(dummy1, aes(x = D, y = Y)) + geom_point() + facet_grid(~X) + 
    geom_hline(data = dummy2, aes(yintercept = Z))

dummy2$X <- factor(dummy2$X)
ggplot(dummy1, aes(x = D, y = Y)) + geom_point() + facet_grid(~X) + 
    geom_hline(data = dummy2, aes(yintercept = Z))

Label hline in facetwrap ggplot2

Maybe with second geom_text:

# Using OPs provided data

library(ggplot2)
Rating <- factor(Rating, Rating)
ggplot(df_long, aes(variable, value, label = value)) +
    geom_bar(aes(fill = variable), stat = "identity") +  
    geom_text(hjust = -0.5, position = position_dodge(width = -1), size = 5) +
    geom_text(data = df_full, aes(1, Benchmark, label = Benchmark), 
              vjust = 2, hjust = -0.2) +
    geom_hline(data = df_full, aes(yintercept = Benchmark), 
               linetype = "dashed") +
    facet_wrap(~ Rating, scales = "free") +
    coord_flip(ylim = c(0, 100))

How can I add a line to one of the facets?

I don't have your data, so I made some up:

df <- data.frame(x=rnorm(100),y=rnorm(100),z=rep(letters[1:4],each=25))

ggplot(df,aes(x,y)) +
  geom_point() +
  theme_bw() +
  facet_wrap(~z)

To add a vertical line at x = 1 we can use geom_vline() with a dataframe that has the same faceting variable (in my case z='b', but yours will be levels='major'):

ggplot(df,aes(x,y)) +
  geom_point() +
  theme_bw() +
  facet_wrap(~z) +
  geom_vline(data = data.frame(xint=1,z="b"), aes(xintercept = xint), linetype = "dotted")

Add a main legend for colored line types on ggplot2 facet_wrap plot

If you want to have a legend the first step is to map on aesthetics instead of setting your color and linetypes as arguments, i.e. move color=... and linetype=... inside aes(). Second step is to set your desired colors and linetypes via scale_xxx_manual. Note, that to get only one legend we have to use the same name (which I simply set to NULL, i.e. no legend title) and the same labels:

library(ggplot2)

df <- data.frame(symbol, CurrentPrice, lowline, highline)

labels <- c("Current Price", "lowline", "highline")
names(labels) <- c("current", "low", "high")

ggplot(newdata) +
  geom_line(aes(Date, Close)) +
  geom_hline(data = df, aes(yintercept = CurrentPrice, linetype = "current", color = "current")) +
  geom_hline(data = df, aes(yintercept = lowline, linetype = "low", color = "low")) +
  geom_hline(data = df, aes(yintercept = highline, linetype = "high", color = "high")) +
  scale_linetype_manual(values = c(current = "dotted", high = "dashed", low = "dashed"), labels = labels, name = NULL) +
  scale_color_manual(values = c(current = "black", high = "red", low = "green"), labels = labels, name = NULL) +
  facet_wrap(~symbol, scales = "free_y") +
  theme(axis.text.x = element_text(size = 8, angle = 90, hjust = 0.95, vjust = 0.2)) +
  theme(axis.text.y = element_text(size = 6))

Add hline with population median for each facet

If you don't want to add a new column with the computed median, you can add a geom_smooth using a quantile regression :

library(ggplot2)
library(quantreg)

set.seed(1234)

dt <- data.frame(gr = rep(1:2, each = 500),
                id = rep(1:5, 2, each = 100), 
                y = c(rnorm(500, mean = 0, sd = 1),
                      rnorm(500, mean = 1, sd = 2)))

ggplot(dt, aes(y = y)) +
  geom_boxplot(aes(x = as.factor(id))) +
  geom_smooth(aes(x = id), method = "rq", formula = y ~ 1, se = FALSE) +
  facet_wrap(~ gr)

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