Stacke Different Plots in a Facet Manner

Stacke different plots in a facet manner

First, melt your data to long format.

library(reshape2)
dat.long<-melt(dat,id.vars="time")
head(dat.long)
  time variable     value
1    0     surv 1.0000000
2    5     surv 0.9956140
3   11     surv 0.9824561
4   12     surv 0.9780702
5   13     surv 0.9692982
6   15     surv 0.9649123

Then use subset() to use only surv data in geom_step() and nr data in geom_area() and with facet_grid() you will get each plot in separate facet as variable is used to divide data for facetting and for subsetting. scales="free_y" will make pretty axis.

ggplot()+geom_step(data=subset(dat.long,variable=="surv"),aes(time,value))+
  geom_area(data=subset(dat.long,variable=="nr"),aes(time,value))+
  facet_grid(variable~.,scales="free_y")

Stacking calculated plots in a facet manner

you could make a dummy facetting variable,

d <- lattice::make.groups(first=df, second=df)

ggplot(data=d, aes(x=player, fill=is.winner)) +
  facet_grid(which~., scales="free") +
  geom_bar(position = "stack", data=subset(d, which=="first")) +
  geom_bar(position = 'fill', data=subset(d, which=="second")) +
  scale_fill_brewer(palette="Set2")

interestingly, flipping the coordinates produces an incorrect plot, at least with the dev version of ggplot2.

  last_plot() + coord_flip()

GGPlot: Different chart types in facets?

Following our comments, I would probably do something like this:

new_dat <- melt(list(trial.df,trial.df),id.vars = 1:2)
new_dat$trial.id <- factor(new_dat$trial.id)
new_dat$surv <- factor(new_dat$surv)
ggplot() +
    facet_wrap(~L1,nrow = 2,scales = "free_y") + 
    geom_bar(data = subset(new_dat,L1 == 1),
             aes(x = trial.id , fill = surv),
             stat = "bin", 
             position = "fill") +
    geom_bar(data = subset(new_dat,L1 == 2),
             aes(x = trial.id , fill = surv),
             stat = "bin") +
    ggtitle("Surival by Trial\n") +
    labs(x = "\nTrial", y = "Patients (%)\n") +
    scale_fill_discrete(name = "Survival") 

(And ignore the warnings.)

Adding plots in between faceted plots with ggplot

There is a function grid.arrange() from gridExtra package (nice explanation [here])1. This allows you to take separately plotted plots and then arrange them in a consistent grid and adjust the size of each plot individually if needed. For this to work you would need to plot each one of your facets separately and then pass them to the package.

Assuming that each of your facets is called something like A1 for top left, B4 for bottom left. Your code would look something like this:

grid.arrange(
   grobs = c(Al:B4)
   widths = c(2, 1, 2, 1),
   layout_matrix = rbind(c(1, 2, 3, 4),
                         c(5, 6, 7, 8))
)

Using this format, you would individually label your plots so as to overcome the difference in types of scale.

Different function curves for each facet in ggplot2

And with many thanks to comment from @Roland

If we add to toy.data predicted data from the function predict.hedgehogs above:

pred.hogs <- predict.hedgehogs(year, rate)
toy.data <- data.frame(toy.data, pred.hogs)

We can plot:

ggplot(toy.data, aes(year, hedgehogs)) +
  geom_point(aes(colour=queen), size=10) +
  scale_colour_manual(values=c("red", "white")) +
  facet_grid(rate ~ site) +
  geom_smooth(aes(x=year, y=pred.hogs), stat="identity", colour = "black")

How to use 'facet' to create multiple density plot in GGPLOT

You'll have to prepare your data first. I've illustrated this on your data.frame df as it is a proper normal distribution.

require(ggplot2)
require(reshape2)
df$id <- 1:nrow(df)

df.m <- melt(df, "id")
df.m$grp1 <- factor(gsub("\\..*$", "", df.m$variable))
df.m$grp2 <- factor(gsub(".*\\.", "", df.m$variable))

p <- ggplot(data = df.m, aes(x=value)) + geom_density(aes(fill=grp2), alpha = 0.4)
p <- p + facet_wrap( ~ grp1)
p + scale_fill_brewer(palette = "Set1")

Doing the same by replacing df with df_log you'd get something like this:

require(ggplot2)
require(reshape2)
df_log$id <- 1:nrow(df_log)

df.m <- melt(df_log, "id")
df.m$grp1 <- factor(gsub("\\..*$", "", df.m$variable))
df.m$grp2 <- factor(gsub(".*\\.", "", df.m$variable))

p <- ggplot(data = df.m, aes(x=value)) + geom_density(aes(fill=grp2), alpha = 0.5)
p <- p + facet_wrap( ~ grp1)
p

Bar plot with facets and same bar size (binwidth) with option to shrink the panel size

Perhaps an approach using facet grid would be satisfactory:

ggplot(df, aes(x = product, y = customer.satisfaction)) +
  geom_bar(stat = "identity", width = 0.9) +
  coord_flip() +
  facet_grid(store ~., scales = "free", space = "free")

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