Hollow histogram or binning for geom_step

Question 1

I propose making a new Geom like so:

library(ggplot2)
library(proto)

geom_stephist <- function(mapping = NULL, data = NULL, stat="bin", position="identity", ...) {
  GeomStepHist$new(mapping=mapping, data=data, stat=stat, position=position, ...)
}

GeomStepHist <- proto(ggplot2:::Geom, {
  objname <- "stephist"

  default_stat <- function(.) StatBin
  default_aes <- function(.) aes(colour="black", size=0.5, linetype=1, alpha = NA)

  reparameterise <- function(., df, params) {
    transform(df,
              ymin = pmin(y, 0), ymax = pmax(y, 0),
              xmin = x - width / 2, xmax = x + width / 2, width = NULL
    )
  }

  draw <- function(., data, scales, coordinates, ...) {
    data <- as.data.frame(data)[order(data$x), ]

    n <- nrow(data)
    i <- rep(1:n, each=2)
    newdata <- rbind(
      transform(data[1, ], x=xmin, y=0),
      transform(data[i, ], x=c(rbind(data$xmin, data$xmax))),
      transform(data[n, ], x=xmax, y=0)
    )
    rownames(newdata) <- NULL

    GeomPath$draw(newdata, scales, coordinates, ...)
  }
  guide_geom <- function(.) "path"
})

This also works for non-uniform breaks. To illustrate the usage:

d <- data.frame(x=runif(1000, -5, 5))
ggplot(d, aes(x)) +
  geom_histogram(breaks=seq(-4,4,by=.5), color="red", fill=NA) +
  geom_stephist(breaks=seq(-4,4,by=.5), color="black")

plot

Question 2

This isn't ideal, but it's the best I can come up with:

h <- hist(d$x,breaks=seq(-4,4,by=.5))
d1 <- data.frame(x = h$breaks,y = c(h$counts,NA))

ggplot() + 
    geom_histogram(data = d,aes(x = x),breaks = seq(-4,4,by=.5),
                                 color = "red",fill = "transparent") + 
    geom_step(data = d1,aes(x = x,y = y),stat = "identity")

enter image description here

Question 3

Yet another one. Use ggplot_build to build a plot object of the histogram for rendering. From this object x and y values are extracted, to be used for geom_step. Use by to offset x values.

by <- 0.5
p1 <- ggplot(data = d, aes(x = x)) +
  geom_histogram(breaks = seq(from = -4, to = 4, by = by),
                 color = "red", fill = "transparent")

df <- ggplot_build(p1)$data[[1]][ , c("x", "y")]

p1 +
  geom_step(data = df, aes(x = x - by/2, y = y))

enter image description here

Edit following comment from @Vadim Khotilovich (Thanks!)

The xmin from the plot object can be used instead (-> no need for offset adjustment)

df <- ggplot_build(p1)$data[[1]][ , c("xmin", "y")]

p1 +
  geom_step(data = df, aes(x = xmin, y = y))

Question 4

An alternative, also less than ideal:

qplot(x, data=d, geom="histogram", breaks=seq(-4,4,by=.5), color=I("red"), fill = I("transparent")) +
  stat_summary(aes(x=round(x * 2 - .5) / 2, y=1), fun.y=length, geom="step")

Missing some bins that you can probably add back if you mess around a bit. Only (somewhat meaningless) advantage is it is more in ggplot than @Joran's answer, though even that is debatable.

enter image description here

Question 5

I answer my own comment earlier today: here is a modified version of @RosenMatev's answer updated for the v2 (ggplot2_2.0.0) using ggproto:

GeomStepHist <- ggproto("GeomStepHist", GeomPath,
                        required_aes = c("x"),

                        draw_panel = function(data, panel_scales, coord, direction) {
                          data <- as.data.frame(data)[order(data$x), ]

                          n <- nrow(data)
                          i <- rep(1:n, each=2)
                          newdata <- rbind(
                            transform(data[1, ], x=x - width/2, y=0),
                            transform(data[i, ], x=c(rbind(data$x-data$width/2, data$x+data$width/2))),
                            transform(data[n, ], x=x + width/2, y=0)
                          )
                          rownames(newdata) <- NULL

                          GeomPath$draw_panel(newdata, panel_scales, coord)
                        }
)


geom_step_hist <- function(mapping = NULL, data = NULL, stat = "bin",
                           direction = "hv", position = "stack", na.rm = FALSE, 
                           show.legend = NA, inherit.aes = TRUE, ...) {
  layer(
    data = data,
    mapping = mapping,
    stat = stat,
    geom = GeomStepHist,
    position = position,
    show.legend = show.legend,
    inherit.aes = inherit.aes,
    params = list(
      direction = direction,
      na.rm = na.rm,
      ...
    )
  )
}

Question 6

TLDR: use geom_step(..., direction = "mid")

This has become much easier since Daniel Mastropietro and Dewey Dunnington implemented the "mid" as an additional option for the direction argument of geom_step for ggplot2 v3.3.0:

library(ggplot2)

set.seed(1)
d <- data.frame(x = rnorm(1000))
ggplot(d, aes(x)) + 
  geom_histogram(breaks = seq(-4, 4, by=.5), color="red", fill = "transparent") +
  geom_step(stat="bin", breaks=seq(-4, 4, by=.5), color = "black", direction = "mid")

Below, for reference, the code from the question formatted like above answer:

ggplot(d, aes(x)) + 
  geom_histogram(breaks = seq(-4, 4, by=.5), color = "red", fill = "transparent") +
  geom_step(stat="bin", breaks = seq(-4, 4, by=.5), color = "black", direction = "vh")

^{Created on 2020-09-02 by the reprex package (v0.3.0)}

Question 7

a simple way to do something similar to @Rosen Matev (that does not work with ggplot2_2.0.0 as mentioned by @julou), I would just 1) calculate manually the value of the bins (using a small function as shown below) 2) use geom_step() Hope this helps !

geom_step_hist<- function(d,binw){
  dd=NULL
  bin=min(d$y) # this enables having a first value that is = 0 (to have the left vertical bar of the plot when using geom_step)
  max=max(d$y)+binw*2 # this enables having a last value that is = 0 (to have the right vertical bar of the plot when using geom_step)
  xx=NULL
  yy=NULL
  while(bin<=max){
    n=length(temp$y[which(temp$y<bin & temp$y>=(bin-binw))])
    yy=c(yy,n)
    xx=c(xx,bin-binw)
    bin=bin+binw
    rm(n)
  }
  dd=data.frame(xx,yy)
  return(dd)
}
hist=ggplot(dd,aes(x=xx,y=yy))+
geom_step()