Making a specific quantile plot in R - r

Question

I am very intrigued by the following visulization (Decile term)
And I wonder how it would be possible to do it in R.
There is of course histograms and density plots, but they do not make such a nice visualization. Especially, I would like to know if it possible to do it with ggplot/tidyverse.
edit in response to the comment
library(dplyr)
library(ggplot2)
someData <- data_frame(x = rnorm(1000))
ggplot(someData, aes(x = x)) +
geom_histogram()
this produces a histogram (see http://www.r-fiddle.org/#/fiddle?id=LQXazwMY&version=1)
But how I can get the coloful bars? How to implement the small rectangles? (The arrows are less relevant).

Answer 1

You have to define a number of breaks, and use approximate deciles that match those histogram breaks. Otherwise, two deciles will end up in one bar.
d <- data_frame(x = rnorm(1000))
breaks <- seq(min(d$x), max(d$x), length.out = 50)
quantiles <- quantile(d$x, seq(0, 1, 0.1))
quantiles2 <- sapply(quantiles, function(x) breaks[which.min(abs(x - breaks))])
d$bar <- as.numeric(as.character(cut(d$x, breaks, na.omit((breaks + dplyr::lag(breaks)) / 2))))
d$fill <- cut(d$x, quantiles2, na.omit((quantiles2 + dplyr::lag(quantiles2)) / 2))
ggplot(d, aes(bar, y = 1, fill = fill)) +
geom_col(position = 'stack', col = 1, show.legend = FALSE, width = diff(breaks)[1])
Or with more distinct colors:
ggplot(d, aes(bar, y = 1, fill = fill)) +
geom_col(position = 'stack', col = 1, show.legend = FALSE, width = diff(breaks)[1]) +
scale_fill_brewer(type = 'qual', palette = 3) # The only qual pallete with enough colors
Add some styling and increase the breaks to 100:
ggplot(d, aes(bar, y = 1, fill = fill)) +
geom_col(position = 'stack', col = 1, show.legend = FALSE, width = diff(breaks)[1], size = 0.3) +
scale_fill_brewer(type = 'qual', palette = 3) +
theme_classic() +
coord_fixed(diff(breaks)[1], expand = FALSE) + # makes square blocks
labs(x = 'x', y = 'count')
And here is a function to make that last one:
decile_histogram <- function(data, var, n_breaks = 100) {
breaks <- seq(min(data[[var]]), max(data[[var]]), length.out = n_breaks)
quantiles <- quantile(data[[var]], seq(0, 1, 0.1))
quantiles2 <- sapply(quantiles, function(x) breaks[which.min(abs(x - breaks))])
data$bar <- as.numeric(as.character(
cut(data[[var]], breaks, na.omit((breaks + dplyr::lag(breaks)) / 2)))
)
data$fill <- cut(data[[var]], quantiles2, na.omit((quantiles2 + dplyr::lag(quantiles2)) / 2))
ggplot2::ggplot(data, ggplot2::aes(bar, y = 1, fill = fill)) +
ggplot2::geom_col(position = 'stack', col = 1, show.legend = FALSE, width = diff(breaks)[1], size = 0.3) +
ggplot2::scale_fill_brewer(type = 'qual', palette = 3) +
ggplot2::theme_classic() +
ggplot2::coord_fixed(diff(breaks)[1], expand = FALSE) +
ggplot2::labs(x = 'x', y = 'count')
}
Use as:
d <- data.frame(x = rnorm(1000))
decile_histogram(d, 'x')