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gf_squareplot()gf_squareplot() creates histograms where individual data
points are visible as stacked unit rectangles. Instead of abstract bars,
each observation becomes a countable square, making sample size and
distribution shape tangible.
This is particularly useful for teaching statistical concepts like sampling distributions and hypothesis testing, where students benefit from seeing that “n = 47” means 47 actual squares.
Pass a formula and data frame, just like other gf_*
functions:
The bars parameter controls how the histogram is
displayed:
"none" (default): Individual squares only"outline": Squares with bar outlines around each
bin"solid": Traditional filled barsYou can customize fill color, binwidth, and axis
limits:
For integer-valued data with a small range,
gf_squareplot() automatically selects a
binwidth of 1, so each integer gets its own column:
int_data <- data.frame(rolls = sample(1:6, 30, replace = TRUE))
gf_squareplot(~rolls, data = int_data)When any bin has more than 75 observations, the function
automatically switches to solid bars to keep the display readable. You
can opt into subdivision instead with
auto_subdivide = TRUE, which splits wide bins into
sub-columns so rectangles remain countable:
Show a dashed line at the sample mean:
The show_dgp = TRUE option adds a teaching overlay for
hypothesis testing contexts. It shows:
set.seed(42)
samp_dist <- do(100) * b1(Thumb ~ Height, data = sample(Fingers, 30))
gf_squareplot(~b1, data = samp_dist,
show_dgp = TRUE,
show_mean = TRUE,
xrange = c(-0.5, 1.5),
xbreaks = seq(-0.5, 1.5, by = 0.25))When the input is a factor with numeric levels, all levels are displayed on the x-axis even if some have zero counts:
ratings <- factor(sample(1:5, 20, replace = TRUE, prob = c(1, 2, 4, 2, 1)),
levels = 1:5)
df <- data.frame(rating = ratings)
gf_squareplot(~rating, data = df)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.