This package contains various, not necessarily related, functions to make some data analysis tasks a little easier.
Why “motley”? Because “misc” or “miscellaneous” is already used too often, so I went looking for a synonym.
Also, this is more like an educational sandbox for myself to learn more about R package development and everything related to that.
You can install MMmotley from GitHub with:
# install.packages("devtools")
devtools::install_github("milanmlft/MMmotley")
library(MMmotley)
## Generate some random uniform p-values
p_values <- runif(1000)
By default, ggplot2::geom_histogram() centers the first and last bins
of the histogram on the x-axis lower and upper limits, respectively.
library(ggplot2)
ggplot(mapping = aes(x = p_values)) +
geom_histogram(binwidth = 0.05)
In case of p-values, which lie in the interval [0, 1], it makes more
sense to set the boundaries of the first and last bins at 0 and 1. This
is what gg_pval_hist does, with some additional tweaks to improve the
layout. By default, the binwidths are set at 0.05, commonly used as a
cut-off for significance, so that the height of the first bar represents
the number of p-values lying between 0 and 0.05, i.e. the number of
cases that would be deemed significant.
p <- gg_pval_hist(p_values, binwidth = 0.05)
p
This is a convenience function if you have a list of plots and want to save them to a PDF file with each plot ending up on its own page.
# Generate list of plots
mtcars_split <- split(mtcars, mtcars$cyl)
plot_list <- lapply(mtcars_split, function(d) {
ggplot(d, aes(mpg, wt)) +
geom_point()
})
# Save plots
file <- tempfile()
save_plots(plot_list, file)
This is a simple wrapper around scales::label_percent() to convert
numeric input to percentages and return them as characters.
x <- seq(0, 1, by = 0.25)
format_percentage(x)
#> [1] "0%" "25%" "50%" "75%" "100%"