In JaneEverydayDoe/cbds: Jane Doe's Personal R Package

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(cbds)

This package includes a number of functions helpful to our daily work working with tabular data. While the functionality of this package is currently limited to a few functions, over time, we intend to include additional functions that will help make our work easier!

To demonstrate how to utilize the functionality in this package, we'll use a dataset available from the package ggplot2: msleep

The Data

library(ggplot2)
msleep

Missing Data: check_na()

check_na() is a small function that returns the number of observations in a single variable as well as the number of missing and non-missing variables. It's a quick check on the data.

# calculate missingness
check_na(msleep$brainwt)

Custom Plotting: theme_cbds()

In data analysis, we often generate a number of plots using ggplot2. theme_cbds generates a custom theme that we can apply to all of our plots.

For example, if we did not use this custom theme, a plot may look as follows (with ggplot2 default settings):

ggplot(msleep, aes(sleep_rem, sleep_total)) + geom_point()

But, with our custom theme, it would look as follows:

ggplot(msleep, aes(sleep_rem, sleep_total)) + 
  geom_point() + 
  theme_cbds()

The data themselves don't change, but we've:

• removed the gridlines
• plotted only the x- and y-axis lines
• specified a white background
• moved the tick labels closer to the axes
• removed axis tick marks

Note, that this does not only apply to scatterplots. For example, this theme can be used for any type of ggplot2 plot:

ggplot(msleep, aes(vore)) + 
  geom_bar() + 
  theme_cbds()

JaneEverydayDoe/cbds documentation built on Oct. 30, 2019, 7:36 p.m.