R/data-blizzard_salary.R

In openintro: Data Sets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

#' Blizzard Employee Voluntary Salary Info.
#'
#' Employee generated anonymous survey of salary information.
#'
#' @name blizzard_salary
#' @docType data
#' @format A data frame with 466 rows and 9 variables.
#' \describe{
#'   \item{timestamp}{Time data was entered}
#'   \item{status}{Specifies employment status.}
#'   \item{current_title}{Current job title.}
#'   \item{current_salary}{Current salary (in USD).}
#'   \item{salary_type}{Frequency with levels year, hour, week.}
#'   \item{percent_incr}{Raise given July 2020.}
#'   \item{other_info}{Other information submitted by employee.}
#'   \item{location}{Current office of employment.}
#'   \item{performance_rating}{Most recent review performance rating.}
#' }
#' @source [Bloomberg - Blizzard workers share salaries in revolt over wage disparities](https://www.bloomberg.com/news/articles/2020-08-03/blizzard-workers-share-salaries-in-revolt-over-wage-disparities).
#' @keywords datasets
#' @examples
#' library(ggplot2)
#' library(dplyr)
#'
#' plot_data <- blizzard_salary %>%
#'   mutate(annual_salary = case_when(
#'     salary_type == "week" ~ current_salary * 52,
#'     salary_type == "hour" ~ current_salary * 40 * 52,
#'     TRUE ~ current_salary
#'   ))
#'
#' ggplot(plot_data, aes(annual_salary)) +
#'   geom_histogram(binwidth = 25000, color = "white") +
#'   labs(
#'     title = "Current Salary of Blizzard Employees",
#'     x = "Salary",
#'     y = "Number of Employees"
#'   )
#'
"blizzard_salary"