R/house.R

In tripaccess: American Travel Behavior and Access Datasets

#' House data
#'
#' Include household characteristics categorical and numeric variables.
#'
#' @format A data frame with 129695 rows (each row is a household) and 9 columns
#' \describe{
#'   \item{household_id}{Household identifier. Use this variable to join the house dataset and the person dataset as well as join the house dataset and the trip dataset.}
#'   \item{region}{2010 Census division classification for the respondent's home address.}
#'   \item{number_drivers}{Number of drivers in household.}
#'   \item{count_household_members}{Count of household members.}
#'   \item{number_vehicles}{Count of household vehicles.}
#'   \item{household_life_cycle}{Life Cycle classification for the household, derived by attributes pertaining to age, relationship, and work status.}
#'   \item{count_adult_household_members}{Count of adult household members at least 18 years old.}
#'   \item{number_workers}{Number of workers in household.}
#'   \item{count_young_child}{Count of persons with an age between 0 and 4 in household.}
#' }
#' @source <https://nhts.ornl.gov/>
#' @examples
#' if (require("tidyverse")) {
#' # Filtered to households with at least one driver
#' house_with_drivers <- house |>
#'   filter(number_drivers > 0)
#'
#' # Filtered to households with at least one vehicle
#' house_with_vehicles <- house_with_drivers |>
#'   filter(number_vehicles > 0)
#'
#' # Plot household vehicles by number of drivers
#' ggplot(data = house_with_vehicles,
#'        aes(x = number_drivers,
#'            y = number_vehicles)) +
#'   geom_jitter(alpha = 0.08, width = 0.15, height = 0.15) +
#'   geom_smooth(method = lm, se = FALSE, formula = y ~ x, color = "blue") +
#'   labs(title = "Household Vehicles versus Number of Drivers",
#'        x = "Number of Drivers in Household",
#'        y = "Number of Household Vehicles") +
#'   theme_bw()
#' }
"house"