R/BirthsDoc.R

In mosaicData: Project MOSAIC Data Sets

#' US Births
#'
#' Number of births in the United States.
#' There are several data sets covering different date ranges and obtaining data from different sources.
#'
#' @docType data
#' @name Births
#' @aliases Births78 Births2015 BirthsSSA BirthsCDC
#' @usage data(Births)
#' @usage data(Births78)
#' @usage data(Births2015)
#' @usage data(BirthsSSA)
#' @usage data(BirthsCDC)
#' @format  A data.frame with the following 8 variables.
#'
#'  * `date`   Date
#'  * `births` Number of births on `date` (integer)
#'  * `wday`   Day of week (ordered factor)
#'  * `year`   Year (integer)
#'  * `month`  Month (integer)
#'  * `day_of_year`  Day of year (integer)
#'  * `day_of_month` Day of month (integer)
#'  * `day_of_week`  Day of week (integer)
#'
#' @source
#' * Data source for `Births`: National Vital Statistics System natality data, as provided by
#'   Google BigQuery and exported to csv by
#'   Robert Kern <http://www.mechanicalkern.com/static/birthdates-1968-1988.csv>.
#' * Data source for `BirthsSSA`  US Social Security Administration, as curated at <https://github.com/fivethirtyeight/data/tree/master/births>
#' * Data source for `BirthsCDC`  US Centers for Disease Control, as curated at <https://github.com/fivethirtyeight/data/tree/master/births>
#' * Data source for `Births2015`: Obtained from the National Center for Health Statistics,
#'   National Vital Statistics System,  Natality, 2015 data.
#'
#' @details
#' There are some overlapping dates in the various data sets, but the number of births does **not** always agree
#' due to the different sources of the data.
#' See the examples.
#'
#' @seealso `Birthdays` for a data set aggregated at the state level.
#'
#' @examples
#' data(Births78)
#' data(Births2015)
#' data(Births)
#' data(BirthsSSA)
#' data(BirthsCDC)
#' # date ranges for the different data sets
#' lapply(
#'   list(Births = Births, Births78 = Births78, Biths2015 = Births2015, BirthsSSA = BirthsSSA,
#'        BirthsCDC = BirthsCDC),
#'        function(x) range(x$date))
#' range(Births78$date)
#' range(Births2015$date)
#' range(Births$date)
#' range(BirthsSSA$date)
#' range(BirthsCDC$date)
#'
#' # Births and Births78 have slightly different numbers of births
#'
#' if(require(ggplot2)) {
#'   ggplot(data = Births, aes(x = date, y = births, colour = ~ wday)) +
#'     stat_smooth(se = FALSE, alpha = 0.8, geom = "line")
#'   ggplot(data = Births, aes(x = day_of_year, y = births, colour = ~ wday)) +
#'     geom_point(size = 0.4, alpha = 0.5) +
#'     stat_smooth(se = FALSE, geom = "line", alpha = 0.6, size = 1.5)
#'   if (require(dplyr)) {
#'     ggplot(
#'      data =  bind_cols(Births %>% filter(year == 1978),
#'                        Births78 %>% rename(births78 = births)),
#'      aes(x = births - births78)
#'      ) +
#'      geom_histogram(binwidth = 1)
#'   }
#' }
#'
#' if(require(ggplot2)) {
#'   ggplot(data = Births, aes(x = date, y = births, colour = ~ wday)) +
#'     stat_smooth(se = FALSE, alpha = 0.8, geom = "line")
#'   ggplot(data = Births, aes(x = day_of_year, y = births, colour = ~ wday)) +
#'     geom_point(size = 0.4, alpha = 0.5) +
#'     stat_smooth(se = FALSE, geom = "line", alpha = 0.6, size = 1.5)
#'   if (require(dplyr)) {
#'     ggplot(
#'      data =  bind_cols(Births %>% filter(year == 1978),
#'                        Births78 %>% rename(births78 = births)),
#'      aes(x = births - births78)
#'      ) +
#'      geom_histogram(binwidth = 1)
#'
#'     # SSA records more births than CDC
#'     ggplot(
#'      data =  bind_cols(BirthsSSA %>% filter(year <= 2003) %>% rename(SSA = births),
#'                        BirthsCDC %>% filter(year >= 2000) %>% rename(CDC = births)),
#'      aes(x = SSA - CDC)
#'      ) +
#'      geom_histogram(binwidth = 10)
#'   }
#' }
#'
#'
#'
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#' US Births in 1969 - 1988
#'
#' A day by day record of the number of births in each US State.
#'
#' @docType data
#' @name Birthdays
#' @usage data(Birthdays)
#' @format
#'   A data frame with 374221 observations on the following variables.
#'   \itemize{
#'     \item{\code{state}} {state where child was born}
#'     \item{\code{year}} {year (1969-1988)}
#'     \item{\code{month}} {month (1-12)}
#'     \item{\code{day}} {day of month}
#'     \item{\code{date}} {date as a date object}
#'     \item{\code{births}} {number of births}
#'   }
#'
#' @seealso `Births`, `Births78`, `Births2015`, `BirthsSSA`, `BirthsCDC` for data sets that are
#' aggregated at the level of the entire country.
#'
#' @examples
#' data(Birthdays)
#' if (require(mosaic)) {
#'   MI <- Birthdays %>% filter(state == "MI")
#'   gf_point(births ~ date, Birthdays, data = MI)
#'   gf_line(births ~ date, Birthdays, data = MI, color = ~ wday)
#'   gf_line(births ~ date,
#'     data = Birthdays %>% group_by(date) %>% summarise(births = sum(births)))
#'   }

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