Births

R Documentation

US Births

Description

Number of births in the United States. There are several data sets covering different date ranges and obtaining data from different sources.

Usage

data(Births)

data(Births78)

data(Births2015)

data(BirthsSSA)

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)

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.

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.

See Also

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)
  }
}