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 https://www.mechanicalkern.com:443/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)
  }
}