| Births | R Documentation |
Number of births in the United States. There are several data sets covering different date ranges and obtaining data from different sources.
data(Births)
data(Births78)
data(Births2015)
data(BirthsSSA)
data(BirthsCDC)
A data.frame with the following 8 variables.
dateDate
birthsNumber of births on date (integer)
wdayDay of week (ordered factor)
yearYear (integer)
monthMonth (integer)
day_of_yearDay of year (integer)
day_of_monthDay of month (integer)
day_of_weekDay of week (integer)
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.
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.
Birthdays for a data set aggregated at the state level.
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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