Closed rpruim closed 8 years ago
Here's the documentation. Any suggested improvements? Better attribution?
Births2015 {mosaicData} R Documentation US Births in 2015
Description
A day by day record of the number of births in the United States in 2015.
Usage
data(Births2015) Format
A data frame with 365 observations on the following variables.
date date in 2015
births number of US births
dayofyear sequential number of days from 1 to 365
wday day of week as an ordered factor
Source
United States Centers for Disease Control (based on 2015 US Natality data).
See Also
Births78, Births
Examples
data(Births2015) if (require(lattice)) { xyplot(births ~ date, Births2015) xyplot(births ~ date, Births2015, groups = wday) }
Interestingly, the seasonal effect is much less pronounced in 2015. The weekend effect has grown:
Births78 %>%
group_by(wday) %>% summarise(births = sum(births)) %>%
ungroup() %>% mutate(frac = births / sum(births))
# A tibble: 7 × 3
wday births frac
<ord> <int> <dbl>
1 Sun 421400 0.1264236
2 Mon 487309 0.1461968
3 Tues 504858 0.1514617
4 Wed 493897 0.1481733
5 Thurs 493149 0.1479489
6 Fri 500541 0.1501665
7 Sat 432085 0.1296292
Births2015 %>%
group_by(wday) %>% summarise(births = sum(births)) %>%
ungroup() %>% mutate(frac = births / sum(births))
# A tibble: 7 × 3
wday births frac
<ord> <dbl> <dbl>
1 Sun 384686 0.09669129
2 Mon 610448 0.15343684
3 Tues 654462 0.16449981
4 Wed 638513 0.16049101
5 Thurs 640422 0.16097084
6 Fri 615397 0.15468078
7 Sat 434569 0.10922944
Acknowledging Brady Hamilton for his assistance generating the aggregated data would be a nice touch.
I modified the documentation to this:
Source
Obtained from the United States Centers for Disease Control (based on 2015 US Natality data) with assistance from Brady Hamilton.
Update based on email from Brady Hamilton:
Source
Obtained from the National Center for Health Statistics, National Vital Statistics System, Natality, 2015 data.