SwimmeR is intended to assist those working with times from competitive pool swimming races, such as those conducted under the NHFS, NCAA, or FINA. For more information please see vignette("SwimmeR").

install.packages("SwimmeR")

library(SwimmeR)

devtools::install_github("gpilgrim2670/SwimmeR", build_vignettes = TRUE)

Version 0.5.3 of SwimmeR has two major uses - importing results and formatting times. It also has functions for course conversions and drawing brackets.

SwimmeR reads swimming results into R and outputs tidy dataframes of the results. SwimmeR uses read_results to read in either a PDF or HTML file (like a url) and the swim_parse or swim_parse_ISL function to convert the read file to a tidy dataframe. Reading .hy3 files is also now possible with swim_parse, although .hy3 functionality is still under development and quite buggy.

read_results has two arguments, file, which is the file path to read in, and node, required only for HTML files, this is a CSS node where the results reside. node defaults to "pre", which has been correct in every instance tested thus far.

swim_parse has four arguments. file is the output of read_results and is required. avoid is a list of strings. Rows of the read in file containing any of those strings will not be included. avoid is optional. Incorrectly specifying it may lead to nonsense rows in the final dataframe, but will not cause an error. typo and replacement work together to fix typos, by replacing them with replacements. Strings in typo will be replaced by strings in replacement in element index order - that is the first element of typo will be replaced everywhere it appears by the first element of replacement. Typos can cause lost data and nonsense rows. See ?swim_parse or the package vignette for more information.

swim_parse(
    read_results(
      "http://www.nyhsswim.com/Results/Boys/2008/NYS/Single.htm",
      node = "pre"
    ),
    typo = c("-1NORTH ROCKL"),
    replacement = c("1-NORTH ROCKL")
  )

swim_parse_ISL only takes one argument, file, the output of read_results.

swim_parse_ISL(
    read_results(
      "https://isl.global/wp-content/uploads/2019/10/isl-indianapols-results-day-2-2.pdf")
  )

SwimmeR can only read files in single column format, not double. SwimmeR also does not capture split times.

SwimmeR also converts times between the conventional swimming format of minutes:seconds.hundredths (1:35.37) and the computationally useful format of seconds, reported to the 100ths place (e.g. 95.37). This is accomplished with sec_format and mmss_format, which are inverses of one another. Both sec_format and mmss_format work well with tidyverse functions.

times <- c("1:35.97", "57.34", "16:53.19", NA)
times_sec <- sec_format(times)
times_sec
times_mmss <- mmss_format(times_sec)
times_mmss
all.equal(times, times_mmss)

Team names are often abbreviated. Rather than specifying every abbreviation SwimmeR provides get_mode to make the task simpler.

name <- c(rep("Lilly King", 5), rep("James Sullivan", 3))
team <- c(rep("IU", 2), "Indiana", "IUWSD", "Indiana University", rep("Monsters University", 2), "MU")
df <- data.frame(name, team, stringsAsFactors = FALSE)
df %>% 
  group_by(name) %>% 
  mutate(Team = get_mode(team))

Brackets for single elimination tournaments can be produced for any number of teams between 5 and 64. Byes will automatically be included for higher seeds as required.

teams <- c("red", "orange", "yellow", "green", "blue", "indigo", "violet")
round_two <- c("red", "yellow", "blue", "indigo")
round_three <- c("red", "blue")
champion <- "red"
draw_bracket(teams = teams,
            round_two = round_two,
            round_three = round_three,
            champion = champion)

Additionally 'SwimmeR' also converts between the various pool sizes used in competitive swimming, namely 50m length (LCM), 25m length (SCM) and 25y length (SCY). This is accomplished with either convert_courses or convert_courses_DF, both of which have the same basic functionality. The difference is the convert_courses_DF returns a dataframe including the input variables whereas convet_courses only returns the converted time(s). Both functions will take inputs in either seconds or swimming format.

swim <- tibble(time = c("6:17.53", "59.14", "4:14.32", "16:43.19"), course = c("LCM", "LCM", "SCY", "SCM"), course_to = c("SCY", "SCY", "SCM", "LCM"), event = c("400 Free", "100 Fly", "400 IM", "1650 Free"))

course_convert(time = swim$time, course = swim$course, course_to = swim$course_to, event = swim$event)

course_convert_DF(time = swim$time, course = swim$course, course_to = swim$course_to, event = swim$event)

I do a lot of demos on how to use SwimmeR at my blog Swimming + Data Science.

SwimmeR also has a vignette. Call vignette("SwimmeR"). If you download from github don't forget to set build_vignettes = TRUE.

If you find bug, please provide a minimal reproducible example at github.