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SwimmeR

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

Latest Released Version from CRAN

install.packages("SwimmeR")

library(SwimmeR)

Latest Development Version from Github

Version 0.14.2

• function make_lineup will take two data frames containing athlete/event/time combinations (one for each team) and create a lineup maximizing returns for one team
• swim_parse handles some Hytek psych sheets (single column only)
• read_results now handles both pdf and html results at .aspx addresses
• swim_parse handles Hytek Top Times reports via toptimes_parse_hytek. Still under development.
• new function place supersedes swim_place and dive_place, handling both swimming and diving
• major change swim_parse output columns Finals_Time and Prelims_Time have been renamed Finals and Prelims

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

Usage

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

Importing Results

SwimmeR reads swimming results into R and outputs tidy data frames 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 data frame. Reading .hy3 files is also now possible with swim_parse, although .hy3 functionality is still under development and quite buggy. As of version 0.7.0 SwimmeR can also read S.A.M.M.S. style results.

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 seven arguments as of version 0.7.0.

file is the output of read_results and is required.

avoid is a list of strings. Rows 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 data frame, but will not cause an error. Nonsense rows can be removed after import.

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.

The following three arguments are only available in SwimmeR v0.6.0 and higher

splits and split_length tell swim_parse if and how to import split times. Setting splits = TRUE will import splits as columns. split_length refers to the pool course (length) as defaults to 50. It may also be set to 25, if splits are recorded every 25 rather than every 50. Split reporting within source files is very inconsistent, so while swim_parse will import whatever splits are present they may require some inspection after import. swim_parse_ISL also has a splits argument that works the same way. Set splits = TRUE to record splits. See the Splits sections of vignette("SwimmeR") for more information and examples.

relay_swimmers tells swim_parse or swim_parse_ISL whether or not to include the names of relay swimmers as additional columns. Set relay_swimmers = TRUE to include. There is more information available in vignette("SwimmeR")

swim_parse(
    read_results(
      "http://www.nyhsswim.com/Results/Boys/2008/NYS/Single.htm"
    ),
    typo = c("-1NORTH ROCKL"),
    replacement = c("1-NORTH ROCKL"),
    splits = TRUE, # requires version 0.6.0 or greater
    relay_swimmers = TRUE # requires version 0.6.0 or greater
  )

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

swim_parse_ISL(
    file = read_results(
      "https://isl.global/wp-content/uploads/2019/10/isl-indianapols-results-day-2-2.pdf"),
      splits = TRUE, # requires version 0.6.0 or greater
      relay_swimmers = TRUE # requires version 0.6.0 or greater
  )

Imported Information

swim_parse will attempt to capture the following information, assuming it is present in the raw results.

Place: Order of finish

Name: An athlete’s name. Relays do not have names.

Age: Could be a number of years (25) or a year in school (SR)

Para: An athlete’s para-swimming classification (e.g. S10)

Team: The name of a team, for athletes or relays

Prelims_Time: If two times/scores are listed, this is the first one. swim_parse currently can’t differentiate between a seed time and a prelims time. They’re both called Prelims_Time. Prelim/seed diving scores are also included here even though they’re not technically times.

Finals_Time: If two times/scores are listed this is the second one. If only one time/score is listed this is it.

DQ: Was an athlete/relay team disqualified (1) or not (0)

Exhibition: Was an athlete/relay team competing as a non-scoring (exhibition) entry (1) or not (0)

Points: Points award based on place (not diving score)

Relay_Swimmer_X: Names of athletes in a relay

Split_X: Split corresponding to a given distance X

Usable Formats

SwimmeR can only read files in single column format, not double.

Will work - results in single column

Will also work - results in single column

Will not work - results in multiple columns

Formatting 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)

Regularizing Team Names

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))

Reordering Athlete Names

Athlete names are sometimes formatted as “Firstname Lastname” and sometimes as “Lastname, Firstname”. For purposes of plotting and presentation it’s often desirable to format all names the same way. The name_reorder function, available in versions >= 0.8.0, will reorder all “Lastname, Firstname” names as “Firstname Lastname”.

df <- data.frame(Name = c("King, Lilly", "Lilly King", NA, "Richards Ross, Sanya", "Phelps, Michael F"))
name_reorder(df)

While “Lastname, Firstname” is actually more informative in that it differentiates between last names and first names it’s not always possible to convert “Firstname Lastname” to “Lastname, Firstname”. Consider an athlete named “Michael Fred Phelps II” - it’s not possible to determine programmatically where a comma should go. Is it “II, Michael Fred Phelps”? Or maybe “Fred Phelps II, Michael”? There’s no way to tell. On the other hand converting “Phelps II, Michael Fred” to “Michael Fred Phelps II” is straightforward.

Drawing brackets

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)

Course conversions

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 course_convert. The verbose parameter determines what course_convert outputs. Setting verbose = FALSE (the default) returns a data frame including the input variables whereas verbose = TRUE only returns the converted time(s). course_convert 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(time = swim$time, course = swim$course, course_to = swim$course_to, event = swim$event, verbose = TRUE)

Getting help

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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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