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)
Version 0.13.0
devtools::install_github("gpilgrim2670/SwimmeR", build_vignettes = TRUE)
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 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
)
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 ages
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
Exhibition
: Was an athlete/relay team competing as a non-scoring (exhibition) entry
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
SwimmeR
can only read files in single column format, not double.
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))
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.
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 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)
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.