tf_parse: Parses track and field data from Flash or Hytek format data...
In JumpeR: Importing and Working with Track and Field Data

Description Usage Arguments Value See Also Examples

Outputs a data frame containing track and field data

tf_parse(
  file,
  avoid = avoid_default,
  typo = typo_default,
  replacement = replacement_default,
  relay_athletes = FALSE,
  rounds = FALSE,
  round_attempts = FALSE,
  split_attempts = FALSE,
  splits = FALSE,
  split_length = 1
)

`file`	a .pdf or .html file (could be a url) where containing track and field results. Must be formatted in a "normal" fashion - see vignette
`avoid`	a list of strings. Rows in `file` containing these strings will not be included. For example "Record:", often used to label records, could be passed to `avoid`. The default is `avoid_default`, which contains many strings similar to "Record:". Users can supply their own lists to `avoid`.
`typo`	a list of strings that are typos in the original results. `tf_parse` is particularly sensitive to accidental double spaces, so "Central High School", with two spaces between "Central" and "High" is a problem, which can be fixed. Pass "Central High School" to `typo`.
`replacement`	a list of fixes for the strings in `typo`. Here one could pass "Central High School" (one space between "Central" and "High") to fix the issue described in `typo`
`relay_athletes`	should `tf_parse` try to include the names of relay athletes for relay events? Names will be listed in new columns "Relay-Athlete_1", "Relay_Athlete_2" etc. Defaults to `FALSE`.
`rounds`	should `tf_parse` try to include rounds for jumping/throwing events? Please note this will add a significant number of columns to the resulting data frame. Defaults to `FALSE`.
`round_attempts`	should `tf_parse` try to include rounds results (i.e. "PASS", "X", "O") for high jump and pole value events? Please note this will add a significant number of columns to the resulting data frame. Defaults to `FALSE`
`split_attempts`	should `tf_parse` split attempts from each round into separate columns? For example "XXO" would result in three columns, one for "X', another for the second "X" and third for "O". There will be a lot of columns. Defaults to `FALSE`
`splits`	either `TRUE` or the default, `FALSE` - should `tf_parse` attempt to include splits.
`split_length`	either the distance at which splits are collected (must be constant distance) or the default, `1`, the length of track at which splits are recorded. Not all results are internally consistent on this issue. If in doubt use the default `1`

a data frame of track and field results

tf_parse is meant to be preceded by read_results

tf_parse(
read_results("https://www.flashresults.com/2018_Meets/Outdoor/05-05_A10/015-1.pdf"),
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE)