R/deprec_swim_parse.R
In gpilgrim2670/SwimmeR: Data Import, Cleaning, and Conversions for Swimming Results
Defines functions
swim_parse_old
Documented in
swim_parse_old
#' Formats swimming and diving data read with \code{read_results} into a data
#' frame
#'
#' Takes the output of \code{read_results} and cleans it, yielding a data frame
#' of swimming (and diving) results. Old version, retired in dev build on Dec
#' 21, 2020 and release version 0.7.0
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr lead
#' @importFrom dplyr lag
#' @importFrom dplyr case_when
#' @importFrom dplyr na_if
#' @importFrom dplyr select
#' @importFrom dplyr coalesce
#' @importFrom dplyr arrange
#' @importFrom dplyr filter
#' @importFrom dplyr full_join
#' @importFrom dplyr n_distinct
#' @importFrom dplyr bind_rows
#' @importFrom dplyr everything
#' @importFrom dplyr group_by
#' @importFrom dplyr ungroup
#' @importFrom dplyr pull
#' @importFrom dplyr between
#' @importFrom stringr str_replace
#' @importFrom stringr str_replace_all
#' @importFrom stringr str_extract
#' @importFrom stringr str_extract_all
#' @importFrom stringr str_split
#' @importFrom stringr str_split_fixed
#' @importFrom stringr str_detect
#' @importFrom stringr str_length
#' @importFrom purrr map_lgl
#' @importFrom purrr map
#' @importFrom stats setNames
#'
#' @param file output from \code{read_results}
#' @param avoid a list of strings. Rows in \code{file} containing these strings
#' will not be included. For example "Pool:", often used to label pool
#' records, could be passed to \code{avoid}. The default is
#' \code{avoid_default}, which contains many strings similar to "Pool:", such
#' as "STATE:" and "Qual:". Users can supply their own lists to \code{avoid}.
#' @param typo a list of strings that are typos in the original results.
#' \code{swim_parse_old} 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
#' \code{typo}. Unexpected commas as also an issue, for example "Texas,
#' University of" should be fixed using \code{typo} and \code{replacement}
#' @param replacement a list of fixes for the strings in \code{typo}. Here one
#' could pass "Central High School" (one space between "Central" and "High")
#' and "Texas" to \code{replacement} fix the issues described in \code{typo}
#' @param splits either \code{TRUE} or the default, \code{FALSE} - should
#' \code{swim_parse_old} attempt to include splits.
#' @param split_length either \code{25} or the default, \code{50}, the length of
#' pool at which splits are recorded. Not all results are internally
#' consistent on this issue - some have races with splits by 50 and other
#' races with splits by 25.
#' @param relay_swimmers either \code{TRUE} or the default, \code{FALSE} -
#' should relay swimmers be reported. Relay swimmers are reported in separate
#' columns named \code{Relay_Swimmer_1} etc.
#' @return returns a data frame with columns \code{Name}, \code{Place},
#' \code{Age}, \code{Team}, \code{Prelims_Time}, \code{Finals_Time},
#' \code{Points}, \code{Event} & \code{DQ}. Note all swims will have a
#' \code{Finals_Time}, even if that time was actually swam in the prelims
#' (i.e. a swimmer did not qualify for finals). This is so that final results
#' for an event can be generated from just one column.
#'
#' @examples \dontrun{
#' swim_parse_old(
#' read_results("http://www.nyhsswim.com/Results/Boys/2008/NYS/Single.htm", node = "pre"),
#' typo = c("-1NORTH ROCKL"), replacement = c("1-NORTH ROCKL"),
#' splits = TRUE,
#' relay_swimmers = TRUE)
#' }
#' \dontrun{
#' swim_parse_old(read_results("inst/extdata/Texas-Florida-Indiana.pdf"),
#' typo = c("Indiana University", ", University of"), replacement = c("Indiana University", ""),
#' splits = TRUE,
#' relay_swimmers = TRUE)
#' }
#' @seealso \code{swim_parse_old} must be run on the output of
#' \code{\link{read_results}}
#'
swim_parse_old <-
function(file,
avoid = avoid_default,
typo = typo_default,
replacement = replacement_default,
splits = FALSE,
split_length = 50,
relay_swimmers = FALSE) {
#### default typo and replacement strings ####
typo_default <- c("typo")
replacement_default <- c("typo")
if(length(typo) != length(replacement)) {
stop("typo and replacement must have the same number of elements (be the same length)")
}
if(is.logical(splits) == FALSE) {
stop("splits must be logical, either TRUE or FALSE")
}
if(is.numeric(split_length) == FALSE) {
stop("split_length must be numeric, usually 50 or 25")
}
if(is.logical(relay_swimmers) == FALSE) {
stop("relay_swimmers must be logical, either TRUE or FALSE")
}
#### strings that if a line begins with one of them the line is ignored ####
avoid_default <-
c(
"Record",
"RECORD",
"^\\s*Public\\:",
"^\\s*NYSPHSAA",
"^\\s*NYSPHAA",
"^\\s*State:",
"^\\s*States:",
"^\\s*STATE:",
"^\\s*STATES:",
"\\d\\:\\s",
"^\\s*Finals",
"^\\s*Prelims",
"^\\s*Section\\:",
"^\\s*SECTION\\:",
"^\\s*Section [:alpha:]{1,2}\\:",
"^\\s*SECTION [:alpha:]{1,2}\\:",
"^\\s*Sectional\\:",
"^\\s*Sectionals\\:",
"^\\s*Hosted",
"^\\s*Meet",
"^\\s*MEET",
"^\\s*Points",
"^\\s*Rec\\.?\\:",
"^\\s*REC\\.?\\:",
"\\sRec\\.?\\:\\s",
"^\\s*Rcd\\:",
"^\\s*Cty\\:",
"^\\s*League",
"^\\s*League Rec\\.?\\:",
"^\\s*LEAGUE",
"^\\s*IAC\\:",
"^\\s*AA\\:",
"^\\s*AAA\\:",
"^\\s*AAC\\:",
"^\\s*Con\\.\\:",
"^\\s*Auto\\:",
"^\\s*Auto\\.\\:",
"^\\s*Cons\\.\\:",
"^\\s*Eastern\\:",
"^\\s*Class [[:alpha:]]\\:",
"^\\s*CLASS [[:alpha:]]\\:",
"^\\s*Class '[[:alpha:]]'\\:",
"^\\s*Pool\\:",
"^\\s*POOL\\:",
"^\\s*\\'A\\'\\:",
"^\\s*Nassau\\:",
"^\\s*CONS\\:",
"^\\s*CONS\\.\\:",
"^\\s*Qual\\.\\:",
"^\\s*QUAL\\.\\:",
"^\\s*Qual\\:",
"^\\s*QUAL\\:",
"^\\s*Qual\\.\\:",
"^\\s*Qualify\\:",
"^\\s*QUALIFY\\:",
"QUALIFY\\:",
"^\\s*School\\:",
"^\\s*SCHOOL\\:",
"^\\s*School\\s*Prelims\\s*Finals",
"^\\s*NFL\\:",
"^\\s*NYS\\:",
"^\\s*FED\\:",
"^\\s*Sectio\\:",
"^\\s*Sect\\:",
"^\\s*SECT\\:",
"^\\s*Sec\\:",
"^\\s*SEC\\:",
"^\\s*CHS\\:",
"^\\s*Chs\\:",
"^\\s*Large\\:",
"^\\s*Small\\:",
"^\\s*r\\:",
"National\\:",
"Meet\\:",
"NCAA\\:"
)
#### define avoid_minimal ####
avoid_minimal <- c("^\\s{1,}r\\:")
#### assign row numbers ####
as_lines_list_2 <- add_row_numbers(text = file)
# stringr::str_remove_all("\n") %>%
# # trimws() %>%
# stringr::str_replace_all(stats::setNames(replacement, typo))
#### parsing html and pdf files ####
if (stringr::str_detect(file[1], "^A107") == FALSE) {
#### Pulls out event labels from text ####
events <- event_parse(as_lines_list_2)
#### set up strings ####
# Name_String <- "_?[:alpha:]+'?[:alpha:]+\\s?[:alpha:]*\\s?[:alpha:]*,\\s?[:alpha:]*\\s?[:alpha:]*,? [:alpha:]+\\s?[:alpha:\\-\\']*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
# Name_String <- "_?[:alpha:]+'?[:alpha:]+\\s?[:alpha:]*\\s?[:alpha:]*,\\s?[:alpha:]*\\s?[:alpha:]*,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
# Name_String <- "_?[:alpha:]+'?[:alpha:\\-\\'\\.]+\\s?[:alpha:]*\\s?[:alpha:]*,\\s?[:alpha:]*\\s?[:alpha:]*,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
# Name_String <- "_?[:alpha:]+\\s?\\'?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*,?\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:]*\\.?,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
Name_String <-
"_?[:alpha:]+\\s?\\'?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*,?\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:]*\\.?,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
Time_Score_String <- "\\d{0,2}\\:?\\d{1,3}\\.\\d{2}"
Time_Score_Specials_String <- paste0(Time_Score_String, "|^NT$|^NP$|^DQ$")
Age_String <- "^SR$|^JR$|^SO$|^FR$|^[:digit:]{1,3}$"
Colon_String <- "\\:\\d\\d"
#### clean input data ####
suppressWarnings(
data_1 <- as_lines_list_2 %>%
# stringr::str_replace_all(stats::setNames(replacement, typo)) %>% # moved to top 8/26
stringr::str_replace_all("\\*(\\d{1,})", replacement = "\\1") %>% # removes * placed in front of place number in ties
stringr::str_extract_all(
"\n\\s*\\d*\\s* \\*?[:alpha:].*|\n\\s*\\d* \\d*\\-[:alpha:].*|\n\\s*-{2,5}\\s* [:alpha:].*|\n\\s*\\d* \\d*\\-[:alpha:].*"
) %>%
.[purrr::map(., length) > 0] %>%
.[purrr::map(., stringr::str_length) > 50] %>%
.[purrr::map_lgl(., stringr::str_detect, paste0(Time_Score_String,"|DQ"))] %>% # must have \\.\\d\\d because all swimming and diving times do
# .[purrr::map_lgl(., stringr::str_detect, "\\.\\d\\d")] %>% # must have \\.\\d\\d because all swimming and diving times do
.[purrr::map_lgl(., stringr::str_detect, "[:alpha:]{2,}")] %>% # must have at least two letters in a row
.[purrr::map_lgl(., ~ !any(stringr::str_detect(., avoid)))] %>%
stringr::str_remove_all("\n") %>%
# trimws() %>%
stringr::str_replace_all(stats::setNames(replacement, typo)) %>% # moved to top of pipeline 8/26
stringr::str_replace_all("\\s*[&%]\\s*", " ") %>% # added 8/21 for removing "&" and "%" as record designator
# removed J etc. from next to swim, but does not remove X or x (for exhibition tracking)
stringr::str_replace_all("[A-WYZa-wyz]+(\\d{1,2}\\:\\d{2}\\.\\d{2})", "\\1") %>%
stringr::str_replace_all("(\\d{1,2}\\:\\d{2}\\.\\d{2})[A-WYZa-wyz]+", "\\1") %>%
stringr::str_replace_all("[A-WYZa-wyz]+(\\d{2,3}\\.\\d{2})", "\\1") %>%
stringr::str_replace_all("(\\d{2,3}\\.\\d{2})[A-WYZa-wyz]+", "\\1") %>%
stringr::str_replace_all(" [:punct:]+(\\d{1,2}\\:\\d{2}\\.\\d{2})", " \\1") %>%
stringr::str_replace_all("(\\d{1,2}\\:\\d{2}\\.\\d{2})[:punct:]+", " \\1") %>%
stringr::str_replace_all(" [:punct:]+(\\d{2,3}\\.\\d{2})", " \\1") %>%
stringr::str_replace_all("(\\d{2,3}\\.\\d{2})[:punct:]+", " \\1") %>%
# stringr::str_replace_all("(\\d{2,3}\\.\\d{2})[:punct:]+", "\\1 ") %>% should swap for line above 12/21 - need to test
stringr::str_remove_all("\\s{2}J\\s{2}") %>%
# remove 'A', 'B' etc. relay designators - should this go in typo instead?
stringr::str_replace_all(" \\'[A-Z]\\' ", " ") %>%
stringr::str_replace_all(" [A-Z] ", " ") %>%
stringr::str_replace_all("\\'\\'", " ") %>%
# remove q from next to time 10/21/2020
stringr::str_remove_all(" q ") %>% # removes " q " sometimes used to designate a qualifying time
stringr::str_replace_all("-{2,5}", "10000") %>% #8/26
stringr::str_replace_all("(\\.\\d{2})\\d+", "\\1 ") %>% # added 8/21 for illinois to deal with points column merging with final times column
stringr::str_replace_all("\\d{1,2} (\\d{1,})$", " \\1 ") %>% # added 8/21 for illinois to deal with points column merging with final times column
stringr::str_replace_all("\\*", "_") %>%
trimws()
)
#### splits data into variables by splitting at multiple (>= 2) spaces ####
data_1 <-
unlist(purrr::map(data_1, stringr::str_split, "\\s{2,}"),
recursive = FALSE)
#### breaks data into subsets based on how many variables it has ####
data_length_3 <- data_1[purrr::map(data_1, length) == 3]
data_length_4 <- data_1[purrr::map(data_1, length) == 4]
data_length_5 <- data_1[purrr::map(data_1, length) == 5]
data_length_6 <- data_1[purrr::map(data_1, length) == 6]
data_length_7 <- data_1[purrr::map(data_1, length) == 7]
# treatment of DQs new 8/19
suppressWarnings(DQ <-
data_1[stringr::str_detect(data_1, Time_Score_String, negate = TRUE) == TRUE])
DQ_length_3 <- DQ[purrr::map(DQ, length) == 3]
DQ_length_4 <- DQ[purrr::map(DQ, length) == 4]
#### seven variables ####
if (length(data_length_7) > 0) {
suppressWarnings(
df_7 <- data_length_7 %>%
list_transform() %>%
dplyr::mutate(
Place = dplyr::case_when(
stringr::str_detect(V1, "^[:digit:]*$") == TRUE ~ V1,
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 1]
)
) %>%
dplyr::mutate(
Name = dplyr::case_when(
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V1, "[:alpha:] [:alpha:]") == TRUE &
stringr::str_detect(V2, "^\\'[:upper:]\\'$") == FALSE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, ",") == TRUE ~ V2
)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_detect(V2, Age_String) == TRUE ~ V2,
stringr::str_detect(V2, "^SR |^JR |^SO |^FR |^[:digit:]{1,3} ") == TRUE ~ stringr::str_extract(V2, "^SR |^JR |^SO |^FR |^10 |^11 |^[:digit:]{1,2} "),
stringr::str_detect(V3, "^SR |^JR |^SO |^FR |^[:digit:]{1,3}\\s?") == TRUE ~ stringr::str_extract(V3, "^SR |^JR |^SO |^FR |^10 |^11 |^[:digit:]{1,2}\\s?"),
any(stringr::str_detect(V2, Age_String)) == FALSE &
any(stringr::str_detect(V3, Age_String)) == TRUE ~ V3
),
Age = trimws(Age),
) %>%
dplyr::mutate(
Team = dplyr::case_when(
stringr::str_detect(V1, Name) &
stringr::str_detect(V2, Age) &
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE ~ V3,
stringr::str_detect(V1, paste0("^", Place, "$")) == TRUE &
stringr::str_detect(V2, paste0("^", Name, "$")) == TRUE &
stringr::str_detect(V3, paste0("^", Age, "$")) == TRUE ~ V4,
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V1, "^[:digit:]*$") == FALSE &
stringr::str_detect(V1, "[:alpha:] [:alpha:]") == FALSE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V2, "^\\'[:upper:]\\'$") == TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V2, "^\\'[:upper:]\\'$") == FALSE &
stringr::str_detect(V1, "^[:digit:]*$") == FALSE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
TRUE ~ V3
)
) %>%
mutate(Team = str_remove(Team, Age),
Team = trimws(Team)
) %>%
# na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
# any(stringr::str_detect(V3, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE ~ V3,
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V5, Time_Score_Specials_String)) == TRUE ~ V4,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V6, Time_Score_Specials_String) == TRUE ~ V5,
any(stringr::str_detect(V4, "SEC")) == TRUE ~ V5
)
) %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
# any(stringr::str_detect(V3, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE ~ V4,
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V5, Time_Score_Specials_String)) == TRUE ~ V5,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V5,
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V6, Time_Score_Specials_String) == TRUE ~ V6,
any(stringr::str_detect(V4, "SEC")) == TRUE ~ V6
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time != V6 ~ V6,
Finals_Time == V6 ~ ""),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Place,
Name,
Age,
Team,
Prelims_Time,
Finals_Time,
Points,
Row_Numb = V7
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
DQ = case_when(str_detect(Finals_Time, "^DQ$") ~ 1,
TRUE ~ 0),
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = stringr::str_remove(Finals_Time, "J"),
Finals_Time = dplyr::case_when(
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) != TRUE ~ Finals_Time,
TRUE ~ Finals_Time
)) %>%
dplyr::mutate(
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Age, "[[:alpha:]]") == TRUE ~ Age,
is.na(Team) == FALSE &
stringr::str_detect(Age, "[[:alpha:]]") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:upper:]]\\'|^\\-?[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
TRUE ~ Team
),
Age = replace(Age, Age == Team, NA),
Team = dplyr::case_when(
stringr::str_length(Age) > 2 &
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, "\\.\\d") == FALSE ~ paste(Age, Team, sep = " "),
stringr::str_length(Age) <= 2 |
is.na(Age) == TRUE |
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == TRUE |
stringr::str_detect(Age, "\\.\\d") == TRUE ~ Team
),
Age = replace(Age, (
stringr::str_length(Age) > 2 & is.na(Age) == FALSE
), NA),
Age = dplyr::case_when(
stringr::str_detect(Age, "^\\-?[:upper:]$") == TRUE ~ "",
TRUE ~ Age
),
Name = replace(Name, Name == Team, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String)
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == FALSE ~ Team,
stringr::str_detect(Team, "^A$") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "^A$") == FALSE ~ Team
),
Team = stringr::str_remove(Team, "^SR |^JR |^SO |^FR |^10 |^11 |^12 |^9 |^8 |^7 "),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
)
# dplyr::mutate(DQ = 0)
)
} else {
df_7 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### six variables ####
if (length(data_length_6) > 0) {
suppressWarnings(
df_6 <- data_length_6 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Name = dplyr::case_when(
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, Name_String),
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, Name_String),
V1 == Place &
stringr::str_detect(V2, "[:digit:]") == FALSE ~ V2,
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
),
V1 = stringr::str_remove(V1, Place),
V1 = trimws(V1)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 2 &
stringr::str_detect(V2, "^SR |^JR |^SO |^FR |^[:digit:]{1,3} ") == TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
stringr::str_detect(V3, "^SR |^JR |^SO |^FR |^[:digit:]{1,3} ") == TRUE ~ stringr::str_split_fixed(V3, " ", n = 2)[, 1],
stringr::str_length(V2) <= 2 &
stringr::str_detect(V2, "[[:alpha:]\\.]") == FALSE ~ V2,
stringr::str_length(V2) <= 2 &
stringr::str_detect(V2, Age_String) == TRUE ~ V2,
stringr::str_length(V3) <= 2 &
stringr::str_detect(V3, Age_String) == TRUE ~ V3,
TRUE ~ ""
)
) %>%
dplyr::mutate(V3 = case_when(is.na(Age) == FALSE & str_detect(V3, paste0("^", Age, " ")) ==TRUE ~ str_remove(V3, paste0(Age, " ")),
TRUE ~ V3)) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V3 == Age ~ V4,
V2 == Age ~ V3,
any(stringr::str_detect(V3, "SEC")) == TRUE ~ stringr::str_remove(V1, Name),
is.na(Age) &
stringr::str_detect(V2, Time_Score_String) == FALSE &
stringr::str_detect(V2, Name) == FALSE &
stringr::str_detect(V2, "[:lower:]{1,}") == TRUE ~ V2,
is.na(Age) &
stringr::str_detect(V2, Time_Score_String) == FALSE &
stringr::str_detect(V2, Name) == FALSE &
stringr::str_detect(V2, "[:alpha:]{2,}") == TRUE ~ V2,
is.na(Age) &
stringr::str_detect(V2, Time_Score_String) == FALSE &
stringr::str_detect(V2, Name) == FALSE &
stringr::str_detect(V2, "[:lower:]{1,}") == FALSE ~ "",
is.na(Age) == TRUE &
stringr::str_detect(V2, Name) == TRUE &
stringr::str_detect(V3, "[:lower:]{2,}") == TRUE ~ V3,
is.na(Age) == FALSE &
stringr::str_detect(V2, Name) == TRUE &
stringr::str_detect(V3, "[:lower:]{1,}") == TRUE ~ V3,
is.na(Age) == TRUE &
stringr::str_detect(V2, Name) == TRUE &
stringr::str_detect(V3, "[:lower:]{1,}") == FALSE ~ V2,
is.na(Age) == TRUE &
stringr::str_detect(V2, Name) == TRUE ~ V3,
is.na(Age) == FALSE &
stringr::str_detect(V2, Name) == TRUE ~ V3,
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
)
) %>%
### df_6 cannot have NT as time string since there are some schools called NT ###
dplyr::mutate(
Prelims_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE & # new 8/18
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V2,
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V4, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ "",
TRUE ~ V3
)
) %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE & # new 8/18
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V5,
TRUE ~ V4
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time == V5 ~ "",
# Finals_Time == V4 ~ V5
TRUE ~ V5),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Points,
Row_Numb = V6
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = dplyr::case_when(
Place >= 1 &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
Place >= 1 &
is.na(Finals_Time) != TRUE ~ Finals_Time
),
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Age, "[[:alpha:]]") == TRUE ~ Age,
is.na(Team) == FALSE &
stringr::str_detect(Age, "[[:alpha:]]") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Age = replace(Age, Age == Team, NA),
Team = dplyr::case_when(
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, Time_Score_String) == FALSE &
stringr::str_detect(Age, "\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE &
Age != Team ~ paste(Age, Team, sep = " "),
TRUE ~ Team
),
Age = replace(Age, (
stringr::str_length(Age) > 2 & is.na(Age) == FALSE
), NA),
Name = replace(Name, Name == Team, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String),
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Team = dplyr::case_when(
stringr::str_detect(Team, Time_Score_String) == TRUE ~ stringr::str_extract(Team, "[:alpha:]*"),
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == FALSE ~ Team,
stringr::str_detect(Team, "^\\-?[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
# stringr::str_detect(Team, "^-[:upper:]$") == TRUE &
# is.na(Name) == FALSE ~ Name,
TRUE ~ Team),
Team = stringr::str_remove(
Team,
"^[:digit:]{1,2}\\s"
)) %>%
dplyr::mutate(
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
) %>%
dplyr::mutate(DQ = 0)
)
} else {
df_6 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### five variables ####
if (length(data_length_5) > 0) {
suppressWarnings(
df_5 <- data_length_5 %>%
list_transform() %>%
dplyr::mutate(Place = dplyr::case_when(stringr::str_detect(V1, "^\\d{1,}$") ~ V1,
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 1])) %>%
dplyr::mutate(
Name = dplyr::case_when(
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, Name_String),
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, Name_String),
stringr::str_detect(V2, ",") == FALSE & V1 == Place & stringr::str_detect(V3, Time_Score_Specials_String) == FALSE ~ stringr::str_extract(V2, Name_String),
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, Time_Score_String) == TRUE ~ "",
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
)
) %>%
na_if_character("") %>%
dplyr::mutate(
V1 = dplyr::case_when(
is.na(Place) == FALSE ~ stringr::str_remove(V1, Place),
TRUE ~ V1
),
V1 = dplyr::case_when(
is.na(Name) == FALSE ~ stringr::str_remove(V1, Name),
TRUE ~ V1
),
V1 = trimws(V1),
Name = trimws(Name)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(V2) <= 3 &
stringr::str_detect(V2, "^SR|^JR|^SO|^FR|^\\d{1,3}$") == TRUE ~ V2,
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 3 &
stringr::str_detect(V2, "SR|JR|SO|FR|^\\d{1,3} ") ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
stringr::str_length(stringr::str_split_fixed(V3, " ", n = 2)[, 1]) <= 3 &
stringr::str_detect(V3, "SR|JR|SO|FR|^\\d{1,3} ") ~ stringr::str_split_fixed(V3, " ", n = 2)[, 1],
TRUE ~ ""
)) %>%
na_if_character("") %>%
dplyr::mutate(
Age = trimws(Age),
V3 = case_when(is.na(Age) == FALSE & stringr::str_detect(V3, Age) == TRUE & stringr::str_detect(V3, Time_Score_Specials_String) == FALSE & Age != "" ~ stringr::str_remove(V3, Age),
TRUE ~ V3),
V2 = case_when(is.na(Age) == FALSE & stringr::str_detect(V2, Age) == TRUE & stringr::str_detect(V2, Time_Score_Specials_String) == FALSE & Age != "" ~ stringr::str_remove(V2, Age),
TRUE ~ V2),
V2 = trimws(V2),
V3 = trimws(V3)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V2 == Name & str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
is.na(V2) & is.na(Name) == FALSE & str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == FALSE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == TRUE ~ V1,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|^\\'\\'$") == FALSE &
stringr::str_detect(V2, Time_Score_Specials_String) == FALSE ~ V2,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|'[:upper:]'|^\\'\\'$") == TRUE &
(V1 != Name | is.na(Name)) ~ V1,
(V1 == Name |
is.na(Name)) &
V2 != Age ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE ~ V1,
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
),
Team = dplyr::case_when(
stringr::str_detect(Team, Age) == TRUE &
is.na(Team) == FALSE ~ stringr::str_remove(Team, Age),
TRUE ~ Team
),
Team = trimws(Team)
) %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V2,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ "",
TRUE ~ V2
)
) %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
TRUE ~ V3
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time == V3 ~ V4,
Finals_Time == V4 ~ "",
TRUE ~ ""),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Points,
Row_Numb = V5
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
DQ = case_when(str_detect(Finals_Time, "^DQ$") ~ 1,
TRUE ~ 0)
) %>%
### dealing with exhibition times 8/18/2020
dplyr::mutate(
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String), # added 11/6
) %>%
na_if_character("") %>%
dplyr::mutate(
Finals_Time = replace(Finals_Time, dplyr::n_distinct(Finals_Time) <= 2, ""),
Prelims_Time = replace(Prelims_Time, dplyr::n_distinct(Prelims_Time) <= 2, "")
) %>%
na_if_character("") %>%
na_if_character("''") %>%
# dplyr::mutate(
# Finals_Time = dplyr::case_when(
# sum(stringr::str_detect(Finals_Time, Time_Score_String)) >= 1 ~ stringr::str_remove(Finals_Time, "NT"),
# sum(stringr::str_detect(Finals_Time, Time_Score_String)) < 1 ~ Finals_Time,
# TRUE ~ Finals_Time
# )
# ) %>%
na_if_character("") %>% # good 11/9
dplyr::mutate(
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Finals_Time, Time_Score_String) == FALSE ~ Finals_Time,
is.na(Team) == FALSE |
stringr::str_detect(Finals_Time, Time_Score_String) == TRUE ~ Team
),
Finals_Time = replace(
Finals_Time,
stringr::str_detect(Finals_Time, "^NT$") == TRUE,
NA
), # okay 11/9
Finals_Time = replace(Finals_Time, Team == Finals_Time, NA),
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA), # okay 11/9
Finals_Time = dplyr::case_when(
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) != TRUE ~ Finals_Time,
TRUE ~ Finals_Time
),
# ### dealing with exhibition times 8/18/2020
# Exhibition = dplyr::case_when(
# stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
# TRUE ~ 0
# ),
# ###
# Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
# Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String), # added 11/6
) %>%
# na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Points_2 = dplyr::case_when(
stringr::str_detect(Points, Colon_String) == TRUE ~ "",
as.numeric(Points) > 20 &
stringr::str_detect(Points, Time_Score_String) == TRUE ~ "",
stringr::str_detect(Points, Colon_String) == FALSE ~ Points
),
Prelims_Time = dplyr::case_when(
stringr::str_detect(Points, Colon_String) == TRUE ~ Finals_Time,
as.numeric(Points) > 20 &
stringr::str_detect(Points, Time_Score_String) == TRUE ~ Finals_Time,
TRUE ~ Prelims_Time
),
Finals_Time = dplyr::case_when(
stringr::str_detect(Points, Colon_String) == TRUE ~ Points,
as.numeric(Points) > 20 &
stringr::str_detect(Points, Time_Score_String) == TRUE ~ Points,
TRUE ~ Finals_Time
)
) %>%
na_if_character("") %>%
dplyr::mutate(
Points = dplyr::case_when(
is.na(Points_2) == FALSE ~ Points_2,
Points == Finals_Time ~ "",
TRUE ~ Points
),
Points_2 = NULL,
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String),
Prelims_Time = replace(
Prelims_Time,
stringr::str_detect(Prelims_Time, Time_Score_String) == FALSE,
NA
)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = replace(Team, stringr::str_detect(Team, "\\.\\d") == TRUE, NA),
Team = dplyr::case_when(
is.na(Team) == TRUE &
Age %!in% c(
"FR",
"SO",
"JR",
"SR",
"7",
"8",
"05",
"06",
"07",
"08",
"09",
as.character(seq(10, 25, 1))
) &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, "\\.\\d") == FALSE ~ Age,
is.na(Team) == FALSE |
Age %in% c(
"FR",
"SO",
"JR",
"SR",
"7",
"8",
"05",
"06",
"07",
"08",
"09",
as.character(seq(10, 25, 1))
) |
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == TRUE |
stringr::str_detect(Age, "\\.\\d") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Team = dplyr::case_when(
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'|\\.?\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE &
Age != Team ~ paste(Age, Team, sep = " "),
TRUE ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:upper:]]\\'|^\\-?[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
TRUE ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, Time_Score_String) == TRUE ~ stringr::str_extract(Team, "[:alpha:]*"),
TRUE ~ Team
),
Age = replace(Age, Age == Team, NA),
Age = replace(Age, stringr::str_detect(Age, Time_Score_String) == TRUE, NA),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA),
Age = replace(Age, is.na(Name) == TRUE &
is.na(Team) == FALSE, NA),
Age = replace(Age, Age == Team, NA),
Age = replace(Age, (
stringr::str_length(Age) > 2 & is.na(Age) == FALSE
), NA)
)
# dplyr::mutate(DQ = 0)
)
} else {
df_5 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### four variables ####
if (length(data_length_4) > 0) {
suppressWarnings(
df_4 <- data_length_4 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Name = dplyr::case_when(
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, Name_String),
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == FALSE ~ "",
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, Name_String),
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, Time_Score_String) == TRUE ~ "",
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
)
) %>%
na_if_character("") %>%
dplyr::mutate(
V1 = dplyr::case_when(
is.na(Place) == FALSE ~ stringr::str_remove(V1, Place),
TRUE ~ V1
),
V1 = dplyr::case_when(
is.na(Name) == FALSE ~ stringr::str_remove(V1, Name),
TRUE ~ V1
),
V1 = trimws(V1),
Name = trimws(Name)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 2 &
stringr::str_detect(V2, "SR|JR|SO|FR|12|11|10|9|8|7|^\\d\\d ") ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
TRUE ~ ""
),
Age = trimws(Age)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == FALSE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == TRUE ~ V1,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) & # added DQ to string 11/9
stringr::str_detect(V2, "^'[:upper:]'$|^[:upper:]$|^\\'\\'$") == FALSE &
stringr::str_detect(V2, Time_Score_Specials_String) == FALSE ~ V2,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) & # added DQ to string 11/9
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|'[:upper:]'|^\\'\\'$") == TRUE &
(V1 != Name | is.na(Name)) ~ V1,
(V1 == Name |
is.na(Name)) &
V2 != Age ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE ~ V1, # added DQ to string 11/9
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
),
Team = dplyr::case_when(
stringr::str_detect(Team, Age) == TRUE &
is.na(Team) == FALSE ~ stringr::str_remove(Team, Age),
TRUE ~ Team
),
Team = trimws(Team)
) %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V2,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ "",
TRUE ~ ""
)
) %>%
na_if_character("") %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
TRUE ~ V3
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time == V3 ~ V4,
Finals_Time == V4 ~ "",
TRUE ~ ""),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Row_Numb = V4
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
DQ = case_when(str_detect(Finals_Time, "^DQ$") ~ 1,
TRUE ~ 0),
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = dplyr::case_when(
Place >= 1 &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
Place >= 1 &
is.na(Finals_Time) != TRUE ~ Finals_Time
)
) %>%
dplyr::mutate(
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Age, "[[:alpha:]]") == TRUE &
stringr::str_length(Age) > 1 ~ Age,
is.na(Team) == FALSE &
stringr::str_detect(Age, "[[:alpha:]]") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
)
) %>%
dplyr::mutate(
Age = replace(Age, Age == Team, NA),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
) %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
is.na(Name) == TRUE &
stringr::str_detect(Age, Time_Score_String) == TRUE ~ Age,
TRUE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Age = replace(Age, is.na(Name) == TRUE &
is.na(Team) == FALSE, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String)
) %>%
dplyr::mutate(
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String)
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Age = replace(Age, Age == Team, NA),
Team = dplyr::case_when(
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, Time_Score_String) == FALSE &
stringr::str_detect(Age, "\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE &
Age != Team ~ paste(Age, Team, sep = " "),
TRUE ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:upper:]]\\'") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "^[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "^[:upper:]$") == FALSE |
is.na(Name) == TRUE ~ Team
),
Age = replace(
Age,
(
stringr::str_detect(Age, "\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE
),
NA
),
Age = dplyr::case_when(
stringr::str_detect(Name, "\\.d{1,3}") == TRUE ~ stringr::str_extract(Name, "\\d{1,3}"),
stringr::str_detect(Name, "\\.d{1,3}") == FALSE ~ Age
),
Name = stringr::str_remove(Name, "\\d{1,3}"),
Prelims_Time = dplyr::case_when(
is.na(Prelims_Time) == TRUE &
stringr::str_detect(Team, "\\.") == TRUE ~ stringr::str_extract(
Team,
"[:digit:]*[:punct:]?[:digit:]*[:punct:]?[:digit:]*"
),
is.na(Prelims_Time) == FALSE |
stringr::str_detect(Team, "\\.") == FALSE ~ Prelims_Time
),
Team = stringr::str_remove(Team, "-[:alpha:]*\\d.*$"),
Team = stringr::str_remove(
Team,
"^[:digit:]{1,2}\\s")
) %>%
na_if_character("") %>%
dplyr::mutate(
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
)
# dplyr::mutate(DQ = 0)
)
} else {
df_4 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### three variables ####
if (length(data_length_3) > 0) {
suppressWarnings(
df_3 <- data_length_3 %>%
list_transform() %>%
dplyr::mutate(
Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1],
Name = stringr::str_split_fixed(V1, " ", n = 2)[, 2],
Age = as.character(NA),
Team = as.character(NA),
Finals_Time = V2,
Prelims_Time = as.character(NA),
) %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Row_Numb = V3
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = dplyr::case_when(
Place >= 1 &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
Place >= 1 &
is.na(Finals_Time) != TRUE ~ Finals_Time
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA),
Prelims_Time = dplyr::case_when(
is.na(Name) == TRUE ~ Age,
is.na(Name) == FALSE ~ Prelims_Time
),
Age = replace(Age, is.na(Name) == TRUE &
is.na(Team) == FALSE, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String)
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(DQ = 0)
)
} else {
df_3 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### DQ data ####
#### DQ 4 ####
if (length(DQ_length_4) > 0) {
suppressWarnings(
df_DQ_4 <- DQ_length_4 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Name = dplyr::case_when(
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, "_?[:alpha:]+'?[:alpha:]+, [:alpha:]+\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?"),
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == FALSE ~ "",
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, "_?[:alpha:]+'?[:alpha:]+, [:alpha:]+\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?"),
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, Time_Score_String) == TRUE ~ "",
# stringr::str_detect(V2, Time_Score_Special_String) == TRUE ~ "",
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
)
) %>%
na_if_character("") %>%
dplyr::mutate(
V1 = dplyr::case_when(
is.na(Place) == FALSE ~ stringr::str_remove(V1, Place),
TRUE ~ V1
),
V1 = dplyr::case_when(
is.na(Name) == FALSE ~ stringr::str_remove(V1, Name),
TRUE ~ V1
),
V1 = trimws(V1),
Name = trimws(Name)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 3 &
stringr::str_detect(V2, "SR|JR|SO|FR|12|11|10|9|8|7|^\\d{1,3} ") ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
TRUE ~ ""
),
Age = trimws(Age)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == FALSE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == TRUE ~ V1,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|^\\'\\'$") == FALSE &
stringr::str_detect(V2, Time_Score_String) == FALSE ~ V2,
(is.na(V1) == TRUE & stringr::str_detect(V3, Time_Score_Specials_String) == TRUE & stringr::str_detect(V2, "\\d") == FALSE) ~ V2,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|'[:upper:]'|^\\'\\'$") == TRUE &
(V1 != Name | is.na(Name)) ~ V1,
(V1 == Name |
is.na(Name)) &
V2 != Age ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE ~ V1,
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
),
Team = dplyr::case_when(
stringr::str_detect(Team, Age) == TRUE &
is.na(Team) == FALSE ~ stringr::str_remove(Team, Age),
TRUE ~ Team
),
Team = trimws(Team)
) %>%
na_if_character("") %>%
dplyr::select(Name,
Place,
Age,
Team,
Row_Numb = V4) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(DQ = 1)
)
} else {
df_DQ_4 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### DQ 3 ####
if (length(DQ_length_3) > 0) {
suppressWarnings(
df_DQ_3 <- DQ_length_3 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Team = stringr::str_split_fixed(V1, " ", n = 2)[, 2],
Team = trimws(Team)
) %>%
na_if_character("") %>%
dplyr::select(Place,
Team,
Row_Numb = V3) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(DQ = 1)
)
} else {
df_DQ_3 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### Rejoin dataframes from each number of variables ####
Min_Row_Numb <- min(events$Event_Row_Min)
suppressWarnings(
# data <- dplyr::full_join(df_7, df_6) %>%
# dplyr::full_join(df_5) %>%
# dplyr::full_join(df_4) %>%
# dplyr::full_join(df_3) %>%
# dplyr::left_join(df_DQ_4) %>%
# dplyr::left_join(df_DQ_3) %>%
data <- dplyr::bind_rows(df_7, df_6) %>%
dplyr::bind_rows(df_5) %>%
dplyr::bind_rows(df_4) %>%
dplyr::bind_rows(df_3) %>%
dplyr::left_join(df_DQ_4) %>%
dplyr::left_join(df_DQ_3) %>%
dplyr::mutate(Row_Numb = as.numeric(Row_Numb)) %>%
dplyr::arrange(Row_Numb) %>%
### moved up from below for DQ work 8/20
dplyr::mutate(DQ = dplyr::case_when(Place == 10000 & Exhibition == 0 ~ 1, # added exhibition condition 8/27
TRUE ~ DQ)) %>%
na_if_numeric(10000) %>%
dplyr::mutate(dplyr::across(c(Name, Team), ~ stringr::str_replace_all(., "10000", "--"))) %>% # remove any "10000"s added in erroniuously
####
dplyr::mutate(
Place = as.numeric(Place),
Place = dplyr::case_when(
is.na(dplyr::lag(Place)) == TRUE ~ Place,
dplyr::lag(Place) == Place ~ Place + 0.1,
dplyr::lag(Place) != Place ~ Place
),
Place = as.character(Place),
Row_Numb = as.numeric(Row_Numb)
) %>%
dplyr::filter(Row_Numb >= Min_Row_Numb)
)
if("Points" %in% names(data) == FALSE)
{data$Points <- NA}
#### add in events based on row number ranges ####
data <-
transform(data, Event = events$Event[findInterval(Row_Numb, events$Event_Row_Min)])
#### cleaning up final results ####
suppressWarnings(
data <- data %>%
dplyr::mutate(
Name = stringr::str_replace(Name, "_", "\\*"),
Prelims_Time = replace(
Prelims_Time,
stringr::str_detect(Prelims_Time, "\\.") == FALSE,
NA
),
Prelims_Time = replace(
Prelims_Time,
(stringr::str_detect(Prelims_Time, "\\.") == TRUE &
stringr::str_detect(Prelims_Time, "\\:") == FALSE &
as.numeric(Prelims_Time) < 15
),
NA
),
Points = replace(
Points,
stringr::str_detect(Points, "[[:alpha:]]") == TRUE,
NA
),
Points = replace(
Points,
stringr::str_detect(Points, "[^[:digit:]|\\.]"),
NA
),
Place = round(as.numeric(Place)),
Event = as.character(Event)
) %>%
dplyr::mutate(
Place = dplyr::case_when(is.na(Place) == TRUE &
DQ == 0 ~ lag(Place) + 1,
TRUE ~ Place)
) %>%
### added 8/20 as part of DQ, to remove records and such but not DQ results
dplyr::filter(
DQ == 0 &
stringr::str_detect(Finals_Time, Time_Score_String) == TRUE |
DQ == 0 & stringr::str_detect(Prelims_Time, Time_Score_String) == TRUE | DQ == 1
) %>%
dplyr::mutate(Exhibition = dplyr::case_when(is.na(Exhibition) == TRUE ~ 0,
TRUE ~ Exhibition)) %>%
dplyr::mutate(Finals_Time = dplyr::case_when(DQ == 1 ~ "NA",
TRUE ~ Finals_Time)) %>%
na_if_character("NA")
)
#### adding relay swimmers in ####
if (relay_swimmers == TRUE) {
relay_swimmers_df <- collect_relay_swimmers_old(as_lines_list_2, typo_2 = typo, replacement_2 = replacement)
data <- data %>%
dplyr::left_join(relay_swimmers_df, by = 'Row_Numb')
}
#### adding splits back in ####
if (splits == TRUE) {
splits_df <- splits_parse(as_lines_list_2, split_len = split_length)
if (any(str_detect(data$Event, "Relay")) == TRUE) {
relay_row <- data %>%
dplyr::filter(stringr::str_detect(Event, "Relay")) %>%
head(1) %>%
dplyr::select(Row_Numb) %>%
dplyr::pull()
relay_offset <-
ifelse(stringr::str_detect(as_lines_list_2[relay_row + 2], "\\d\\d\\.\\d\\d") == TRUE,
1,
2)
data <- data %>%
dplyr::mutate(
Row_Numb = dplyr::case_when(
stringr::str_detect(Event, "Relay") == TRUE ~ Row_Numb + relay_offset,
TRUE ~ Row_Numb
)
) %>%
dplyr::left_join(splits_df, by = 'Row_Numb')
} else {
data <- data %>%
dplyr::left_join(splits_df, by = 'Row_Numb')
}
### remove empty columns (all values are NA) ###
data <- Filter(function(x)
!all(is.na(x)), data)
}
#### if there is a Place column it should be first ####
if("Place" %in% names(data)){
data <- data %>%
dplyr::select(Place, dplyr::everything())
}
data$Row_Numb <- NULL
message("Beginning with version 0.6.0 the Grade and School output columns have been renamed Age and Team respectively. Please adjust your work flows as needed.")
return(data)
} else if (stringr::str_detect(file[1], "^A107") == TRUE) {
# file <- add_row_numbers(text = file)
data <- hy3_parse(file = file)
return(data)
}
}
gpilgrim2670/SwimmeR documentation built on March 26, 2023, 5:05 p.m.
R Package Documentation
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Defines functions swim_parse_old
Documented in swim_parse_old
#' Formats swimming and diving data read with \code{read_results} into a data
#' frame
#'
#' Takes the output of \code{read_results} and cleans it, yielding a data frame
#' of swimming (and diving) results. Old version, retired in dev build on Dec
#' 21, 2020 and release version 0.7.0
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr lead
#' @importFrom dplyr lag
#' @importFrom dplyr case_when
#' @importFrom dplyr na_if
#' @importFrom dplyr select
#' @importFrom dplyr coalesce
#' @importFrom dplyr arrange
#' @importFrom dplyr filter
#' @importFrom dplyr full_join
#' @importFrom dplyr n_distinct
#' @importFrom dplyr bind_rows
#' @importFrom dplyr everything
#' @importFrom dplyr group_by
#' @importFrom dplyr ungroup
#' @importFrom dplyr pull
#' @importFrom dplyr between
#' @importFrom stringr str_replace
#' @importFrom stringr str_replace_all
#' @importFrom stringr str_extract
#' @importFrom stringr str_extract_all
#' @importFrom stringr str_split
#' @importFrom stringr str_split_fixed
#' @importFrom stringr str_detect
#' @importFrom stringr str_length
#' @importFrom purrr map_lgl
#' @importFrom purrr map
#' @importFrom stats setNames
#'
#' @param file output from \code{read_results}
#' @param avoid a list of strings. Rows in \code{file} containing these strings
#' will not be included. For example "Pool:", often used to label pool
#' records, could be passed to \code{avoid}. The default is
#' \code{avoid_default}, which contains many strings similar to "Pool:", such
#' as "STATE:" and "Qual:". Users can supply their own lists to \code{avoid}.
#' @param typo a list of strings that are typos in the original results.
#' \code{swim_parse_old} 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
#' \code{typo}. Unexpected commas as also an issue, for example "Texas,
#' University of" should be fixed using \code{typo} and \code{replacement}
#' @param replacement a list of fixes for the strings in \code{typo}. Here one
#' could pass "Central High School" (one space between "Central" and "High")
#' and "Texas" to \code{replacement} fix the issues described in \code{typo}
#' @param splits either \code{TRUE} or the default, \code{FALSE} - should
#' \code{swim_parse_old} attempt to include splits.
#' @param split_length either \code{25} or the default, \code{50}, the length of
#' pool at which splits are recorded. Not all results are internally
#' consistent on this issue - some have races with splits by 50 and other
#' races with splits by 25.
#' @param relay_swimmers either \code{TRUE} or the default, \code{FALSE} -
#' should relay swimmers be reported. Relay swimmers are reported in separate
#' columns named \code{Relay_Swimmer_1} etc.
#' @return returns a data frame with columns \code{Name}, \code{Place},
#' \code{Age}, \code{Team}, \code{Prelims_Time}, \code{Finals_Time},
#' \code{Points}, \code{Event} & \code{DQ}. Note all swims will have a
#' \code{Finals_Time}, even if that time was actually swam in the prelims
#' (i.e. a swimmer did not qualify for finals). This is so that final results
#' for an event can be generated from just one column.
#'
#' @examples \dontrun{
#' swim_parse_old(
#' read_results("http://www.nyhsswim.com/Results/Boys/2008/NYS/Single.htm", node = "pre"),
#' typo = c("-1NORTH ROCKL"), replacement = c("1-NORTH ROCKL"),
#' splits = TRUE,
#' relay_swimmers = TRUE)
#' }
#' \dontrun{
#' swim_parse_old(read_results("inst/extdata/Texas-Florida-Indiana.pdf"),
#' typo = c("Indiana University", ", University of"), replacement = c("Indiana University", ""),
#' splits = TRUE,
#' relay_swimmers = TRUE)
#' }
#' @seealso \code{swim_parse_old} must be run on the output of
#' \code{\link{read_results}}
#'
swim_parse_old <-
function(file,
avoid = avoid_default,
typo = typo_default,
replacement = replacement_default,
splits = FALSE,
split_length = 50,
relay_swimmers = FALSE) {
#### default typo and replacement strings ####
typo_default <- c("typo")
replacement_default <- c("typo")
if(length(typo) != length(replacement)) {
stop("typo and replacement must have the same number of elements (be the same length)")
}
if(is.logical(splits) == FALSE) {
stop("splits must be logical, either TRUE or FALSE")
}
if(is.numeric(split_length) == FALSE) {
stop("split_length must be numeric, usually 50 or 25")
}
if(is.logical(relay_swimmers) == FALSE) {
stop("relay_swimmers must be logical, either TRUE or FALSE")
}
#### strings that if a line begins with one of them the line is ignored ####
avoid_default <-
c(
"Record",
"RECORD",
"^\\s*Public\\:",
"^\\s*NYSPHSAA",
"^\\s*NYSPHAA",
"^\\s*State:",
"^\\s*States:",
"^\\s*STATE:",
"^\\s*STATES:",
"\\d\\:\\s",
"^\\s*Finals",
"^\\s*Prelims",
"^\\s*Section\\:",
"^\\s*SECTION\\:",
"^\\s*Section [:alpha:]{1,2}\\:",
"^\\s*SECTION [:alpha:]{1,2}\\:",
"^\\s*Sectional\\:",
"^\\s*Sectionals\\:",
"^\\s*Hosted",
"^\\s*Meet",
"^\\s*MEET",
"^\\s*Points",
"^\\s*Rec\\.?\\:",
"^\\s*REC\\.?\\:",
"\\sRec\\.?\\:\\s",
"^\\s*Rcd\\:",
"^\\s*Cty\\:",
"^\\s*League",
"^\\s*League Rec\\.?\\:",
"^\\s*LEAGUE",
"^\\s*IAC\\:",
"^\\s*AA\\:",
"^\\s*AAA\\:",
"^\\s*AAC\\:",
"^\\s*Con\\.\\:",
"^\\s*Auto\\:",
"^\\s*Auto\\.\\:",
"^\\s*Cons\\.\\:",
"^\\s*Eastern\\:",
"^\\s*Class [[:alpha:]]\\:",
"^\\s*CLASS [[:alpha:]]\\:",
"^\\s*Class '[[:alpha:]]'\\:",
"^\\s*Pool\\:",
"^\\s*POOL\\:",
"^\\s*\\'A\\'\\:",
"^\\s*Nassau\\:",
"^\\s*CONS\\:",
"^\\s*CONS\\.\\:",
"^\\s*Qual\\.\\:",
"^\\s*QUAL\\.\\:",
"^\\s*Qual\\:",
"^\\s*QUAL\\:",
"^\\s*Qual\\.\\:",
"^\\s*Qualify\\:",
"^\\s*QUALIFY\\:",
"QUALIFY\\:",
"^\\s*School\\:",
"^\\s*SCHOOL\\:",
"^\\s*School\\s*Prelims\\s*Finals",
"^\\s*NFL\\:",
"^\\s*NYS\\:",
"^\\s*FED\\:",
"^\\s*Sectio\\:",
"^\\s*Sect\\:",
"^\\s*SECT\\:",
"^\\s*Sec\\:",
"^\\s*SEC\\:",
"^\\s*CHS\\:",
"^\\s*Chs\\:",
"^\\s*Large\\:",
"^\\s*Small\\:",
"^\\s*r\\:",
"National\\:",
"Meet\\:",
"NCAA\\:"
)
#### define avoid_minimal ####
avoid_minimal <- c("^\\s{1,}r\\:")
#### assign row numbers ####
as_lines_list_2 <- add_row_numbers(text = file)
# stringr::str_remove_all("\n") %>%
# # trimws() %>%
# stringr::str_replace_all(stats::setNames(replacement, typo))
#### parsing html and pdf files ####
if (stringr::str_detect(file[1], "^A107") == FALSE) {
#### Pulls out event labels from text ####
events <- event_parse(as_lines_list_2)
#### set up strings ####
# Name_String <- "_?[:alpha:]+'?[:alpha:]+\\s?[:alpha:]*\\s?[:alpha:]*,\\s?[:alpha:]*\\s?[:alpha:]*,? [:alpha:]+\\s?[:alpha:\\-\\']*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
# Name_String <- "_?[:alpha:]+'?[:alpha:]+\\s?[:alpha:]*\\s?[:alpha:]*,\\s?[:alpha:]*\\s?[:alpha:]*,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
# Name_String <- "_?[:alpha:]+'?[:alpha:\\-\\'\\.]+\\s?[:alpha:]*\\s?[:alpha:]*,\\s?[:alpha:]*\\s?[:alpha:]*,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
# Name_String <- "_?[:alpha:]+\\s?\\'?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*,?\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:]*\\.?,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
Name_String <-
"_?[:alpha:]+\\s?\\'?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\'\\.]*,?\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:]*\\.?,? [:alpha:]+\\s?[:alpha:\\-\\'\\.]*\\s?[:alpha:\\-\\']*\\s?[:alpha:]*\\s?[:alpha:]*\\s?[:alpha:\\.]*"
Time_Score_String <- "\\d{0,2}\\:?\\d{1,3}\\.\\d{2}"
Time_Score_Specials_String <- paste0(Time_Score_String, "|^NT$|^NP$|^DQ$")
Age_String <- "^SR$|^JR$|^SO$|^FR$|^[:digit:]{1,3}$"
Colon_String <- "\\:\\d\\d"
#### clean input data ####
suppressWarnings(
data_1 <- as_lines_list_2 %>%
# stringr::str_replace_all(stats::setNames(replacement, typo)) %>% # moved to top 8/26
stringr::str_replace_all("\\*(\\d{1,})", replacement = "\\1") %>% # removes * placed in front of place number in ties
stringr::str_extract_all(
"\n\\s*\\d*\\s* \\*?[:alpha:].*|\n\\s*\\d* \\d*\\-[:alpha:].*|\n\\s*-{2,5}\\s* [:alpha:].*|\n\\s*\\d* \\d*\\-[:alpha:].*"
) %>%
.[purrr::map(., length) > 0] %>%
.[purrr::map(., stringr::str_length) > 50] %>%
.[purrr::map_lgl(., stringr::str_detect, paste0(Time_Score_String,"|DQ"))] %>% # must have \\.\\d\\d because all swimming and diving times do
# .[purrr::map_lgl(., stringr::str_detect, "\\.\\d\\d")] %>% # must have \\.\\d\\d because all swimming and diving times do
.[purrr::map_lgl(., stringr::str_detect, "[:alpha:]{2,}")] %>% # must have at least two letters in a row
.[purrr::map_lgl(., ~ !any(stringr::str_detect(., avoid)))] %>%
stringr::str_remove_all("\n") %>%
# trimws() %>%
stringr::str_replace_all(stats::setNames(replacement, typo)) %>% # moved to top of pipeline 8/26
stringr::str_replace_all("\\s*[&%]\\s*", " ") %>% # added 8/21 for removing "&" and "%" as record designator
# removed J etc. from next to swim, but does not remove X or x (for exhibition tracking)
stringr::str_replace_all("[A-WYZa-wyz]+(\\d{1,2}\\:\\d{2}\\.\\d{2})", "\\1") %>%
stringr::str_replace_all("(\\d{1,2}\\:\\d{2}\\.\\d{2})[A-WYZa-wyz]+", "\\1") %>%
stringr::str_replace_all("[A-WYZa-wyz]+(\\d{2,3}\\.\\d{2})", "\\1") %>%
stringr::str_replace_all("(\\d{2,3}\\.\\d{2})[A-WYZa-wyz]+", "\\1") %>%
stringr::str_replace_all(" [:punct:]+(\\d{1,2}\\:\\d{2}\\.\\d{2})", " \\1") %>%
stringr::str_replace_all("(\\d{1,2}\\:\\d{2}\\.\\d{2})[:punct:]+", " \\1") %>%
stringr::str_replace_all(" [:punct:]+(\\d{2,3}\\.\\d{2})", " \\1") %>%
stringr::str_replace_all("(\\d{2,3}\\.\\d{2})[:punct:]+", " \\1") %>%
# stringr::str_replace_all("(\\d{2,3}\\.\\d{2})[:punct:]+", "\\1 ") %>% should swap for line above 12/21 - need to test
stringr::str_remove_all("\\s{2}J\\s{2}") %>%
# remove 'A', 'B' etc. relay designators - should this go in typo instead?
stringr::str_replace_all(" \\'[A-Z]\\' ", " ") %>%
stringr::str_replace_all(" [A-Z] ", " ") %>%
stringr::str_replace_all("\\'\\'", " ") %>%
# remove q from next to time 10/21/2020
stringr::str_remove_all(" q ") %>% # removes " q " sometimes used to designate a qualifying time
stringr::str_replace_all("-{2,5}", "10000") %>% #8/26
stringr::str_replace_all("(\\.\\d{2})\\d+", "\\1 ") %>% # added 8/21 for illinois to deal with points column merging with final times column
stringr::str_replace_all("\\d{1,2} (\\d{1,})$", " \\1 ") %>% # added 8/21 for illinois to deal with points column merging with final times column
stringr::str_replace_all("\\*", "_") %>%
trimws()
)
#### splits data into variables by splitting at multiple (>= 2) spaces ####
data_1 <-
unlist(purrr::map(data_1, stringr::str_split, "\\s{2,}"),
recursive = FALSE)
#### breaks data into subsets based on how many variables it has ####
data_length_3 <- data_1[purrr::map(data_1, length) == 3]
data_length_4 <- data_1[purrr::map(data_1, length) == 4]
data_length_5 <- data_1[purrr::map(data_1, length) == 5]
data_length_6 <- data_1[purrr::map(data_1, length) == 6]
data_length_7 <- data_1[purrr::map(data_1, length) == 7]
# treatment of DQs new 8/19
suppressWarnings(DQ <-
data_1[stringr::str_detect(data_1, Time_Score_String, negate = TRUE) == TRUE])
DQ_length_3 <- DQ[purrr::map(DQ, length) == 3]
DQ_length_4 <- DQ[purrr::map(DQ, length) == 4]
#### seven variables ####
if (length(data_length_7) > 0) {
suppressWarnings(
df_7 <- data_length_7 %>%
list_transform() %>%
dplyr::mutate(
Place = dplyr::case_when(
stringr::str_detect(V1, "^[:digit:]*$") == TRUE ~ V1,
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 1]
)
) %>%
dplyr::mutate(
Name = dplyr::case_when(
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V1, "[:alpha:] [:alpha:]") == TRUE &
stringr::str_detect(V2, "^\\'[:upper:]\\'$") == FALSE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, ",") == TRUE ~ V2
)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_detect(V2, Age_String) == TRUE ~ V2,
stringr::str_detect(V2, "^SR |^JR |^SO |^FR |^[:digit:]{1,3} ") == TRUE ~ stringr::str_extract(V2, "^SR |^JR |^SO |^FR |^10 |^11 |^[:digit:]{1,2} "),
stringr::str_detect(V3, "^SR |^JR |^SO |^FR |^[:digit:]{1,3}\\s?") == TRUE ~ stringr::str_extract(V3, "^SR |^JR |^SO |^FR |^10 |^11 |^[:digit:]{1,2}\\s?"),
any(stringr::str_detect(V2, Age_String)) == FALSE &
any(stringr::str_detect(V3, Age_String)) == TRUE ~ V3
),
Age = trimws(Age),
) %>%
dplyr::mutate(
Team = dplyr::case_when(
stringr::str_detect(V1, Name) &
stringr::str_detect(V2, Age) &
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE ~ V3,
stringr::str_detect(V1, paste0("^", Place, "$")) == TRUE &
stringr::str_detect(V2, paste0("^", Name, "$")) == TRUE &
stringr::str_detect(V3, paste0("^", Age, "$")) == TRUE ~ V4,
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V1, "^[:digit:]*$") == FALSE &
stringr::str_detect(V1, "[:alpha:] [:alpha:]") == FALSE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V2, "^\\'[:upper:]\\'$") == TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2],
stringr::str_detect(V2, "^\\'[:upper:]\\'$") == FALSE &
stringr::str_detect(V1, "^[:digit:]*$") == FALSE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
TRUE ~ V3
)
) %>%
mutate(Team = str_remove(Team, Age),
Team = trimws(Team)
) %>%
# na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
# any(stringr::str_detect(V3, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE ~ V3,
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V5, Time_Score_Specials_String)) == TRUE ~ V4,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V6, Time_Score_Specials_String) == TRUE ~ V5,
any(stringr::str_detect(V4, "SEC")) == TRUE ~ V5
)
) %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
# any(stringr::str_detect(V3, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE ~ V4,
# any(stringr::str_detect(V4, Time_Score_Specials_String)) == TRUE &
# any(stringr::str_detect(V5, Time_Score_Specials_String)) == TRUE ~ V5,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V5,
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V6, Time_Score_Specials_String) == TRUE ~ V6,
any(stringr::str_detect(V4, "SEC")) == TRUE ~ V6
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time != V6 ~ V6,
Finals_Time == V6 ~ ""),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Place,
Name,
Age,
Team,
Prelims_Time,
Finals_Time,
Points,
Row_Numb = V7
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
DQ = case_when(str_detect(Finals_Time, "^DQ$") ~ 1,
TRUE ~ 0),
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = stringr::str_remove(Finals_Time, "J"),
Finals_Time = dplyr::case_when(
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) != TRUE ~ Finals_Time,
TRUE ~ Finals_Time
)) %>%
dplyr::mutate(
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Age, "[[:alpha:]]") == TRUE ~ Age,
is.na(Team) == FALSE &
stringr::str_detect(Age, "[[:alpha:]]") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:upper:]]\\'|^\\-?[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
TRUE ~ Team
),
Age = replace(Age, Age == Team, NA),
Team = dplyr::case_when(
stringr::str_length(Age) > 2 &
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, "\\.\\d") == FALSE ~ paste(Age, Team, sep = " "),
stringr::str_length(Age) <= 2 |
is.na(Age) == TRUE |
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == TRUE |
stringr::str_detect(Age, "\\.\\d") == TRUE ~ Team
),
Age = replace(Age, (
stringr::str_length(Age) > 2 & is.na(Age) == FALSE
), NA),
Age = dplyr::case_when(
stringr::str_detect(Age, "^\\-?[:upper:]$") == TRUE ~ "",
TRUE ~ Age
),
Name = replace(Name, Name == Team, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String)
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == FALSE ~ Team,
stringr::str_detect(Team, "^A$") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "^A$") == FALSE ~ Team
),
Team = stringr::str_remove(Team, "^SR |^JR |^SO |^FR |^10 |^11 |^12 |^9 |^8 |^7 "),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
)
# dplyr::mutate(DQ = 0)
)
} else {
df_7 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### six variables ####
if (length(data_length_6) > 0) {
suppressWarnings(
df_6 <- data_length_6 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Name = dplyr::case_when(
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, Name_String),
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, Name_String),
V1 == Place &
stringr::str_detect(V2, "[:digit:]") == FALSE ~ V2,
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
),
V1 = stringr::str_remove(V1, Place),
V1 = trimws(V1)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 2 &
stringr::str_detect(V2, "^SR |^JR |^SO |^FR |^[:digit:]{1,3} ") == TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
stringr::str_detect(V3, "^SR |^JR |^SO |^FR |^[:digit:]{1,3} ") == TRUE ~ stringr::str_split_fixed(V3, " ", n = 2)[, 1],
stringr::str_length(V2) <= 2 &
stringr::str_detect(V2, "[[:alpha:]\\.]") == FALSE ~ V2,
stringr::str_length(V2) <= 2 &
stringr::str_detect(V2, Age_String) == TRUE ~ V2,
stringr::str_length(V3) <= 2 &
stringr::str_detect(V3, Age_String) == TRUE ~ V3,
TRUE ~ ""
)
) %>%
dplyr::mutate(V3 = case_when(is.na(Age) == FALSE & str_detect(V3, paste0("^", Age, " ")) ==TRUE ~ str_remove(V3, paste0(Age, " ")),
TRUE ~ V3)) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V3 == Age ~ V4,
V2 == Age ~ V3,
any(stringr::str_detect(V3, "SEC")) == TRUE ~ stringr::str_remove(V1, Name),
is.na(Age) &
stringr::str_detect(V2, Time_Score_String) == FALSE &
stringr::str_detect(V2, Name) == FALSE &
stringr::str_detect(V2, "[:lower:]{1,}") == TRUE ~ V2,
is.na(Age) &
stringr::str_detect(V2, Time_Score_String) == FALSE &
stringr::str_detect(V2, Name) == FALSE &
stringr::str_detect(V2, "[:alpha:]{2,}") == TRUE ~ V2,
is.na(Age) &
stringr::str_detect(V2, Time_Score_String) == FALSE &
stringr::str_detect(V2, Name) == FALSE &
stringr::str_detect(V2, "[:lower:]{1,}") == FALSE ~ "",
is.na(Age) == TRUE &
stringr::str_detect(V2, Name) == TRUE &
stringr::str_detect(V3, "[:lower:]{2,}") == TRUE ~ V3,
is.na(Age) == FALSE &
stringr::str_detect(V2, Name) == TRUE &
stringr::str_detect(V3, "[:lower:]{1,}") == TRUE ~ V3,
is.na(Age) == TRUE &
stringr::str_detect(V2, Name) == TRUE &
stringr::str_detect(V3, "[:lower:]{1,}") == FALSE ~ V2,
is.na(Age) == TRUE &
stringr::str_detect(V2, Name) == TRUE ~ V3,
is.na(Age) == FALSE &
stringr::str_detect(V2, Name) == TRUE ~ V3,
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
)
) %>%
### df_6 cannot have NT as time string since there are some schools called NT ###
dplyr::mutate(
Prelims_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE & # new 8/18
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V2,
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V4, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ "",
TRUE ~ V3
)
) %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE & # new 8/18
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V5, Time_Score_Specials_String) == TRUE ~ V5,
TRUE ~ V4
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time == V5 ~ "",
# Finals_Time == V4 ~ V5
TRUE ~ V5),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Points,
Row_Numb = V6
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = dplyr::case_when(
Place >= 1 &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
Place >= 1 &
is.na(Finals_Time) != TRUE ~ Finals_Time
),
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Age, "[[:alpha:]]") == TRUE ~ Age,
is.na(Team) == FALSE &
stringr::str_detect(Age, "[[:alpha:]]") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Age = replace(Age, Age == Team, NA),
Team = dplyr::case_when(
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, Time_Score_String) == FALSE &
stringr::str_detect(Age, "\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE &
Age != Team ~ paste(Age, Team, sep = " "),
TRUE ~ Team
),
Age = replace(Age, (
stringr::str_length(Age) > 2 & is.na(Age) == FALSE
), NA),
Name = replace(Name, Name == Team, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String),
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Team = dplyr::case_when(
stringr::str_detect(Team, Time_Score_String) == TRUE ~ stringr::str_extract(Team, "[:alpha:]*"),
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "\\'[[:alpha:]]\\'") == FALSE ~ Team,
stringr::str_detect(Team, "^\\-?[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
# stringr::str_detect(Team, "^-[:upper:]$") == TRUE &
# is.na(Name) == FALSE ~ Name,
TRUE ~ Team),
Team = stringr::str_remove(
Team,
"^[:digit:]{1,2}\\s"
)) %>%
dplyr::mutate(
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
) %>%
dplyr::mutate(DQ = 0)
)
} else {
df_6 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### five variables ####
if (length(data_length_5) > 0) {
suppressWarnings(
df_5 <- data_length_5 %>%
list_transform() %>%
dplyr::mutate(Place = dplyr::case_when(stringr::str_detect(V1, "^\\d{1,}$") ~ V1,
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 1])) %>%
dplyr::mutate(
Name = dplyr::case_when(
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, Name_String),
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, Name_String),
stringr::str_detect(V2, ",") == FALSE & V1 == Place & stringr::str_detect(V3, Time_Score_Specials_String) == FALSE ~ stringr::str_extract(V2, Name_String),
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, Time_Score_String) == TRUE ~ "",
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
)
) %>%
na_if_character("") %>%
dplyr::mutate(
V1 = dplyr::case_when(
is.na(Place) == FALSE ~ stringr::str_remove(V1, Place),
TRUE ~ V1
),
V1 = dplyr::case_when(
is.na(Name) == FALSE ~ stringr::str_remove(V1, Name),
TRUE ~ V1
),
V1 = trimws(V1),
Name = trimws(Name)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(V2) <= 3 &
stringr::str_detect(V2, "^SR|^JR|^SO|^FR|^\\d{1,3}$") == TRUE ~ V2,
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 3 &
stringr::str_detect(V2, "SR|JR|SO|FR|^\\d{1,3} ") ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
stringr::str_length(stringr::str_split_fixed(V3, " ", n = 2)[, 1]) <= 3 &
stringr::str_detect(V3, "SR|JR|SO|FR|^\\d{1,3} ") ~ stringr::str_split_fixed(V3, " ", n = 2)[, 1],
TRUE ~ ""
)) %>%
na_if_character("") %>%
dplyr::mutate(
Age = trimws(Age),
V3 = case_when(is.na(Age) == FALSE & stringr::str_detect(V3, Age) == TRUE & stringr::str_detect(V3, Time_Score_Specials_String) == FALSE & Age != "" ~ stringr::str_remove(V3, Age),
TRUE ~ V3),
V2 = case_when(is.na(Age) == FALSE & stringr::str_detect(V2, Age) == TRUE & stringr::str_detect(V2, Time_Score_Specials_String) == FALSE & Age != "" ~ stringr::str_remove(V2, Age),
TRUE ~ V2),
V2 = trimws(V2),
V3 = trimws(V3)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V2 == Name & str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
is.na(V2) & is.na(Name) == FALSE & str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == FALSE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == TRUE ~ V1,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|^\\'\\'$") == FALSE &
stringr::str_detect(V2, Time_Score_Specials_String) == FALSE ~ V2,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|'[:upper:]'|^\\'\\'$") == TRUE &
(V1 != Name | is.na(Name)) ~ V1,
(V1 == Name |
is.na(Name)) &
V2 != Age ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE ~ V1,
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
),
Team = dplyr::case_when(
stringr::str_detect(Team, Age) == TRUE &
is.na(Team) == FALSE ~ stringr::str_remove(Team, Age),
TRUE ~ Team
),
Team = trimws(Team)
) %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V2,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ "",
TRUE ~ V2
)
) %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
TRUE ~ V3
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time == V3 ~ V4,
Finals_Time == V4 ~ "",
TRUE ~ ""),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Points,
Row_Numb = V5
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
DQ = case_when(str_detect(Finals_Time, "^DQ$") ~ 1,
TRUE ~ 0)
) %>%
### dealing with exhibition times 8/18/2020
dplyr::mutate(
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String), # added 11/6
) %>%
na_if_character("") %>%
dplyr::mutate(
Finals_Time = replace(Finals_Time, dplyr::n_distinct(Finals_Time) <= 2, ""),
Prelims_Time = replace(Prelims_Time, dplyr::n_distinct(Prelims_Time) <= 2, "")
) %>%
na_if_character("") %>%
na_if_character("''") %>%
# dplyr::mutate(
# Finals_Time = dplyr::case_when(
# sum(stringr::str_detect(Finals_Time, Time_Score_String)) >= 1 ~ stringr::str_remove(Finals_Time, "NT"),
# sum(stringr::str_detect(Finals_Time, Time_Score_String)) < 1 ~ Finals_Time,
# TRUE ~ Finals_Time
# )
# ) %>%
na_if_character("") %>% # good 11/9
dplyr::mutate(
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Finals_Time, Time_Score_String) == FALSE ~ Finals_Time,
is.na(Team) == FALSE |
stringr::str_detect(Finals_Time, Time_Score_String) == TRUE ~ Team
),
Finals_Time = replace(
Finals_Time,
stringr::str_detect(Finals_Time, "^NT$") == TRUE,
NA
), # okay 11/9
Finals_Time = replace(Finals_Time, Team == Finals_Time, NA),
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA), # okay 11/9
Finals_Time = dplyr::case_when(
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
dplyr::between(Place, 1, 9999) &
is.na(Finals_Time) != TRUE ~ Finals_Time,
TRUE ~ Finals_Time
),
# ### dealing with exhibition times 8/18/2020
# Exhibition = dplyr::case_when(
# stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
# TRUE ~ 0
# ),
# ###
# Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
# Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String), # added 11/6
) %>%
# na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Points_2 = dplyr::case_when(
stringr::str_detect(Points, Colon_String) == TRUE ~ "",
as.numeric(Points) > 20 &
stringr::str_detect(Points, Time_Score_String) == TRUE ~ "",
stringr::str_detect(Points, Colon_String) == FALSE ~ Points
),
Prelims_Time = dplyr::case_when(
stringr::str_detect(Points, Colon_String) == TRUE ~ Finals_Time,
as.numeric(Points) > 20 &
stringr::str_detect(Points, Time_Score_String) == TRUE ~ Finals_Time,
TRUE ~ Prelims_Time
),
Finals_Time = dplyr::case_when(
stringr::str_detect(Points, Colon_String) == TRUE ~ Points,
as.numeric(Points) > 20 &
stringr::str_detect(Points, Time_Score_String) == TRUE ~ Points,
TRUE ~ Finals_Time
)
) %>%
na_if_character("") %>%
dplyr::mutate(
Points = dplyr::case_when(
is.na(Points_2) == FALSE ~ Points_2,
Points == Finals_Time ~ "",
TRUE ~ Points
),
Points_2 = NULL,
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String),
Prelims_Time = replace(
Prelims_Time,
stringr::str_detect(Prelims_Time, Time_Score_String) == FALSE,
NA
)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = replace(Team, stringr::str_detect(Team, "\\.\\d") == TRUE, NA),
Team = dplyr::case_when(
is.na(Team) == TRUE &
Age %!in% c(
"FR",
"SO",
"JR",
"SR",
"7",
"8",
"05",
"06",
"07",
"08",
"09",
as.character(seq(10, 25, 1))
) &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, "\\.\\d") == FALSE ~ Age,
is.na(Team) == FALSE |
Age %in% c(
"FR",
"SO",
"JR",
"SR",
"7",
"8",
"05",
"06",
"07",
"08",
"09",
as.character(seq(10, 25, 1))
) |
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == TRUE |
stringr::str_detect(Age, "\\.\\d") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Team = dplyr::case_when(
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'|\\.?\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE &
Age != Team ~ paste(Age, Team, sep = " "),
TRUE ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:upper:]]\\'|^\\-?[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
TRUE ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, Time_Score_String) == TRUE ~ stringr::str_extract(Team, "[:alpha:]*"),
TRUE ~ Team
),
Age = replace(Age, Age == Team, NA),
Age = replace(Age, stringr::str_detect(Age, Time_Score_String) == TRUE, NA),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA),
Age = replace(Age, is.na(Name) == TRUE &
is.na(Team) == FALSE, NA),
Age = replace(Age, Age == Team, NA),
Age = replace(Age, (
stringr::str_length(Age) > 2 & is.na(Age) == FALSE
), NA)
)
# dplyr::mutate(DQ = 0)
)
} else {
df_5 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### four variables ####
if (length(data_length_4) > 0) {
suppressWarnings(
df_4 <- data_length_4 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Name = dplyr::case_when(
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, Name_String),
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == FALSE ~ "",
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, Name_String),
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, Time_Score_String) == TRUE ~ "",
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
)
) %>%
na_if_character("") %>%
dplyr::mutate(
V1 = dplyr::case_when(
is.na(Place) == FALSE ~ stringr::str_remove(V1, Place),
TRUE ~ V1
),
V1 = dplyr::case_when(
is.na(Name) == FALSE ~ stringr::str_remove(V1, Name),
TRUE ~ V1
),
V1 = trimws(V1),
Name = trimws(Name)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 2 &
stringr::str_detect(V2, "SR|JR|SO|FR|12|11|10|9|8|7|^\\d\\d ") ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
TRUE ~ ""
),
Age = trimws(Age)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == FALSE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == TRUE ~ V1,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) & # added DQ to string 11/9
stringr::str_detect(V2, "^'[:upper:]'$|^[:upper:]$|^\\'\\'$") == FALSE &
stringr::str_detect(V2, Time_Score_Specials_String) == FALSE ~ V2,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) & # added DQ to string 11/9
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|'[:upper:]'|^\\'\\'$") == TRUE &
(V1 != Name | is.na(Name)) ~ V1,
(V1 == Name |
is.na(Name)) &
V2 != Age ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE ~ V1, # added DQ to string 11/9
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
),
Team = dplyr::case_when(
stringr::str_detect(Team, Age) == TRUE &
is.na(Team) == FALSE ~ stringr::str_remove(Team, Age),
TRUE ~ Team
),
Team = trimws(Team)
) %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE ~ V2,
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V3,
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ "",
TRUE ~ ""
)
) %>%
na_if_character("") %>%
dplyr::mutate(
Finals_Time = dplyr::case_when(
stringr::str_detect(V3, Time_Score_Specials_String) == TRUE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
stringr::str_detect(V3, Time_Score_Specials_String) == FALSE &
stringr::str_detect(V4, Time_Score_Specials_String) == TRUE ~ V4,
TRUE ~ V3
)
) %>%
dplyr::mutate(
Points = dplyr::case_when(Finals_Time == V3 ~ V4,
Finals_Time == V4 ~ "",
TRUE ~ ""),
Points = dplyr::case_when(stringr::str_detect(Points, "^\\d{1,}$") == FALSE ~ "",
TRUE ~ Points)
) %>%
na_if_character("") %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Row_Numb = V4
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
DQ = case_when(str_detect(Finals_Time, "^DQ$") ~ 1,
TRUE ~ 0),
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = dplyr::case_when(
Place >= 1 &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
Place >= 1 &
is.na(Finals_Time) != TRUE ~ Finals_Time
)
) %>%
dplyr::mutate(
Team = dplyr::case_when(
is.na(Team) == TRUE &
stringr::str_detect(Age, "[[:alpha:]]") == TRUE &
stringr::str_length(Age) > 1 ~ Age,
is.na(Team) == FALSE &
stringr::str_detect(Age, "[[:alpha:]]") == FALSE ~ Team,
is.na(Team) == FALSE ~ Team
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
)
) %>%
dplyr::mutate(
Age = replace(Age, Age == Team, NA),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
) %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
is.na(Name) == TRUE &
stringr::str_detect(Age, Time_Score_String) == TRUE ~ Age,
TRUE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Age = replace(Age, is.na(Name) == TRUE &
is.na(Team) == FALSE, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String)
) %>%
dplyr::mutate(
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String)
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(
Age = replace(Age, Age == Team, NA),
Team = dplyr::case_when(
is.na(Age) == FALSE &
stringr::str_detect(Age, "\\'[[:alpha:]]\\'") == FALSE &
stringr::str_detect(Age, Time_Score_String) == FALSE &
stringr::str_detect(Age, "\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE &
Age != Team ~ paste(Age, Team, sep = " "),
TRUE ~ Team
),
Team = dplyr::case_when(
stringr::str_detect(Team, "\\'[[:upper:]]\\'") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "^[:upper:]$") == TRUE &
is.na(Name) == FALSE ~ Name,
stringr::str_detect(Team, "^[:upper:]$") == FALSE |
is.na(Name) == TRUE ~ Team
),
Age = replace(
Age,
(
stringr::str_detect(Age, "\\d") == FALSE &
Age %in% c("SR", "JR", "SO", "FR") == FALSE
),
NA
),
Age = dplyr::case_when(
stringr::str_detect(Name, "\\.d{1,3}") == TRUE ~ stringr::str_extract(Name, "\\d{1,3}"),
stringr::str_detect(Name, "\\.d{1,3}") == FALSE ~ Age
),
Name = stringr::str_remove(Name, "\\d{1,3}"),
Prelims_Time = dplyr::case_when(
is.na(Prelims_Time) == TRUE &
stringr::str_detect(Team, "\\.") == TRUE ~ stringr::str_extract(
Team,
"[:digit:]*[:punct:]?[:digit:]*[:punct:]?[:digit:]*"
),
is.na(Prelims_Time) == FALSE |
stringr::str_detect(Team, "\\.") == FALSE ~ Prelims_Time
),
Team = stringr::str_remove(Team, "-[:alpha:]*\\d.*$"),
Team = stringr::str_remove(
Team,
"^[:digit:]{1,2}\\s")
) %>%
na_if_character("") %>%
dplyr::mutate(
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA)
)
# dplyr::mutate(DQ = 0)
)
} else {
df_4 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### three variables ####
if (length(data_length_3) > 0) {
suppressWarnings(
df_3 <- data_length_3 %>%
list_transform() %>%
dplyr::mutate(
Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1],
Name = stringr::str_split_fixed(V1, " ", n = 2)[, 2],
Age = as.character(NA),
Team = as.character(NA),
Finals_Time = V2,
Prelims_Time = as.character(NA),
) %>%
dplyr::select(
Name,
Place,
Age,
Team,
Prelims_Time,
Finals_Time,
Row_Numb = V3
) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(
Finals_Time = replace(Finals_Time, stringr::str_length(Finals_Time) < 3, NA),
Finals_Time = dplyr::case_when(
Place >= 1 &
is.na(Finals_Time) == TRUE ~ dplyr::coalesce(Finals_Time, Prelims_Time),
Place >= 1 &
is.na(Finals_Time) != TRUE ~ Finals_Time
),
Team = dplyr::case_when(
stringr::str_length(Team) < 1 | is.na(Team) == TRUE ~ Name,
stringr::str_length(Team) >= 1 ~ Team
),
Name = stringr::str_remove(Name, "^-"),
Name = replace(Name, Name == Team, NA),
Prelims_Time = dplyr::case_when(
is.na(Name) == TRUE ~ Age,
is.na(Name) == FALSE ~ Prelims_Time
),
Age = replace(Age, is.na(Name) == TRUE &
is.na(Team) == FALSE, NA),
### dealing with exhibition times 8/18/2020
Exhibition = dplyr::case_when(
stringr::str_detect(Finals_Time, "x|X") == TRUE ~ 1,
TRUE ~ 0
),
###
Finals_Time = stringr::str_extract(Finals_Time, Time_Score_String),
Prelims_Time = stringr::str_extract(Prelims_Time, Time_Score_String)
) %>%
na_if_character("") %>%
dplyr::mutate(
Prelims_Time = dplyr::case_when(
all(Prelims_Time == Finals_Time, na.rm = TRUE) ~ as.character(NA),
all(Prelims_Time == Finals_Time, na.rm = TRUE) == FALSE ~ Prelims_Time
)
) %>%
dplyr::mutate(DQ = 0)
)
} else {
df_3 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### DQ data ####
#### DQ 4 ####
if (length(DQ_length_4) > 0) {
suppressWarnings(
df_DQ_4 <- DQ_length_4 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Name = dplyr::case_when(
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == TRUE ~ stringr::str_extract(V1, "_?[:alpha:]+'?[:alpha:]+, [:alpha:]+\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?"),
any(stringr::str_detect(V1, ",")) == TRUE &
stringr::str_detect(V1, ",") == FALSE ~ "",
stringr::str_detect(V2, ",") == TRUE ~ stringr::str_extract(V2, "_?[:alpha:]+'?[:alpha:]+, [:alpha:]+\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?\\s?[:alpha:]?"),
stringr::str_detect(V1, ",") == FALSE &
stringr::str_detect(V2, Time_Score_String) == TRUE ~ "",
# stringr::str_detect(V2, Time_Score_Special_String) == TRUE ~ "",
TRUE ~ stringr::str_split_fixed(V1, " ", n = 2)[, 2]
)
) %>%
na_if_character("") %>%
dplyr::mutate(
V1 = dplyr::case_when(
is.na(Place) == FALSE ~ stringr::str_remove(V1, Place),
TRUE ~ V1
),
V1 = dplyr::case_when(
is.na(Name) == FALSE ~ stringr::str_remove(V1, Name),
TRUE ~ V1
),
V1 = trimws(V1),
Name = trimws(Name)
) %>%
dplyr::mutate(
Age = dplyr::case_when(
stringr::str_length(stringr::str_split_fixed(V2, " ", n = 2)[, 1]) <= 3 &
stringr::str_detect(V2, "SR|JR|SO|FR|12|11|10|9|8|7|^\\d{1,3} ") ~ stringr::str_split_fixed(V2, " ", n = 2)[, 1],
TRUE ~ ""
),
Age = trimws(Age)
) %>%
na_if_character("") %>%
dplyr::mutate(
Team = dplyr::case_when(
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == FALSE ~ V3,
V2 == Age &
any(stringr::str_detect(V3, "^SEC \\d+$")) == TRUE ~ V1,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|^\\'\\'$") == FALSE &
stringr::str_detect(V2, Time_Score_String) == FALSE ~ V2,
(is.na(V1) == TRUE & stringr::str_detect(V3, Time_Score_Specials_String) == TRUE & stringr::str_detect(V2, "\\d") == FALSE) ~ V2,
(V2 != Age |
is.na(Age)) &
stringr::str_detect(V3, Time_Score_Specials_String) &
stringr::str_detect(V2, "'[:upper:]'|^[:upper:]$|'[:upper:]'|^\\'\\'$") == TRUE &
(V1 != Name | is.na(Name)) ~ V1,
(V1 == Name |
is.na(Name)) &
V2 != Age ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2],
stringr::str_detect(V2, Time_Score_Specials_String) == TRUE ~ V1,
TRUE ~ stringr::str_split_fixed(V2, " ", n = 2)[, 2]
),
Team = dplyr::case_when(
stringr::str_detect(Team, Age) == TRUE &
is.na(Team) == FALSE ~ stringr::str_remove(Team, Age),
TRUE ~ Team
),
Team = trimws(Team)
) %>%
na_if_character("") %>%
dplyr::select(Name,
Place,
Age,
Team,
Row_Numb = V4) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(DQ = 1)
)
} else {
df_DQ_4 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### DQ 3 ####
if (length(DQ_length_3) > 0) {
suppressWarnings(
df_DQ_3 <- DQ_length_3 %>%
list_transform() %>%
dplyr::mutate(Place = stringr::str_split_fixed(V1, " ", n = 2)[, 1]) %>%
dplyr::mutate(
Team = stringr::str_split_fixed(V1, " ", n = 2)[, 2],
Team = trimws(Team)
) %>%
na_if_character("") %>%
dplyr::select(Place,
Team,
Row_Numb = V3) %>%
na_if_character("") %>%
na_if_character("''") %>%
dplyr::mutate(DQ = 1)
)
} else {
df_DQ_3 <- data.frame(
Row_Numb = character(),
stringsAsFactors = FALSE
)
}
#### Rejoin dataframes from each number of variables ####
Min_Row_Numb <- min(events$Event_Row_Min)
suppressWarnings(
# data <- dplyr::full_join(df_7, df_6) %>%
# dplyr::full_join(df_5) %>%
# dplyr::full_join(df_4) %>%
# dplyr::full_join(df_3) %>%
# dplyr::left_join(df_DQ_4) %>%
# dplyr::left_join(df_DQ_3) %>%
data <- dplyr::bind_rows(df_7, df_6) %>%
dplyr::bind_rows(df_5) %>%
dplyr::bind_rows(df_4) %>%
dplyr::bind_rows(df_3) %>%
dplyr::left_join(df_DQ_4) %>%
dplyr::left_join(df_DQ_3) %>%
dplyr::mutate(Row_Numb = as.numeric(Row_Numb)) %>%
dplyr::arrange(Row_Numb) %>%
### moved up from below for DQ work 8/20
dplyr::mutate(DQ = dplyr::case_when(Place == 10000 & Exhibition == 0 ~ 1, # added exhibition condition 8/27
TRUE ~ DQ)) %>%
na_if_numeric(10000) %>%
dplyr::mutate(dplyr::across(c(Name, Team), ~ stringr::str_replace_all(., "10000", "--"))) %>% # remove any "10000"s added in erroniuously
####
dplyr::mutate(
Place = as.numeric(Place),
Place = dplyr::case_when(
is.na(dplyr::lag(Place)) == TRUE ~ Place,
dplyr::lag(Place) == Place ~ Place + 0.1,
dplyr::lag(Place) != Place ~ Place
),
Place = as.character(Place),
Row_Numb = as.numeric(Row_Numb)
) %>%
dplyr::filter(Row_Numb >= Min_Row_Numb)
)
if("Points" %in% names(data) == FALSE)
{data$Points <- NA}
#### add in events based on row number ranges ####
data <-
transform(data, Event = events$Event[findInterval(Row_Numb, events$Event_Row_Min)])
#### cleaning up final results ####
suppressWarnings(
data <- data %>%
dplyr::mutate(
Name = stringr::str_replace(Name, "_", "\\*"),
Prelims_Time = replace(
Prelims_Time,
stringr::str_detect(Prelims_Time, "\\.") == FALSE,
NA
),
Prelims_Time = replace(
Prelims_Time,
(stringr::str_detect(Prelims_Time, "\\.") == TRUE &
stringr::str_detect(Prelims_Time, "\\:") == FALSE &
as.numeric(Prelims_Time) < 15
),
NA
),
Points = replace(
Points,
stringr::str_detect(Points, "[[:alpha:]]") == TRUE,
NA
),
Points = replace(
Points,
stringr::str_detect(Points, "[^[:digit:]|\\.]"),
NA
),
Place = round(as.numeric(Place)),
Event = as.character(Event)
) %>%
dplyr::mutate(
Place = dplyr::case_when(is.na(Place) == TRUE &
DQ == 0 ~ lag(Place) + 1,
TRUE ~ Place)
) %>%
### added 8/20 as part of DQ, to remove records and such but not DQ results
dplyr::filter(
DQ == 0 &
stringr::str_detect(Finals_Time, Time_Score_String) == TRUE |
DQ == 0 & stringr::str_detect(Prelims_Time, Time_Score_String) == TRUE | DQ == 1
) %>%
dplyr::mutate(Exhibition = dplyr::case_when(is.na(Exhibition) == TRUE ~ 0,
TRUE ~ Exhibition)) %>%
dplyr::mutate(Finals_Time = dplyr::case_when(DQ == 1 ~ "NA",
TRUE ~ Finals_Time)) %>%
na_if_character("NA")
)
#### adding relay swimmers in ####
if (relay_swimmers == TRUE) {
relay_swimmers_df <- collect_relay_swimmers_old(as_lines_list_2, typo_2 = typo, replacement_2 = replacement)
data <- data %>%
dplyr::left_join(relay_swimmers_df, by = 'Row_Numb')
}
#### adding splits back in ####
if (splits == TRUE) {
splits_df <- splits_parse(as_lines_list_2, split_len = split_length)
if (any(str_detect(data$Event, "Relay")) == TRUE) {
relay_row <- data %>%
dplyr::filter(stringr::str_detect(Event, "Relay")) %>%
head(1) %>%
dplyr::select(Row_Numb) %>%
dplyr::pull()
relay_offset <-
ifelse(stringr::str_detect(as_lines_list_2[relay_row + 2], "\\d\\d\\.\\d\\d") == TRUE,
1,
2)
data <- data %>%
dplyr::mutate(
Row_Numb = dplyr::case_when(
stringr::str_detect(Event, "Relay") == TRUE ~ Row_Numb + relay_offset,
TRUE ~ Row_Numb
)
) %>%
dplyr::left_join(splits_df, by = 'Row_Numb')
} else {
data <- data %>%
dplyr::left_join(splits_df, by = 'Row_Numb')
}
### remove empty columns (all values are NA) ###
data <- Filter(function(x)
!all(is.na(x)), data)
}
#### if there is a Place column it should be first ####
if("Place" %in% names(data)){
data <- data %>%
dplyr::select(Place, dplyr::everything())
}
data$Row_Numb <- NULL
message("Beginning with version 0.6.0 the Grade and School output columns have been renamed Age and Team respectively. Please adjust your work flows as needed.")
return(data)
} else if (stringr::str_detect(file[1], "^A107") == TRUE) {
# file <- add_row_numbers(text = file)
data <- hy3_parse(file = file)
return(data)
}
}
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