Helper function to convert Turftrax PDF times to neat dataframe

turftrax.R

# SHORT SCRIPT TO GET TURFTRAX TIMES FROM PDF INTO R

# example PDF http://www.turftrax.co.uk/tracking/Glorious2014/GWD290714R1_1M2F.pdf

# highlight horses names and times in the table in Turftrax PDF using mouse 
# (don't highlight the table headers)
# copy to clipboard using "Ctrl-C"

# in R (once PDF table is copied to clipboard)
df <- read.delim("clipboard", h=F, stringsAsFactors=F)
# for example PDF (above)
dim(df)
##[1] 18  1
head(df)
#                                                                              V1
# 3 Sennockian Star 5 13.69 11.86 12.19 12.71 14.14 11.91 11.15 11.59 11.71 11.89
#  14 Ajman Bridge 18 13.93 11.95 12.36 12.87 14.30 11.68 11.16 11.08 11.47 12.14
#     6 Salutation 16 13.60 11.66 12.27 12.87 14.07 11.85 11.06 11.35 11.70 12.60
#       15 Busatto 12 13.68 11.55 12.03 12.81 14.07 11.97 11.21 11.39 11.72 12.74
# 16 Charles Camoin 8 14.04 12.15 12.31 13.04 14.09 11.61 11.04 11.38 11.68 12.19
#       4 Blue Surf 1 13.93 11.87 12.01 12.80 14.08 11.82 11.17 11.33 11.92 12.73


# this function will extract the horses names and sectional times from df above 
turftrax <- function(df) {
    # load required libraries
    library(stringr, quietly = TRUE)
    library(plyr, quietly = TRUE)
    # extract horses name (apostrophes will be removed from any name)
    horse <- str_replace_all(df$V1, "[[:digit:]]|[[:punct:]]", "")
    # clean up name, by removing double spaces and trim whitespace
    horse <- str_trim(str_replace_all(horse, "\\s+", " "), side = "both")
    # extract times and convert into dataframe
    times <- str_extract_all(df$V1, "[[:digit:]]+\\.[[:digit:]]+")
    times <- ldply(times)
    # combine horses names and times
    df <- cbind(horse, times)
    return(df)
}

newdf <- turftrax(df)
head(newdf)
#           horse    V1    V2    V3    V4    V5    V6    V7    V8    V9   V10
# Sennockian Star 13.69 11.86 12.19 12.71 14.14 11.91 11.15 11.59 11.71 11.89
#    Ajman Bridge 13.93 11.95 12.36 12.87 14.30 11.68 11.16 11.08 11.47 12.14
#      Salutation 13.60 11.66 12.27 12.87 14.07 11.85 11.06 11.35 11.70 12.60
#         Busatto 13.68 11.55 12.03 12.81 14.07 11.97 11.21 11.39 11.72 12.74
#  Charles Camoin 14.04 12.15 12.31 13.04 14.09 11.61 11.04 11.38 11.68 12.19
#       Blue Surf 13.93 11.87 12.01 12.80 14.08 11.82 11.17 11.33 11.92 12.73