Grafiski attēlots ātrāko skrējēju laiks kontrolpunktos

SB2017-Pokaini-Buks

# Stirnu buks
# 2017
# Pokaiņi
# Distance: Buks

require(rvest)
require(data.table)
require(ggplot2)


# HTML
html <- read_html("http://www.stirnubuks.lv/rezultati/spliti/?posms=pokaini&distance=buks")

# Table header
thead <- html %>% html_node("thead") %>% html_nodes("th") %>% html_text()
thead[thead == ""] <- paste0("V", 1:length(thead[thead == ""]))
thead <- gsub(" ", "", thead)
thead <- gsub("\\.", "", thead)
thead

# Table
dat <- html %>% html_node("table") %>% html_table(fill = T)
setDT(dat)
setnames(dat, thead)
names(dat)
dat[, .N]
# 466

# Izņem DNF
dat[Rezultāts == "DNF"]
dat <- dat[Rezultāts != "DNF"]
dat[, .N]
# 463

# Izņem dīvainus ierakstus ar tukšumiem
dat[is.na(V1) | is.na(V2) | is.na(V3) | is.na(V4) | is.na(V5) | is.na(V6)]
dat <- dat[!(is.na(V1) | is.na(V2) | is.na(V3) | is.na(V4) | is.na(V5) | is.na(V6))]
dat[, .N]
# 461

# Pārrēķina vietas

# Rezultātu skaits
N <- dat[, .N]
N

# CP skaits + finišs
n <- length(grep("^CP[1-9]", names(dat))) + 1L
n

# Starts
dat[, CP0 := "00:00:00"]
dat[, V0 := as.integer(NA)]

# Saglabā vietu
dat[, tmp := Vieta]

# Vieta dzimuma grupā
dat[, Vieta_dzim := as.integer(substring(Dzim, 2))]

# Dzimums
dat[, sex := substring(Dzim, 1, 1)]

setnames(dat, c("Rezultāts", "tmp"), paste0(c("CP", "V"), n))

for (i in 1:n) {
  setorderv(dat, paste0(c("CP", "V"), i))
  set(dat, j = paste0("V", i), value = 1:N)
}

dat

datl1 <- melt(dat, id.vars = c("Nr", "Dalībnieks", "sex", "Grupa",
                               "Vieta", "Vieta_dzim", "Dzim"),
              measure.vars = paste0("CP", 0:n),
              variable.name = "id", value.name = "CP")
datl1[, id := sub("CP|V", "", id)]
datl1

datl2 <- melt(dat, id.vars = "Nr", measure.vars = paste0("V", 0:n),
              variable.name = "id", value.name = "V")
datl2[, id := sub("CP|V", "", id)]
datl2

datl <- merge(datl1, datl2, by = c("Nr", "id"))
setorder(datl, Vieta, id)
datl

datl[, class(CP)]
datl[, CP := as.POSIXct(CP, format = "%H:%M:%S")]

# datl[, pos := factor(Vieta, datl[order(-Vieta)][id == 0, Vieta],
#                      datl[order(-Vieta)][id == 0, paste(Vieta, Dalībnieks)])]

tmpval <- datl[order(-Vieta)][id == 0, Dzim]
tmplab <- datl[order(-Vieta)][id == 0, paste(Vieta_dzim, Dalībnieks, Grupa)]
datl[, pos := factor(Dzim, tmpval, tmplab)]

datl[Vieta < 11][order(pos)]
datl[sex == "V" & Vieta_dzim < 11][order(pos)]
datl[sex == "S" & Vieta_dzim < 11][order(pos)]

datl[, .N, keyby = Grupa]

plot_grupa <- function(dom = "VB") {
  datp <- datl[grep(dom, Grupa)][1:min(.N, (n + 1L) * 15)]
  pl <- ggplot(datp, aes(x = CP, y = pos, colour = pos)) +
    geom_point() + geom_path() +
    guides(colour = guide_legend(reverse = T)) +
    ggtitle("Stirnu buks 2017 Poikaiņi", paste("Grupa:", dom)) +
    xlab("Laiks") + ylab("") +
    theme_bw()
  return(pl)
}

plot_grupa("VB")
plot_grupa("SB")

tmp <- c("", "J", 2:4)
dom <- c(paste0("VB", tmp), paste0("SB", tmp))
nr <- sprintf("%02d", seq_along(dom))

plots <- lapply(dom, plot_grupa)
names(plots) <- paste0("SB2017-Pok-Buks-", nr, "-", dom, ".png")
names(plots)

for (f in names(plots)) {
  ggsave(f, plot = plots[[f]], device = "png")
}