R/england_current.R

In jalapic/engsoccerdata: English and European Soccer Results 1871-2020

#' Get current England season data for all tiers
#'
#' @return a dataframe with results for current
#' season for top four divisions
#' @param Season the current Season
#' @importFrom utils "read.csv"
#' @examples
#' england_current()
#' @export

england_current <- function(Season=2022){

   ee1<-ee2<-myseason<-e1<-e2<-e3<-e4<-df1<-NULL
   myseason<-Season
   ee2<-as.numeric(substr(myseason,3,4))
   ee1 <- ee2+1

e1=read.csv(paste0("https://www.football-data.co.uk/mmz4281/",ee2,ee1,"/E0.csv"))
e2=read.csv(paste0("https://www.football-data.co.uk/mmz4281/",ee2,ee1,"/E1.csv"))
e3=read.csv(paste0("https://www.football-data.co.uk/mmz4281/",ee2,ee1,"/E2.csv"))
e4=read.csv(paste0("https://www.football-data.co.uk/mmz4281/",ee2,ee1,"/E3.csv"))

df1 <- rbind(engsoccerdata::getCurrentData(e1,1,1,Season=myseason),engsoccerdata::getCurrentData(e2,2,2,Season=myseason),
             engsoccerdata::getCurrentData(e3,3,3,Season=myseason),engsoccerdata::getCurrentData(e4,4,4,Season=myseason))

df1$Date <- as.Date(df1$Date, format="%Y-%m-%d")
eng <- engsoccerdata::england
if(identical(max(df1$Date), max(eng$Date))) warning("The returned dataframe contains data already included in 'scotland' dataframe")
tm <- engsoccerdata::teamnames
df1$home <- tm$name[match(df1$home,tm$name_other)]
df1$visitor <- tm$name[match(df1$visitor,tm$name_other)]
return(df1)
}



#################
#' Get current England season data for all tiers
#'
#' @return a dataframe with results for current
#' season for all top four divisions
#' @importFrom rvest "html_table"
#' @importFrom xml2 "read_html"
#' @importFrom dplyr "case_when"
#' @importFrom dplyr "mutate"
#' @importFrom magrittr "%>%"
#' @examples
#' england_current()
#' @export

# england_current <- function(){
#
#
#   home<-visitor<-hgoal<-vgoal<-goaldif<-FT<-Season<-division<-result<-NULL
#
#   url1 <- "https://www.11v11.com/competitions/premier-league/2022/matches/"
#   url2 <- "https://www.11v11.com/competitions/league-championship/2022/matches/"
#   url3 <- "https://www.11v11.com/competitions/league-one/2022/matches/"
#   url4 <- "https://www.11v11.com/competitions/league-two/2022/matches/"
#
#   x1 <- xml2::read_html(url1) %>% rvest::html_table(fill = TRUE)
#   x2 <- xml2::read_html(url2) %>% rvest::html_table(fill = TRUE)
#   x3 <- xml2::read_html(url3) %>% rvest::html_table(fill = TRUE)
#   x4 <- xml2::read_html(url4) %>% rvest::html_table(fill = TRUE)
#
#   make_data <- function(x){
#     x <- x[[1]][,1:4]
#     #    x <-x[grepl("([0-9]+).*$", x[,1]),]#get rid of months text
#     x <-x[grepl("([0-9]+).*$", unlist(x[,3])),]#get rid of months text
#     colnames(x)<-c("Date","home","FT","visitor")
#     x$Date <- as.character(as.Date(x$Date, format="%d %b %Y"))
#     x$Season <- 2021
#     x$FT <- gsub(":", "-", x$FT)
#     x <- x[nchar(x$FT)>1,]
#     hgvg <- matrix(unlist(strsplit(x$FT, "-")), ncol=2, byrow = T)
#     x$hgoal <- as.numeric(hgvg[,1])
#     x$vgoal <- as.numeric(hgvg[,2])
#     x$totgoal <- x$hgoal+x$vgoal
#     x$goaldif <- x$hgoal-x$vgoal
#     x$result <- ifelse(x$hgoal>x$vgoal, "H", ifelse(x$hgoal<x$vgoal, "A", "D"))
#     return(x)
#   }
#
#   x1d <- make_data(x1)
#   x2d <- make_data(x2)
#   x3d <- make_data(x3)
#   x4d <- make_data(x4)
#
#   x1d$division <- 1
#   x1d$tier <- 1
#   x2d$division <- 2
#   x2d$tier <- 2
#   x3d$division <- 3
#   x3d$tier <- 3
#   x4d$division <- 4
#   x4d$tier <- 4
#
#   xd <- rbind(x1d,x2d,x3d,x4d)
#   xd <- xd[colnames(engsoccerdata::england)]
#
#   xd %>%
#     dplyr::mutate(home = dplyr::case_when(
#       grepl("Brighton and Hove", home) ~ "Brighton & Hove Albion",
#       grepl("Cheltenham Town", home) ~ "Cheltenham",
#       grepl("Stevenage", home) ~ "Stevenage Borough",
#       grepl("Harrogate Town", home) ~ "Harrogate Town A.F.C.",
#       grepl("Macclesfield Town", home) ~ "Macclesfield",
#       grepl("Yeovil", home) ~ "Yeovil",
#       TRUE ~ home
#     )) %>%
#     dplyr::mutate(visitor = dplyr::case_when(
#       grepl("Brighton and Hove", visitor) ~ "Brighton & Hove Albion",
#       grepl("Cheltenham Town", visitor) ~ "Cheltenham",
#       grepl("Stevenage", visitor) ~ "Stevenage Borough",
#       grepl("Macclesfield Town", visitor) ~ "Macclesfield",
#       grepl("Harrogate Town", visitor) ~ "Harrogate Town A.F.C.",
#       grepl("Yeovil", visitor) ~ "Yeovil",
#       TRUE ~ visitor
#     )) -> xd
#
#   return(xd)
#
# }
#
#
# ## this is a nightmare with the teamnames Tranmere, Forest Green Rovers, Harrogate, Salford, Lincoln
#
# #   s1 <- s2 <- myseason <- tm <- df1 <- df <- . <- Date <- tier <- home <- visitor <- hgoal <- vgoal <- goaldif <- FT <- division <- result <- name <- name_other <- most_recent <- country <- NULL
# #
# #   myseason <- Season
# #   s2 <- as.numeric(substr(myseason, 3, 4))
# #   s1 <- s2 + 1
# #
# #   df <- rbind(read.csv(paste0("http://www.football-data.co.uk/mmz4281/ ", s2, s1, "/E0.csv")),
# #               read.csv(paste0("http://www.football-data.co.uk/mmz4281/ ", s2, s1, "/E1.csv")),
# #               read.csv(paste0("http://www.football-data.co.uk/mmz4281/ ", s2, s1, "/E2.csv")),
# #               read.csv(paste0("http://www.football-data.co.uk/mmz4281/ ", s2, s1, "/E3.csv"))
# #   )
# #
# #   df <- df[1:8]
# #   df$Date <- as.Date(df$Date, "%d/%m/%y")
# #
# #
# # df1 <- data.frame(Date = df$Date,
# #                   Season = myseason,
# #                   home = as.character(df$HomeTeam),
# #                   visitor = as.character(df$AwayTeam),
# #                   FT = paste0(df$FTHG,"-", df$FTAG),
# #                   hgoal = df$FTHG,
# #                   vgoal = df$FTAG,
# #                   division = as.numeric(factor(df$Div)),
# #                   tier = as.numeric(factor(df$Div)),
# #                   totgoal = df$FTHG + df$FTAG,
# #                   goaldif = df$FTHG - df$FTAG,
# #                   result = as.character(df$FTR)
# # )
# #
# # i <- sapply(df1, is.factor)
# # df1[i] <- lapply(df1[i], as.character)
# # df1$Date <- as.character(df1$Date)
# #
# # #fix teamnames
# # df1$home <- as.character(as.character(teamnames$name)[match(as.character(df1$home), as.character(teamnames$name_other))])
# # df1$visitor <- as.character(as.character(teamnames$name)[match(as.character(df1$visitor), as.character(teamnames$name_other))])
# #
# # return(df1)
#
#
#