函数if else语句从不同的数据集中读取

Question

我对R非常陌生我试图让我的函数将输出的表格与我在函数中指定的列进行比较，当用户输入日期（mm/dd/yy）和季节（yyyy/yy）。我很困惑如何设置我的初始数据框。

所以有3个季节我从（3个网站）拉。我的IF语句应该读入一个df（称为dfmess，因为它是一团糟）。我该怎么做，希望这是有道理的，有人可以帮助我。我会很感激，如果有人能理清这个烂摊子给我...

Season_2015_16 <- read.csv("http://www.football-data.co.uk/mmz4281/1516/E0.csv", stringsAsFactors = FALSE) 
    Season_2014_15 <- read.csv("http://www.football-data.co.uk/mmz4281/1415/E0.csv", stringsAsFactors = FALSE) 
    Season_2013_14 <- read.csv("http://www.football-data.co.uk/mmz4281/1314/E0.csv", stringsAsFactors = FALSE) 

    **dfmess <- read.csv("http://www.football-data.co.uk/mmz4281/1516/E0.csv", stringsAsFactors = FALSE) 
    dfmess <- read.csv("http://www.football-data.co.uk/mmz4281/1415/E0.csv", stringsAsFactors = FALSE) 
    dfmess <- read.csv("http://www.football-data.co.uk/mmz4281/1314/E0.csv", stringsAsFactors = FALSE)** 

    EPL_Standings <- function(Standingdate, season){ 
     Standingdate <- as.Date(Standingdate, format = "%m/%d/%Y") 
     Standingdate <- as.Date("08/30/15", format = "%m/%d/%y") 
     if (season == "2015/16"){ 

     read.csv("http://www.football-data.co.uk/mmz4281/1516/E0.csv", stringsAsFactors = FALSE) -> dfmess 

     } else if (season == "2014/15") { 
     read.csv("http://www.football-data.co.uk/mmz4281/1415/E0.csv", stringsAsFactors = FALSE) -> dfmess 

     } else if (season == "2013/14"){ 
     read.csv("http://www.football-data.co.uk/mmz4281/1314/E0.csv", stringsAsFactors = FALSE) -> dfmess 

     } 

    dfmess[dfmess$Date <= Standingdate, 2:6] 
    #Team Record 


    ddply(dfmess, 
     .(HomeTeam) 
     , summarize 
     , win = sum(FTR == "H") 
     , Loss = sum(FTR == "A") 
     , Draws = sum(FTR == "D") 
) -> homewins1 #Homerecord 
    ddply(dfmess, 
     .(AwayTeam) 
     , summarize 
     , win = sum(FTR == "A") 
     , Loss = sum(FTR == "H") 
     , Draws = sum(FTR == "D") 
) -> awaywins1 #Awayrecord 

    merge(homewins1, awaywins1, by.x = "HomeTeam", by.y = "AwayTeam", all = TRUE) -> homeawayrec 

    #homeawayrec 
    (homeawayrec$win.x + homeawayrec$win.y) -> homeawayrec$totalwins #adds away and home wins together, then puts on table. renamed column later 
    (homeawayrec$Loss.x + homeawayrec$Loss.y) -> homeawayrec$Total.Losses #same as above, but Losses. Named consistently with what I changed too after I changed above column. 
    (homeawayrec$Draws.x + homeawayrec$Draws.y) -> homeawayrec$Total.Draws #same as above, but with Draws. 
    #names(homeawayrec) <- c("Teams","Home.Wins", "Home.Losses", "Home.Draws", "Away.Wins", "Away.Losses", "Away.Draws", "Total.Wins") #Name all columns. make sure name right thing. 

    #homeawayrec[, c("Teams", "Total.Wins", "Total.Draws", "Total.Losses")] -> WDL 

    #Need to make home and away record, should be easy. 

    #homewins1 #homerecord 
    #awaywins1 #awayrecord 

    #Matches Played 

    (homeawayrec$totalwins + homeawayrec$Total.Draws + homeawayrec$Total.Losses) -> homeawayrec$MatchesPlayed 
    #homeawayrec 

    #homeawayrec[, c("Teams", "MatchesPlayed")] -> Matches.Played 
    #Matches.Played #number of matches played 
    #POINTS (need to make it per match) 

    #ddply(dfmess, 
    # .(HomeTeam)     #DDPLY Points was eliminated because multiplying the wins by 3 and draws by 1 was easier. 
    # , summarize 
    # , win = 3*(sum(FTR == "H")) 
    # , Loss = 0*(sum(FTR == "A")) 
    #  , Draws = 1*(sum(FTR == "D")) 
    #) -> HomePoints #team points at home 

    #ddply(dfmess, 
    #  .(AwayTeam) 
    # , summarize 
    # , win = 3*(sum(FTR == "A")) 
    # , Loss = 0*(sum(FTR == "H")) 
    #  , Draws = 1*(sum(FTR == "D")) 
    #) -> AwayPoints #team points on road 

    #merge(HomePoints, AwayPoints, by.x = "HomeTeam", by.y = "AwayTeam", all = TRUE) -> Pointshomeaway 

    #(HomePoints$win +HomePoints$Draws + AwayPoints$win + AwayPoints$Draws) -> Pointshomeaway$TotalPoints 

    #names(Pointshomeaway) <- c("Teams", "HomeWinPoints", "HomeLossPoints", "HomeDrawPoints", "AwayWinPoints", "AwayLossPoints", "AwayDrawPoints", "TotalPoints") 

    #Pointshomeaway[, c("Teams", "TotalPoints")] -> Points.standings #table with just total points, total points standings. 
    #homeawayrec 
    (3*(homeawayrec$totalwins)+(1*(homeawayrec$Total.Draws))) -> homeawayrec$Points 

    #points per match and point percentage % 
    #homeawayrec 
    (3*(homeawayrec$totalwins)+(1*(homeawayrec$Total.Draws)))/(homeawayrec$MatchesPlayed) -> homeawayrec$PPM 

    #homeawayrec[, c("Teams", "PointsPerMatch")] -> PointsPer.Standings #standings with teams and points per match. 

    #Point Percentage 
    (homeawayrec$Points)/(3*(homeawayrec$MatchesPlayed)) -> homeawayrec$PtPct 
    #homeawayrec 
    #Goals Scored 

    ddply(dfmess,       #THIS WORKED, make sure HomeTeam and FTHG/AwayTeam and FTAG match up. Goals allowed will be the inverse for each. 
     .(HomeTeam) 
     , summarize 
     , goalsscored1 = sum(FTHG) 
) -> Homegoalmade1 
    ddply(dfmess, 
     .(AwayTeam) 
     , summarize 
     , goalsscored1 = sum(FTAG) 
) -> Awaygoalsmade1 

    merge(Homegoalmade1, Awaygoalsmade1, by.x = "HomeTeam", by.y = "AwayTeam", all = TRUE) -> goalsmade1 #merged home/away goalsmmade1 THIS WORKED 
    (goalsmade1$goalsscored1.x + goalsmade1$goalsscored1.y) -> goalsmade1$allgoalsmade1 #total goalsmade 

    #goalsmade1 

    goalsmade1[, c("HomeTeam", "allgoalsmade1")] -> GS 

    merge(homeawayrec, GS, by.x = "HomeTeam", by.y = "HomeTeam", all = TRUE) -> homeawayrec1 
    #homeawayrec 
    #homeawayrec1 

    #Goals Scored Per Match 
    ((homeawayrec1$allgoalsmade1)/(homeawayrec1$MatchesPlayed)) -> homeawayrec1$GSM 
    #homeawayrec1 

    #Goals Allowed 
    ddply(dfmess,       #THIS WORKED, make sure HomeTeam and FTAG/AwayTeam and FTHG match up. Goals scored will be the inverse for each. 
     .(HomeTeam) 
     , summarize 
     , goalsscored1 = sum(FTAG) 
) -> Homegoalallowed1 
    ddply(dfmess, 
     .(AwayTeam) 
     , summarize 
     , goalsscored1 = sum(FTHG) 
) -> Awaygoalsallowed1 

    merge(Homegoalallowed1, Awaygoalsallowed1, by.x = "HomeTeam", by.y = "AwayTeam", all = TRUE) -> goalsallowed1 

    (goalsallowed1$goalsscored1.x + goalsallowed1$goalsscored1.y) -> goalsallowed1$GA 

    #goalsallowed1 

    goalsallowed1[, c("HomeTeam", "allgoalsallowed1")] -> GoalsAllowedall 

    merge(homeawayrec1, goalsallowed1, by.x = "HomeTeam", by.y = "HomeTeam", all = TRUE) -> homeawayrec2 

    #Goals Allowed Per Match 

    ((homeawayrec2$GA)/homeawayrec2$MatchesPlayed) -> homeawayrec2$GAM 
    names(homeawayrec2) 
    #putting columns in correct order 
    #if I rename columns the function gets confused and won't work? 
    homeawayrec2[, c(1, 8, 10, 9, 2, 4, 3, 5, 7, 6, 11, 12, 13, 14, 15, 16, 19, 20)] 
    #Last 10 matches played 
    ((tail(homeawayrec2$totalwins, n=10)) (tail(homeawayrec2$Total.Draws, n=10)) (tail(homeawayrec2$Total.Losses, n=10))) 
    tail(homeawayrec2[, c("totalwins", "Total.Draws", "Total.Losses")], n=10) 
    homeawayrec2 
    print(homeawayrec2) 
    return(dfmess) 
} 
     ((homeawayrec2$GA)/homeawayrec2$MatchesPlayed) -> homeawayrec2$GAM 
     names(homeawayrec2) 
     homeawayrec2[, c(1, 8, 10, 9, 2, 4, 3, 5, 7, 6, 11, 12, 13, 14, 15, 16, 19, 20)] 
     print(homeawayrec2) 
     return(dfmess) 
    } 
    A <- EPL_Standings("09/26/14", "2013/14") #example numbers, placeholders. 
    head(A) 

Answer 1

这里是一个开始。一般来说，最好将相似的数据保存在同一张表中。

library(dplyr) 
library(lubridate) 
library(magrittr) 

data = 
    data_frame(start_season = c(2013, 2014, 2015)) %>% 
    mutate(url = 
      (start_season - 2000) %>% 
      paste0(., . + 1) %>% 
      sprintf("http://www.football-data.co.uk/mmz4281/%s/E0.csv", .)) %>% 
    group_by(start_season) %>% 
    do(read.csv(.$url)) %>% 
    mutate(Date = dmy(Date) %>% as.Date) %>% 
    arrange(Date) 

cutoffs = 
    data %>% 
    group_by(start_season) %>% 
    summarize(start_date = first(Date)) 

EPL_Standings = function(specific_date) { 

    specific_date = mdy(specific_date) %>% as.Date 

    this_season_so_far = 
    cutoffs %>% 
    filter(specific_date > start_date) %>% 
    last %>% 
    left_join(data) %>% 
    filter(Date <= specific_date) 

    # some sort of processing here 
}