计算足球队的积分

本文介绍了计算足球队的积分的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

每个人.我正在尝试计算足球队的积分.我有我的数据框df.work"行名=团队名: rownames(df.work)<-c(as.vector(teams $ HomeTeam))

everyone. I am trying to calculate football team points. I have my dataframe "df.work" with rownames = teamnames: rownames(df.work) <- c(as.vector(teams$HomeTeam))

我已从另一个数据帧导入了所有已进行的比赛.对于每个团队，我都尝试根据团队匹配项的子集执行if循环.首先，我过滤所有主场比赛.所以我的代码是

I have imported all played matches from another dataframe. And for every team I try to execute if loop based on subset of team matches. First I filter all home matches. So my code is

for (Team1 in row.names.data.frame(df.work)){ a1 <- filter(df.clean, HomeTeam == Team1) if (a1$home.goals > a1$away.goals) { df.work[Team1,"Points"] <- df.work[Team1,"Points"] + 3 } else if(a1$home.goals == a1$away.goals) { df.work[Team1,"Points"] <- df.work[Team1,"Points"] + 1 }

但是我很努力，为什么它没有对a1中的每一行进行循环并求和呢?

But I struggle why it did not loop for every row in a1 and sum the points?

这是头(df.clean):

this is head(df.clean):

HomeTeam AwayTeam home.goals away.goals 1 Liverpool Norwich 4 1 2 West Ham Man City 0 5 3 Bournemouth Sheffield United 1 1 4 Burnley Southampton 3 0 5 Crystal Palace Everton 0 0 6 Watford Brighton 0 3

头(df.work)是

and head(df.work) is

Games Goals.Scored Goals.Conceded Points Liverpool 32 70 25 3 West Ham 32 38 56 0 Bournemouth 32 30 54 1 Burnley 32 36 45 3 Crystal Palace 32 28 37 1 Watford 32 29 49 0

推荐答案

我相信以下是问题的要求.

I believe the following is what the question asks for.

goals2points <- function(x, y){ pnts <- sign(x - y) + 1 pnts[pnts == 2] <- 3 sum(pnts) } hg <- aggregate(home.goals ~ HomeTeam, df.clean, sum) ag <- aggregate(away.goals ~ AwayTeam, df.clean, sum) Goals.Scored <- hg[[2]] + ag[[2]] hg <- aggregate(home.goals ~ AwayTeam, df.clean, sum) ag <- aggregate(away.goals ~ HomeTeam, df.clean, sum) Goals.Conceded <- hg[[2]] + ag[[2]] sp1 <- split(df.clean, df.clean$HomeTeam) home <- sapply(sp1, function(DF){ goals2points(DF[['home.goals']], DF[['away.goals']]) }) sp2 <- split(df.clean, df.clean$AwayTeam) away <- sapply(sp2, function(DF){ goals2points(DF[['away.goals']], DF[['home.goals']]) }) Points <- rowSums(cbind(home, away)) result <- data.frame(Games = lengths(sp1) + lengths(sp2), Goals.Scored, Goals.Conceded, Points) result # Games Goals.Scored Goals.Conceded Points #A 8 24 22 12 #B 8 26 21 15 #C 8 23 21 12 #D 8 17 24 7 #E 8 23 25 13

测试数据

set.seed(2020) df.clean <- expand.grid(HomeTeam = LETTERS[1:5], AwayTeam = LETTERS[1:5]) df.clean <- df.clean[apply(df.clean, 1, function(x) x[1] != x[2]), ] df.clean$home.goals <- sample(0:5, nrow(df.clean), TRUE) df.clean$away.goals <- sample(0:5, nrow(df.clean), TRUE)