问题
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$HomeTeam))
I have imported all played matches from another dataframe. And for every team I try to execute if loop based on subset of team matches. First I filter all home matches. So my code is
for (Team1 in row.names.data.frame(df.work)){
a1 <- filter(df.clean, HomeTeam == Team1)
if (a1$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
}
But I struggle why it did not loop for every row in a1 and sum the points?
Edit: 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
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
回答1:
Here's a dplyr solution to transform df.clean into the desired result without using loops. The data set was easy enough to replicate from public resources.
library(dplyr)
library(tidyr)
df.clean %>%
pivot_longer(1:2, names_to = "HA", values_to = "Team") %>%
group_by(Team) %>%
mutate(Goals.Conceded = ifelse(HA == "HomeTeam", away.goals, home.goals)) %>%
mutate(Goals.Scored = ifelse(HA == "HomeTeam", home.goals, away.goals)) %>%
mutate(Points = ifelse(Goals.Scored > Goals.Conceded, 3,
ifelse(Goals.Scored == Goals.Conceded, 1, 0))) %>%
mutate(Games = 1) %>%
select(c(8, 6:5, 7)) %>%
summarise_all(sum) %>%
arrange(-Points)
Which yields:
#> # A tibble: 20 x 5
#> Team Games Goals.Scored Goals.Conceded Points
#> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 Liverpool 32 70 25 86
#> 2 Man City 32 81 33 66
#> 3 Leicester 32 60 31 55
#> 4 Chelsea 32 57 44 54
#> 5 Man Utd 32 51 31 52
#> 6 Wolves 32 45 34 52
#> 7 Sheffield Utd 32 33 32 47
#> 8 Arsenal 32 47 41 46
#> 9 Burnley 32 36 45 45
#> 10 Spurs 32 51 44 45
#> 11 Everton 32 40 47 44
#> 12 Crystal Palace 32 28 37 42
#> 13 Newcastle 32 33 43 42
#> 14 Southampton 32 41 55 40
#> 15 Brighton 32 34 44 33
#> 16 West Ham 32 38 56 30
#> 17 Watford 32 29 49 28
#> 18 Aston Villa 32 36 60 27
#> 19 Bournemouth 32 30 54 27
#> 20 Norwich 32 25 60 21
Data
df.clean <- structure(list(HomeTeam = structure(c(10L, 19L, 3L, 5L, 7L, 18L,
17L, 9L, 13L, 12L, 1L, 2L, 4L, 8L, 14L, 16L, 11L, 15L, 6L, 20L,
2L, 14L, 4L, 12L, 15L, 18L, 10L, 3L, 17L, 20L, 16L, 6L, 7L, 9L,
11L, 13L, 19L, 5L, 8L, 1L, 10L, 4L, 12L, 15L, 17L, 20L, 14L,
3L, 18L, 2L, 16L, 9L, 5L, 8L, 11L, 13L, 7L, 19L, 1L, 6L, 15L,
3L, 2L, 6L, 7L, 17L, 20L, 8L, 9L, 12L, 4L, 5L, 10L, 14L, 18L,
19L, 1L, 11L, 16L, 13L, 8L, 3L, 2L, 6L, 9L, 17L, 20L, 7L, 12L,
15L, 16L, 11L, 4L, 18L, 19L, 5L, 13L, 1L, 10L, 14L, 3L, 1L, 2L,
4L, 11L, 15L, 19L, 18L, 7L, 8L, 14L, 6L, 5L, 13L, 16L, 17L, 9L,
12L, 20L, 10L, 19L, 3L, 1L, 4L, 7L, 8L, 18L, 11L, 15L, 2L, 13L,
5L, 6L, 10L, 17L, 16L, 14L, 20L, 9L, 12L, 7L, 5L, 9L, 20L, 12L,
6L, 16L, 10L, 15L, 1L, 8L, 3L, 17L, 18L, 11L, 2L, 13L, 14L, 4L,
19L, 10L, 5L, 6L, 9L, 15L, 16L, 12L, 20L, 1L, 7L, 8L, 3L, 2L,
4L, 13L, 14L, 11L, 18L, 17L, 17L, 3L, 2L, 6L, 7L, 8L, 15L, 12L,
9L, 20L, 4L, 13L, 16L, 18L, 14L, 19L, 5L, 1L, 10L, 11L, 4L, 5L,
13L, 16L, 18L, 11L, 14L, 19L, 1L, 10L, 15L, 7L, 6L, 8L, 9L, 12L,
20L, 17L, 3L, 2L, 18L, 1L, 4L, 11L, 14L, 16L, 19L, 13L, 5L, 10L,
3L, 2L, 8L, 15L, 7L, 6L, 9L, 17L, 12L, 20L, 19L, 9L, 3L, 7L,
10L, 13L, 18L, 19L, 12L, 5L, 17L, 8L, 4L, 15L, 20L, 16L, 14L,
2L, 1L, 6L, 11L, 6L, 5L, 7L, 15L, 16L, 9L, 12L, 20L, 1L, 10L,
14L, 4L, 3L, 13L, 19L, 18L, 8L, 17L, 10L, 1L, 7L, 15L, 16L, 20L,
5L, 6L, 12L, 9L, 2L, 11L, 14L, 17L, 18L, 4L, 19L, 3L, 13L, 2L,
8L, 11L, 9L, 17L, 12L, 13L, 14L, 20L, 10L, 5L, 16L, 6L, 2L, 18L,
7L, 4L, 3L, 1L, 8L, 19L, 15L, 11L), .Label = c("Arsenal", "Aston Villa",
"Bournemouth", "Brighton", "Burnley", "Chelsea", "Crystal Palace",
"Everton", "Leicester", "Liverpool", "Man City", "Man Utd", "Newcastle",
"Norwich", "Sheffield Utd", "Southampton", "Spurs", "Watford",
"West Ham", "Wolves"), class = "factor"), AwayTeam = structure(c(14L,
11L, 15L, 16L, 8L, 4L, 2L, 20L, 1L, 6L, 5L, 3L, 19L, 18L, 13L,
10L, 17L, 7L, 9L, 12L, 8L, 6L, 16L, 7L, 9L, 19L, 1L, 11L, 13L,
5L, 12L, 15L, 2L, 3L, 4L, 18L, 14L, 10L, 20L, 17L, 13L, 5L, 9L,
16L, 7L, 6L, 11L, 8L, 1L, 19L, 3L, 17L, 14L, 15L, 18L, 4L, 20L,
12L, 2L, 10L, 10L, 19L, 5L, 4L, 14L, 16L, 18L, 11L, 13L, 1L,
17L, 8L, 9L, 2L, 15L, 7L, 3L, 20L, 6L, 12L, 19L, 14L, 4L, 13L,
5L, 18L, 16L, 11L, 10L, 1L, 9L, 2L, 8L, 3L, 15L, 6L, 20L, 7L,
17L, 12L, 12L, 20L, 10L, 14L, 16L, 5L, 13L, 6L, 9L, 17L, 18L,
7L, 19L, 3L, 8L, 15L, 1L, 4L, 2L, 11L, 17L, 20L, 16L, 9L, 10L,
14L, 5L, 6L, 12L, 13L, 11L, 7L, 19L, 4L, 3L, 18L, 1L, 15L, 8L,
2L, 3L, 11L, 18L, 19L, 17L, 2L, 14L, 8L, 13L, 4L, 6L, 10L, 5L,
7L, 12L, 9L, 16L, 15L, 20L, 1L, 18L, 13L, 3L, 14L, 2L, 19L, 8L,
17L, 11L, 4L, 1L, 5L, 16L, 15L, 7L, 20L, 9L, 12L, 6L, 4L, 1L,
14L, 16L, 19L, 5L, 18L, 13L, 10L, 11L, 3L, 8L, 7L, 2L, 17L, 9L,
12L, 6L, 20L, 15L, 6L, 2L, 9L, 17L, 20L, 8L, 7L, 3L, 12L, 15L,
19L, 1L, 5L, 4L, 16L, 14L, 13L, 10L, 18L, 11L, 17L, 15L, 2L,
7L, 3L, 20L, 8L, 6L, 9L, 12L, 4L, 18L, 13L, 11L, 16L, 1L, 19L,
14L, 5L, 10L, 10L, 6L, 2L, 15L, 16L, 14L, 8L, 4L, 20L, 1L, 11L,
7L, 18L, 3L, 9L, 5L, 10L, 17L, 13L, 12L, 19L, 17L, 3L, 13L, 4L,
2L, 11L, 18L, 14L, 8L, 19L, 9L, 7L, 6L, 5L, 16L, 10L, 12L, 20L,
3L, 19L, 18L, 14L, 13L, 4L, 17L, 8L, 11L, 2L, 15L, 1L, 16L, 12L,
9L, 1L, 20L, 7L, 15L, 6L, 10L, 5L, 4L, 19L, 15L, 2L, 8L, 3L,
7L, 18L, 1L, 11L, 20L, 16L, 5L, 12L, 13L, 14L, 9L, 6L, 17L, 10L
), .Label = c("Arsenal", "Aston Villa", "Bournemouth", "Brighton",
"Burnley", "Chelsea", "Crystal Palace", "Everton", "Leicester",
"Liverpool", "Man City", "Man Utd", "Newcastle", "Norwich", "Sheffield Utd",
"Southampton", "Spurs", "Watford", "West Ham", "Wolves"), class = "factor"),
home.goals = c(4, 0, 1, 3, 0, 0, 3, 0, 0, 4, 2, 1, 1, 1,
3, 1, 2, 1, 1, 1, 2, 2, 0, 1, 1, 1, 3, 1, 0, 1, 1, 2, 1,
3, 4, 1, 2, 0, 3, 2, 3, 1, 1, 0, 4, 2, 3, 3, 2, 0, 1, 2,
2, 0, 8, 0, 1, 2, 3, 1, 0, 2, 2, 2, 2, 2, 2, 1, 5, 1, 3,
1, 2, 1, 0, 1, 1, 0, 1, 1, 2, 0, 2, 1, 2, 1, 1, 0, 1, 1,
0, 3, 3, 0, 1, 2, 1, 2, 2, 1, 1, 1, 1, 2, 2, 3, 2, 1, 0,
1, 0, 2, 3, 2, 1, 1, 2, 3, 2, 3, 2, 1, 2, 0, 1, 0, 0, 2,
3, 2, 2, 0, 0, 2, 3, 2, 2, 1, 2, 2, 1, 1, 2, 2, 2, 2, 2,
5, 0, 1, 3, 0, 5, 0, 1, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 0,
1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 3, 2, 0, 2, 1, 1, 0, 2, 1,
1, 4, 0, 3, 2, 1, 1, 3, 2, 1, 0, 1, 1, 2, 1, 1, 0, 1, 2,
2, 1, 4, 2, 2, 1, 1, 3, 1, 1, 4, 1, 0, 0, 1, 0, 1, 1, 2,
1, 2, 1, 1, 2, 2, 3, 2, 2, 0, 0, 2, 4, 2, 0, 1, 0, 2, 2,
0, 4, 0, 2, 3, 0, 0, 2, 3, 1, 2, 0, 1, 0, 2, 4, 0, 2, 2,
3, 1, 1, 2, 0, 3, 3, 3, 3, 1, 0, 2, 0, 3, 3, 1, 2, 2, 1,
1, 1, 0, 0, 1, 4, 2, 4, 0, 3, 0, 1, 1, 2, 0, 0, 3, 1, 0,
5, 0, 2, 3, 1, 0, 1, 4, 1, 0, 2, 0, 1, 0, 0, 1, 4, 2, 3,
3, 4), away.goals = c(1, 5, 1, 0, 0, 3, 1, 0, 1, 0, 1, 2,
1, 0, 1, 2, 2, 0, 1, 1, 0, 3, 2, 2, 2, 3, 1, 3, 1, 1, 1,
2, 0, 1, 0, 1, 0, 3, 2, 2, 1, 1, 0, 1, 0, 5, 2, 1, 2, 0,
3, 1, 0, 2, 0, 0, 1, 0, 2, 2, 1, 2, 2, 0, 0, 1, 0, 3, 0,
1, 0, 0, 1, 5, 0, 2, 0, 2, 4, 0, 0, 0, 1, 0, 1, 1, 1, 2,
1, 0, 9, 0, 2, 0, 1, 4, 1, 2, 1, 3, 0, 1, 2, 0, 1, 0, 3,
2, 2, 1, 2, 0, 0, 1, 2, 1, 0, 1, 1, 1, 3, 2, 2, 2, 2, 2,
3, 1, 3, 0, 2, 2, 1, 1, 2, 1, 2, 1, 1, 2, 0, 4, 0, 0, 1,
1, 1, 2, 2, 2, 1, 3, 0, 0, 2, 4, 1, 2, 2, 3, 0, 0, 1, 1,
0, 1, 1, 2, 3, 1, 0, 1, 3, 1, 0, 2, 1, 0, 2, 1, 1, 0, 2,
1, 0, 1, 1, 4, 2, 0, 2, 1, 0, 2, 2, 2, 2, 0, 0, 1, 2, 3,
0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 2, 0, 1, 1, 3, 6, 0, 1,
1, 2, 0, 3, 1, 0, 1, 0, 1, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2,
2, 1, 1, 0, 0, 3, 3, 0, 0, 0, 1, 1, 1, 0, 2, 1, 3, 0, 2,
0, 1, 0, 0, 1, 0, 1, 0, 0, 2, 2, 0, 1, 2, 0, 1, 0, 1, 3,
1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 3, 1, 1, 1, 2, 2, 0,
2, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 2, 1, 1, 3, 1, 3, 4, 0,
1, 2, 1, 0)), row.names = c(NA, 320L), class = "data.frame")
回答2:
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$AwayTeam)
away <- sapply(sp2, function(DF){
goals2points(DF[['away.goals']], DF[['home.goals']])
})
Points <- rowSums(cbind(home, away))
result <- data.frame(Games = lengths(sp1) + lengths(sp2),
Goals.Scored,
Goals.Conceded,
Points)
result
# Games Goals.Scored Goals.Conceded Points
#A 8 24 22 12
#B 8 26 21 15
#C 8 23 21 12
#D 8 17 24 7
#E 8 23 25 13
Test data
set.seed(2020)
df.clean <- expand.grid(HomeTeam = LETTERS[1:5], AwayTeam = LETTERS[1:5])
df.clean <- df.clean[apply(df.clean, 1, function(x) x[1] != x[2]), ]
df.clean$home.goals <- sample(0:5, nrow(df.clean), TRUE)
df.clean$away.goals <- sample(0:5, nrow(df.clean), TRUE)
来源：https://stackoverflow.com/questions/62740230/computing-points-for-a-football-team