data.frame：有条件地添加行

Question

我有一个数据punkt_tabelle其中包含游戏中的得分。 每个游戏有2套或3套（MRE中为3套）。 数据框包含这些点的制作方式。 我也有分数的结尾，存储在scores 。 我计算每个组中每个团队的总和。 （我在total_pts中total_pts ）。

我要达到的目的是将数据表中的得分总和（每个团队和每个组）与该团队根据scores得出的scores 。 如果此集合中的scores大于计算为total的总和，那么我想向数据表添加额外的一行。 此新行应包含队名，此新行的设置和技能应为“ Pkt Errors” ，而Pkt的值将是scores和total之间的差。 可能（在MRE中就是这种情况），必须为每个团队和每个组添加一个新行。

如果您在添加新行后重新运行total_pts计算，则它将等于scores的结果。

我根据这些问题和文章尝试了以下代码的变体（ R使用管道运算符％>％时的条件评估， 为每个组id向数据框中插入新行 ），但无法解决我的问题。

这是我的代码的最新版本：

library(dplyr)
library (devtools)

punkt_tabelle <- structure(list(Team = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 
                 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
                 1L), .Label = c("Miller/Myer", "Winter/Summer"), class = "factor"), 
                 Skill = structure(c(1L, 1L, 3L, 2L, 2L, 2L, 1L, 1L, 3L, 2L, 
                 2L, 2L, 4L, 4L, 5L, 6L, 6L, 6L, 4L, 4L, 5L, 6L, 6L, 6L), .Label = c("Attack", 
                 "Service", "Block", "Opp. Attack Error", "Opp. Block Error", 
                 "Opp. Serve Error"), class = "factor"), Set = c(2L, 3L, 2L, 
                 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 2L, 1L, 2L, 3L, 
                 1L, 2L, 3L, 1L, 2L, 3L), Pkt = c(2L, 1L, 1L, 0L, 0L, 0L, 
                 3L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 
                 0L, 1L, 0L)), row.names = c(NA, -24L), vars = c("Team", "Skill"
                 ), indices = list(0:1, 2L, 18:19, 20L, 21:23, 3:5, 6:7, 8L, 12:13, 
                 14L, 15:17, 9:11), group_sizes = c(2L, 1L, 2L, 1L, 3L, 3L, 
                 2L, 1L, 2L, 1L, 3L, 3L), biggest_group_size = 3L, labels = structure(list(
                 Team = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
                 2L, 2L), .Label = c("Miller/Myer", "Winter/Summer"), class = "factor"), 
                 Skill = c("Attack", "Block", "Opp. Attack Error", "Opp. Block Error", 
                 "Opp. Serve Error", "Service", "Attack", "Block", "Opp. Attack Error", 
                 "Opp. Block Error", "Opp. Serve Error", "Service")), row.names = c(NA, 
                 -12L), class = "data.frame", vars = c("Team", "Skill")), class = c("grouped_df", 
                  "tbl_df", "tbl", "data.frame"))



score_miller_myer <- c(3,6,3) #total points in sets 1, 2, 3
score_winter_summer <- c(5,4,5)
scores <- c(score_miller_myer, score_winter_summer)

#calculate the sum of the points per team and per set
total_pts <- punkt_tabelle %>% group_by(Team, Set) %>% summarize(total = sum(Pkt))
total_pts

#try to compare with the score and add en entry in the dataframe
punkt_tabelle %>% 
  group_by (Team, Set) %>% 
  mutate(total = sum(Pkt)) %>% 
  {if (total<scores) dplyr::bind_rows(Team=Team, Set=Set, Skill="Opp. Other Error", Pkt=(total-scores))}

punkt_tabelle

可以这样做吗？ 还是我需要使用循环并为每个组和每个团队手动执行？ 请帮忙！

编辑：此示例中的预期输出将如下所示：

Team          Skill               Set   Pkt
<fct>         <fct>             <int> <int>
 1 Miller/Myer   Attack                2     2
 2 Miller/Myer   Attack                3     1
 3 Miller/Myer   Block                 2     1
 4 Miller/Myer   Service               1     0
 5 Miller/Myer   Service               2     0
 6 Miller/Myer   Service               3     0
 7 Winter/Summer Attack                1     3
 8 Winter/Summer Attack                2     1
 9 Winter/Summer Block                 3     1
10 Winter/Summer Service               1     0
11 Winter/Summer Service               2     1
12 Winter/Summer Service               3     1
13 Winter/Summer Opp. Attack Error     2     0
14 Winter/Summer Opp. Attack Error     3     0
15 Winter/Summer Opp. Block Error      2     0
16 Winter/Summer Opp. Serve Error      1     0
17 Winter/Summer Opp. Serve Error      2     1
18 Winter/Summer Opp. Serve Error      3     1
19 Miller/Myer   Opp. Attack Error     1     1
20 Miller/Myer   Opp. Attack Error     2     0
21 Miller/Myer   Opp. Block Error      3     0
22 Miller/Myer   Opp. Serve Error      1     0
23 Miller/Myer   Opp. Serve Error      2     1
24 Miller/Myer   Opp. Serve Error      3     0
25 Winter/Summer Opp. Other Error      1     2  #here start the added rows
26 Winter/Summer Opp. Other Error      2     1  
27 Winter/Summer Opp. Other Error      3     2
28 Miller/Myer   Opp. Other Error      1     2
29 Miller/Myer   Opp. Other Error      2     2
30 Miller/Myer   Opp. Other Error      3     2

问题的进一步解释：团队以各种方式评分。 他们要么自己得分（进攻，发球，盖帽），要么对手犯错（进攻错误，进攻发球，盖帽错误）。 仍然给他们达到的总分留下一些差异，因为对手的一些错误未指定。 为此，我要在计算差异后添加“其他错误”行。

示例：在第26行：Pkt的值为1，因为在total_pts 2组团队的total_pts中，Winter / Summer获得3分。 但是他们根据score_winter_summer组中的score_winter_summer的得分是4分。 因此，在新行中添加了1点的差异。

Answer 1

这是一种可能性。

1. 首先，我们需要将scores存储在data.frame ，其中包含有关Team和Set

    df.scores <- data.frame( Team = c(rep("Miller/Myer", 3), rep("Winter/Summer", 3)), Set = 1:3, scores = scores) 

   让我们检查df.scores

    df.scores # Team Set scores #1 Miller/Myer 1 3 #2 Miller/Myer 2 6 #3 Miller/Myer 3 3 #4 Winter/Summer 1 5 #5 Winter/Summer 2 4 #6 Winter/Summer 3 5 

2. 接下来，我们做一个左连接的punk_tabelle与df.scores的Team和Set ，计算总积分Total = sum(Pkt)的Team和Set ; Opp. Other Error 然后，通过scores与Total之间的差异给出Opp. Other Error 。 通过长到宽到长的转换，可以达到最终的预期输出。

    punkt_tabelle %>% left_join(df.scores) %>% group_by(Team, Set) %>% mutate( Total = sum(Pkt), `Opp. Other Error` = scores - Total) %>% spread(Skill, Pkt) %>% select(-scores, -Total) %>% gather(Skill, Pkt, -Team, -Set) #Joining, by = c("Team", "Set") ## A tibble: 42 x 4 ## Groups: Team, Set [6] # Team Set Skill Pkt # <fct> <int> <chr> <dbl> # 1 Miller/Myer 1 Opp. Other Error 2 # 2 Miller/Myer 2 Opp. Other Error 2 # 3 Miller/Myer 3 Opp. Other Error 2 # 4 Winter/Summer 1 Opp. Other Error 2 # 5 Winter/Summer 2 Opp. Other Error 1 # 6 Winter/Summer 3 Opp. Other Error 2 # 7 Miller/Myer 1 Attack NA # 8 Miller/Myer 2 Attack 2 # 9 Miller/Myer 3 Attack 1 #10 Winter/Summer 1 Attack 3 ## ... with 32 more rows