用R列中的下一个值替换NA值

我正在努力 lag() 不生产 NA 价值观

df <- data.frame("Score" = as.numeric(c("20", "10", "15", "30", "15", "10")),
             "Time" = c("1", "2", "1", "2", "1", "2"),
             "Team" = c("A", "A", "B", "B", "C", "C"))

Diff 这将计算每个团队的得分差异:

 df <- df %>% 
 group_by(Team) %>% 
 mutate(Diff = Score - lag(Score))

我的问题是,这种方法会产生 显然,价值观:

  Score Time  Team   Diff
  20     1     A        NA
  10     2     A       -10
  15     1     B        NA
  30     2     B        15
  15     1     C        NA
  10     2     C        -5

我的目标是在最后做到这一点:

  Score Time  Team   Diff
  20     1     A       -10
  10     2     A       -10
  15     1     B        15
  30     2     B        15
  15     1     C        -5
  10     2     C        -5

我尝试使用 case_when() 函数替换 不适用

 df %>% 
 group_by(Team) %>% 
 mutate(Diff = Score - lag(Score)) %>% 
 mutate(Diff = case_when(
 NA ~ lead(Diff)
 ))

不管怎样,我该怎么做 值替换为下一个值 差异 价值