R 如何跨多个列对同一值进行分组并对后续值求和？

我有一个如下所示的信息表：

  rusher_full_name  receiver_full_name rushing_fpts receiving_fpts
  <chr>             <chr>                     <dbl>          <dbl>
1 Aaron Jones       NA                          5              0  
2 NA                Aaron Jones                 0              5
3 Mike Davis        NA                          0.5            0
4 NA                Allen Robinson              0              3  
5 Mike Davis        NA                          0.7            0

rusher\u full\u name receiver\u full\u name rush\u fpts receiving\u fpts
1 Aaron Jones NA 5 0
2纳阿伦琼斯0 5
3迈克·戴维斯NA 0.5 0
4NA艾伦·罗宾逊03
5迈克·戴维斯NA 0.7 0

我想做的是根据rusher\u full\u名称和RECEINER\u full\u名称的值，从rusher\u FPT和RECEINER\u FPT中获取所有的值。例如，对于“Aaron Jones”的每个实例（无论是rusher_full_name还是receiver_full_name），将Rush_FPT和receiving_FPT的值相加

最后，我希望它是这样的：

  player_full_name    total_fpts
  <chr>                    <dbl>
1 Aaron Jones                 10  
2 Mike Davis                 1.2
3 Allen Robinson               3  

player\u full\u name总计\u fpts
1亚伦·琼斯10
2迈克·戴维斯1.2
艾伦·罗宾逊3

我对使用R非常陌生，在谷歌上搜索了很多东西，但找不到任何解决方案。关于如何做到这一点有什么建议吗

library(tidyverse)

df %>%
  mutate(player_full_name = coalesce(rusher_full_name, receiver_full_name)) %>%
  group_by(player_full_name) %>%
  summarise(total_fpts = sum(rushing_fpts+receiving_fpts))

输出

# A tibble: 3 x 2
  player_full_name total_fpts
  <chr>                 <dbl>
1 Aaron Jones            10  
2 Allen Robinson          3  
3 Mike Davis              1.2

#一个tible:3 x 2
玩家全名总FPT
1亚伦·琼斯10
2艾伦·罗宾逊3
3迈克·戴维斯1.2

数据

df <- data.frame(
  rusher_full_name = c("Aaron Jones", NA, "Mike Davis", NA, "Mike Davis"),
  receiver_full_name = c(NA, "Aaron Jones", NA, "Allen Robinson", NA),
  rushing_fpts = c(5,0,0.5,0,.7),
  receiving_fpts = c(0,5,0,3,0),
  stringsAsFactors = FALSE
)

df