在filter的数据中仅保留2018年至2022年，然后按学校、年份和filter添加频率计数列（仅"学校"），所有计数均大于或等于10，并且如果存在all，则为范围中的年份

library(dplyr)# version >= 1.1.0
Schools %>%
   filter(all(table(year[year %in% 2018:2022]) >= 10) & 
          all(2018:2022 %in% year), .by = c("school")) %>%
   as_tibble()

• 输出

# A tibble: 60 × 3
   school      year   stuff
   <chr>      <dbl>   <dbl>
 1 Washington  2016  0.680 
 2 Washington  2016 -1.14  
 3 Washington  2016  0.0420
 4 Washington  2016 -0.603 
 5 Washington  2016  2.05  
 6 Washington  2018 -0.810 
 7 Washington  2018  0.692 
 8 Washington  2018 -0.502 
 9 Washington  2018  0.464 
10 Washington  2018  0.397 
# … with 50 more rows

或者使用count

library(magrittr)
Schools %>% 
  filter(tibble(year) %>%
        filter(year %in% 2018:2022) %>%
        count(year) %>%
       pull(n) %>% 
       is_weakly_greater_than(10) %>% 
       all, all(2018:2022 %in% year) , .by = "school")

事实证明，一个朋友刚刚帮我想出了一个基R的解决方案。

# form 2-way table, school against year
sdTable = table(Schools$school, Schools$year)

# say want years 2018-2022 having lots of rows in school data
sdTable = sdTable[,3:7]

# which have >= 10 rows in all years 2018-2022
allGtEq = function(oneRow) all(oneRow >= 10)
whichToKeep = which(apply(sdTable,1,allGtEq))

# now whichToKeep is row numbers from the table; get the school names
whichToKeep = names(whichToKeep)

# back to school data
whichOrigRowsToKeep = which(Schools$school %in% whichToKeep)
newHousing = Schools[whichOrigRowsToKeep,]
newHousing