如果你想在列表中找到重复的行，可以使用group_split()和hablar::find_duplicates：

library(dplyr)                                                                                                                                                                   

df %>% 
  group_split(annee) %>% 
  purrr::map(hablar::find_duplicates)

输出：

[[1]]
# A tibble: 2 × 7
  finess    ghm2   dp    dr     sexe modeEntree annee
  <chr>     <chr>  <chr> <chr> <int> <chr>      <int>
1 450000245 02C05J H251  NA        1 8           2018
2 450000245 02C05J H251  NA        1 8           2018

[[2]]
# A tibble: 0 × 7
# … with 7 variables: finess <chr>, ghm2 <chr>, dp <chr>, dr <chr>, sexe <int>,
#   modeEntree <chr>, annee <int>
# ℹ Use `colnames()` to see all variable names

[[3]]
# A tibble: 2 × 7
  finess    ghm2   dp    dr     sexe modeEntree annee
  <chr>     <chr>  <chr> <chr> <int> <chr>      <int>
1 570000646 02C05J H258  NA        2 8           2020
2 570000646 02C05J H258  NA        2 8           2020

你的代码确实可以工作，但是当你设置一个列表的第2018个元素时，R会将之前的所有2017个元素都创建为NULL。所以打印整个列表会显示很多NULL元素。
你可以只打印你想要的：

> mylist[2018:2020]
[[1]]

FALSE  TRUE 
    9     1 

[[2]]

FALSE 
   10 

[[3]]

FALSE  TRUE 
    9     1

或者你可以使用一个字符来索引它们：

mylist<-list()
for(i in 2018:2020){
  temp<-mydata%>%filter(annee==i)
  mylist[[as.character(i)]]<-table(duplicated(temp))
}
mylist
$`2018`

FALSE  TRUE 
    9     1 

$`2019`

FALSE 
   10 

$`2020`

FALSE  TRUE 
    9     1

最后，我不知道你为什么要这样做，要将每组重复行的数量制成表格，这样做可能更容易：

by(mydata , mydata$annee , \(d) table(duplicated(d)))

mydata$annee: 2018

FALSE  TRUE 
    9     1 
---------------------------------------------------------------------- 
mydata$annee: 2019

FALSE 
   10 
---------------------------------------------------------------------- 
mydata$annee: 2020

FALSE  TRUE 
    9     1

或者如果你想使用data.table，你可以做一个交叉表：

setDT(mydata)
dcast(mydata[ , .(duplicated=duplicated(.SD)), by=annee], duplicated~annee, length)

   duplicated 2018 2019 2020
1:      FALSE    9   10    9
2:       TRUE    1    0    1

你也可以使用我的函数fduplicates()，它使用了tidyverse数据屏蔽规则，就像dplyr::distinct()和friends一样。
它还可以优雅地与许多组一起工作，因为它在幕后使用data.table。

# remotes::install_github("NicChr/timeplyr")
library(timeplyr)
library(dplyr)
df %>%
  group_by(annee) %>%
  fduplicates(.both_ways = TRUE, # Duplicates + first non-duplicate
              .add_count = TRUE) %>% # Duplicate count
  group_split()
#> [[1]]
#> # A tibble: 2 x 8
#>   annee finess    ghm2   dp    dr     sexe modeEntree     n
#>   <int> <chr>     <chr>  <chr> <chr> <int> <chr>      <int>
#> 1  2018 450000245 02C05J H251  <NA>      1 8              2
#> 2  2018 450000245 02C05J H251  <NA>      1 8              2
#> 
#> [[2]]
#> # A tibble: 2 x 8
#>   annee finess    ghm2   dp    dr     sexe modeEntree     n
#>   <int> <chr>     <chr>  <chr> <chr> <int> <chr>      <int>
#> 1  2020 570000646 02C05J H258  <NA>      2 8              2
#> 2  2020 570000646 02C05J H258  <NA>      2 8              2

# Alernatively..
df %>%
  group_by(annee) %>%
  summarise(n = n(), 
            n_dupes = nrow(fduplicates(pick(everything()), 
                                       .both_ways = TRUE)),
            n_non_dupes = n - n_dupes)
#> # A tibble: 3 x 4
#>   annee     n n_dupes n_non_dupes
#>   <int> <int>   <int>       <int>
#> 1  2018    10       2           8
#> 2  2019    10       0          10
#> 3  2020    10       2           8

创建于2023-03-25带有reprex v2.0.2

你得到了正确的结果，但是你将元素位置2018赋值给2020。为了使你的方法更可读，在赋值时减去2017：

library(dplyr)

mylist<-list()
for(i in 2018:2020){
  temp <- mydata%>%filter(annee==i)
  mylist[[i - 2017]] <- table(duplicated(temp))
}

mylist
#> [[1]]
#> 
#> FALSE  TRUE 
#>     9     1 
#> 
#> [[2]]
#> 
#> FALSE 
#>    10 
#> 
#> [[3]]
#> 
#> FALSE  TRUE 
#>     9     1

因为你使用的是'dplyr'，我们也可以使用dplyr::group_map()来得到相同的结果：

mydata %>% 
  group_by(annee) %>% 
  group_map(~ duplicated(.x) %>% 
              table())
#> [[1]]
#> .
#> FALSE  TRUE 
#>     9     1 
#> 
#> [[2]]
#> .
#> FALSE 
#>    10 
#> 
#> [[3]]
#> .
#> FALSE  TRUE 
#>     9     1

创建于2023-03-22带有reprex v2.0.2
数据来自OP

mydata <- structure(list(finess = c("450010079", "450000245", "450000245", 
                          "570005165", "300788502", "300788502", "940300270", "290004142", 
                          "350005179", "350005179", "130786049", "020004404", "020004404", 
                          "020004404", "020004404", "630781839", "570005165", "570005165", 
                          "350005179", "350005179", "130786049", "130786049", "630781839", 
                          "570000646", "570000646", "770300010", "500000146", "710780644", 
                          "310780382", "310780382"), ghm2 = c("06K02Z", "02C05J", "02C05J", 
                                                              "10M092", "06M20T", "16M111", "13K02Z", "06K04J", "04M133", "04M15T", 
                                                              "10C111", "06K02Z", "01C15J", "05M122", "06M121", "02C02J", "10C131", 
                                                              "23M20Z", "06C071", "04M22Z", "17K091", "10C111", "02C05J", "02C05J", 
                                                              "02C05J", "90Z00Z", "06K02Z", "06M032", "05M15T", "05K102"), 
               dp = c("Z8000", "H251", "H251", "E6686", "D128", "D508", 
                      "N840", "K293", "J952", "J9868", "C73", "K635", "G560", "I712", 
                      "R101", "H358", "E6686", "R798", "Z432", "Z098", "Z5101", 
                      "C73", "H251", "H258", "H258", "RSSABS", "D125", "K291", 
                      "I10", "I209"), dr = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 
                                             NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "J961+1", "C73", 
                                             NA, NA, NA, NA, "XXXX", NA, NA, NA, NA), sexe = c(1L, 1L, 
                                                                                               1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 
                                                                                               1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L), modeEntree = c("8", 
                                                                                                                                                                   "8", "8", "8", "8", "8", "8", "8", "7", "8", "8", "8", "8", 
                                                                                                                                                                   "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", 
                                                                                                                                                                   "x", "8", "8", "8", "8"), annee = c(2018L, 2018L, 2018L, 
                                                                                                                                                                                                       2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2019L, 2019L, 
                                                                                                                                                                                                       2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2020L, 
                                                                                                                                                                                                       2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L
                                                                                                                                                                   )), row.names = c(NA, -30L), class = c("tbl_df", "tbl", "data.frame"
                                                                                                                                                                   ))

创建于2023-03-22带有reprex v2.0.2