帶有dplyr的標簽名稱的摘要

Question

我已經用Haven導入了一個.sav文件，但我遇到的困難是我似乎無法弄清楚如何就地打印標簽名稱或使用標簽編碼打印出來。 標簽： 1 =失業， 2 =外觀，等等。

Employment <- select(well_being_df, EmploymentStatus, Gender) %>% <group_by(EmploymentStatus) %>% summarise_all(funs(mean, n = n(), sd,min(.,is.na = TRUE), max(.,is.na = TRUE)))


# A tibble: 5 x 6
  EmploymentStatus  mean     n    sd   min   max
  <dbl+lbl>        <dbl> <int> <dbl> <dbl> <dbl>
 1 1                 1.67    12 0.492     1     2
 2 2                 1.17     6 0.408     1     2
 3 3                 1.8     85 0.431     1     3
 4 4                 1.5     62 0.504     1     2
 5 5                 1.5      4 0.577     1     2

理想的情況是：

 # A tibble: 5 x 6
EmploymentStatus  mean     n    sd   min   max
<dbl+lbl>        <dbl> <int> <dbl> <dbl> <dbl>
1 1  Unemployed     1.67    12 0.492     1     2
2 2  Looking        1.17     6 0.408     1     2
3 3  Etc            1.8     85 0.431     1     3
4 4                 1.5     62 0.504     1     2
5 5                 1.5      4 0.577     1     2

dput(head(well_being_df, 10))
structure(list(Age = c(22, 20, 23, 20, 25, 18, 24, 21, 21, 30.7344197070233
), Gender = structure(c(2, 2, 1, 2, 1, 2, 2, 2, 2, 1), labels = c(Male = 1, 
Female = 2, Transgender = 3), class = "labelled"), EmploymentStatus = structure(c(3, 
1, 4, 3, 3, 3, 3, 4, 3, 4), labels = c(`Unemployed but not looking` = 1, 
`Unemployed and looking` = 2, `Part-time` = 3, `Full-time` = 4, 
Retired = 5), class = "labelled"), Cognition1 = structure(c(6, 
3, 6, 5, 9, 6, 4, 4, 7, 5), labels = c(`Provides nothing that you want` = 0, 
`Provides half of what you want` = 5, `Provides all that you want` = 10
), class = "labelled"), Cognition2 = structure(c(7, 3, 8, 
5, 8, 5, 5, 7, 7, 3), labels = c(`Far below average` = 0, 
`About Average` = 5, `Far above average` = 10), class = "labelled"), 
Cognition3 = structure(c(6, 5, 4, 5, 6, 5, 5, 5, 5, 5), labels = c(`Far less than you deserve` = 0, 
`About what you deserve` = 5, `Far more than you deserve` = 10
), class = "labelled"), Cognition4 = structure(c(7, 3, 6, 
2, 8, 3, 3, 5, 6, 2), labels = c(`Far less than you need` = 0, 
`About what you need` = 5, `Far more than you need` = 10), class = "labelled"), 
Cognition5 = structure(c(10, 9, 6, 3, 7, 2, 2, 0, 4, 0), labels = c(`Far less than expected` = 0, 
`About as expected` = 5, `Far more than expected` = 10), class = "labelled"), 
Cognition6 = structure(c(8, 6, 0, 3, 3, 8, 9, 10, 5, 10), labels = c(`Far more than it will in the future` = 0, 
`About what you expect in the future` = 5, `Far less than what the future will offer` = 10
), class = "labelled"), Cognition7 = structure(c(9, 7, 10, 
5, 6, 2, 3, 0, 8, 3), labels = c(`Far below previous best` = 0, 
`Equals previous best` = 5, `Far above previous best` = 10
), class = "labelled")), row.names = c(NA, -10L), class = c("tbl_df", 
"tbl", "data.frame"))

Answer 1

Employment <- select(well_being_df, EmploymentStatus, Gender) %>% 
    mutate(EmploymentStatus = labelled::to_factor(EmploymentStatus)) %>% # use labelled package 
    group_by(EmploymentStatus) %>% 
    summarise_all(funs(mean, n = n(), sd,min(.,is.na = TRUE), max(.,is.na = TRUE)))