title: Summary with label names with dplyr
body: <p>I have imported a .sav file with Haven but where I am stuck is that I cant seem to work out how to print the label names in place or, with the label codings. Labels: <strong>1</strong> = unemployed, <strong>2</strong> = looking etc. </p>
  
  <pre><code>Employment &lt;- select(well_being_df, EmploymentStatus, Gender) %&gt;% &lt;group_by(EmploymentStatus) %&gt;% 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
    &lt;dbl+lbl&gt;        &lt;dbl&gt; &lt;int&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;
   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
  </code></pre>
  
  <p><strong>Ideally:</strong></p>
  
  <pre><code> # A tibble: 5 x 6
  EmploymentStatus  mean     n    sd   min   max
  &lt;dbl+lbl&gt;        &lt;dbl&gt; &lt;int&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;
  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"))
  </code></pre>