title: Using skimr to create a data frame of summary statistics
body: <p>I have recently come across the package called <code>skimr</code> which helps create useful summary statistics. I have written the following codes to extract summary stats only on numerical columns. My first question is, is there a more direct way that skimr permits to specify the type of variables for which I want summary stats? My second question is, what does <code>append == TRUE </code> actually achieve when I write the <code>my_skim</code> &quot;closure&quot;?</p>
  <pre><code>library(skimr)
  library(dplyr)
  
  ### Creating an example dataset 
  
  test.df1 &lt;- data.frame(&quot;Year&quot; = sample(2018:2020, 20, replace = TRUE), 
                         &quot;Firm&quot; = head(LETTERS, 5), 
                         &quot;Exporter&quot;= sample(c(&quot;Yes&quot;, &quot;No&quot;), 20, replace = TRUE), 
                         &quot;Revenue&quot; = sample(100:200, 20, replace = TRUE),
                           stringsAsFactors =  FALSE)
  
  test.df1 &lt;- rbind(test.df1, 
                      data.frame(&quot;Year&quot; = c(2018, 2018),
                                 &quot;Firm&quot; = c(&quot;Y&quot;, &quot;Z&quot;),
                                 &quot;Exporter&quot; = c(&quot;Yes&quot;, &quot;No&quot;),
                                 &quot;Revenue&quot; = c(NA, NA)))
  
  test.df1 &lt;- test.df1 %&gt;% mutate(Profit = Revenue - sample(20:30, 22, replace = TRUE ))
  
  ### Using skimr package to extract summary stats
  
  my_skim &lt;- skim_with(numeric = sfl(minimum = min, maximum = max, hist = NULL), append = TRUE)
  
  test.df1_skim1 &lt;- test.df1 %&gt;% 
   group_by(Year) %&gt;% 
    my_skim() %&gt;% 
     filter (skim_type != &quot;character&quot;) %&gt;% 
      select(-starts_with(&quot;character&quot;))
  </code></pre>