title: data.table aggregate by group and keep corresponding values from other columns
body: <p>I want to aggregate values of a data.table in R via multiple functions by a grouping variable <strong>AND</strong> keep the information that is in other columns (not included in the aggregation) in the corresponding rows (=the same row as the aggregation). An example: </p>
  
  <p><strong>Note:</strong> The code uses this <a href="https://stackoverflow.com/questions/10256503/function-for-median-similar-to-which-max-and-which-min-extracting-median-r">which_quantile()-function</a> (using sort(x) instead of order(x) in its code). It finds an actual value of a data set which is close to the defined quantile.</p>
  
  <pre><code># sample data
  dt &lt;- structure(list(State = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L),
  .Label = c("AK", "RI"), class = "factor"), Company = structure(1:8, .Label = c("A", 
  "B", "C", "D", "E", "F", "G", "H"), class = "factor"), Employees = c(82L, 
  104L, 37L, 24L, 19L, 118L, 88L, 42L), Number=c(1L,2L,3L,4L,5L,6L,7L,8L), Number2=c(9,10,11,12,13,14,15,16)),
  .Names = c("State", "Company", "Employees", "Number", "Number2"), class = "data.frame", row.names = c(NA, 8L))
  
  require(data.table)
  setDT(dt)
  
  # aggregation
  agg &lt;- dt[ , .(max = max(Employees),
                 min = min(Employees),
                 quantile70 = which.quantile(Employees, 0.7)), by=State]
  agg_m &lt;- dt[agg, on="State"]
  </code></pre>
  
  <p><em>aggregating a DT leads to the following output:</em></p>
  
  <pre><code>     State  max   min   quantile70
  1:    AK    104   24    82
  2:    RI    118   19    88
  </code></pre>
  
  <p><em>merging the aggregation with the original DT to that:</em></p>
  
  <pre><code>     State Company Employees Number Number2    max      min quantile70
  1:    AK       A        82      1       9      104       24     82
  2:    AK       B       104      2      10      104       24     82
  3:    AK       C        37      3      11      104       24     82
  4:    AK       D        24      4      12      104       24     82
  5:    RI       E        19      5      13      118       19     88
  6:    RI       F       118      6      14      118       19     88
  7:    RI       G        88      7      15      118       19     88
  8:    RI       H        42      8      16      118       19     88
  </code></pre>
  
  <p><strong>Question:</strong> How can I aggregate the data.table and at the same time keep the corresponding values in the columns Company, Number and Number2? The max. of the Number column in the State AK is 104 and the corresponding value in column Number2 is 10. The min is 24 and the corresponding value 12 and so on. How to keep this information when aggregating a data.table?</p>
  
  <p><em>desired output:</em></p>
  
  <pre><code>    State Company Employees Number Number2 aggregation
  1:    AK       A        82      1       9      quantile70
  2:    AK       B       104      2      10      max
  3:    AK       D        24      4      12      min
  4:    RI       E        19      5      13      min
  5:    RI       F       118      6      14      max
  6:    RI       H        88      8      16      quantile70
  </code></pre>
  
  <p>The question is similar to <a href="https://stackoverflow.com/questions/24070714/r-how-to-group-data-by-column-find-min-value-in-each-group-then-extract-3rd-c">this one</a>. The sample data was also taken from there and adapted.</p>
  
  <hr>
  
  <p>The following aggregations don't solve my problem:</p>
  
  <pre><code>dt[ ,.SD[ which.max(Employees) ], by=State]
  dt[dt[ ,.I[ which.max(Employees) ], by=State ]$V1]
  # only which.max() OR which.min() are possible
  
  dt[ , max_Empl := max(Employees), by=State ]
  # only ONE aggregation function at a time is possible
  </code></pre>