title: Applying group_by and summarise on data while keeping all the columns' info
body: <p>I have a large dataset with 22000 rows and 25 columns. I am trying to group my dataset based on one of the columns and take the min value of the other column based on the grouped dataset. However, the problem is that it only gives me two columns containing the grouped column and the column having the min value... but I need all the information of other columns related to the rows with the min values. 
  Here is a simple example just to make it reproducible:</p>
  
  <pre><code>    data&lt;- data.frame(a=1:10, b=c("a","a","a","b","b","c","c","d","d","d"), c=c(1.2, 2.2, 2.4, 1.7, 2.7, 3.1, 3.2, 4.2, 3.3, 2.2), d= c("small", "med", "larg", "larg", "larg", "med", "small", "small", "small", "med"))
  
      d&lt;- data %&gt;%
      group_by(b) %&gt;%
      summarise(min_values= min(c))
      d
      b min_values
      1 a        1.2
      2 b        1.7
      3 c        3.1
      4 d        2.2
  </code></pre>
  
  <p>So, I need to have also the information related to columns a and d, however, since I have duplications in the values in column c I cannot merge them based on the min_value column... I was wondering if there is any way to keep other columns' information when we are using dplyr package.</p>
  
  <p>I have found some explanation here "<a href="https://stackoverflow.com/questions/29597970/dplyr-group-by-subset-and-summarise">dplyr: group_by, subset and summarise</a>" and here "<a href="https://stackoverflow.com/questions/29549731/dplyr-finding-percentage-in-a-sub-group-using-group-by-and-summarise">Finding percentage in a sub-group using group_by and summarise</a>" but none of the addresses my problem.</p>