title: using group_by function from dplyr to manipulate set of data.frame object
body: <p>This is my first question I ever raised to this community, I hope I could resolve my doubt by communicating great experienced people over here. 
  I have three group where each contains 3 different data.frame objects with different length and dimension. I want to some sort of manipulation that group them by specific data.frame objects. I think group_by from dply package may do this task, but I am not sure for this and even I have not perfectly known of using dplyr packages, so please give your contribution on my question. Thanks everyone.</p>
  
  <p>Here is simple reproducible example to make my question clear:</p>
  
  <h1>simulated data</h1>
  
  <pre><code>group1 &lt;- list(a1 &lt;- iris[1:10,],
                 b1 &lt;- airquality[1:20,],
                 c1 &lt;- cars[1:20,])
  
  group2 &lt;- list(a2 &lt;- iris[15:35,],
                 b2 &lt;- airquality[10:25,],
                 c2 &lt;- cars[15:30,])
  group3 &lt;- list(a3 &lt;- iris[40:60,],
                 b3 &lt;- airquality[30:50,],
                 c3 &lt;- cars[25:45,])
  </code></pre>
  
  <p>imagine group1, group2, group3 are placed in three different directory in R memory, so I want to acess each group simultaneously, and group them by specific data.frame objects. So this is my expected output:</p>
  
  <h1>desired output:</h1>
  
  <pre><code>group_a &lt;- list(a1, a2, a3)
  group_b &lt;- list(b1, b2, b3)
  group_c &lt;- list(c1, c2, c3)
  </code></pre>
  
  <p>To be clear, my reproducible example simulated based on the result of function that I implemented, every time I execute my function it return result as list and store them in different R directory, that's why I need to access each group of result same time, and group them what I expected. Can any experienced member give some idea how to achieve my expected result respect to problem that I stated? I am thankful everyone who try to help here. </p>
  
  <p>Best</p>
  
  <p>Jeff</p>