title: Compact way to save JuMP optimization results in DataFrames
body: <p>I would like to save all my variables and dual variables of my finished lp-optimization in an efficient manner. My current solution works, but is neither elegant nor suited for larger optimization programs with many variables and constraints because I define and push! every single variable into DataFrames separately. Is there a way to iterate through the variables using all_variables() and all_constraints() for the duals? While iterating, I would like to push the results into DataFrames with the variable index name as columns and save the DataFrame in a Dict().
  A <strong>conceptual</strong> example would be for variables:</p>
  <pre><code>Result_vars = Dict()
  for vari in all_variables(Model)
  Resul_vars[&quot;vari&quot;] = DataFrame(data=[indexval(vari),value(vari)],columns=[index(vari),&quot;Value&quot;]) 
  end
  </code></pre>
  <p>An example of the appearance of the declared variable in JuMP and DataFrame:</p>
  <pre><code>@variable(Model, p[t=s_time,n=s_n,m=s_m], lower_bound=0,base_name=&quot;Expected production&quot;)
  </code></pre>
  <p>And Result_vars[p] shall approximately look like:</p>
  <pre><code>t,n,m,Value
  1,1,1,50
  2,1,1,60 
  3,1,1,145
  </code></pre>