title: Merge two DataFrames on multiple columns
body: <p>hope you can help me. </p>
  
  <p>I have two pretty big Datasets.
  DF1 Example:</p>
  
  <pre><code>|id| A_Workflow_Type_ID | B_Workflow_Type_ID | ...
   1   123                  456
   2   789                  222                  ...
   3   333                  NULL                 ...
  </code></pre>
  
  <p>DF2 Example:</p>
  
  <pre><code>Workflow| Operation | Profile |    Type     | Name | ...
  123           1          2       Low_Cost     xyz    ...
  456           2          5       High_Cost    z      ...
  </code></pre>
  
  <p>I need to merge the two datasets without creating many NaNs and multiple columns. So i merge on the informations A_Workflow_Type_ID and B_Workflow_Type_ID from DF1 on Workflow from DF2. 
  I tried it with several join operations in pandas and the merge option it failure. </p>
  
  <p>My last try:</p>
  
  <pre><code>all_Data = pd.merge(left=DF1,right=DF2, how='inner', left_on =['A_Workflow_Type_ID ','B_Workflow_Type_ID '], right_on=['Workflow'])
  </code></pre>
  
  <p>But that returns an error that they have to be equal lenght on both sides.</p>
  
  <p>Thanks for the help!</p>