title: Comparing Boolean Values of Pandas Dataframes- Returning String
body: <p>I have 4 dataframes I'm going to be comparing, that each look like</p>
  
  <pre><code>ID    Jan    Feb    Mar
  1     True   True   False
  2     True   True   True
  3     False  False  False
  </code></pre>
  
  <p>anywhere from 2 to 3000 rows. They will have the exact same column names but may not always share all the same index IDs.</p>
  
  <p>What I would like to do is compare them and generate a new dataframe based on their values. For any cell that was False in at least one dataframe, I want to assign it a string (e.g. "False in Dataframe1") and if multiple, append both (e.g. "False in Dataframe1, Dataframe2").</p>
  
  <p>Output would look like </p>
  
  <pre><code>ID    Jan            Feb              Mar
  1     True           True             False in A, B, C
  2     True           False in B       True
  3     False in A     False in A, B    False in A
  </code></pre>
  
  <p>Is there some kind of direct dataframe to dataframe comparison I can use? Or do I need to concat the dataframes so I can compare the columns to each other?</p>
  
  <p>EDIT- I do not want row-wise comparison, but rather based off of the index, for circumstances where one dataframes does not have the same records.</p>