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Sorry from my crude representation of two different dataframes with rows. Essentially, I want to compare the data between two different dataframes that are of different sizes.

So let's just say have df1 which is a master list. I want to determine what data is missing from df2 by checking all the rows when I compare it to df1. But as mentioned, the two dataframes are of different sizes, single column but number of rows are different.

Yes the source file is an Excel file and there will be multiple data in one cell. I intend on pulling out the multiple data from one call and then place each data in it's own cell. Any suggestions are appreciated.

Perhaps, I am over complicating this and maybe the 'pandas.index.difference' should do the trick.

df1                   df2

SRD Aspects            SRD Aspects
  9855.01              9855.03
  9855.03              -------- 
  9855.04              10130.03
  ----------           ---------
  10130.01             9899.01
  10130.02             --------
  10330.03             10130.01
  --------             9855.02   
  9899.01
  9899.02

Regards, Gus

GusG
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    Thanks for sharing the link. This question definitely did not come up in my search for similar questions. How you had that link handy is beyond me. – GusG Jun 27 '18 at 02:49
  • Your link is actually the same link as provided by ZaxR. I think my question may be a duplicate, but in my case, for df2 the values are scattered among different rows and there will be duplicate values in df2. – GusG Jun 27 '18 at 12:41

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