Compare two DataFrames of different lengths using a shared ID column - ValueError: Can only compare identically-labeled Series objects

Question

I am looking to grab all unique IDs in DF_2015 by comparing it to DF_2014 using the "Employee_ID" column. The logic is to analyze all 2015 new hires.

The problem is that I have different lengths for both DataFrames; however both share the same number of columns and column names. DF_2015 length is 1219 while DF_2014 length is 1356.

I have tried to reset the Index for both DataFrames.

The following is the code that I attempted:

DF_14_15= np.where [(DF_2015['Employee_ID'] != DF_2014['Employee_ID'])]

I am getting the following error:

~\Anaconda3\lib\site-packages\pandas\core\series.py in _cmp_method(self, other, op)

   5494

   5495         if isinstance(other, Series) and not self._indexed_same(other):

-> 5496             raise ValueError("Can only compare identically-labeled Series objects")

   5497

   5498         lvalues = self._values

 

ValueError: Can only compare identically-labeled Series objects

The "Employee_ID column is int.