fuzzy matching with pandas

#df is the original dataframe with a list of names you want to prevail
#dfF is the dataframe with Names that can be matched only fuzzily
#For each Name in df the code finds the most likely match from the dfF and saves that name
#We then merge on that new key 'Name_r'
#some code is to cover the event of no match (perhaps b/c df has names not in dfF) 
# From http://stackoverflow.com/questions/13636848/is-it-possible-to-do-fuzzy-match-merge-with-python-pandas 
# http://stackoverflow.com/questions/36557722/python-pandas-difflib-throws-list-index-out-of-range-error

import difflib
df['Name_r'] = df.Name_x.map(lambda x: (difflib.get_close_matches(x, dfF.Name)[:1] or [None])[0])      

hi there!

I get the error IndexError: list index out of range because the dataframes are not the same length.. any suggestion?