python - ValueError: Can only compare identically-labeled Series objects in pandas?

Question

[Sample Code]

d = {
   'country': ['IN', 'USA', 'USA', 'IN'],
   'username': ['abi.g', 'pugal.g', 'jan.g', 'jacob.h'],
   'email': ['[email protected]', '[email protected]', '[email protected]', '[email protected]'],
   'ClusterID': ['', '4', '5', '9']
}
df1 = pd.DataFrame(d)

data = [
   ['USA', 3490.89, 'qcx_taskid85_duns250437449', '3'], 
   ['JA', 1211, 'Pugal Gandi', '4'], 
   ['USA', 3455.00, 'Janani Khannan', '6']
]
df2 = pd.DataFrame(data, columns=['country', 'salary', 'name', 'ClusterID'])

df1.reset_index(inplace=True, drop=True)
df2.reset_index(inplace=True, drop=True)
df1.loc[df1['ClusterID'] == df2['ClusterID']]

Qns: How to compare/filter the two columns using .loc, while the no. of records are different in pandas?

Thanks,

question from:https://stackoverflow.com/questions/65640759/valueerror-can-only-compare-identically-labeled-series-objects-in-pandas

Answer 1

Try this >>

df1.loc[df1['ClusterID'].isin(df2['ClusterID'])]

Both df1['ClusterID'] & df2['ClusterID'] are series. Equating two series within loc method will throw the exception. Instead, calling isin method will give bool outputs and hence for all True values you will get the corresponding output with loc method.