I'm having throuble working with the isin method when working with pandas indexes, it always returns False.
from pandas import DataFrame
df = DataFrame(data=[['a', 1], ['b', 2], ['c', 3]], index=['N01', 'N02', 'N03'])
df.index.isin(['01', '02'])
returns
array([False, False, False], dtype=bool)
2 Answers
Use str.contains and pass a regex pattern:
In[5]: df.index.str.contains('01|02')
Out[5]: array([ True, True, False], dtype=bool)
isin looks for exact matches which is why you get all False array returned
df.index.isin(['01', '02']) method in your example is checking if each of the values in the index is equal to one of the values in the range (similar to SQL).
Therefore in your case the check is:
'N01'=='01' or 'N01' == '02'
which is False
The correct usage of .isin() in your case would be:
from pandas import DataFrame
df = DataFrame(data=[['a', 1], ['b', 2], ['c', 3]], index=['N01', 'N02', 'N03'])
df.index.isin(['N01', 'N02'])
which will result in
array([True, True, False], dtype=bool)
