["python","pandas","datetime"]
AttributeError: Can only use .dt accessor with datetimelike values

Hi I am using pandas to convert a column to month. When I read my data they are objects: Date object dtype: object So I am first making them to date time and then try to make them as months: import pandas as pd file = '/pathtocsv.csv' df = pd.read_csv(file, sep = ',', encoding='utf-8-sig', usecols= ['Date', 'ids']) df['Date'] = pd.to_datetime(df['Date']) df['Month'] = df['Date'].dt.month Also if that helps: In [10]: df['Date'].dtype Out[10]: dtype('O') So, the error I get is like this: /Library/Frameworks/Python.framework/Versions/2.7/bin/User/lib/python2.7/site-packages/pandas/core/series.pyc in _make_dt_accessor(self) 2526 return maybe_to_datetimelike(self) 2527 except Exception: -> 2528 raise AttributeError("Can only use .dt accessor with datetimelike " 2529 "values") 2530 AttributeError: Can only use .dt accessor with datetimelike values EDITED: Date columns are like this: 0 2014-01-01 1 2014-01-01 2 2014-01-01 3 2014-01-01 4 2014-01-03 5 2014-01-03 6 2014-01-03 7 2014-01-07 8 2014-01-08 9 2014-01-09 Do you have any ideas? Thank you very much!
Your problem here is that to_datetime silently failed so the dtype remained as str/object, if you set param errors='coerce' then if the conversion fails for any particular string then those rows are set to NaT. df['Date'] = pd.to_datetime(df['Date'], errors='coerce') So you need to find out what is wrong with those specific row values. See the docs