AttributeError Can only use dt accessor with datetimelike values

Question

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  - gt  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

User · Answer

Your problem here is that the dtype of  Date  remained as str object  You can use the parse dates parameter when using read csv  import pandas as pd file     pathtocsv csv  df   pd read csv file  sep        parse dates   col  encoding  utf-8-sig   usecols    Date    ids         df  Month     df  Date   dt month   From the documentation for the parse dates parameter     parse dates   bool or list of int or names or list of lists or dict  default False      The behavior is as follows          boolean  If True -  try parsing the index    list of int or names  e g  If  1  2  3  -  try parsing columns 1  2  3 each as a separate date column    list of lists  e g  If   1  3   -  combine columns 1 and 3 and parse as a single date column    dict  e g      foo       1  3   -  parse columns 1  3 as date and call result    foo            If a column or index cannot be represented as an array of datetimes  say because of an unparseable value or a mixture of timezones  the column or index will be returned unaltered as an object data type  For non-standard datetime parsing  use pd to datetime after pd read csv  To parse an index or column with a mixture of timezones  specify date parser to be a partially-applied pandas to datetime   with utc True  See Parsing a CSV with mixed timezones for more       Note  A fast-path exists for iso8601-formatted dates    The relevant case for this question is the  list of int or names  one    col is the columns index of  Date  which parses as a separate date column

User · Answer

When you write df  Date     pd to datetime df  Date    errors  coerce   df  Date     df  Date   dt strftime   m  d    It can fixed

User · Answer

First you need to define the format of date column  df  Date     pd to datetime df Date  format   Y- m- d  H  M  S    For your case base format can be set to  df  Date     pd to datetime df Date  format   Y- m- d    After that you can set change your desired output as follows  df  Date     df  Date   dt strftime   Y- m- d

User · Answer

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

[python] AttributeError: Can only use .dt accessor with datetimelike values

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