Convert Pandas Series to DateTime in a DataFrame

Question

I have a Pandas DataFrame as below           ReviewID       ID      Type               TimeReviewed 205     76032930  51936827  ReportID 2015-01-15 00 05 27 513000 232     76032930  51936854  ReportID 2015-01-15 00 06 46 703000 233     76032930  51936855  ReportID 2015-01-15 00 06 56 707000 413     76032930  51937035  ReportID 2015-01-15 00 14 24 957000 565     76032930  51937188  ReportID 2015-01-15 00 23 07 220000   gt  gt  gt  type df   lt class  pandas core frame DataFrame  gt    TimeReviewed is a series type    gt  gt  gt  type df TimeReviewed   lt class  pandas core series Series  gt    I ve tried below  but it still doesn t change the Series type   import pandas as pd review   pd to datetime pd Series df TimeReviewed    gt  gt  gt  type review   lt class  pandas core series Series  gt    How can I change the df TimeReviewed to DateTime type and pull out year  month  day  hour  min  sec separately   I m kinda new to python  thanks for your help

User · Answer

df pd read csv  filename csv    parse dates    lt column name gt      type df  lt column name gt     example  if you want to convert day which is initially a string to a Timestamp in Pandas  df pd read csv  weather data2 csv    parse dates   day     type df day    The output will be pandas tslib Timestamp

User · Answer

You can t  DataFrame columns are Series  by definition   That said  if you make the dtype  the type of all the elements  datetime-like  then you can access the quantities you want via the  dt accessor  docs    gt  gt  gt  df  quot TimeReviewed quot     pd to datetime df  quot TimeReviewed quot     gt  gt  gt  df  quot TimeReviewed quot   205  76032930   2015-01-24 00 05 27 513000 232  76032930   2015-01-24 00 06 46 703000 233  76032930   2015-01-24 00 06 56 707000 413  76032930   2015-01-24 00 14 24 957000 565  76032930   2015-01-24 00 23 07 220000 Name  TimeReviewed  dtype  datetime64 ns   gt  gt  gt  df  quot TimeReviewed quot   dt  lt pandas tseries common DatetimeProperties object at 0xb10da60c gt   gt  gt  gt  df  quot TimeReviewed quot   dt year 205  76032930    2015 232  76032930    2015 233  76032930    2015 413  76032930    2015 565  76032930    2015 dtype  int64  gt  gt  gt  df  quot TimeReviewed quot   dt month 205  76032930    1 232  76032930    1 233  76032930    1 413  76032930    1 565  76032930    1 dtype  int64  gt  gt  gt  df  quot TimeReviewed quot   dt minute 205  76032930     5 232  76032930     6 233  76032930     6 413  76032930    14 565  76032930    23 dtype  int64   If you re stuck using an older version of pandas  you can always access the various elements manually  again  after converting it to a datetime-dtyped Series    It ll be slower  but sometimes that isn t an issue   gt  gt  gt  df  quot TimeReviewed quot   apply lambda x  x year  205  76032930    2015 232  76032930    2015 233  76032930    2015 413  76032930    2015 565  76032930    2015 Name  TimeReviewed  dtype  int64

User · Answer

Some handy script   hour   df  assess time   dt hour values 0

[python] Convert Pandas Series to DateTime in a DataFrame

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