to_datetime not showing timestamp

user_2460780 0
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I have a column in pandas dataframe like this:

>>> print(df['SESSION_DATE'])
0    2008-05-20
1    2013-03-15
2    2014-10-14
3    2006-08-04
4    2006-11-20
Name: SESSION_DATE, dtype: datetime64[ns]

I am trying to create a new column based on this one. But I want the timestamp to show as well. Here is what I tried:

>>> df['NEW_COMPL_DTE'] = pd.to_datetime(df['SESSION_DATE'])
>>> print(df['NEW_COMPL_DTE'])
0    2008-05-20
1    2013-03-15
2    2014-10-14
3    2006-08-04
4    2006-11-20
Name: NEW_COMPL_DTE, dtype: datetime64[ns]

I was hoping the output would include a 00:00:00 after each date. Please advise.

pandas datetime python
3 Answers

If no timestamp is included, 00:00:00 is assumed, so pd.to_datetime does not explicitly display it.

If all you want to do is display it, you may do:

pd.to_datetime(s).dt.strftime('%y-%m-%d %h:%I:%s')
0    2008-05-20 00:00:00
1    2013-03-15 00:00:00
2    2014-10-14 00:00:00
3    2006-08-04 00:00:00
4    2006-11-20 00:00:00
Name: 1, dtype: object

Alternatively, this is simpler, but not as neat. You can use this if your column has strings.

s + ' 00:00:00'
0    2008-05-20 00:00:00
1    2013-03-15 00:00:00
2    2014-10-14 00:00:00
3    2006-08-04 00:00:00
4    2006-11-20 00:00:00
Name: 1, dtype: object
user_49090870

I think you should use strptime. Like:

from datetime import datetime
mywanteddate = datetime.strptime("%s 00:00:00" % (df['SESSION_DATE']), "%Y-%m-%d %H:%M:%S")
print(mywanteddate) # 2008-05-20 00:00:00
user_8545280

You should be able to use this

import numpy as np
import pandas as pd
from datetime import datetime
dates = [datetime(2008, 5, 20), datetime(2013, 3, 15), datetime(2012, 10, 14), datetime(2006, 8, 4), datetime(2006, 11,20)]
index = pd.DatetimeIndex(dates)
for i in index.astype(np.int64):
    print(pd.to_datetime(i, unit='ns'))

to get this 

2008-05-20 00:00:00
2013-03-15 00:00:00
2012-10-14 00:00:00
2006-08-04 00:00:00
2006-11-20 00:00:00
user_87087740
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