python pandas - how to merge date from one and time from another column and create new column

Question

I have a dataframe that comes from a database like this: Both FltDate and ESTAD2 are datetime64[ns]

>>> print df[['Airport', 'FltDate', 'Carrier', 'ESTAD2']]

     Airport    FltDate Carrier              ESTAD2
0       EDI 2017-06-18    BACJ 1899-12-30 05:35:00
1       EDI 2017-06-18      BA 1899-12-30 06:40:00
2       EDI 2017-06-18    BACJ 1899-12-30 07:00:00
3       EDI 2017-06-18      BA 1899-12-30 07:05:00
4       EDI 2017-06-18      BA 1899-12-30 09:00:00
5       EDI 2017-06-18      I2 1899-12-30 11:05:00
6       EDI 2017-06-18      BA 1899-12-30 11:25:00
7       EDI 2017-06-18      BA 1899-12-30 13:45:00


>>> df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 214 entries, 0 to 213
Data columns (total 12 columns):
Airport         214 non-null object
FltDate         214 non-null datetime64[ns]
<snip>
ESTAD2          214 non-null datetime64[ns]
<snip>
dtypes: datetime64[ns](4), object(8)
memory usage: 20.1+ KB

How to get the Date Part from FltDate and Time Part from ESTAD2.

Result should be like this say for Row 0

2017-06-18 05:35:00 (that is 18Jun2017 of FltDate + 05:35 of ESTAD2)

I may replace ESTAD2 with above result.. or create a new column as FltDateTime.

Tried various ways and failed... like below... adding was unsuccessful.

>>> df.FltDate.dt.date

0      2017-06-18
1      2017-06-18
2      2017-06-18
>>> df.ESTAD2.dt.time

0      05:35:00
1      06:40:00
2      07:00:00

Answer 1

You can use strftime with to_datetime :

df['date'] = pd.to_datetime(df.FltDate.dt.strftime('%Y-%m-%d ') +
                            df.ESTAD2.dt.strftime('%H:%M:%S'))
print (df)
  Airport    FltDate Carrier              ESTAD2                date
0     EDI 2017-06-18    BACJ 1899-12-30 05:35:00 2017-06-18 05:35:00
1     EDI 2017-06-18      BA 1899-12-30 06:40:00 2017-06-18 06:40:00
2     EDI 2017-06-18    BACJ 1899-12-30 07:00:00 2017-06-18 07:00:00
3     EDI 2017-06-18      BA 1899-12-30 07:05:00 2017-06-18 07:05:00
4     EDI 2017-06-18      BA 1899-12-30 09:00:00 2017-06-18 09:00:00
5     EDI 2017-06-18      I2 1899-12-30 11:05:00 2017-06-18 11:05:00
6     EDI 2017-06-18      BA 1899-12-30 11:25:00 2017-06-18 11:25:00
7     EDI 2017-06-18      BA 1899-12-30 13:45:00 2017-06-18 13:45:00

Alternative solution:

df['date'] = pd.to_datetime(df.FltDate.dt.strftime('%Y-%m-%d ') +
                            df.ESTAD2.astype(str).str.split().str[1])

print (df)
  Airport    FltDate Carrier              ESTAD2                date
0     EDI 2017-06-18    BACJ 1899-12-30 05:35:00 2017-06-18 05:35:00
1     EDI 2017-06-18      BA 1899-12-30 06:40:00 2017-06-18 06:40:00
2     EDI 2017-06-18    BACJ 1899-12-30 07:00:00 2017-06-18 07:00:00
3     EDI 2017-06-18      BA 1899-12-30 07:05:00 2017-06-18 07:05:00
4     EDI 2017-06-18      BA 1899-12-30 09:00:00 2017-06-18 09:00:00
5     EDI 2017-06-18      I2 1899-12-30 11:05:00 2017-06-18 11:05:00
6     EDI 2017-06-18      BA 1899-12-30 11:25:00 2017-06-18 11:25:00
7     EDI 2017-06-18      BA 1899-12-30 13:45:00 2017-06-18 13:45:00