How to convert a datetime object to milliseconds

Question

I am analyzing date and time values ​​as follows:

df['actualDateTime'] = pd.to_datetime(df['actualDateTime'])

How can I convert datetime objects to milliseconds?

I did not see a mention of milliseconds in the to_datetime document .

Update (based on feedback): This is the current version of the code that throws an error. TypeError: Cannot convert input to Timestamp. The column Date3should contain milliseconds (as the numerical equivalent of a datetime object).

import pandas as pd
import time

s1 = {'Date' : ['2015-10-20T07:21:00.000','2015-10-19T07:18:00.000','2015-10-19T07:15:00.000']}

df = pd.DataFrame(s1)

df['Date2'] = pd.to_datetime(df['Date'])

t = pd.Timestamp(df['Date2'])

df['Date3'] = time.mktime(t.timetuple())

print df

Answer 1

You may try pd.to_datetime(df['actualDateTime'], unit='ms')

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html

, , 's', 'ms', 'ns'...

14567899..

import pandas as pd
import time
t = pd.Timestamp('2015-10-19 07:22:00')
time.mktime(t.timetuple())

>> 1445219520.0

df = pd.DataFrame(s1)
df1 = pd.to_datetime(df['Date'])
pd.DatetimeIndex(df1)
>>>DatetimeIndex(['2015-10-20 07:21:00', '2015-10-19 07:18:00',
           '2015-10-19 07:15:00'],
          dtype='datetime64[ns]', freq=None)
df1.astype(np.int64) 
>>>0    1445325660000000000
1    1445239080000000000
2    1445238900000000000
df1.astype(np.int64) // 10**9
>>>0    1445325660
1    1445239080
2    1445238900
Name: Date, dtype: int64

Answer 2

.

(1970-01-01):

df['actualDateTime'] = df['actualDateTime'].astype(np.int64) / int(1e6)

Answer 3

pandas.to_datetime - pandas datetime[ns]

'actualDateTime' milliseconds. , , .

,

df
Out[60]: 
                         a  b
0  2015-11-02 18:04:32.926  0
1  2015-11-02 18:04:32.928  1
2  2015-11-02 18:04:32.927  2

df.a
Out[61]: 
0    2015-11-02 18:04:32.926
1    2015-11-02 18:04:32.928
2    2015-11-02 18:04:32.927
Name: a, dtype: object

df.a = pd.to_datetime(df.a)

df.a
Out[63]: 
0   2015-11-02 18:04:32.926
1   2015-11-02 18:04:32.928
2   2015-11-02 18:04:32.927
Name: a, dtype: datetime64[ns]

df.a.dt.nanosecond
Out[64]: 
0    0
1    0
2    0
dtype: int64

df.a.dt.microsecond
Out[65]: 
0    926000
1    928000
2    927000
dtype: int64

Answer 4

from datetime import datetime

print datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3]

>>>> OUTPUT >>>>
2015-11-02 18:04:32.926

Answer 5

Pandas , :

import time
time.mktime(<timestamp_object>.timetuple())*1000