Convert time zone date column to timestamp format-CodePudding

I have column containing dates in format as seen here....

2021-09-02 06:00:10.474000 00:00

However, I need to convert this column into a 13 numbered timestamp.

I have tried...

df['date_timestamp'] = df[['date']].apply(lambda x: x[0].timestamp(), axis=1).astype(int)

...but this is not producing a 13 numbered timestamp, just 10 numbers instead.

How can get it to spit a 13 numbered timestamp?

CodePudding user response：

you parse to datetime, take the int64 representation and divide that by 1e6 to get Unix time in milliseconds since the epoch (1970-01-01 UTC). Ex:

import numpy as np
import pandas as pd

# string to datetime
s = pd.to_datetime(["2021-09-02 06:00:10.474000 00:00"])

# datetime to Unix time in milliseconds
unix = s.view(np.int64)/1e6

print(unix[0])
# 1630562410473.9998

The standard int64 representation is nanoseconds; so divide by 1e3 if you need microseconds.