从日期时间剥离微秒

Question

For a given timedata - 2018-06-01 06:36:40.047883+00:00 , I want to remove microsecond and strip the value after '+'. Most of my dataset contains values like 2018-06-04 11:30:00+00:00 without the microsecond part.

How to have a common date time format for all values?

Answer 1

Let's say you have a mix of different formats that looks like this:

import pandas as pd

df = pd.DataFrame()
df['time'] = ['2018-06-01 06:36:40.047883+00:00', '2018-06-01 06:36:40.047883+00:00', '2018-06-04 11:30:00+00:00', '2018-06-01 06:36:40.047883']

Corresponding output:

                               time
0  2018-06-01 06:36:40.047883+00:00
1  2018-06-01 06:36:40.047883+00:00
2         2018-06-04 11:30:00+00:00
3        2018-06-01 06:36:40.047883

You wish to get to a common format by removing microseconds and anything after +. In short, you want something that is in YMD HMS format.

Currently, let me assume that your column is in string format. So, we now convert this to a datetime format and then replace the microseconds part with 0 and get rid of it.

df['time'] = pd.to_datetime(df['time'])
df['time'] = df['time'].apply(lambda x: x.replace(microsecond = 0))

Output:

                 time
0 2018-06-01 06:36:40
1 2018-06-01 06:36:40
2 2018-06-04 11:30:00
3 2018-06-01 06:36:40

Answer 2

Another way to achieve that is by using str.split:

t = "2018-06-04 11:30:00+00:00"
t.split('+')[0]

Answer 3

I'm answering your question with an assumption that the type of the data is a string .

If you are facing problem in handling in different formats like "2018-06-01 06:36:40.047883+00:00" and "2018-06-04 11:30:00+00:00" you can use split() . Learn more about split() at here

str_data_time.split("+")[0].split(".")[0]

Like,

for str_data_time in ["2018-06-01 06:36:40.047883+00:00", "2018-06-04 11:30:00+00:00"]:
    output = str_data_time.split("+")[0].split(".")[0]
    print(output)

The output of the above script is,

2018-06-01 06:36:40
2018-06-04 11:30:00