CODEWITHSUNDEEP
pythonpandasdatetime
bbartling
bbartling

Reputation: 3502

python transform time stamp

Is it possible with pandas to transform a column Date that looks like this: (I think ISO format without the T)

2020-06-29 14:04:21.000000
2020-06-29 14:19:26.000000
2020-06-29 14:34:30.000000
2020-06-29 14:49:35.000000
2020-06-29 15:04:39.000000
2020-06-29 15:19:44.000000
2020-06-29 15:34:48.000000
2020-06-29 15:49:53.000000
2020-06-29 16:20:02.000000
2020-06-29 16:35:07.000000
2020-06-29 16:50:11.000000
2020-06-29 17:05:16.000000
2020-06-29 17:20:20.000000
2020-06-29 17:35:25.000000
2020-06-29 17:50:30.000000
2020-06-29 18:05:34.000000
2020-06-29 18:20:39.000000
2020-06-29 18:35:43.000000
2020-06-29 18:50:48.000000
2020-06-29 19:05:52.000000

To a format like this with only hours & minutes. Rounding to closest minute would be good enough. Can I go right from time.time.now() to a format that looks this below? Thanks for any tips...

1/19/2019 0:30
1/19/2019 0:45
1/19/2019 1:00
1/19/2019 1:15
1/19/2019 1:30
1/19/2019 1:45
1/19/2019 2:00
1/19/2019 2:15
1/19/2019 2:30
1/19/2019 2:45
1/19/2019 3:00
1/19/2019 3:15
1/19/2019 3:30
1/19/2019 3:45

Upvotes: 0

Views: 53

Answers (3)

CU_dev
CU_dev

Reputation: 353

def formatTime(origTD):
    date = origTD.split(' ')[0]
    time = origTD.split(' ')[1]

    day = int(date.split('-')[2])
    month = int(date.split('-')[1])
    year = date.split('-')[0][-2:]

    hour = time.split(':')[0]
    minute = time.split(':')[1]

    newTD = str(month)+'/'+str(day)+'/'+year+' '+hour+':'+minute

    return newTD

Upvotes: 0

Zaraki Kenpachi
Zaraki Kenpachi

Reputation: 5730

import pandas as pd

data = {'Date': ['2019-05-30 00:00:44.000000', '2019-05-30 00:00:50.000000','2019-05-30 00:23:26.000000']}
df = pd.DataFrame(data=data)

df['New_Date'] = pd.to_datetime(df['Date']).dt.round('min').dt.strftime('%m/%d/%Y %H:%M')

Output:

                  Date          New_Date
0  2019-05-30 00:00:44  05/30/2019 00:01
1  2019-05-30 00:00:50  05/30/2019 00:01
2  2019-05-30 00:23:26  05/30/2019 00:23

Upvotes: 2

marcuse
marcuse

Reputation: 3999

If you are looking to go from the time.time() method to the desired format you can use this:

time.strftime('%m/%d/%Y %H:%M')

Furthermore if your pandas variable is a valid Datetime object you can apply strftime to it.

Upvotes: 1

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