Convert Object to Datetime

Question

I have a pandas column which contain time data and column datatype is object.

time
Aug 23, 2019 16:30:00
Aug 24, 2019 13:50:00
Aug 16, 2019 08:20:00
Aug 18, 2019 09:00:00

How to convert the column to Datatime

Add the things you tried to your question, also add the error. This helps others to understand your problem. — chefhose, Aug 24 '19 at 13:22
I am doing this way. anythin wrong. **df['Date'] = pd.to_datetime(df['time']).strftime('%d_%m_%Y')** — Rohit Lamba K, Aug 24 '19 at 13:29

score 2 · Accepted Answer · answered Aug 24 '19 at 13:36

2

For speedup, better to specify the date format,

df['DATE'] = pd.to_datetime(df['DATE'], format="%b %d, %Y %H:%M:%S")

answered Aug 24 '19 at 13:36

crayxt

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Amandeep Singh · Answer 2 · 2019-08-24T13:36:07.343

1

you can try the following

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

do not do

df['Date'] = pd.to_datetime(df['time']).strftime('%d_%m_%Y')

as series objects has no attribute 'strftime'

edited Aug 24 '19 at 13:36

answered Aug 24 '19 at 13:29

Amandeep Singh

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TheSHETTY-Paradise · Answer 3 · 2019-08-24T13:47:40.570

Convert any string pattern into datetime object using this

1. Write a function which takes in the string object and convertes it into datetime object

2. Use .apply() to use the function to all rows of the Series object.

Check the below code

import datetime

def splitdates(string):
    month, date, year, time = string.split()
    return datetime.date(int(year), month, date[:len(date)-1])

# Assuming time is a Series object
# Do something like this

time.apply(lambda x: splitdates(x))

Convert Object to Datetime

3 Answers3