I have a column I_DATE of type string(object) in a dataframe called train as show below.
I_DATE 28-03-2012 2:15:00 PM 28-03-2012 2:17:28 PM 28-03-2012 2:50:50 PM
How to convert I_DATE from string to datatime format & specify the format of input string. I saw some answers to this but its not for AM/PM format.
Also, how to filter rows based on a range of dates in pandas?
Answers:
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Method 1
Use to_datetime, there is no need for a format string the parser is man/woman enough to handle it:
In [51]: pd.to_datetime(df['I_DATE']) Out[51]: 0 2012-03-28 14:15:00 1 2012-03-28 14:17:28 2 2012-03-28 14:50:50 Name: I_DATE, dtype: datetime64[ns]
To access the date/day/time component use the dt accessor:
In [54]: df['I_DATE'].dt.date Out[54]: 0 2012-03-28 1 2012-03-28 2 2012-03-28 dtype: object In [56]: df['I_DATE'].dt.time Out[56]: 0 14:15:00 1 14:17:28 2 14:50:50 dtype: object
You can use strings to filter as an example:
In [59]:
df = pd.DataFrame({'date':pd.date_range(start = dt.datetime(2015,1,1), end = dt.datetime.now())})
df[(df['date'] > '2015-02-04') & (df['date'] < '2015-02-10')]
Out[59]:
date
35 2015-02-05
36 2015-02-06
37 2015-02-07
38 2015-02-08
39 2015-02-09
Method 2
Approach: 1
Given original string format: 2019/03/04 00:08:48
you can use
updated_df = df['timestamp'].astype('datetime64[ns]')
The result will be in this datetime format: 2019-03-04 00:08:48
Approach: 2
updated_df = df.astype({'timestamp':'datetime64[ns]'})
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