Converting object to datetime format in python

Question

Below is the first row of my csv DateTime column:

Mon Nov 02 20:37:10 GMT+00:00 2015

The DateTime column is currently an object and I want to convert it to datetime format so that I can get the date to appear as 2015-11-02 and I will create a separate column for the time.

The code I am using to convert the column to date time format is:

for item, frame in df['DateTime'].iteritems():
     datetime.datetime.strptime(df['DateTime'], "%a-%b-%d-%H-%M-%S-%Z-%Y")

I am getting this error:

> TypeError: must be str, not Series

Any help would be greatly appreciated!

@bernie: that yields `AttributeError: 'Series' object has no attribute 'to_datetime'`, — Alicia Garcia-Raboso, Jul 12 '16 at 16:11

score 67 · Accepted Answer · answered Jul 12 '16 at 16:08

67

Use pd.to_datetime():

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

For example,

pd.to_datetime('Mon Nov 02 20:37:10 GMT+00:00 2015')

produces Timestamp('2015-11-02 20:37:10').

answered Jul 12 '16 at 16:08

Alicia Garcia-Raboso

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Any idea what to do where there is a huge list, and one time is nan? Should i first try to find and edit/change that one value to something or is there a nice trick? – IceQueeny Oct 28 '18 at 08:06

score 0 · Answer 2 · answered Sep 08 '22 at 09:26

Another solution is to pass errors parameter as per below and its application

df['DateTime'] = pd.to_datetime(df['DateTime'], errors='coerce')

errors{‘ignore’, ‘raise’, ‘coerce’}, default ‘raise’

If ‘raise’, then invalid parsing will raise an exception.
If ‘coerce’, then invalid parsing will be set as NaN.
If ‘ignore’, then invalid parsing will return the input.

Converting object to datetime format in python

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