Convert DataFrame column type from string to datetime


How can I convert a DataFrame column of strings (in dd/mm/yyyy format) to datetimes?

Asked By: perigee



The easiest way is to use to_datetime:

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

It also offers a dayfirst argument for European times (but beware this isn’t strict).

Here it is in action:

In [11]: pd.to_datetime(pd.Series(['05/23/2005']))
0   2005-05-23 00:00:00
dtype: datetime64[ns]

You can pass a specific format:

In [12]: pd.to_datetime(pd.Series(['05/23/2005']), format="%m/%d/%Y")
0   2005-05-23
dtype: datetime64[ns]
Answered By: Andy Hayden

If your date column is a string of the format ‘2017-01-01’
you can use pandas astype to convert it to datetime.

df['date'] = df['date'].astype('datetime64[ns]')

or use datetime64[D] if you want Day precision and not nanoseconds



<class 'pandas._libs.tslib.Timestamp'>

the same as when you use pandas.to_datetime

You can try it with other formats then ‘%Y-%m-%d’ but at least this works.

Answered By: sigurdb

You can use the following if you want to specify tricky formats:

df['date_col'] =  pd.to_datetime(df['date_col'], format='%d/%m/%Y')

More details on format here:

Answered By: Ekhtiar

If you have a mixture of formats in your date, don’t forget to set infer_datetime_format=True to make life easier.

df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True)

Source: pd.to_datetime

or if you want a customized approach:

def autoconvert_datetime(value):
    formats = ['%m/%d/%Y', '%m-%d-%y']  # formats to try
    result_format = '%d-%m-%Y'  # output format
    for dt_format in formats:
            dt_obj = datetime.strptime(value, dt_format)
            return dt_obj.strftime(result_format)
        except Exception as e:  # throws exception when format doesn't match
    return value  # let it be if it doesn't match

df['date'] = df['date'].apply(autoconvert_datetime)
Answered By: otaku