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#Converting column to datetime dtype while loading file.
#Create a date parser function
d_parser = lambda x: pd.to_datetime(x)
df = pd.read_csv(file_name.csv, parse_dates=['date_column'], date_parser=d_parser)
#If date is not in parseable format, use
pd.to_datetime.strptime(x, format)
#Eg. format for '2017-03-13 04-PM' is '%Y-%M-%D %I-%p'
#Datetime Formatting Codes - http://bit.ly/python-dt-fmt
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# convert the 'Date' column to datetime format
df['Date']= pd.to_datetime(df['Date'])
# Check the format of 'Date' column
df.info()
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df = pd.DataFrame({'date':['31DEC2002','31 December 2015 00:00:00.000 GMT','.']})
df['date'] = pd.to_datetime(df['date'], utc=True, errors='coerce')
print (df)
date
0 2002-12-31 00:00:00+00:00
1 2015-12-31 00:00:00+00:00
2 NaT
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df['date'] = pd.to_datetime(df['date'], utc=True, errors='coerce')
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df = pd.DataFrame({'year': [2015, 2016],
'month': [2, 3],
'day': [4, 5]})
pd.to_datetime(df)
0 2015-02-04
1 2016-03-05
dtype: datetime64[ns]