PYTHON

convert column in pandas to datetime

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

pandas dataframe column to datetime

# convert the 'Date' column to datetime format
df['Date']= pd.to_datetime(df['Date'])
 
# Check the format of 'Date' column
df.info()

pandas convert series of datetime to date

df['date_only'] = df['date_time_column'].dt.date

how to conver a column in pandas to datetime type

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

convert column series to datetime in pandas dataframe

#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

pandas convert column to datetime

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

python pandas column to date

df['date'] = pd.to_datetime(df['date'], utc=True, errors='coerce')

python pandas column to date

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

converting a panda column to a datetime()

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]