df['col'] = pd.to_datetime(df['col'])
# convert the 'Date' column to datetime format
df['Date']= pd.to_datetime(df['Date'])
# Check the format of 'Date' column
df.info()
# importing pandas package
import pandas as pd
#date to datetime
df['Dates'] = pd.to_datetime(df['Dates'], format='%Y%m%d')
df['time'] = df['time'].apply(lambda x: x.value)
#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
df['col'] = pd.to_datetime(df['col'])
pd.to_datetime(old_df['oldDate'], format='%b %d, %Y')