Answers for "converting a column to datetime pandas"

convert column in pandas to datetime

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

convert column to datetime format python

df['Dates'] = pd.to_datetime(df['Dates'], format='%y%m%d') 

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

dtype = pd.SparseDtype(np.dtype('datetime64[ns]'))
series = pd.Series(df.date, dtype=dtype)
df['date']=np.array(series)

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

convert a number column into datetime pandas

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

pandas convert column to datetime

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