« Pandas
Current Date and time
import pandas as pd
print(pd.to_datetime('now'))
Output
2022-06-10 12:13:23.001423
Any Date and time
present_time=pd.to_datetime('12252020:233445',format='%m%d%Y:%H%M%S')
Using any date and time
import pandas as pd
tm=pd.to_datetime('2020-12-29 18:15:05')
# Use day,month, year, hour , second , dayofweek, day_name()
print(tm.minute)
import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex','Ron','King'],
'dt_start':['2020-12-28 18:15:05', '2021-01-31 23:15:45',
'2021-02-14 04:15:37', '2021-05-17 09:15:26','2022-06-20 13:45:54']
}
my_data = pd.DataFrame(data=my_dict)
my_data['dt_start'] = pd.to_datetime(my_data['dt_start'])
print(my_data)
Managing Date
Exercise datetime 3-1
Exercise datetime 3-2
Exercise datetime 3-3
Date & time offset Aliases
Alias | Description |
B | business day frequency |
C | custom business day frequency |
D | calendar day frequency |
W | weekly frequency |
M | month end frequency |
SM | semi-month end frequency (15th and end of month) |
BM | business month end frequency |
CBM | custom business month end frequency |
MS | month start frequency |
SMS | semi-month start frequency (1st and 15th) |
BMS | business month start frequency |
CBMS | custom business month start frequency |
Q | quarter end frequency |
BQ | business quarter end frequency |
QS | quarter start frequency |
BQS | business quarter start frequency |
A,Y | year end frequency |
BA,BY | business year end frequency |
AS,YS | year start frequency |
BAS, BYS | business year start frequency |
BH | business hour frequency |
H | hourly frequency |
T,min | minutely frequency |
S | secondly frequency |
L,ms | milliseconds |
U,us | microseconds |
N | nanoseconds |
← Subscribe to our YouTube Channel here