Exercise : Pandas and Date time Basic

1. Create a datetime out of your birthday. Use year, month, day , hour , minute and second.
2. Using the above datetime of your birthday, print your birth year , birth month , birth day , hour , minute and second.
3. How old you were as on 1st of Jan 2020, 13 PM 22 minutes and 34 seconds
4. How old you are as on present date and time.
5. Add 5 years , 2 months and 25 days to your birthday.
6. What is the date and time now. Write in different formats ( 1st April 2019, 20 December 2010, 16/02/2020 12:32:45 )
7. Create a date and time series with 10 elements, with a frequency of 3 days 6 hours starting from previous 10 days
8. Write milliseconds and microseconds to above format.
9. Prepare a list of name and date of birth of your friends. Find out the name of the weekday from their date of birth.
10. Print the business days in last 10 days from today.

Create a datetime out of your birthday. Use year, month, day , hour , minute and second.

import pandas as pd 
dt_bd=pd.to_datetime('2001-12-02 16:20:05')
print(dt_bd)

Using the above datetime of your birthday, print your birth year , birth month , birth day , hour , minute and second.

import pandas as pd 
dt_bd=pd.to_datetime('2000-12-23 16:20:05')
print("year : ",dt_bd.year)
print("year : ",dt_bd.month)
print("year : ",dt_bd.day)
print("year : ",dt_bd.hour)

How old you were as on 1st of Jan 2020, 13 Hours, 22 minutes and 34 seconds

import pandas as pd 
dt_bd=pd.to_datetime('2000-12-23 16:20:05')
dt_target=pd.to_datetime('2020-01-01 13:22:34')
print(dt_target-dt_bd)

6947 days 21:02:29

import pandas as pd 
import numpy as np
from dateutil.relativedelta import relativedelta

dt_bd=pd.to_datetime('2001-11-22 16:20:05')
dt_target=pd.to_datetime('2020-01-01 13:22:34')
dt_diff=dt_target-dt_bd
print(dt_diff)
print(dt_diff/np.timedelta64(1,'W'))

6613 days 21:02:29
944.8395320767196

import pandas as pd 
import numpy as np
from dateutil.relativedelta import relativedelta

dt_bd=pd.to_datetime('2001-11-22 16:20:05')
dt_target=pd.to_datetime('2020-01-01 13:22:34')
dt_diff=dt_target-dt_bd
print(dt_diff)
print(dt_diff/np.timedelta64(1,'M'))

6613 days 21:02:29
217.29815312961784

How old you are as on present date and time.

import pandas as pd 
dt_now=pd.to_datetime('now')
dt_bd=pd.to_datetime('2001-11-22 16:20:05')
dt_diff=dt_now-dt_bd
print(dt_diff)

6721 days 10:37:40.983745

Add 5 years , 2 months and 25 days to your birthday.

import pandas as pd 
import numpy as np
dt_bd=pd.to_datetime('2001-11-22 16:20:05')
dt_new=dt_bd + np.timedelta64(5,'Y') + np.timedelta64(2,'M') + np.timedelta64(25,'D')
print(dt_new)

2007-02-16 18:24:17

What is the date and time now. Write in different formats ( 1st April 2019, 20 December 2010, 16/02/2020 12:32:45 )

import pandas as pd 
dt_now=pd.to_datetime('now')
print(dt_now)

import pandas as pd 
dt_now=pd.to_datetime('now')
print(dt_now)
print(dt_now.strftime('%d-%b-%Y')) #18-Apr-2020
print(dt_now.strftime('%d-%B-%Y')) #18-April-2020
print(dt_now.strftime('%D %X')) # 04/18/20 20:59:42
print(dt_now.strftime('%c')) # Sat Apr 18 20:05:03 2020

Create a date and time series with 10 elements, with a frequency of 3 days 6 hours starting from previous 10 days

import pandas as pd 
dt_now=pd.to_datetime('now')
dt_start=dt_now -  pd.to_timedelta(10,unit='days')
my_data=pd.date_range(start=dt_start, periods=10,freq='3D6H')
print(my_data)

Write milliseconds and microseconds to above format

print(my_data.strftime('%H:%M:%S %f'))

Prepare a list of name and date of birth of your friends. Find out the name of the weekday from their date of birth.

import pandas as pd 
dt_now=pd.to_datetime('now')
dt_start=pd.to_datetime('2001-01-22 16:20:05')
my_data=pd.date_range(start=dt_start, periods=10,freq='25D')
#print(my_data)
print(my_data.day_name())

Index(['Monday', 'Friday', 'Tuesday', 'Saturday', 'Wednesday', 'Sunday',
       'Thursday', 'Monday', 'Friday', 'Tuesday'],
      dtype='object')

Print the business days in last 10 days from today.

import pandas as pd 
dt_now=pd.to_datetime('now')
dt_start=dt_now -  pd.to_timedelta(10,unit='days')
my_data=pd.period_range(start=dt_start, periods=10,freq='B')
print(my_data.strftime('%x %A'))

Index(['04/08/20 Wednesday', '04/09/20 Thursday', '04/10/20 Friday',
       '04/13/20 Monday', '04/14/20 Tuesday', '04/15/20 Wednesday',
       '04/16/20 Thursday', '04/17/20 Friday', '04/20/20 Monday',
       '04/21/20 Tuesday'],
      dtype='object')