Converting date formats - simple
Sales area A in Europe and Sales area B in Australia have different date formats.
- Sale A: 4000 on 14/02/2018
- Sale B: 3000 on 2 March 2018
If we want to consolidate or compare sales periods, we need to convert to the same date format. We can easily do this by using the datetime library and the datetime.strptime(date_string, format) method, using the following directives:
| Directive | Meaning | Example |
|---|---|---|
| %d | Day of the month as a zero-padded decimal number | 01, 02, …, 31 |
| %b | Month as locale’s abbreviated name | Jan, Feb, …, Dec |
| %B | Month as locale’s full name | January, …, December |
| %m | Month as a zero-padded decimal number | 01, 02, …, 12 |
| %y | Year without century as a zero-padded decimal number | 00, 01, …, 99 |
| %Y | Year with century as a decimal number | 1970, 1988, 2001, 2013 |
Cet exercice fait partie du cours
Financial Forecasting in Python
Instructions
- Import the
datetimelibrary. - Create a
dt_objectthat converts the dates of each sale into a standardized format of day-month-year. - Print each result to compare
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Import the datetime python library
from ____ import ____
# Create a dt_object to convert the first date and print the month result
dt_object1 = datetime.strptime('14/02/2018', '____')
print(____)
# Create a dt_object to convert the second date and print the month result
dt_object2 = datetime.strptime('2 March 2018', '____')
print(____)