The datetime library and Split function

Financial Forecasting in Python

Victoria Clark

CGMA Financial Analyst

Types of conflicts

Date: 09/10/2018

Regional differences

  • Day-Month-Year
  • Month-Day-Year

Punctuation differences

  • dd-mm-yy
  • dd/mm/yyyy

financial statements

Financial Forecasting in Python

The datetime function

# Import datetime module
from datetime import datetime

datetime.strptime(date_string,
                  format)

12-25-2000 --> %m-%d-%Y'

datetime.strptime('12-25-2000',
                  '%m-%d-%Y')

print(dt_object.month)

12

Dates

Financial Forecasting in Python

Using the split() function

  • split() function
date = '14/02/2018'

# Split date string into named variables using /
day, month, year = date.split('/')

print(year)

2018
Financial Forecasting in Python

Let's practice!

Financial Forecasting in Python

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