Merging months into quarters
Now we saw what to do when we wanted to split quarters into months for more detailed monthly information. But what happens when the opposite is true and we wish to combine data into fewer columns? This is typical when dealing with historical data, when monthly details may not be necessary, or when we need a highly consolidated version of the data for a report.
The key here is to create an index, and then only add to the quarter total quarter in cycles of 3, or until the length of the list. We can do this with the following code:
if index % 3 == 0 or index == len(months):
This code checks whether the index divided by three yields a remainder of 0, or if the index is at the end of the list months. Thus, in a loop it will execute the specified code every three months or when it reaches the end of the list.
The monthly sales are already provided in the code as months, containing the sales from the first two quarters, as well as the first month of Q3. Your task is to generate a new list called quarters that contains the quarterly totals from the first three months (which includes the partial total of Q3).
This is a part of the course
“Financial Forecasting in Python”
Exercise instructions
Initialize an empty list
quartersto contain the new quarterly values, and an index variableindexset to1.Create a for loop to find the monthly
salesinmonths:- Add the monthly sales to
quarter. - If it's the end of the quarter or the end of the list
months, append your quarterly total toquarters. - Reset the quarterly total
quarterto 0, increment the index by 1 (this has been done for you).
- Add the monthly sales to
Print the quarterly totals.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a months list, as well as an index, and set the quarter to 0
months = [100, 100, 150, 250, 300, 10, 20]
quarter = 0
____ = ____
____ = ____
# Create for loop for quarter, print result, and increment the index
for sales in months:
quarter += ____
if index % ____ == ____ or index == len(____):
____.append(____)
quarter = 0
index = index + 1
print("The quarter totals are Q1: {}, Q2: {}, Q3: {}".format(quarters[0], ____, ____))This exercise is part of the course
Financial Forecasting in Python
Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.
We have gotten a basic understanding of income statements and balance sheets. However, consolidating data for forecasting is complex, so in this chapter, we will look at some basic tools to help solve some of the complexities specifically relating to finance - working with dates and different financial periods, and formatting our raw data into the correct format for financial forecasting.
Exercise 1: Financial periods and how to work with themExercise 2: Converting quarters into monthsExercise 3: Merging months into quartersExercise 4: The datetime libraryExercise 5: Working with the datetime libraryExercise 6: Converting date formats - simpleExercise 7: Converting date formats - explicitExercise 8: Tips and tricks when working with datasetsExercise 9: Working with datasets - month totalsExercise 10: Working with datasets - combining datasetsExercise 11: Working with datasets - exporting dataWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.