Get startedGet started for free

Cumulative statistics

Cumulative statistics can also be helpful in tracking summary statistics over time. In this exercise, you'll calculate the cumulative sum and cumulative max of a department's weekly sales, which will allow you to identify what the total sales were so far as well as what the highest weekly sales were so far.

A DataFrame called sales_1_1 has been created for you, which contains the sales data for department 1 of store 1. pandas is loaded as pd.

This exercise is part of the course

Data Manipulation with pandas

View Course

Exercise instructions

  • Sort the rows of sales_1_1 by the date column in ascending order.
  • Get the cumulative sum of weekly_sales and add it as a new column of sales_1_1 called cum_weekly_sales.
  • Get the cumulative maximum of weekly_sales, and add it as a column called cum_max_sales.
  • Print the date, weekly_sales, cum_weekly_sales, and cum_max_sales columns.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Sort sales_1_1 by date
sales_1_1 = ____

# Get the cumulative sum of weekly_sales, add as cum_weekly_sales col
sales_1_1[____] = ____

# Get the cumulative max of weekly_sales, add as cum_max_sales col
____

# See the columns you calculated
print(sales_1_1[["date", "weekly_sales", "cum_weekly_sales", "cum_max_sales"]])
Edit and Run Code