Python in Excel Step-by-Step

Chapter 3Data Structures

Take a step back and think about what Microsoft Excel does. Sure, Excel allows you to analyze data using pivot tables and charts. However, it must first do something more fundamental – Microsoft Excel must store data.

You can think of Excel as storing data in multiple ways:

• Workbooks
• Worksheets
• Tables
• Cells

Intuitively, you can think of all these as being containers in which you store data. Just like in the real world, each type of container has different capabilities for storing data.

Consider an Excel worksheet. It provides you with the capabilities of storing data in terms of rows and columns. Similarly, an Excel table does the same thing but provides additional capabilities (e.g. header filters).

Worksheets and tables are examples of Excel’s built-in data structures. Data structures provide functionality for storing, organizing, and managing data based on rules.

Just as skills with worksheets and tables are fundamental to being successful with Excel, so it is with learning Python’s most important built-in data structures.

3.1 LISTS

Imagine that you’re about to head out to purchase some groceries. Like so many, you make a list of what you need to make sure you don’t forget anything. You could use Excel to write your grocery list, as shown in Figure 3.1.

Figure 3-1: Your Grocery List.

Think about Figure 3.1 for a second. Conceptually, the grocery ...