In Post #58, we learned that tuples are created using parentheses, like my_tuple = (1, 2, 3). This seems straightforward, but there is a subtle syntax rule that catches nearly every new Python programmer by surprise, especially when trying to create a tuple with only one item. In this post, we’ll look at this specific … Read more
Throughout Part 3 so far, we’ve focused on the list, Python’s workhorse for storing collections of data. We’ve emphasized that lists are mutable, meaning they are designed to be changed (a concept we covered in Post #49). But what if you have a collection of items that you want to ensure never changes after it’s … Read more
It’s time for another project! We’ve spent the last several posts exploring Python’s most versatile data structure, the list. We’ve learned how to create them, add to them, remove from them, and loop through them like a pro. Now, we will combine all of that knowledge to build a useful, interactive program: a command-line to-do … Read more
In Post #34, we learned that the for loop is the best way to iterate over the items in a list. The simple for fruit in fruits: syntax is clean and effective for when you only care about the items themselves. But what happens when you need to know the position of an item as … Read more
In our previous post on copying lists (Post #54), we briefly mentioned the idea of “nested lists.” This simple concept—putting lists inside other lists—unlocks the ability to represent complex, grid-like data structures. In this post, we will explore 2D lists (also known as matrices). You’ll learn how to structure them to represent tabular data and … Read more
This is one of the most important conceptual posts in this entire section. Understanding the difference between assigning a list and copying a list will save you from hours of debugging mysterious and frustrating bugs. Because lists are mutable (a concept we covered in Post #49), the way we duplicate them is critically important. A … Read more
In the last few posts, we’ve learned how to add (Post #50), remove (Post #51), and sort (Post #52) the items in our lists. Python’s lists come equipped with several other handy utility methods for finding information about their contents. In this post, we’ll cover three of these essential methods: .index() to find an item’s … Read more
In Post #50 and Post #51, we learned how to change lists by adding and removing items. Another common and crucial operation is to organize the data within a list by sorting it, for example, from lowest to highest or in alphabetical order. Python provides two ways to do this: the .sort() method and the … Read more
In Post #50, we learned how to grow lists using methods like .append() and .insert(). But the mutability of lists (which we discussed in Post #49) also means we can shrink them. Removing items is just as common and important as adding them. In this post, we’ll explore the three primary ways to remove items … Read more
In Post #49, we established that lists are mutable, meaning we can change them after they are created. This ability to grow and shrink is what makes them so useful for managing dynamic collections of data. But how exactly do we add new items to a list? In this post, we’ll explore the three primary … Read more