Lists, Tuples, Slicing, Sets, and List Comprehensions with Python

Python Lists

Lists give us the power to store data/values into a collection, reorder and modify them.

Manually Creating a List with Python

Manual list creation is as easy as definining comma-separated values within square brackets. By storing the list into the variable numbers, we can access its elements by index, starting at 0.

Creating a Python List Dynamically Using Range

When we need to define a range of elements, we pass the starting value and ending value into the range function. The following example also demonstrates how to iterate through each item in the list with a for loop.

Appending to a Python List

The append function allows us to add elements to our list.

Negative Indices with Python

Negative indices allow us to retrieve an element from the end of a list. So if numbers is 10 elements long, numbers[-1] will return the last element of the list. numbers[-2] will return the second to last element of the list.

Extracting a Range of Elements from a Python List with Slice

Reversing a Python List

Here's a neat trick you can use to reverse the items in a list. This even works on a string.

Python Stride

Stride is how many steps to take across a range of elements. So providing a stride of 2 will iterate by 2 instead of 1. Check out the following examples to learn more:

Python Append vs. Extend

extend ends up being the better tool for merging lists together, since append inserts the set of values, which produces a nested list.

Python Pop vs. Remove

Use pop when you want to delete an element by index and remove when you want to delete an element by value. If you don't pass an index to pop, it will delete the element at the end of the list.

Python Tuples

Tuples are very similar to lists, but they're immutable. Once defined, you can't change the values, add to, or remove from a tuple. So what is the advantage of immutability? Immutable objects are inherently simpler and reduce the number of bugs in a program because the state of the object doesn't change and dependencies don't need to account for all the possible states.

Also, while lists have order, tuples have structure. Tuples are often found to store pairs or triplets of data, i.e. XY coordinates or RGB values. Note: you create tuples with parenthesis, rather than square brackets. Check out the examples below.

Knowing that tuples are immutable, what do you think would happen if you tried to append, pop, or index?

Python Tuple vs. Lists

• Tuples perform better than lists. Always use tuples when working with constant values you just need to iterate over.
• Tuples require less memory than lists. Because you can append to lists, Python will actually create a larger allocation for lists in memory in case you append.
• Tuples can be used as dictionary keys because they are immutable, where a list isn't.

Python List Comprehensions

List comprehensions are kind of a shorthand way of writing loops.

Performing Mathematical Operations on Every Element

Filtering Elements with Python

Python Sets

What makes sets different is that they are unordered, and unindexed, and written with a different syntax.

Creating and Retrieving Values from a Python Set

Modifying a Python Set

Python Programming Exercises

Try to solve the following problems, using everything you've learned up to this point. Feel free to share solutions in the comments. Optimize each solution, as much as possible.

1. Write a Python function that accepts a string and returns True if that string is a palindrome

   Input: 'moon'

   Expected Output: False

   Input: 'noon'

   Expected Output: True

   Input: 'rotator'

   Expected Output: True

   Show solution

   Try It Yourself

   def is_palindrome(word): return word == word[::-1] print(is_palindrome('moon')) print(is_palindrome('noon')) print(is_palindrome('rotator'))
   Run

2. Write a Python list comprehension that filters out the even numbers of a list of integers

   Input: [1, 3, 4, 6, 2, 9, 68, 53]

   Expected Output: [4, 6, 2, 68]

   Show solution

   Try It Yourself

   numbers = [1, 3, 4, 6, 2, 9, 68, 53] even_numbers = [x for x in numbers if x % 2 == 0] print(even_numbers)
   Run

3. Write a Python list comprehension that squares all of the integers of a list

   Input: [2, 5, 3, 4, 8]

   Expected Output: [4, 25, 9, 16, 64]

   Show solution

   Try It Yourself

   numbers = [2, 5, 3, 4, 8] squared = [x*x for x in numbers] print(squared)
   Run

4. Write a Python list comprehension that cubes all of the integers of a list

   Input: [2, 5, 3, 4, 8]

   Expected Output: [8, 125, 27, 64, 512]

   Show solution

   Try It Yourself

   numbers = [2, 5, 3, 4, 8] cubed = [x*x*x for x in numbers] print(cubed)
   Run

5. Write a Python function that accepts two parameters - a list of integers: numbers and an integer: power. Have the function return a new list of all the integer items raised to power

   Input: [2, 5, 3, 4, 8], 4

   Expected Output: [16, 625, 81, 256, 4096]

   Input: [2, 5, 3, 4, 8], 6

   Expected Output: [64, 15625, 729, 4096, 262144]

   Show solution

   Try It Yourself

   def exponentiate(numbers, power): return [x**power for x in numbers] numbers = [2, 5, 3, 4, 8] print(exponentiate(numbers, 4)) print(exponentiate(numbers, 6))
   Run