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Learn how to work with Python lists efficiently. Explore creation, manipulation, and advanced operations with examples. Dive into using lists as stacks, queues, filtering, mapping, and reducing. Discover sets and dictionaries in Python.
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Python Data Structures CS 265 Seth Simpson
Lists • Creating Lists • exampleList = [1,3,5,7,9] • List methods • Append(element) – appends element to end • Extend(list) – extends the list with another list • Insert(position, element) – insert element at the given position • Remove(element) – removes the first occurrence of the element
Lists (Cont) • More List methods • Pop(index) – Remove and return the element at index (last element by default) • Index(element) – returns index of the first occurrence of element • Count(element) – returns the number of times element appears in the list • Sort() – sorts the list • Reverse() – reverses the list
Lists as Stacks • Last in – First out • List pop function enables us to treat lists as stacks.
Lists as Queues • First in – first out • Popping end elements of a list is fast because the elements don’t need to be rearranged • Popping from the front of a list is slow because the list needs to be rearranged
List Filtering • Filter(function name, list) • Returns a sequence of items for which function(item) is true. • Example:
List Mapping • Map(function name, list) • Calls the function for each value in the list and outputs the results as list • Example:
List Reducing • Reduce(function name, list) • Returns a single value by computing the function value on the first two elements, then the result of that with the next element and so on.
Sets • Unordered collection with no duplicates
Dictionaries • Unsorted set of Key : Value pairs
Dictionaries (Cont) • Can also call the dict() constructor to create a dictionary. • Printing out Dictionaries