Module 3 | Python Data Structures

The Importance of Data Structures

They determine efficiency of accessing, modifying, and organizing data

Real-World Use of Data Structures

In search engines, operating systems, and AI applications

A Python data structure which is mutable and stores ordered items

List

A Python data structure which stores key-value pairs

Dictionary

A Python data structure which ensures uniqueness of elements

Set

A Python sequence type

List

A Python mapping type

Dict

Data structures determine how quickly data can be retrieved, updated, inserted, or deleted

Efficient Data Access and Modification

The right data structure saves memory and CPU time, especially with large data

Optimal Use of Resources

Data structures allow you to organize data logically

Organizing Complex Data

The right data structure can make algorithms faster and more scalable

Improved Algorithm Performance

Many programming problems are fundamentally about data organization

Foundation for Problem Solving

Search engines, databases, operating systems, and AI all rely on data structures

Use in Real-World Applications

Choosing the right data structure makes code easier to read, understand, and maintain

Readability and Maintainability

List

A dynamic, ordered, mutable sequence of items

An immutable ordered collection of items

Tuple

An unordered collection of unique items

Set

A mutable collection of key-value pairs

Dictionary

An immutable sequence of Unicode characters

String

An ordered collection of elements indexed by position (starting at 0)

Sequence

A collection of key-value pairs, where each value is associated with a unique key

Mapping

A mutable sequence type in Python

List

An immutable ordered collection in Python

Tuple

An immutable sequence that generates numbers (e.g., 0,1,2,3,4)

Range

An example of a sequence type

Tuple

An example of a mapping type

Dict