In Python, the way you manage your data can have a significant impact on memory usage. By understanding the implications of different data structures, you can write more efficient and effective code.

Implementations of common data structures like lists, stacks, queues, trees, and graphs. Code for various algorithms including searching, sorting, traversing, and dynamic programming. Examples ...

“The ability to run Python in Excel simplifies McKinney's reporting workflows. We used to manipulate data structures, filter, and aggregate data in a Jupyter Notebook, and build visuals in Excel. Now ...

Welcome to the Data Structure Revision repository! This repo is designed to help you revise fundamental data structures, key concepts, algorithms, and practical implementations across various ...

This includes basic control structures in Python: conditional branches, for loops and recursion; functions: defining and calling functions, and recursion; in-built data structures: lists and ...

This course introduces data structures and algorithms for constructing efficient computer programs based on Python. Principles of algorithmic analysis will be studied. Emphasis is on data structures ...