This repository is a collection of structured coding challenges designed to build proficiency in data manipulation, cleaning, and transformation using the Python data analysis library. It functions as a hands-on tutorial for learning how to process and analyze tabular datasets through a series of practical, real-world exercises.
The project utilizes interactive documents that combine live code cells with narrative text, allowing users to execute data manipulation logic in a persistent environment. The content is organized into modular, progressive units that increase in complexity, enabling users to master core techniques such as filtering, aggregation, and the restructuring of information.
These exercises cover the full spectrum of data wrangling workflows, from initial data ingestion to the application of analytical techniques. The repository serves as a resource for developing practical data science skills and preparing for technical assessments involving complex data structures.
