Python for Data Science – Overview

This beginner-friendly series teaches the fundamentals of Python and pandas for working with data. Each chapter introduces essential data science techniques through hands-on coding examples using real-world datasets like NBA player statistics. Our goal is to make data science accessible, practical, and engaging—even for those with no prior programming experience.

Table of Contents

• Chapter 1: Introduction to Python and Jupyter Notebooks
• Chapter 2: Pandas Basics – Series, DataFrames, and Indexing
• Chapter 3: Data Cleaning – Handling Missing Data, Filtering, and Sorting
• Chapter 4: Grouping and Aggregation – Summarizing Data with groupby
• Chapter 5: Exploratory Data Analysis – Distributions and Summary Statistics
• Chapter 6: Data Visualization with Seaborn and Matplotlib