Introduction to SQL and Python for Data Analysis

This book provides a brief and gentle introduction to using Python and SQL for data analysis. The goal is not to cover the fundamentals of programming in Python, or to understand the database architecture behind relational database. Instead, this book aims to present practical tools and serve as a jumping off point for doing data analysis with SQL and Python. Keeping this goal in mind, this book assumes no prior programming knowledge, and only a minimum level of statistical knowledge.

Start by reading through the material in the Getting Started section to get a sense for how to use the Jupyter notebooks used in this book, as well as understand the structure of the data used in the examples.

In each chapter, we will start with a motivating question, then walk through the process we need to go through in order to answer the motivating question. Along the way, we will walk through various SQL and Python commands and develop skills as we work towards answering the question. As you work through this book, you will run into some headers that are in RED. These headers indicate a checkpoint to practice writing the code yourself. You should stop at these checkpoints and try doing the exercises and answering the questions posed in these sections by clicking on the rocketship icon button at the top of the page and choosing Binder or Colab. Note that Colab will not work for SQL material.

Getting Started

• Introduction to Jupyter Notebooks
• Data

Data Analysis with Python

• Introduction to Python and Pandas
• Data Management in Python
• Functions and Loops
• Visualizations

SQL

• Introduction to SQL and Relational Databases
• SQL Joins

SQL in Python

• Using SQL and Python Together
• Example: Finding Jobs by County over Years