🗄️ SQL for Data Science

Personal notes and reference guide covering SQL fundamentals, advanced queries, and database access with Python.

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📚 Contents

Part I — SQL for Data Manipulation

• Introduction to databases, RDBMS, and SQL
• SELECT statement: filtering, pattern matching, ranges, sorting
• COUNT, DISTINCT, LIMIT, OFFSET
• Grouping and aggregating with GROUP BY, HAVING, AS
• INSERT, UPDATE, DELETE statements

Part II — Functions, Multiple Tables & Subqueries

• Aggregate functions: SUM, MIN, MAX, AVG, COUNT
• Scalar and string functions
• Date and time functions
• Subqueries (nested SELECT in WHERE, SELECT, FROM)
• Accessing multiple tables: subqueries, implicit joins, explicit JOIN operations

Part III — SQL Statement Types & DDL

• Relational model, Entity-Relationship (ER) model
• Primary keys, foreign keys, and constraints
• DDL vs DML categories
• CREATE TABLE, ALTER TABLE, DROP TABLE, TRUNCATE

Part IV — Accessing Databases with Python

• Python DB-API overview and workflow
• Connection objects and cursor objects
• SQL Magic in Jupyter Notebooks (%sql, %%sql)
• Exploratory Data Analysis with pandas and seaborn
• Practical case study: McDonald's nutritional dataset (SQLite + Python)

👤 Author

Matthieu Vanhoecke