📅 2025-06-21 — Session: Developed SQL and Pandas Split-Apply-Combine Exercises
🕒 01:00–01:35
🏷️ Labels: SQL, Pandas, Data Analysis, Education, Exercise, Pipeline
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal:
The session aimed to explore and develop exercises using the split-apply-combine pattern in both SQL and Pandas, focusing on data manipulation and analysis techniques.
Key Activities:
- SQL Split-Apply-Combine Pattern Example: A minimal example was provided to demonstrate calculating total revenue per product category using SQL queries.
- Pandas Split-Apply-Combine Pattern: A step-by-step guide was created to implement this pattern in Pandas, using a toy DataFrame for demonstration.
- SQL Exercise Using Spanish Variables: An exercise was outlined using Spanish-language variables to engage specific audiences, with a focus on SQL data manipulation.
- Ejercicio de Análisis de Compras en SQL: Proposed an exercise to design a mini-process for purchase analysis, promoting critical thinking and logical planning in SQL.
- Diseño de un ejercicio de SQL sobre pipelines: Detailed a pedagogical exercise for learning SQL through a cheatsheet and practical pipeline design problem.
- SQL Cheatsheet and Exercise for Pipelines: An expanded cheatsheet and exercise were provided, incorporating a four-step pipeline using JOIN operations.
- Construcción de un Pipeline SQL en 3 Pasos: Described a structured activity to build a SQL pipeline calculating total sales by category.
Achievements:
- Developed comprehensive exercises and guides for both SQL and Pandas, enhancing educational resources.
- Created SQL exercises tailored for Spanish-speaking audiences, expanding accessibility.
Pending Tasks:
- Further testing and refinement of exercises to ensure clarity and effectiveness.
- Translation of SQL exercises into other languages to broaden reach.