Developed SQL and Pandas Split-Apply-Combine Exercises

• Day: 2025-06-21
• Time: 01:00 to 01:35
• Project: Teaching
• Workspace: WP 1: Strategic / Growth & Development
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: SQL, Pandas, Data Analysis, Education, Exercise, Pipeline

Description

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.

Evidence

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• event_ids: []