Developed Election Database Schema and Data Processing Scripts

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Developed Election Database Schema and Data Processing Scripts

  • Day: 2023-07-13
  • Time: 00:20 to 01:10
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Database, Election, Python, Pandas, DBML, SQL

Description

Session Goal

The session aimed to design and implement a database schema for managing election data and to develop Python scripts for data processing.

Key Activities

  • Database Schema Design: Developed a comprehensive database schema for election management using markdown and DBML formats, detailing tables, primary keys, and foreign key relationships.
  • SQL Table Creation: Provided SQL DDL examples for creating election-related tables, ensuring proper key definitions.
  • Data Processing with Python: Created Python scripts using Pandas for loading, filtering, and concatenating CSV datasets, focusing on election vote data.

Achievements

  • Successfully outlined and documented a database schema for elections, including tables for elections, districts, sections, and circuits.
  • Developed SQL scripts for table creation with a focus on maintaining data integrity through key constraints.
  • Implemented Python scripts for efficient data manipulation, enabling the loading and processing of election data.

Pending Tasks

  • Further testing and validation of the database schema and Python scripts to ensure robustness and accuracy.
  • Integration of the database schema with existing systems for real-time data management.

Evidence

  • source_file=2023-07-13.sessions.jsonl, line_number=1, event_count=0, session_id=37366b9ab7ce5312f8a86bece1a1034e4ae4f425199306f1015ac3d1e621a421
  • event_ids: []

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