Enhanced Data Visualization and Processing Techniques

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Enhanced Data Visualization and Processing Techniques

  • Day: 2023-10-14
  • Time: 18:20 to 20:20
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, Data Visualization, Code Refactoring, Matplotlib, Data Processing

Description

Session Goal

The session aimed to enhance [[data visualization]] and processing techniques using Python, focusing on improving code modularity, clarity, and effectiveness.

Key Activities

  • Developed essential documentation for resource-limited projects to maintain clarity and usability.
  • Adjusted data processing code to include unique combinations involving base_str for more comprehensive data handling.
  • Modified DataFrame operations to manage multiple groupers and filter data using compound boolean masks.
  • Refactored code to modularize data retrieval processes, enhancing readability and maintainability.
  • Created a function for plotting time series data with Matplotlib, iterating over multiple files.
  • Implemented subplots for visualizing CBA and CBT data, including economic indicators like CB_EQUIV, Poverty, and Indigencia.
  • Updated plotting code to improve subplot arrangements, figure height, grid addition, and legend positioning.
  • Ensured consistent color mapping across plots and corrected color mapping in grouped DataFrame.
  • Plotted raw data and moving averages, adding statistical analysis for poverty and indigence data.

Achievements

  • Successfully modularized data retrieval and visualization processes, improving code structure and performance.
  • Enhanced visualization techniques with consistent color mapping and improved subplot management.

Pending Tasks

  • Further refine documentation to ensure all project stakeholders can easily understand and utilize the code.
  • Explore additional statistical methods for data analysis and visualization to provide deeper insights.

Evidence

  • source_file=2023-10-14.sessions.jsonl, line_number=1, event_count=0, session_id=8a21347653520631ba912a594f311cbe013bacb1d734a6d7d7e069588ff8cec3
  • event_ids: []

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