Enhanced Graph Initialization and DataFrame Analysis

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📅 2023-09-11 — Session: Enhanced Graph Initialization and DataFrame Analysis

🕒 21:30–23:15
🏷️ Labels: Python, Graph Theory, Dataframe, Seaborn, Performance Optimization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to implement and optimize graph initialization methods in Python, along with analyzing and visualizing data using DataFrames and Seaborn.

Key Activities:

  • Implemented various graph initialization methods focusing on initialize_from_edges to enhance performance.
  • Set default behaviors for vertex insertion and edge operations in graph classes, ensuring robust handling of cases with unspecified parameters.
  • Conducted timing experiments on different methods, aggregating results in a DataFrame.
  • Utilized pandas to group data and identify optimal representation methods based on performance metrics.
  • Restructured code for analyzing winning methods and corrected execution errors.
  • Visualized execution times using Seaborn’s boxplot and lineplot, correcting code for proper visualization.

Achievements:

  • Successfully implemented default parameter handling for graph operations.
  • Enhanced data analysis through optimized DataFrame operations and visualization techniques.

Pending Tasks:

  • Further refine the graph initialization methods for additional performance gains.
  • Explore additional visualization techniques to better represent execution time data.

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