📅 2023-09-11 — Session: Enhanced Graph and DataFrame Operations in Python
🕒 21:30–23:15
🏷️ Labels: Python, Graph Theory, Dataframe, Optimization, Visualization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance graph operations and optimize DataFrame manipulations using Python, focusing on algorithmic improvements and performance measurement.
Key Activities
- Implemented various graph initialization methods, particularly focusing on
initialize_from_edges. - Set default behaviors for vertex insertion, linking new vertices to existing ones by default.
- Modified edge operations to use default values when none are provided.
- Conducted timing experiments on DataFrame operations and identified optimal representation methods using
idxmin. - Grouped data by method and size in pandas to find the most frequent optimal method.
- Visualized execution times using Seaborn’s boxplot and lineplot functions, correcting code for better visualization.
Achievements
- Successfully implemented default parameter handling in graph operations, enhancing flexibility.
- Optimized DataFrame operations to identify and utilize the most efficient methods.
- Improved visualization of execution times, aiding in performance analysis.
Pending Tasks
- Further refine graph algorithms to handle larger datasets efficiently.
- Explore additional visualization techniques to better represent data trends.