📅 2023-02-25 — Session: Optimized Data Loading and Regression Code
🕒 00:15–00:35
🏷️ Labels: Python, Data Analysis, Code Optimization, Regression, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The aim of this session was to optimize Python code for data loading and regression analysis, as well as to develop flexible data aggregation functions.
Key Activities
- Implemented an optimized version of Python code for loading datasets, including project information, violence levels, and covariates.
- Conducted regression analysis with improved data handling and merging techniques.
- Developed a Python function for aggregating pandas DataFrames with customizable grouping and operations (sum or mean).
- Enhanced the
groupby_aggregatefunction to accept custom aggregation functions for flexible data analysis.
Achievements
- Successfully optimized data loading and regression code, resulting in cleaner and more efficient data processing.
- Created flexible data aggregation functions to support diverse analytical needs.
Pending Tasks
- Further testing and validation of the optimized code and aggregation functions to ensure robustness and accuracy in various scenarios.