📅 2024-04-15 — Session: Enhanced EDA and Flask API Documentation

🕒 00:40–02:00
🏷️ Labels: EDA, Flask, Swagger, Python, Data Visualization, API
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal:

The session aimed to enhance the Exploratory Data Analysis (EDA) of the diamonds dataset and to document a Flask API using Swagger.

Key Activities:

  • Enhanced the EDA notebook for the diamonds dataset by improving visualizations with clearer plot titles and additional analyses using Python libraries such as Pandas, Seaborn, and Matplotlib.
  • Created subplots with scatter plots in Matplotlib to visualize data more effectively.
  • Adjusted data preprocessing functions to filter out erroneous data entries, improving data quality for machine learning models.
  • Streamlined the preprocess_data function for better efficiency and integration with machine learning workflows.
  • Documented a Flask API using Swagger, including setting up OpenAPI documentation and integrating Swagger UI.
  • Organized the main.py file in the Flask application to improve code maintainability and resolve blueprint registration conflicts.

Achievements:

  • Successfully enhanced the EDA process with improved data visualizations and preprocessing techniques.
  • Documented a Flask API effectively using Swagger, ensuring clear and accessible API documentation.

Pending Tasks:

  • Further testing and validation of the enhanced EDA notebook and Flask API documentation to ensure robustness and accuracy.