Enhanced EDA and Flask API documentation

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

🕒 00:35–02:05
🏷️ Labels: EDA, Flask, API, Data Visualization, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal:

The session aimed to enhance the Exploratory Data Analysis (EDA) notebook for the diamonds dataset and improve the Flask API documentation process.

Key Activities:

• EDA Enhancements: Improved visualizations in the EDA notebook for the diamonds dataset, including clearer plot titles and additional analyses using Python libraries such as pandas, seaborn, and matplotlib.
• [[Data Visualization]]: Created subplots with scatter plots in Matplotlib to enhance data representation.
• Data Preprocessing: Adjusted data preprocessing functions to filter out erroneous data, improving model accuracy.
• Function Streamlining: Refined the preprocess_data function to optimize data handling and preprocessor initialization.
• API Documentation: Documented a Flask API using Swagger, including setup, creating OpenAPI documentation, and integrating Swagger UI.
• Flask App Structuring: Organized the Flask application structure in main.py for better code maintainability.
• Blueprint Registration: Resolved conflicts related to multiple registrations of the api blueprint in Flask.

Achievements:

• Completed enhancements to the EDA notebook, leading to more insightful data visualizations.
• Successfully documented the Flask API using Swagger, improving API usability and maintenance.
• Resolved technical issues related to Flask application structure and blueprint registration.

Pending Tasks:

• Further refine the EDA notebook based on additional feedback or data insights.
• Continue monitoring the Flask API for any additional documentation needs or structural improvements.