📅 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.