Enhanced Data Visualization and Food Data Processing

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📅 2023-03-06 — Session: Enhanced Data Visualization and Food Data Processing

🕒 01:10–03:00
🏷️ Labels: Python, Data Visualization, Pandas, CSV, Nutrition
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to enhance data visualization techniques using Python libraries and to process food nutritional data for meal planning.

Key Activities

  • Date Formatting in Pandas: Implemented strftime to format dates as year-week labels.
  • Code Optimization: Improved Python code organization for data visualization using seaborn and matplotlib.
  • [[Data Visualization]] Enhancements: Added horizontal lines in Matplotlib plots and rotated x-axis labels in Seaborn boxplots.
  • Polynomial Fitting: Utilized NumPy to fit a second-order polynomial to data.
  • Food Data Export: Exported nutritional data to a CSV file using pandas.
  • CSV Processing: Developed functions to process CSV files for calculating macros and meal planning.

Achievements

  • Successfully formatted dates for better week separation in datasets.
  • Improved readability and maintainability of data visualization code.
  • Enhanced data visualization with additional plotting techniques.
  • Efficiently exported and processed food data for nutritional analysis.

Pending Tasks

  • Further refine the meal planning algorithm to incorporate more dietary preferences and constraints.

Graph View

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