📅 2023-11-02 — Session: Enhanced Data Visualization with Python
🕒 15:25–16:10
🏷️ Labels: Python, Data Visualization, Error Correction, Code Optimization, Matplotlib
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance and correct a Python script for data visualization, focusing on improving the plotting logic and addressing errors in data manipulation.
Key Activities
- Modified the code for generating plots, including setting percentage formats, line styles, and specific markers for data groups.
- Corrected a syntax error in marker assignment within a data plotting loop.
- Provided guidance on extracting and using values from a DataFrame for grouping operations, ensuring correct usage of the
file_info['grouper']. - Resolved a TypeError in DataFrame indexing by suggesting the use of
.loc[]or direct column access. - Improved code efficiency by compacting the plotting logic with a warning check for unique ‘base’ values.
- Conducted a final code review, emphasizing best practices in structure, readability, and debugging.
- Added annotations to Matplotlib plots to mark specific data points, such as the start dates of presidents.
Achievements
- Successfully refined the plotting logic and corrected errors, enhancing both the efficiency and readability of the code.
- Implemented best practices in Python coding and data visualization.
Pending Tasks
- Further testing of the final code in diverse datasets to ensure robustness and accuracy.