📅 2023-11-02 — Session: Enhanced Data Visualization with Python
🕒 15:25–16:10
🏷️ Labels: Python, Data Visualization, Error Correction, Matplotlib, Code Optimization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session focused on improving data visualization techniques using Python, specifically targeting the enhancement of plotting capabilities and error correction in data manipulation.
Key Activities
- Modified graph generation code to include percentage formatting, line styles, and specific markers for different data groups.
- Addressed and corrected syntax errors in marker assignments within a data plotting loop.
- Provided guidance on extracting and utilizing DataFrame values for grouping operations, ensuring correct usage of the
file_info['grouper']for unique value grouping. - Resolved DataFrame indexing errors by suggesting the use of
.loc[]or direct column access instead of.iloc[]. - Improved method for accessing ‘base’ column values in grouped DataFrames, emphasizing direct access methods.
- Developed a compact code version for group plotting, integrating warning checks for unique ‘base’ values.
- Conducted a final code review, providing feedback on structure, readability, and debugging practices.
- Added annotations to Matplotlib plots to mark specific events, such as start dates of presidents, using the
ax.annotate()function.
Achievements
- Enhanced the efficiency and readability of the plotting code.
- Corrected multiple errors in data manipulation and visualization processes.
Pending Tasks
- No pending tasks were identified during this session.