📅 2023-08-19 — Session: Data Analysis and Visualization Enhancements
🕒 21:45–22:30
🏷️ Labels: Data Analysis, Visualization, Python, Matplotlib, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance data analysis and visualization techniques using Python, focusing on identifying representative regions and generating plots for districts and unique regions.
Key Activities
- Identifying Representative Region: Grouped dataset entries by ‘distrito_id’, ‘seccion_id’, and ‘seccion_nombre’ to determine the representative region based on the highest count.
- Generating Plots: Created Python scripts to generate and save plots for each unique district using Matplotlib, ensuring proper labeling.
- Plotting by Unique Regions: Implemented a loop to filter data by unique regions in a DataFrame and generate region-specific plots.
- Fixing Plot Title Cutoff: Addressed an issue with Matplotlib’s
plt.tight_layout()method, ensuring super titles are not cut off by adjusting layout settings after setting the super title. - Filtering Data: Filtered a DataFrame for the ‘Pampeana’ region and ‘La Libertad Avanza’ agrupación, extracting specific columns for further analysis.
Achievements
- Successfully implemented data grouping and filtering techniques to identify and analyze representative regions.
- Enhanced data visualization by generating district and region-specific plots with proper labeling and layout adjustments.
- Resolved layout issues in Matplotlib to improve the presentation of plots.
Pending Tasks
- Further refine the data filtering criteria to include additional regions and agrupaciones for comprehensive analysis.
- Explore additional visualization techniques to enhance data insights.