Data Analysis and Visualization Enhancements
- Day: 2023-08-19
- Time: 21:45 to 22:30
- Project: Dev
- Workspace: WP 2: Operational
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Data Analysis, Visualization, Python, Matplotlib, Pandas
Description
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.
Evidence
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- event_ids: []