📅 2023-08-19 — Session: Data Analysis and Visualization Enhancements
🕒 21:45–22:30
🏷️ Labels: Data Analysis, Python, Matplotlib, Pandas, Data Visualization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance data analysis and visualization techniques using Python, focusing on identifying representative regions, generating district plots, and addressing visualization issues.
Key Activities
- Representative Region Identification: Utilized Pandas to group dataset entries by ‘distrito_id’, ‘seccion_id’, and ‘seccion_nombre’, counting rows to identify the most representative region.
- District Plot Generation: Developed Python scripts using Matplotlib to create and save plots for each unique district, ensuring proper labeling.
- Region Plotting: Implemented a loop in Python to filter data by unique regions in a DataFrame and generate corresponding plots, saving them with specific filenames.
- Super Title Adjustment: Addressed and resolved a Matplotlib issue where the super title was being cut off by adjusting the layout after setting the title.
- DataFrame Filtering: Filtered a DataFrame for the ‘Pampeana’ region and ‘La Libertad Avanza’ agrupación, extracting necessary columns.
Achievements
- Successfully identified the representative region from the dataset.
- Generated and saved district and region-specific plots with accurate labels and filenames.
- Resolved the Matplotlib super title cutoff issue, ensuring better presentation of plots.
Pending Tasks
- Further exploration of data visualization techniques for other regions and agrupacións.
- Optimization of data filtering processes for enhanced performance.