📅 2023-10-26 — Session: Enhanced Data Visualization with Python and Matplotlib
🕒 21:40–22:25
🏷️ Labels: Python, Data Visualization, Matplotlib, Pandas, Percentiles
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance data visualization techniques using Python and Matplotlib, focusing on household and individual datasets.
Key Activities
- Developed Python scripts to plot household and individual datasets with distinct markers using Matplotlib.
- Implemented features to shade colors based on AGLOSI values and added a secondary y-axis.
- Created plots for multiple observables, including ‘P47T_hogar’ and ‘P47T_persona’, with marker customization and moving averages.
- Calculated and visualized 25th and 75th percentiles directly from datasets.
- Filtered datasets based on quantiles and visualized results with area filling between percentiles.
- Applied rolling averages to percentiles and visualized median income data.
- Created side-by-side plots for ‘Hogares’ and ‘Hogares Indigentes’ with color coding and moving averages.
- Modified plots to include grids and set y-axis limits for better visualization of poverty metrics.
Achievements
- Successfully implemented advanced data visualization techniques, enhancing the clarity and insight of the plotted data.
Pending Tasks
- Further refinement of visualization techniques may be needed to address specific analytical goals or datasets.