Enhanced Data Visualization with Python and Matplotlib

• Day: 2023-05-22
• Time: 21:30 to 23:00
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Visualization, Matplotlib, Grid Plotting, Histogram

Description

Session Goal

The session aimed to enhance data visualization capabilities using Python and Matplotlib, focusing on improving the representation of data through various plotting techniques.

Key Activities

• Modified the process_data function to handle optional date ranges, allowing for more flexible data processing.
• Customized histogram legends in Matplotlib to assign specific labels to datasets.
• Created histograms to visualize project counts per month using pandas and Matplotlib.
• Developed a heatmap-like plot to represent event occurrences, similar to GitHub’s contribution graph.
• Generated a grid representation of marked days, using Matplotlib to visualize weekdays and weeks.
• Transposed grids for vertical display, enhancing visualization of resistance events.
• Set x-axis tick labels to days of the week to improve plot readability.
• Corrected week index calculations and grid indexing in plotting, ensuring proper alignment and display of data.

Achievements

• Successfully implemented flexible data processing and enhanced visualization techniques.
• Improved the accuracy and readability of plots through custom labeling and indexing corrections.

Pending Tasks

• Further exploration of advanced visualization techniques to enhance data storytelling and insights.

Evidence

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• event_ids: []