Enhanced Data Visualization Techniques in Python

📅 2023-05-22 — Session: Enhanced Data Visualization Techniques in Python

🕒 21:30–22:55
🏷️ Labels: Python, Data Visualization, Matplotlib, Pandas, Function Modification
📂 Project: Dev
⭐ Priority: MEDIUM

The session aimed to enhance data visualization techniques in Python, focusing on customizing plots and addressing indexing issues.

Modified the process_data function to optionally handle date ranges, allowing the function to return the original dataframe when no date range is specified.
Customized histogram legend labels using Matplotlib for better data representation.
Implemented histogram plotting by month using pandas and Matplotlib, leveraging pd.Grouper for datetime grouping.
Created a heatmap-like plot to visualize event occurrences on specific days, similar to GitHub’s contribution graph.
Developed a weekly grid representation of marked days, utilizing Matplotlib for visualization.
Transposed a grid for vertical display using NumPy, enhancing the visualization of resistance events.
Set x-axis tick labels to days of the week to improve plot readability.
Corrected week index calculation and grid indexing to ensure proper alignment and display of marked days.

Successfully implemented optional date range handling in data processing functions.
Enhanced data visualization plots with customized legends and improved readability.
Resolved indexing issues in grid plots, ensuring accurate representation of time-based data.

Further explore advanced data visualization techniques to enhance user interaction and insights.