Enhanced Time Series Data Visualization in Python

📅 2023-10-26 — Session: Enhanced Time Series Data Visualization in Python

🕒 20:05–21:05
🏷️ Labels: Python, Data Visualization, Time Series, Matplotlib, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The goal of this session was to enhance and refine the process of creating time series plots using Python, focusing on improving visualization techniques and data management.

Key Activities

• Developed a step-by-step guide for creating time series plots from CSV data using Python libraries such as Pandas and Matplotlib.
• Implemented a script to handle the plotting of time series data, including scatter plots, moving averages, and percentile shading.
• Updated the plot_time_series function to enhance its capabilities, including conditional checks for quantiles and specific cases.
• Created plots by grouping data based on specific columns, such as the ‘AGLOSI’ column, to visualize different groups within the dataset.
• Adjusted data visualization techniques by modifying rolling averages, y-axis limits, line styles, and color manipulations to improve clarity.
• Solved color adjustment issues by converting RGB to HLS and back to RGB to handle TypeErrors.
• Expanded the files_info dictionary to better manage time series data attributes for analysis.

Achievements

• Successfully implemented enhanced visualization techniques for time series data.
• Improved data management strategies for handling time series data attributes.

Pending Tasks

• Further testing and validation of the updated plotting functions and scripts in diverse datasets.
• Exploration of additional customization options for time series plots to cater to specific analytical needs.