📅 2024-01-15 — Session: Developed Stock Data Processing and Visualization Workflow
🕒 18:30–19:00
🏷️ Labels: Stock Analysis, Data Processing, Visualization, Python, Matplotlib
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal:
The session aimed to develop a comprehensive workflow for processing and visualizing stock data using Python, Pandas, and Matplotlib.
Key Activities:
- Manual Plotting with Matplotlib: Implemented manual plotting techniques to address x-axis date formatting issues, enhancing control over data visualization.
- Workflow Planning: Outlined a workflow for analyzing stock data, including the creation of functions for data processing and plotting.
- Function Implementation: Developed functions for processing stock data, including date parsing and setting them as an index, and for plotting multiple data columns over time.
- Business Case Atlas Creation: Processed stock data to create an ‘atlas’ of past business cases, involving sampling, sorting, and visualization in Markdown format.
- Data Conversion: Converted Excel-style date integers to Pandas Timestamps using
pandas.to_datetime()within a data processing loop.
Achievements:
- Successfully implemented a workflow for stock data analysis and visualization.
- Developed reusable functions for data processing and plotting.
- Enhanced data visualization techniques with manual date formatting control.
Pending Tasks:
- Further refine the data processing functions to accommodate various data structures and analysis objectives.
- Explore additional visualization techniques to improve data representation.