Enhanced Data Processing and Visualization Techniques

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Enhanced Data Processing and Visualization Techniques

  • Day: 2024-01-15
  • Time: 18:10 to 18:30
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Data Processing, Visualization, Python, Pandas, Finance

Description

Session Goal:

The session aimed to enhance data processing and visualization techniques for financial data, focusing on streamlining processes and improving clarity in visual outputs.

Key Activities:

  • Developed a function to streamline data processing for financial tickers, encapsulating multiple steps into a single callable function for efficiency and maintainability.
  • Created a process_stock_data function to fetch and enhance stock data, adding residuals and return columns for comprehensive analysis.
  • Explored combining line plots and candlestick charts in Matplotlib and mplfinance, detailing the setup for separate y-scales and ensuring clarity in visualization.
  • Addressed the SettingWithCopyWarning in Pandas, providing solutions to avoid it using the .copy() method and .loc[] for assignments.
  • Improved DataFrame modification practices by emphasizing the creation of copies and proper use of .loc[] for stable behavior.
  • Resolved Unix timestamp issues in date handling for line plots, ensuring dates are parsed correctly using pandas.
  • Enhanced date display on Matplotlib x-axis by customizing date formats and rotating labels for better readability.

Achievements:

  • Successfully streamlined data processing functions for financial data.
  • Improved visualization techniques, combining different chart types for better insights.
  • Clarified and resolved common data manipulation warnings and issues in Pandas.

Pending Tasks:

  • Further testing and validation of the combined chart techniques in different scenarios.
  • Exploration of additional visualization libraries for potential enhancements.

Evidence

  • source_file=2024-01-15.sessions.jsonl, line_number=3, event_count=0, session_id=52233dbeecf4b64311f2ecf210322e64864e521982cffa18e47fd8a32f578f85
  • event_ids: []

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