Quick DataViz with Claude Code (matthodges.com)

Claude Code, part of the Opus 4.5 release, has demonstrated its capabilities as a powerful tool for quick data visualization and exploration, particularly in a recent demonstration using data from the Federal Reserve. By simply prompting Claude Code to navigate to a specific webpage and extract banking data, it generated Python code that fetched and presented a bar graph of the top 10 commercial banks by consolidated assets. This process highlighted Claude's ability to effectively manage challenges such as website restrictions by automatically adjusting the user-agent header for web scraping. This development is significant for the AI/ML community as it showcases the versatility of AI agents in automating complex tasks that traditionally required extensive programming knowledge. Claude Code's seamless integration of libraries like pandas and matplotlib allows users to transform raw data into meaningful visual formats with minimal input, making data analysis more accessible. The demonstration underlines a shift in how AI tools can be perceived—not merely as software for developers, but as general-purpose agents that enhance productivity across various domains, including data science and analytics. This evolution could lead to more widespread adoption of AI tools in everyday workflows.