How to Use ChatGPT Code Interpreter

OpenAI's ChatGPT has revolutionized text generation, captivating users with its ability to create charts, maps, and even transform images into videos—all thanks to its Code Interpreter feature (formerly known as Advanced Data Analysis). Initially exclusive to ChatGPT Plus subscribers, this capability is now standard with the GPT-4o model. Code Interpreter empowers ChatGPT to write and execute code, tackling complex tasks like calculations, data analysis, and visualization.

This article explores ChatGPT's Code Interpreter functionality through practical examples.

Understanding ChatGPT Code Interpreter

ChatGPT, powered by a large language model (LLM), predicts the next word in a sequence to generate responses. Code Interpreter significantly enhances this by enabling code writing and execution within ChatGPT. This allows for complex calculations, chart generation from uploaded data, and more. This feature aims to mitigate the inaccuracies often associated with LLMs by providing precise, code-verified answers.

Technically, ChatGPT accesses a Python interpreter in a sandboxed environment, writing, executing, and debugging code to deliver results. While the interpreter remains active throughout a chat, there's a time limit to prevent excessively long sessions. Multiple code snippets can be executed sequentially, and file uploads (up to approximately 500MB) are supported, allowing for data-driven analysis.

Here's a visual example from OpenAI's documentation:

Code Interpreter performing logical calculations

Getting Started with Code Interpreter

Update (May 16, 2024): OpenAI's data analysis enhancements (formerly Code Interpreter) are now integrated into the GPT-4o model for ChatGPT Plus, Team, and Enterprise users. Key improvements include:

• Direct file uploads from Google Drive and Microsoft OneDrive.
• Interactive, expandable tables and charts with real-time interaction.
• Customizable and downloadable bar, line, pie, and scatter plots.

These features are now default with GPT-4o, eliminating the need for manual activation.

Common Use Cases

The primary use case is data analysis. ChatGPT can analyze financial records, health data, or location information to provide insights. Finance professionals utilize it for stock price analysis and budgeting, while researchers leverage it for creating data visualizations. For example, an interactive world population graph can be generated.

Beyond data analysis, Code Interpreter excels in:

• Solving mathematical problems.
• Data analysis and visualization.
• File format conversion.

Examples

Example 1: Simple Dataset Analysis

A simple CSV dataset was uploaded, and a prompt requested analysis. The output (too extensive to fully display here) included key insights derived from the data. The speed and relevance of the insights were impressive.

Example 2: Complex Dataset Analysis (Canadian CPI Inflation)

A more realistic, raw dataset with duplicates, missing values, and encoded information was used. The process demonstrated data cleaning, schema development, visualization, and insightful conclusions, showcasing the capabilities of Code Interpreter to handle real-world data challenges.

Example 3: Image Animation

An image of an apple was uploaded with a request for animation. After clarifying questions, Code Interpreter generated code and produced an animated GIF.

Animated output (GIF)

Conclusion

OpenAI's Code Interpreter is a transformative feature, extending ChatGPT's capabilities significantly. Its code execution abilities enhance accuracy and provide a more interactive experience. From data analysis to mathematical problem-solving, Code Interpreter makes ChatGPT a versatile tool across numerous applications.

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