From the course: Build a Document Search Assistant with Node and OpenAI's Assistants API

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Leveraging Code Interpreter for data analysis and iterative problem solving

Leveraging Code Interpreter for data analysis and iterative problem solving

From the course: Build a Document Search Assistant with Node and OpenAI's Assistants API

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Leveraging Code Interpreter for data analysis and iterative problem solving

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- [Instructor] You've learned about the Code Interpreter tool, which enables the assistant to execute code and even solve math problems. Now, I'll take things a step further by exploring how the assistant can perform more advanced data analysis. You'll learn how to upload data files, process them, and even generate insightful summaries and statistics. First, to enable the assistant to analyze data you'll start by uploading a data file it can work with. So, be sure to prepare your data file, and here are some helpful tips for that. The API supports common data files like CSV, JSON, text files and PDF files. So, make sure that your data files are well structured. For example, CSV files should have headers and consistent delimiters. I'm going to use this sample dataset I've added in my documents folder called sales_data.csv containing some sales records for the fictitious XYZ Robotics Company. The CSV file includes data such as date, region, product, quantity sold, unit price, total…

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