How to Use ChatGPT Advanced Data Analysis (Formerly ChatGPT Code Interpreter)

Key takeaways

ChatGPT Advanced Data Analysis, previously known as Code Interpreter, is a built-in tool that can write and execute code in a sandboxed Python environment.

• Originally released as a plugin in 2023, Code Interpreter has since been renamed Advanced Data Analysis and integrated into ChatGPT’s native chat window [1].

• To use ChatGPT Advanced Data Analysis, first upload the files containing your data and ask ChatGPT to interpret or summarize the information, clean your data set, visualize your data with static or interactive charts, and conduct statistical analyses of your choosing.

• You can use ChatGPT Advanced Data Analysis to debug and test code, convert files and images, solve complex math equations, and conduct thematic analysis, in addition to data analysis and visualization.

Explore how ChatGPT Advanced Data Analysis works, how to use it, and its benefits and limitations. If you’re ready to start learning how to prompt large language models (LLMs) like ChatGPT, enroll in Vanderbilt University’s Prompt Engineering Specialization on Coursera. You’ll have the opportunity to gain experience with prompt ideation, data analysis and presentation, document management, and more using LLMs and generative AI (GenAI) in as little as four weeks. Upon completion, you’ll have earned a career certificate for your resume.

What is ChatGPT Advanced Data Analysis?

ChatGPT’s Advanced Data Analysis feature is a built-in tool that can write and execute code in a sandboxed Python environment. This capability allows ChatGPT to analyze and visualize data, even from uploaded files, test code snippets, and perform complex math functions. It was originally released as a plugin back in 2023, when it was called Code Interpreter. It has since been renamed and integrated into ChatGPT’s native chat window, meaning it’s no longer a separate tool that you have to take extra steps to access[1].

Previously, ChatGPT could only generate code or text outputs of code. With Advanced Data Analysis, ChatGPT can run the code it generates in a secure Python environment to test for errors and automatically correct them, producing more accurate code as the final output. Additionally, while you previously had to copy and paste information into the chat window for ChatGPT to analyze, you can now upload multiple files containing diverse data types, such as images, code, and spreadsheets, and the Advanced Data Analysis feature can interpret, analyze, and visualize the information they contain.

How does ChatGPT Advanced Data Analysis work?

ChatGPT Advanced Data Analysis writes and executes Python code in a secure sandbox to analyze uploaded files, perform calculations, and generate visualizations.

When you upload structured data formats like CSV or Excel files and ask ChatGPT questions about the data, the Advanced Data Analysis feature first opens the data in an isolated virtual machine or container environment. Then, ChatGPT interprets the data by writing Python code using pre-loaded Python libraries. The environment then executes the code, identifies and rectifies any errors, and provides a response integrated with the code as the final output in the chat window.

How do you access ChatGPT Advanced Data Analysis?

You can access Advanced Data Analysis in the Free tier, but your usage will be subject to rate limits that will prevent you from using ChatGPT’s data analysis capabilities after a certain number of uses. Upgrading to ChatGPT Go will extend your access and usage limits for the data analysis feature for $8 per month. A ChatGPT Plus subscription will further extend your usage limits and give you access to advanced reasoning models that can generate even more accurate code and analyses for $20 per month [2].

Another way to access this feature is by using the Data Analyst GPT, a specialized GPT created by the ChatGPT team that has the Code Interpreter and Advanced Data Analysis capabilities enabled for data analysis and visualization [3]. You can find this GPT by clicking on the Explore GPTs button in the ChatGPT sidebar.

ChatGPT Advanced Data Analysis examples

You can use ChatGPT’s Advanced Data Analysis feature for several applications other than data analysis and visualization. Examples include:

• Converting a GIF into a video or an image into a GIF

• Generating QR codes from URLs

• Analyzing playlists, fitness data, or financial holdings to identify trends

• Generating code for a game

• Analyzing themes and linguistic patterns in books

What can ChatGPT Advanced Data Analysis do?

You can use ChatGPT’s Advanced Data Analysis feature to identify trends in your data, make predictions through scenario-based simulations, conduct complex statistical analyses, and more.

Step 1: Upload your files.

First, upload a file or multiple files containing your data by clicking on the “+” button in your chat. ChatGPT supports several file formats, including CSV, Excel, JSON, and PDF, and will automatically transform your data into an interactive table for you to scroll through and review.

Step 2: Interpret your data.

Once you’ve uploaded your files, you can ask ChatGPT questions about your data in natural language without any specific prompting. For example, you can ask “Analyze monthly performance” or “Summarize this data set.” You can also request ChatGPT to provide the output in table format. You’ll also be able to select a column, row, or multiple cells in table view and ask ChatGPT specific questions about the data you selected, like “Calculate the mean of the selected cells”, as well as ask ChatGPT to incorporate any changes in your data, like “Create a column with the mean values in the table.”

Step 3: Clean your data set.

Before you start analyzing and visualizing your data, you can ask ChatGPT to clean your data set of duplicates, empty cells, outliers, incorrect data types, etc., to ensure you're working with accurate data. If you prompt ChatGPT to 'Check the data set for common issues,' it will identify and repair them and even offer options for dealing with specific issues.

Step 4: Visualize your data.

You can ask ChatGPT to visualize your data by prompting it to create a static or interactive chart of your choosing, or you can let ChatGPT select the ideal chart type based on your data. The graphics and colors of your charts are customizable, and you can toggle their interactivity on or off in the top-right corner of the generated chart. As of March 2026, ChatGPT can generate interactive bar, pie, scatter, and line charts, as well as non-interactive histograms, box plots, heat maps, area charts, radar charts, treemaps, bubble charts, and waterfall charts [4].

ChatGPT uses the Python Library pandas to analyze your data and Matplotlib to create your charts. You can click on the “View analysis” button at the end of the response to see the code ChatGPT wrote and executed to perform the analysis, with an option to copy the code for use outside ChatGPT. You can download the charts in PNG format and tables in CSV format by clicking on the download button in the top-right of the generated graphics.

Step 5: Analyze your data.

ChatGPT’s core ability to write and execute code, along with its training on a variety of data analysis tasks, enables it to perform complex mathematical and statistical analyses. ChatGPT can combine large amounts of structured data and analyze it using metrics like sums, averages, standard deviations, minimum and maximum values, etc. All you need to do is select the columns or cells containing numeric data and prompt ChatGPT with, for example, “Calculate the average and standard deviation for the data.” If you have uploaded multiple files, you can ask ChatGPT to merge the files before mathematical computation, or ChatGPT may automatically do it for you if it’s necessary based on your prompt.

Additionally, you can perform several advanced statistical analyses using ChatGPT. If you’re not sure which type of analysis to use, you can ask ChatGPT to suggest appropriate techniques based on what you want to know. A few types of analyses ChatGPT can perform include:

• Comparative statistics, like t-tests and analysis of variance (ANOVA)

• Correlation and regression analysis

• Time series analysis

What else can you do with ChatGPT Advanced Data Analysis?

In addition to data analysis and visualization, ChatGPT can leverage its code-interpreter capabilities for other uses, such as:

• Code debugging and testing: You can upload your code file or code snippets to ChatGPT, ask it to identify any errors, and the Advanced Data Analysis tool will resolve any bugs in your code and execute it iteratively until it successfully runs. You can also experiment with code and different algorithms using the Advanced Data Analysis tool, which creates a sandboxed environment for testing and suggests context-aware improvements.

• File manipulation: The Advanced Data Analysis feature can also convert image and text files you upload from one format to another. It can edit image files, such as adjusting color tones, cropping, resizing, and zooming in and out; convert audio files to transcripts; and convert a data set you upload into an Excel file.

• Solving math equations: Advanced Data Analysis can use Python to solve complex math equations. You can write a math problem or upload a picture or screenshot of a complex equation for ChatGPT to solve, and ChatGPT will not only provide an accurate answer but also explain how it solved the problem.

• Thematic analysis: You can also use ChatGPT’s data analysis capabilities to analyze unstructured, quantitative data and perform a thematic analysis. ChatGPT can generate code for interview transcripts, identify themes from this code, and streamline early-stage analysis and data preparation.

What are the benefits and limitations of ChatGPT Advanced Data Analysis?

The biggest advantage of ChatGPT Advanced Data Analysis is that it allows individuals without coding or data analysis knowledge to perform complex analytics and visualization without writing any code themselves.

Benefits

Even for developers, this feature is useful, since Advanced Data Analysis can rapidly generate code from natural-language prompts and test it in the chat itself without requiring them to switch to another program, increasing the speed, accuracy, and efficiency of the coding process. The feature's ability to provide real-time feedback, code reviews, and context-aware suggestions helps you not only identify and fix errors quickly but also supports new developers with a dynamic, interactive learning environment.

Limitations

However, ChatGPT’s ability may be limited when it encounters data types it doesn't understand, highly complex code, or situations that require big-picture understanding. This means that overreliance on the tool without manual review can lead to erroneous code or reduced team innovation. ChatGPT also raises concerns about data privacy, especially for sensitive personal information like health data, where the model uses your chats and data for training unless you opt out. Additionally, ChatGPT places certain restrictions on usage of the Advanced Data Analysis tool, such as:

• You can only upload a maximum of 10 files in a given conversation, and each file must not exceed 512 MB.

• The code execution environment that ChatGPT creates for your conversation will expire after 13 hours of inactivity.

• ChatGPT can’t generate outbound network requests directly, which means the code execution environment is isolated from the internet. While this improves safety, it doesn’t offer the flexibility of a fully internet-connected coding environment, for example, to download libraries in real time and complete certain tasks [4].

ChatGPT code to image converter

ChatGPT’s Advanced Data Analysis feature can turn code into visualizations, like graphs and charts, and generate files containing data and graphical images. However, at the time of writing, you can only use ChatGPT’s Advanced Data Analysis feature to manipulate images, such as cropping, rotating, or processing them. Nevertheless, you can still generate images with ChatGPT’s other tools, like DALL-E, or by simply prompting the normal model in natural language [4].

Getting started with ChatGPT Advanced Data Analysis

Although ChatGPT Advanced Data Analysis is helpful for non-coders and non-technical individuals to complete data analysis and coding tasks, having some knowledge of these concepts can help you better understand ChatGPT’s suggestions, verify whether it used the correct logic, and determine whether the output is appropriate or requires refinement.

Consider starting out by learning the fundamentals of coding through online courses, tutorials, and boot camps. When you've built up a foundation of coding skills, explore data analysis courses and tutorials if you'll be using AI for data analytics. An online course like the IBM Data Analysis and Visualization Foundations Specialization can help you develop essential data analysis skills like data cleaning, visualization, and wrangling.

Developing a basic understanding of AI technology, especially generative AI and large language models, can help you better grasp the technology underlying ChatGPT and its responses. Consider taking an online course, like the IBM Generative AI Fundamentals Specialization, to gain insights into the capabilities and limitations of AI models like ChatGPT.Finally, knowing how to write clear, effective prompts is key to getting ChatGPT to produce the results you want.

Read more: How to Write ChatGPT Prompts

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