ChatGPT - Data Analysis

This article explains how to upload, explore, clean, analyze, visualize, and export structured data using the built-in data analysis capabilities in ChatGPT Edu.

Detailed Information

Using Data Analysis in ChatGPT

Overview

ChatGPT includes a built-in data analysis capability that lets you upload structured data files and explore them using plain English.

Behind the scenes, ChatGPT writes and executes Python code in a secure, sandboxed environment, but you do not need to write code yourself. Describe what you want to know, and ChatGPT can load the data, run calculations, generate charts, and return results directly in the conversation.

This makes ChatGPT a practical tool for anyone who works with data, including researchers analyzing survey results, staff reviewing enrollment figures, faculty exploring grade distributions, and students working through statistics assignments.

How It Works

When you upload a data file to ChatGPT, the following process happens automatically:

1. ChatGPT examines your data. It reads the first several rows to understand the structure, including column names, data types, and the general shape of the dataset. An interactive table view may be created so you can scroll through the data.
2. You ask questions in natural language. Prompts such as "What is the average GPA by major?" or "Show me enrollment trends over the last five years" are enough to begin.
3. ChatGPT writes and runs Python code. It can use data-analysis and visualization tools to generate code, execute it in a secure environment, and return the results.
4. You refine the analysis. Each follow-up question can build on the previous work. You can adjust filters, request different visualizations, ask for deeper breakdowns, or export results within the same conversation.

You can review the Python code ChatGPT used by selecting the View Analysis option when it appears in a response. This can help you verify the logic, learn from the approach, or reuse the code in another environment.

Supported File Types

ChatGPT can analyze data from a variety of file formats:

• CSV (.csv): The most common and reliable format for tabular data
• Excel (.xlsx, .xls)
• TSV (.tsv)
• JSON (.json)
• XML (.xml)
• SQLite databases (.sqlite, .db)
• Parquet (.parquet)
• Text files (.txt) containing structured data
• PDF: ChatGPT can extract tables and data from PDFs, though results vary depending on how the PDF was created

For best results, use CSV or Excel files with clean headers and consistent formatting.

Files can be up to 512 MB, though CSV and spreadsheet files are practically limited to approximately 50 MB depending on row size.

You may also be able to select files from approved connected services when those services are enabled in the UMS ChatGPT Edu workspace.

What You Can Do

Explore and Summarize Data

Upload a file and ask ChatGPT to describe it. ChatGPT can report the number of rows and columns, list column names and data types, identify missing values, and provide basic summary statistics.

Example prompts:

• "Describe this dataset. What columns are there, and what do they contain?"
• "How many rows have missing values? Which columns are affected?"
• "Give me summary statistics for all numeric columns."

Clean and Transform Data

ChatGPT can perform common data-cleaning tasks, including removing duplicates, filling or dropping missing values, renaming columns, converting data types, filtering rows, and restructuring data for analysis.

Example prompts:

• "Remove any rows where the email column is blank."
• "Convert the date column from text to a proper date format."
• "Split the full_name column into first_name and last_name."
• "Pivot this data so each department is a column and each month is a row."

Perform Calculations and Aggregations

ChatGPT can perform calculations ranging from simple sums and averages to grouped aggregations and cross-tabulations.

Example prompts:

• "What is the total revenue by region?"
• "Calculate the average response time grouped by ticket priority."
• "Show me the month-over-month percentage change in enrollment."
• "Merge these two files on the student_id column and show me the combined result."

Run Statistical Analysis

ChatGPT can perform a range of statistical analyses based on your data and question. This includes descriptive statistics, correlations, regressions, hypothesis testing, and related methods.

Example prompts:

• "Is there a correlation between study hours and GPA in this dataset?"
• "Run a linear regression with GPA as the dependent variable and study_hours and attendance_rate as independent variables."
• "Perform a t-test comparing average scores between Group A and Group B."
• "Calculate the median and standard deviation for each numeric column."

Create Visualizations

ChatGPT can generate static and interactive charts. You can allow ChatGPT to choose a chart type or request a specific visualization.

Supported chart types include:

Bar chart	Histogram
Line chart	Box plot
Pie chart	Heat map
Scatter plot	Area chart
Radar chart	Treemap
Bubble chart	Waterfall chart

Interactive charts may allow you to hover over data points, zoom, and explore the data visually. When available, you can switch between static and interactive views using the chart controls.

You can customize charts by asking ChatGPT to change colors, labels, layouts, or other presentation details. Charts can be downloaded as image files for use in presentations or reports.

Example prompts:

• "Create a bar chart showing total headcount by department."
• "Show me a line chart of monthly ticket volume over the last two years."
• "Make a scatter plot of study_hours versus GPA, color-coded by major."
• "Generate a heat map of correlations between all numeric columns."

Work with Tables

When you upload structured data, ChatGPT may create an interactive table view. You can scroll through the data, select rows or columns, and ask follow-up questions about the selected information.

You can also ask ChatGPT to:

• Create new tables
• Add calculated columns
• Filter or sort records
• Restructure existing data

Tables can be downloaded as CSV files for use in other applications.

Merge Multiple Datasets

If you upload more than one file, ChatGPT can merge them using shared identifiers.

For example, if one spreadsheet contains student information and another contains course enrollments linked by student ID, ChatGPT can join the files and answer questions across both datasets.

Example prompts:

• "Merge these two files on student_id and show me students who appear in both."
• "Join the sales data with the product catalog on product_code and calculate revenue by category."

Practical Use Cases

For Researchers

Upload survey results or experimental data and ask for descriptive statistics, visualizations, correlation matrices, or regression analyses.

ChatGPT can help you explore your data before moving to more specialized statistical tools for final analysis.

For Staff and Administrators

Analyze enrollment trends, budget data, help desk ticket volumes, human resources metrics, or event attendance.

You can also generate charts and summary tables for reports or presentations.

For Faculty

Upload grade distributions to identify patterns, analyze assignment scores across sections, or explore student performance data.

You can also create visualizations for department meetings, program reviews, or accreditation reports.

For Students

Work through statistics assignments, explore datasets for class projects, or learn data-analysis concepts by reviewing how ChatGPT approaches a problem.

Study Mode can also provide step-by-step explanations of statistical techniques.

Tips for Getting Good Results

Start with clean data. Clear column headers, consistent date formats, and minimal unnecessary rows will help ChatGPT interpret the file correctly.

Be specific about what you want. A broad request such as "Analyze this data" may return general summary statistics. A more specific request will usually produce a more useful result.

For example:

Show me the top 10 departments by average salary, sorted from highest to lowest, as a horizontal bar chart.

Continue in the same conversation. Each follow-up can build on the previous analysis. Start with a broad question, then refine the filters, calculations, or visualizations.

Verify important results. Use View Analysis to inspect the Python code and confirm the logic. For decisions with significant consequences, validate key findings using another method or tool.

Use Projects for recurring analyses. If you regularly analyze similar data, create a Project with instructions describing your preferred format, metrics, and terminology.

Export and save your work. Download important charts, tables, and cleaned datasets before ending the session or deleting the conversation.

Limitations

• Live connections may be limited. ChatGPT may not be able to connect directly to a database, API, or live data source unless an approved connection is available in the UMS workspace. You may need to export the data to a file and upload it.
• The analysis environment is sandboxed. Code execution may not be able to make external network requests or access unapproved internet resources.
• Large datasets may reach platform limits. If a file is too large, filter the data to the relevant records or divide the analysis into smaller files.
• Results require verification. ChatGPT may produce incorrect calculations, misinterpret column names, or select an inappropriate statistical method.
• Charts are not persistent dashboards. ChatGPT can create charts within a conversation, but it does not create automatically refreshing reporting dashboards.
• Data sensitivity matters. Follow applicable UMS data-governance requirements when deciding what to upload. Do not upload sensitive or restricted data unless UMS policy explicitly permits it.

Getting Started

To begin analyzing data in ChatGPT Edu:

1. Open a new conversation or an existing Project.
2. Select the attachment icon or drag and drop a supported data file into the conversation.
3. Wait for ChatGPT to load and display the data.
4. Ask a question about the data in plain English.
5. Review the results and continue with follow-up questions as needed.

For more information about ChatGPT Edu access and features, review the related articles in this knowledge base.

Environment

• University of Maine System
• ChatGPT Edu
• Data Analysis
• Supported structured data files
• Supported desktop and mobile web browsers