[综合] How to Use ChatGPT to Analyze Data: Tips and Methods

ChatGPT’s Data Analysis Capabilities

When using ChatGPT for data analysis, you can create interactive tables and charts from uploaded data. ChatGPT automatically generates an interactive table view that lets you scroll through the data and view all rows and columns. After uploading a file, you can also create interactive charts. ChatGPT can determine the ideal chart type for the dataset, or you can specify one of the chart types supported by OpenAI in your prompt. You can customize the appearance of interactive charts and create explanatory summaries to better understand the data.

Supported File Types

ChatGPT can analyze data in a variety of file formats, including:

- Excel (.xls/.xlsx)
- Comma-separated values (.csv)
- PDF (.pdf)
- JSON

When preparing a spreadsheet for analysis, follow these guidelines:

Recommended:
- Include descriptive column headers in the first row.
- Use plain language for column headers, avoiding abbreviations and jargon.
- Use one row per record.

Not recommended:
- Including multiple sections and tables in a single spreadsheet.
- Including empty rows or columns.
- Including images that contain key information.

Data Analysis and Visualization

ChatGPT uses the pandas library to analyze data and the Matplotlib library to create static and interactive charts. After analyzing or visualizing data, you can click the “View analysis” link at the end of the response to see how ChatGPT used these tools.

View Analysis
You can toggle the “Always show details” option so that the analysis window is displayed by default after each response. If you want to use the code locally, you can click the “Copy code” button to copy the code to the clipboard and paste it into a code editor.

Interactive Charts
Currently, in most cases, only bar charts, pie charts, scatter plots, and line charts have interactive functionality. ChatGPT can create a variety of non-interactive charts, including histograms, box plots, heatmaps, area charts, radar charts, treemaps, bubble charts, and waterfall charts.

File and Data Limitations

You can upload up to 10 files per conversation. Each file is limited to 512 MB; for CSV files or spreadsheets, the size cannot exceed approximately 50 MB. ChatGPT handles large data files well.

Data Analysis Process

When you upload structured data, ChatGPT first examines the first few rows of data to understand possible patterns and the types of values. When answering questions about the data, ChatGPT performs the following steps:

1. Access the uploaded data in a code execution environment.
2. Write Python code to process the data and generate the required analytical output.
3. Execute the code and inspect the results.
4. Integrate the results into the response in the chat window.

Core Capabilities

ChatGPT can perform complex analyses based on natural language prompts. Through training on numerous data analysis tasks, GPT-4 can generate new code to perform new analysis tasks. By accessing a secure code execution environment, ChatGPT uses hundreds of preinstalled Python libraries for data analysis. When analyzing data, a new instance of the code execution environment is created and destroyed within 13 hours after the conversation becomes inactive.

Other Applications

In addition to data analysis, ChatGPT’s code execution environment also supports other applications, including:

- File operations and generation
- Topic analysis of unstructured data and text documents

ChatGPT has been trained on a variety of coding tasks and can come up with creative ways to use the code execution environment to complete tasks.