ChatGPT数据分析:10个实战案例(附代码)

Learn how to use ChatGPT's Code Interpreter for data analysis. Real examples with CSV files, Python code, and visualizations you can reproduce.

Why ChatGPT is a Data Analysis Powerhouse

ChatGPT's Code Interpreter (now called Advanced Data Analysis) lets you upload files and analyze them with Python — no coding required. Here are 10 real examples of what it can do.

1. Sales Data Analysis

Upload a CSV of sales data and ask ChatGPT to find trends, seasonality, and outliers. It automatically cleans the data, runs statistical analysis, and creates visualizations.

2. Customer Segmentation

ChatGPT can perform K-means clustering on customer data, creating segments based on purchasing behavior, demographics, and engagement metrics.

3. Time Series Forecasting

Using libraries like Prophet and statsmodels, ChatGPT can forecast future trends from historical data — perfect for inventory planning and budget forecasting.

4. A/B Test Analysis

Upload your A/B test results and ChatGPT will calculate statistical significance, effect sizes, and provide recommendations.

5. Text Analysis & NLP

ChatGPT excels at analyzing text data: sentiment analysis, topic modeling, keyword extraction, and text classification.

6. Financial Data Analysis

Analyze stock prices, calculate returns, build portfolios, and run Monte Carlo simulations — all through natural language conversations.

7. Survey Data Processing

Upload raw survey responses and ChatGPT will clean, code, and analyze open-ended responses, creating summary tables and charts.

8. Data Cleaning

ChatGPT automatically detects and fixes common data issues: missing values, outliers, inconsistent formatting, and duplicate records.

9. Report Generation

After analysis, ChatGPT can generate complete reports with executive summaries, methodology, findings, and recommendations in your preferred format.

10. Dashboard Data Prep

ChatGPT can transform raw data into dashboard-ready formats, creating pivot tables, aggregations, and calculated fields.

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