How to Rightly Use ChatGPT to Analyze Data with Example?

AI for Life

data analysis using chatgpt

Data analysis with ChatGPT is like having a friendly conversation with a smart person. You can talk to ChatGPT, share your data, and ask questions. It helps you understand your information better and make good decisions.

You can do things like figuring out if people like a product from their comments, finding important words in a document, or even asking it to explain things to you.

ChatGPT can make data stuff easier, like talking to a helpful friend.

What Kind of Data Analysis ChatGPT Can Do?

With the ChatGPT web interface, you can perform a variety of data analyses and gain insights from your data without writing code.

image showing data analysis
Photo by Luke Chesser

Let’s the most common types of data analysis tasks you can do:

1. Sentiment Analysis

  • Example: You can analyze customer reviews to understand if they have positive, negative, or neutral sentiments. For instance, you can ask, “Can you tell me the sentiment of these product reviews?”

2. Data Summarization

  • Example: You can request a summary of a long article or report to quickly grasp the main points. Simply ask, “Summarize this article for me.”

3. Text Classification

  • Example: You can classify text data into predefined categories. For instance, you can ask, “Can you categorize these news headlines into topics like politics, sports, and entertainment?”

4. Keyword Extraction

  • Example: You can extract important keywords or phrases from text to identify key topics. You might ask, “What are the main keywords in this research paper?”

5. Data Exploration

  • Example: You can explore your data by asking questions like, “Show me a graph of sales trends over the last year” or “What does the distribution of customer ages look like in this dataset?”

6. Language Translation

  • Example: You can translate text from one language to another. For example, you can say, “Translate this paragraph from English to French.”

7. Information Verification

  • Example: You can verify the accuracy of a statement or claim by asking, “Is the statement ‘Earth orbits the Moon’ true or false?”

8. Question Answering

  • Example: You can ask questions and get detailed answers from text data, like, “What are the main causes of climate change?”

9. Data Insights and Trend Analysis

  • Example: You can ask for insights and trends in your data, such as, “What are the common themes in customer feedback for our product?”

10. Content Generation

  • Example: You can generate content like articles, product descriptions, or code snippets by providing a topic or context. For instance, you can say, “Write an article about the benefits of exercise.”

11. Decision Support

  • Example: You can seek advice or recommendations based on data. For example, you can ask, “Should I invest in stocks or bonds given the current market conditions?”

12. Personal Assistance

  • Example: You can use ChatGPT as a virtual assistant to set reminders, schedule appointments, or get information about the weather, news, or travel.

Remember that while ChatGPT is a powerful tool for various data-related tasks, it’s important to provide clear and specific instructions to get accurate results.

Additionally, critically evaluate the responses, as the quality of the analysis depends on the data and questions you provide. ChatGPT can be a valuable aid in making data-driven decisions and gaining insights from your data in an easy-to-use conversational manner.

A Detailed Example Data Analysis using ChatGPT

You can perform data analysis using ChatGPT without coding directly from the ChatGPT web interface by following a structured conversation format.

customer or user review system
Photo by Towfiqu barbhuiya

Here’s a step-by-step guide on how to do this:

Step 1: Access the ChatGPT Web Interface

Go to the ChatGPT web interface provided by the service you are using (e.g., You will have a chat-like environment where you can interact with ChatGPT.

Step 2: Load Your Sample Data

In this example, let’s assume you have a dataset of customer reviews for a restaurant. You’ll need to provide this data to ChatGPT in a structured manner. You can type or paste your data directly into the chat interface. For example:

User: Here is a sample dataset of restaurant reviews:

Review Text, Rating
“The food was excellent!”, 5
“Service was slow, but food was good.”, 4
“Terrible experience, won’t go back.”, 1

Step 3: Define Your Analysis Questions

Tell ChatGPT what kind of analysis you want to perform on the data. Be specific about your questions and objectives. For example:

User: I would like to analyze this data to gain insights. Specifically, I’m interested in the overall sentiment of the reviews, the most common keywords used in positive and negative reviews, and any patterns or trends in customer feedback.

Step 4: Ask ChatGPT for Analysis

Engage with ChatGPT to request specific analyses. You can use a conversational style to ask questions or request actions. For instance:

User: ChatGPT, please analyze the sentiment of these reviews and summarize it.

User: Could you also extract the most common keywords or phrases used in positive reviews?

User: What insights can you provide regarding the relationship between ratings and review length?

Step 5: Review and Interpret Responses

ChatGPT will generate responses based on your requests and questions. It will provide you with insights, summaries, and analyses based on the data you provided. Review the responses carefully and interpret the results.

Step 6: Ask Follow-up Questions

Based on the initial responses from ChatGPT, you can ask follow-up questions for further clarification or exploration. For example:

User: Can you show me a sentiment distribution chart based on the reviews?

User: What are the top 5 keywords mentioned in negative reviews?

Step 7: Draw Conclusions

Use the information provided by ChatGPT to draw conclusions and insights from your data analysis. You can summarize findings, identify trends, and make data-driven decisions based on the analysis.

Remember that while ChatGPT can assist with data analysis, it’s essential to critically evaluate the results and consider the limitations of the AI model.

The quality of the analysis depends on the quality and structure of the data you provide, as well as the specificity of your questions and requests to ChatGPT.

Good luck.