Aravindpai Pai — Updated On September 14th, 2023
Beginner ChatGPT Data Analysis Data Exploration Data Mining Data Visualization Generative AI NLP


Tired of sifting through mountains of analyzing data without any real insights? ChatGPT is here to change the game. With its advanced natural language processing capabilities, ChatGPT can uncover hidden patterns and trends in your data that you never thought possible. In this blog post, we’ll explore how ChatGPT can revolutionize your data with exploratory data analysis and transform the way you do business.

Why Prompts are Critical in ChatGPT?

I realized that prompts are very critical in order to make use of ChatGPT to its full potential. Even Though ChatGPT is capable of performing any task, in order to make use of it to its full extent, we need to provide the right and detailed prompts. Without the exact prompts, you will not be able to get the desired results.

I am running the experiment to see if ChatGPT can really make sense out of the dataset. I know that ChatGPT can provide me with the code snippets of certain tasks.

For example, given a prompt “help me with the code snippet to check for outliers”. ChatGPT provided me with a code snippet to check and identify the outliers. But can a ChatGPT help me answer the questions such as determining the columns that contain outliers in the dataset? or what is the correlation coefficient between the target variable and features?

In order to answer these questions, ChatGPT has to analyze the specific columns in the dataset and do the math to come up with the answer.

Fingers crossed!

But it’s really interesting to see if ChatGPT can do the math and provide me with the exact answers to the questions. Let’s see!

Exploratory Data Analysis (EDA) Using ChatGPT

Let’s try some of the prompts, EDA using ChatGPT:

Prompt 1:

I want you to act as a data scientist and analyze the dataset. Provide me with the exact and definitive answer for each question. Do not provide me with the code snippets for the questions. The dataset is provided below. Consider the given dataset for analysis. The first row of the dataset contains the header.

eda using chatgpt-1 | Analyzing Data

Prompt 2:

1,0,3,”Braund, Mr. Owen Harris”,male,22,1,0,A/5 21171,7.25,,S
2,1,1,”Cumings, Mrs. John Bradley (Florence Briggs Thayer)”,female,38,1,0,PC 17599,71.2833,C85,C
3,1,3,”Heikkinen, Miss. Laina”,female,26,0,0,STON/O2. 3101282,7.925,,S
4,1,1,”Futrelle, Mrs. Jacques Heath (Lily May Peel)”,female,35,1,0,113803,53.1,C123,S
5,0,3,”Allen, Mr. William Henry”,male,35,0,0,373450,8.05,,S
6,0,3,”Moran, Mr. James”,male,,0,0,330877,8.4583,,Q

Exploratory Data Analysis using chatgpt-2 | Analyzing Data

Prompt 3:

How many rows and columns are present in the dataset?

eda using chatgpt-3

Prompt 4:

List down the numerical and categorical columns

 Analyzing Data | eda using chatgpt-4

Prompt 5:

Check for NANs present in the dataset? If yes, print no. of nans in each column.

Exploratory Data Analysis using chatgpt-5
eda using chatgpt-6 | Analyzing Data

Prompt 6:

Are there any outliers in the dataset?

Exploratory Data Analysis using chatgpt 7

Prompt 7:

Name the columns that contain the outliers. Provide me with the exact answer.

eda using chatgpt-9

Prompt 8:

What are the significant factors that affect the survival rate?

Prompts given for Exploratory Data Analysis

Prompt 9:

Determine the columns that follow the skewed distribution and name them.

eda using chatgpt-8 | Analyzing Data

Prompt 10:

Generate meaningful insights about the dataset.


Such cool stuff 🙂 As you can see here, ChatGPT provided me with a summary of valuable insights and also the important factors that might have affected the survival rate.

Frequently Asked Questions

Q1. Can ChatGPT be used for data analysis?

A. Yes, ChatGPT can be effectively utilized for data analysis tasks. Its advanced language processing capabilities enable it to understand, process, and extract insights from various forms of data, making it a valuable tool for tasks like text mining, sentiment analysis, and generating reports based on data-driven insights.

Q2. What is ChatGPT advanced data analysis?

A. ChatGPT’s advanced data analysis refers to its ability to intelligently interpret and extract insights from complex datasets using natural language processing. It can perform tasks like text summarization, sentiment analysis, and data-driven report generation. By processing and understanding diverse data formats, ChatGPT enhances decision-making processes and provides valuable insights for informed choices.

Q3. How do you analyze large datasets with ChatGPT?

A. To analyze large datasets with ChatGPT, break down the task into smaller segments or queries. Provide clear instructions for data processing and the specific insights you seek. Utilize its text summarization, sentiment analysis, and pattern recognition capabilities to extract relevant information efficiently. Remember that ChatGPT processes text, so convert numerical data into descriptive text for effective analysis.


Impressive! ChatGPT is able to generate meaningful insights in no time. My experiment is successful. And ChatGPT lived up to my expectations.

In this blog post, we have seen how to analyze the data in fractions of seconds using ChatGPT. We also understood the importance of prompts in ChatGPT and the right prompts to achieve the results of exploratory data analysis (EDA). Why don’t you try some of the prompts and share your experience with me in the comments below?

Hope you enjoyed reading the article. How have you been experimenting with generative AI tools? Let me know your thoughts in the comment section below.

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Aravindpai Pai

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2 thoughts on "Analyzing Data Made Effortless Using ChatGPT"

Eric says: May 06, 2023 at 4:20 am
This is really great, but how do I get a really large data set into ChatGPT? I have an 80MB excel file and need to get insights. Tks, Eric Reply
Brent says: May 14, 2023 at 1:41 am
Certainly cool that ChatGPT can do this, but heads up there's EDA tools that can do this (IMHO people tend to reinvent the wheel with simple EDA tasks like this) Packages: R: skimr Python: pandas-profiling (now named ydata-profiling) Reply

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