In todays evolving world of **data science**, it is important to be up to date with the new **trending tools** and **technologies **in order to survive and better growth in the **IT industry**. When we talk about trending technologies, **ChatGPT **is inevitable. Nowadays there are numerous tasks that are getting done by the ChatGPT itself with the help of **machine learning** and **artificial intelligence**. Amidst of this when we talk about Data Science, ChatGPT is revolutionizing the way **data scientists** interact with **machine learning systems**.

## What is ChatGPT?

**ChatGPT** has become incredibly popular since its launch in late 2022, and it’s very easy to understand why. ChatGPT is an amazing **AI chatbot** that can do so many things! It can have a conversation with you and even help you write a whole term paper. But did you know that **ChatGPT can do even more**? It can **make a cool logo** for a brand and even **create music**! There are so many surprising things that ChatGPT is capable of, and in this article, we would be exploring more about **How we can use ChatGPT for Data Science? **or **How Data Scientists can use ChatGPT?**

To read more, refer to this article:** ****What is ChatGPT by OpenAI – Explained!**

## What Are ChatGPT Prompts?

When we talk about interacting with * artificial intelligence* systems then a question pops how?? and the answer is just like humans but just a little bit more specific as simple as that. Whatever you ask ChatGPT in the form of a query or a question or a simple text, all of them are known as

**ChatGPT prompts**. They take input in terms of the prompt, process them, and provide the specific output by using different

**machine learning**techniques.

For Example:

Prompt:What are the key steps in building a machine-learning model?In the above example, the question is considered a prompt and there are different types of answers to this prompt in terms of

lengthandcomplexitywhich is provided by ChatGPT when asked specifically. They can cover a wide range of topics and tasks, includingdata analysis,programming,problem-solving,recommendation systems,natural language processing, and much more.

## ChatGPT For Data Science

If you’re a seasoned practitioner or just starting your journey in **data science**, there are numerous prompts that will help you explore the full potential of ChatGPT which will ultimately enhance your productivity in the endless world of data science.

As the field of data science continues to evolve, so too do the tools. ChatGPT offers an exciting new boundary for data scientists, enabling them to leverage the power of artificial intelligence in their daily work. By using these top 15 ChatGPT prompts in your data science workflow, you’ll be able to **accelerate your analysis**, **improve model performance**, and **ultimately deliver impactful insights**.

## ChatGPT Prompts For Data Scientists

Here, we have listed out the ChatGPT prompts into multiple sections like for Data Analyis, SQL, Machine Learning etc. So, let’s dive into the must-try **15 ChatGPT prompts for data scientists** and unlock the full potential of this powerful tool in our data science journey.

## A. ChatGPT Prompts For Data Analysis

### 1. Data Generation

If you are a Data scientist then this prompt is definitely a lifesaver for you. As you have to create dummy data every second day of your working journey and this prompt makes it a lot easier and you can generate different sizes and lengths of data as you need.

Prompt:Suppose you are a data scientist, create a dummy data with 100 rows and 5 columns: [id, name, contact, email, age]

### 2. Data Exploration

Data exploration AKAE **exploratory data analysis** **[EDA] **is an essential part of data science. In order to investigate and analyze a dataset you have to detect anomalies, uncover patterns and gain insights into the data, and this prompt does this task as a cake walk, you have to just use the below prompt:

Prompt:Suppose you are a data scientist, I have data with 100 rows and 5 columns: [id, name, contact, email, age]. WriteRcode for data visualization and exploration.

### 3. Data Visualisation

Sometimes being a data scientist you may have to represent the data to show **patterns**, **trends**, and **insights **in a visually appealing manner, and to do this you need to transform **data sets** into **visual formats**. This prompt does the same without putting any effort, you just have to type-

Prompt:Suppose you are a data scientist, I have data with 100 rows and 5 columns: [id, name, contact, email, age]. Create a matplotlib bar chart of name vs. age.

## B. ChatGPT Prompts For Machine Learning

### 4. Train Regression Model

Basically, Regression models are used to **predict continuous numerical values**, such as predicting h**ouse prices** based on features like **square footage**, **number of bedrooms**, etc. In order to train a regression model, most of the time you’ll need a dataset with input features and **corresponding target values**. All of this is provided by the ChatGPT in a few seconds and to get that you have to use the below prompt.

Prompt:Suppose you are a data scientist, write Python code for me. I have a Data set with columns [model, hp, speed]. Please build a machine-learning model that predicts speed.

### 5. Hyperparameter Tuning

Hyperparameters are **configuration settings** that are not learned from the data but are set before the training process. They basically control the behavior of the model and can significantly impact its performance. Whenever you are in need of finding the optimal combination of hyperparameter values for a machine-learning model you need to perform Hyperparameter tuning and you can do that by typing the below prompt-

Prompt:Suppose you are a data scientist, I have a logistic regression model and write Python code to tune hyperparameters.

### 6. Explain the Model

Whenever you need to explain a machine learning model using plots with shapes and want a code for it in any language(python) you can directly go to ChatGPT and ask this

Prompt:Suppose you are a data scientist, I have trained a LightGBM model. Write a Python code to explain the output using the series of plots with Shape.

## C. ChatGPT Prompts For SQL

### 7. SQL Formatting

Data Science involves **organizing **and **structuring SQL queries** and statements in a standardized and readable manner, and for that, it needs Proper formatting which enhances **code clarity**, **improves maintainability**, and **facilitates collaboration** among developers. You can do the same by using ChatGPT in seconds-

Prompt:Suppose you are a data scientist, Format the following SQL code and convert all reserved keywords to upper case.

### 8. Translate Between DBMS

Most of the time working as a Data Analyst or Data scientist you may occur in a situation when you have to fire queries in multiple DBMSs and at that time many of us get confused as to which query to use in which database. To simplify this you can translate the between the DBMSs by using this prompt –

Prompt:Suppose you are a data scientist, What is the equivalent of PostgreSQL’s DATE_TRUNC for MySQL?

### 9. Calculate the Runway

Calculating the runway in data science involves estimating the **time**, **budget**, or **resources **required to complete the project and comparing it to the available resources or constraints. To represent the **estimated time** or **capacity remaining to complete the project** we calculate the runway and you can calculate the same using ChatGPT by asking the below prompt-

Prompt:Suppose you are a data scientist, write SQL to calculate your runway.

## D. ChatGPT Prompts For Coding

### 10. Unit Test

There will be several times when you need to test a specific piece of code in order to verify or validate the correctness of the code, at that time you need to perform unit testing and that can easily be done with the help of the below ChatGPT prompt –

Prompt:Suppose you are a data scientist, Write a unit test for the train function. The test cases are: x should not be a null value and y should be a numerical value.

### 11. Code Optimization

In order to make the code **run faster**, **use fewer system resources**, or **occupy less memory** while maintaining or improving its output we need to optimize the code. There are several techniques that are used to optimize a normal code such as **Algorithmic optimization,** **Time and space complexity optimization**, **Data structure optimization, **etc. All of this can be achieved by using ChatGPT prompts.

Prompt:Suppose you are a data scientist, Can you improve the time complexity of the code?

## Python3

`def` `sum_of_squares(n): ` ` ` `result ` `=` `0` ` ` `for` `i ` `in` `range` `(n): ` ` ` `result ` `+` `=` `i ` `*` `*` `2` ` ` `return` `result ` ` ` `def` `main(): ` ` ` `num ` `=` `int` `(` `input` `(` `"Enter a number: "` `)) ` ` ` `print` `(` `"Sum of squares:"` `, sum_of_squares(num)) ` ` ` `if` `__name__ ` `=` `=` `"__main__"` `: ` ` ` `main() ` |

### 12. Code Explanation

Being a human sometimes it becomes difficult to understand the code which is written by someone else or written by you yourself after a long period of time. At that time this ChatGPT prompt can be used effectively.

Prompt:Suppose you are a data scientist, Can you explain what the code is doing?

## Python3

`def` `sum_of_squares(n): ` ` ` `result ` `=` `0` ` ` `for` `i ` `in` `range` `(n): ` ` ` `result ` `+` `=` `i ` `*` `*` `2` ` ` `return` `result ` ` ` `def` `main(): ` ` ` `num ` `=` `int` `(` `input` `(` `"Enter a number: "` `)) ` ` ` `print` `(` `"Sum of squares:"` `, sum_of_squares(num)) ` ` ` `if` `__name__ ` `=` `=` `"__main__"` `: ` ` ` `main()` |

## E. ChatGPT Prompts For Spreadsheets

### 13. Create a Spreadsheet formula

Creating a formula for the specific set of cells could be a time taking task but ChatGPT can do it in a few seconds, you just need to specify your requirements and the limit of the rows and columns to the AI.

Let’s see how we can do this-

Prompt:Suppose you are a data scientist, Create a spreadsheet formula to calculate the sum of cells C1 to C20?

### 14. Generate Dummy Data

Suppose you are a Data scientist and you want to create a dummy data then this prompt is definitely a lifesaver for you. As you have to create dummy data every second day of your working journey and this prompt makes it a lot easier. You can generate different sizes and lengths of data as you need by just providing a simple prompt.

Prompt:Suppose you are a data scientist, Generate the dummy data for me to use as placeholders in my spreadsheet.

### 15. Improve the Efficiency

In order to get more refined results in a minimum period of time you need to improve the efficiency of your spreadsheet and that can be achieved by minimizing calculations, avoiding volatile functions, using cell references, etc. But all of this seems to be very lengthy and time taking, don’t worry you can give this task to your assistant ChatGPT by proving the below prompt-

Prompt:Suppose you are a data scientist, tell me how to improve the efficiency of my spreadsheet?

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## Conclusion

ChatGPT and its applications are indefinite whether it is data science or any other technical or non-technical field, it is capable of giving the best results in every domain. The above prompts are the best out of **numerous prompts** in the **field of data science**. These will definitely help you in achieving your results in a very short period of time but try not to be dependent on the AI or ChatGPT.

## FAQs – ChatGPT Prompts for Data Scientists

### Q1. Can ChatGPT prompt help with complex data science problems?

**Answer:**

Yes, ChatGPT prompts can help with complex Data Science problems by providing right approach and sometimes providing the right code output which heads up to effective solutions.

### Q2. What kind of tasks can ChatGPT prompts assist data scientists with?

**Answer:**

ChatGPT can assist in wide range of tasks, including data analysis, evaluation, exploratory analysis, data creation, data filterization, etc.

### Q3. Are there any limitations to using ChatGPT prompts?

**Answer:**

Yes, although most of the answers given by Chat GPT are correct but ultimately they are based on the preexisting knowledge of the training data. One should seriously evaluate and verify the answers.