10 Exciting Applications of ChatGPT for Data Analysis

This is an exciting blog for specifically for data analysts.This blog can guide the data analyst and data scientists and will tell you some shortcuts to work with the help of ChatGPT. So explore this article and learn new ideas to make your daily work easy.

We are experiencing new discoveries and technologies every day. One of the greatest invention of today is ChatGPT. This is a conversational AI model, a powerful chatbot that answers follow-up questions. On the launch day, everyone was excited about the new technology and the great features of this AI-powered chatbot. And people are still excited to use it even now. In this blog, we will discuss the usecase of ChatGPT in data analysis. This blog will be really helpful for data analyst and data scientists.

Table of contents

• What is ChatGPT?
• ChatGPT for data analysis
  • Analysing the data
  • Getting the insights and recommendations
  • Automating the process
  • Interview preparation
  • Finding datasets with ChatGPT
  • Writing data dictionaries
  • Optimising the code
  • Generating the code
  • Putting data into pandas dataframe
  • Cleaning the dataset

What is ChatGPT?

To use ChatGPT, someone must create an account. When you visit the ChatGPT website or the Open AI website, a banner will appear at the top of your screen directing you to where you can sign in to use ChatGPT. Once you have an account, you can use it for your analytical data and purposes. You will see the following after signing in:

It is critical to ask the bot a series of practise questions in order to understand how to use it.You can make it as simple or complex as you want. Know how your site is being used. This will help you transition to using it for analytical purposes.

Also check about this exciting tool- How to Use MidJourney AI for Creating a Masterpiece Art?

ChatGPT for data analysis

1. Analysing the data

ChatGPT can be used to analyse customer data and generate reports on customer sentiment and behaviour. This enables businesses to better understand their customers and make more informed decisions to improve the customer experience. Additionally, ChatGPT can be used to analyse financial data and generate reports on financial performance. This enables organisations to spot trends, make more informed decisions, and optimise financial performance. We input a dataset related to diabetes, and this is the analysis output we got.

2. Getting the insights and recommendations

Getting insights is very important for a data analyst. We just wrote, You are a data analyst. Could you please provide me with insights and recommendations on this dataset? We got these insights.

3. Automating the process

ChatGPT in data analysis and report automation is the ability to perform tasks in real time. ChatGPT’s ability to process data at high speed enables businesses to gain insights and make decisions in real time instead of waiting for reports to be generated. This allows companies to respond more quickly to market changes and stay ahead of the competition.

Learn how to use ChatGPT for free

4. Interview preparation

Prepare for the interview by simply asking ChatGPT about the latest interview question for a data analyst job. Here is the result.

 5. Finding datasets with ChatGPT

We asked chatGPT to tell us about different datasets for detecting IoT attacks and where we could find them. Check the results.

Personally, I find it hard to find datasets, but ChatGPT provides quick information about potential datasets and the place from where you can get them. You can also ask for specific links for these datasets. Amazing, right?

6. Writing data dictionaries

A data dictionary is a collection of descriptions of data objects or elements in a data model that can be referenced by programmers and other users. A data dictionary is frequently used as a centralised metadata repository. Analysts don’t have to invest many hours studying the data set; just ask chatGPT to provide you with the metadata. You can see here that all the columns with their explanations and data types are written within a few seconds. This is very helpful in cases where the data set is very large.

 7. Optimising the code

Sometimes the data analyst has to work on very long codes. So ChatGPT can help in rescuing the code by optimising it by making it short and understandable with code explanations. Here is an example.

8. Generating the code

It is a common occurrence for data analysts to become stuck while writing code. They can seek assistance from chatGPT, which will provide you with code for simply feeding the query.Additionally, if you do not find an answer to the question, then you don’t have to rely on your teammates to answer that.

9. Putting data into pandas dataframe

We asked chatGPT Is it possible to paste a dataset into a Pandas dataframe? Here is the result.

10. Cleaning the dataset

Here, we tried cleaning the dataset by writing the query Can you clean the above database? We didn’t paste the dataset here, but instead used the word “dataset” because we already gave that data to chatGPT before.

Conclusion

We live in a world composed of data and content. With the availability of AI chatbots, you can generate large numbers of AI chatbots with just a few keyboard clicks. ChatGPT is undoubtedly a powerful and versatile language model that could revolutionise the way we learn and interact with machines. If this article helped you gain some knowledge about chatGPT.Please share it with other data analysts if you like it.So that they can make the best use of chatGPT.

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