ChatGPT is an Artificial Intelligence Chatbot. GPT here stands for Generative Pre-Trained Transformer that uses transformer neural network architecture. It is trained with a huge amount of text data from the internet to learn patterns, grammar, etc. Thus ChatGPT is finely designed to generate human-like responses. It provides relevant coherent replies to the users, however, the responses are based on the trained data and do not involve any consciousness.
With the growing collection of packages, ChatGPT is now available for R programmers to help in coding. This allows incorporating the Artificial Technology techniques in R programming.
To know more about ChatGPT by OpenAI, refer to this article: What is ChatGPT by OpenAI – Explained!
What is R Programming?
R is a programming language generally used for statistical computations. It has got a vast collection of libraries and ecosystems for the computational process. Statistical computing in turn plays a key role in Data Analysis, Data Science, Machine Learning, etc. Though Python is used in Data Analysis techniques, R could help the developer focus more on the computation part.
For FREE Tutorial on R Language Refer To – R Tutorial
As said earlier, the ChatGPT package in R has opened doors to more features. The following article suggests various ChatGPT R Programming tools available.
How Does ChatGPT R Programming Tools Help?
Chat GPT R Programming tools are to help with generating R code or help with errors. They can clear all the doubts while working with interactive ChatGPT features available. The tools are mostly a package either available on CRAN or could be installed from GitHub. The command lines and addins that each of them possesses perform various functions to assist in R Programming.
Kindly note that everything you ask for the tools is sent to OpenAI servers. Hence, it is vital to be careful with the sensitive data. It is also important to know when the answers you get through ChatGPT are not right as they are not always correct. You might mess it up big time. Check on the versions you use as they might not be updated with the latest features.
Top 7 Chat GPT R Programming Tools
The following are the 7 ChatGPT Tools that one can explore and get the required guidance and assistance on coding with R. We have given a clear insight on the addins they have and how each tool could be used.
1. askgpt
‘askgpt’ is a chat interface that helps in R programming. It is a simple command included in the ChatGPT R programming package that gives you answers to any kind of questions you might have. The command line goes like this, “ask_chatgpt( )” The question to ask is fed into the argument. It then generates a response. So basically, it is a simple interactive chatbot to get your doubts cleared when in confusion. Additional functionality includes the use of a prompt say, help! to get help on the last error. Further, R studio add-in could be used to comment, annotate, explain the code, etc.
2. CodeLingo
The CodeLingo tool by Analytica Data Science Solutions helps in translating one programming language to another. This application is multi-lingual. Java, Python, R, JavaScript, C++, etc are the various programming languages available. This lets the users code in any language and converts the codes to R programming as required. However, there are possibilities that the ChatGPT doesn’t understand the code in a few cases. For example, a set of readily available libraries or packages may not be available in the programming language. Hence, the user must have the basic knowledge to falter code or fix errors, if any after conversion. CodeLingo is available only as a web application and requires an OpenAI API key for access.
3. RTutor
R Tutor by South Dakota State University is one of the best and most suggested ChatGPT tools for R programming. It is also simple that you feed the data and get the program. That is, we feed the available data set to the AI, which is uploaded as a data frame called df, and then place our question. The app generates the code along with the results of the questions and graphs. One can also build upon the current code using the “Continue from this chunk” option. The R code will be inserted and get executed. It doesn’t require any ChatGPT API key. This again gives only a draft code that may have errors. Also, R Tutor can be used to generate Python code.
4. gptchatteR
‘gptchatteR’ tool created by Isin Altinkaya from the University of Copenhagen, is described as ‘an experimental and unofficial wrapper for interacting with OpenAI GPT models in R. It is required to install the required packages and load the libraries (packages- dev tools, OpenAI; library- devtools). Forget not to install the gptchatteR package from GitHub. The package is completely built using R ad one of the highlights is that it uses the chatter functions like chatter.create( ), chatter.auth( ), etc. Chatter.plot( ) generates plots based on the data fed and the response by the ChatGPT. The graph then appears on the RStudio view pane.
5. gpttools
Generally, the CRAN (Comprehensive R Archive Network) is where we get the libraries and packages. However, most tools here are independent packages available on GitHub. ‘gpttools’ is one such package by JamesHWade available on GitHub. JamesHWade has designed it in a way that the ‘gpttools’ could be used to extend the gptstudio. This helps the user to document and explain code and even to write tests. The use of the package initially requires an OpenAI account and the OpenAI API key is to be set up in RStudio. Further, comment code, add roxygen, convert the script to function, and write a unit test for a function are a few add-ins available with the package.
6. Chatgpt
The Chatgpt R package is available on CRAN (The Comprehensive R Archive Network). ChatGPT package created by Juan Cruz Rodriguez serves as a coding assistant to RSTudio. The package requires an OpenAI API Key. It is usually used as a command “ask_chatgt( question )”. The argument contains the question to be asked. Further, the package has got many add-ins such as comment_code( ), complete_code( ), create_unit_tests( ), optimize_code( ), parse_response( ), etc. The user can also start an interactive chat session with ChatGPT using ‘run_addin_ask_chatgpt( ). There are also other add-ins available to explain the code, create a variable, find issues, etc. The package has to be loaded with the library (chatgpt) for the addins to work.
7. gptstudio
The gptstudio package by Michael Nivard is considered to be a sibling of the gpttools package by JamesHWade. The latter has contributed to the gptstudio package as well. This package is available on CRAN. The gptstudio allows the R programmers to incorporate the use of Large Language Models (LLMs) into the project. It can work in any IDE or terminal with the use of command-line functions. Further, the addins could also be accessed within the RStudio. The package again requires an OpenAI API Key to set up the package in RStudio. Adding here lets the R programmer make use of the ChatGPT, provide instruction in R, R Markdown, or Quarto files, check spelling and grammar, comment on the code, etc.
Conclusion
With R programming finding its role nowadays in almost all the industries such as e-commerce, finance, retail, entertainment, etc. it is always good to have a good knowledge about the various tools required to code the same. Hope this article must have given you an idea regarding the ChatGPT R programming Tools that every R programmer could use. Given here are overviews of the tools. It is recommended that you dive a little deeper and understand them to easily incorporate them into your projects.
However, in using OpenAI, be careful with the privacy of your data. Try to avoid uploading or highlighting any confidential or sensitive data. Check out the terms of use before performing any action.
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