How to use AI with R?

The first step to building an AI model in R is data preprocessing. This involves importing the dataset, checking for missing values, and encoding categorical data. After preprocessing the data, the next step is to split the dataset into the training set and test set. This can be done using the caTools package in R.

What is the best AI generator free?

Microsoft Designer's Image Creator is the best overall AI image generator. Like DALL-E 3, it combines accuracy, speed, and cost-effectiveness and can generate high-quality images in seconds. Unlike DALL-E 3, Microsoft's tool is entirely free.

Is there a completely free AI?

JADBio, one of the best free ai tools , is an intuitive machine learning platform designed for anyone who wants to dive into the world of machine learning, regardless of coding expertise. With its powerful knowledge extraction tools, you can analyze any kind of curated data.

RTutor 0.98 (2024)

Basic
Summary
Table1
Categorical
Numerical
Correlation
GGpairs
EDA Reports

Data structure: df

Data summary: df

Data structure: df2

Data summary: df2

Generated by the summarytools package using the command:summarytools::dfSummary(df).

Generated by the CreateTableOne() function in the tableone package.

Generated by the plot_bar() function in the DataExplorer package.

Generated by the plot_qq() and plot_histogram() functions in the DataExplorer package.

Generated by the corr_plot() functions in the corrplot package. Blanks indicate no significant correlations.

Please wait 1 minutes for this plot to be generated by the ggpairs() functions in the GGally package.

Comprehensive EDA (exploratory data analysis)

Code chunks to include:

RMarkdown

RTutor uses OpenAI's powerful large language models to translate natural language into R code, which is then excuted. You can request your analysis, just like asking a real person. Upload a data file (CSV, TSV/tab-delimited text files, and Excel) and just analyze it in plain English. Your results can be downloaded as an HTML report in minutes!

For businesses, RTutor can be customized and locally installed to easily gain insights from your data (files, SQL databases, or APIs) at a low cost. We will be happy to discuss.

RTutor went viral on LinkedIn, Twitter, Twitter(Physacourses), and Facebook (Carlo Pecoraro).

Frequently asked questions:

1.What is RTutor?

It is an artificial intelligence (AI)-based app that enables users to interact with your data via natural language. After uploading a dataset, users ask questions about or request analyses in English. The app generates and runs R code to answer that question with plots and numeric results.

2.How does RTutor work?

The requests are structured and sent to OpenAI’s AI system, which returns R code. The R code is cleaned up and executed in a Shiny environment, showing results or error messages. Multiple requests are logged to produce an R Markdown file, which can be knitted into an HTML report. This enables record keeping and reproducibility.

3. Is my data uploaded to OpenAI?

No. The column names of your data, not the data itself, is sent to OpenAI as a prompt to generate R code. Your data is not stored in our server after the session.

4.Who is it for?

The primary goal is to help people with some R experience to learn R or be more productive. RTutor can be used to quickly speed up the coding process using R. It gives you a draft code to test and refine. Be wary of bugs and errors.

5.How do you make sure the results are correct?

Try to word your question differently. And try the same request several time. A higher temperature parameter will give diverse choices. Then users can double-check to see if you get the same results from different runs.

6.Can you use RTutor to do R coding homework?

No. That will defy the purpose. You need to learn R coding properly to be able to tell if the generated R coding is correct.

7.Can private companies use RTutor?

No. It can be tried as a demo. RTutor website dnd source code are freely available for non-profit organizations only and distributed using the CC NC 3.0 license.

8.Can you run RTutor locally?

Yes. Download the R package and install it locally. Then you need to obtain an API key from OpenAI.

9.Why do I get different results with the same request?

OpenAI’s language model has a certain degree of randomness that could be adjusted by parameters called "temperature". Set this in Settings

10.Can people without R coding experience use RTutor for statistical analysis?

Not entirely. This is because the generated code can be wrong. However, it could be used to quickly conduct data visualization, and exploratory data analysis (EDA). Just be mindful of this experimental technology.

11.Can this replace statisticians or data scientists?

No. But RTutor can make them more efficient.

12.How do I write my request effectively?

Imagine you have a summer intern, a collge student who took one semester of statistics and R. You send the intern emails with instructions and he/she sends back code and results. The intern is not experienced, thus error-prone, but is hard working. Thanks to AI, this intern is lightning fast and nearly free.

13. Can I install R package in the AI generated code?

No. But we are working to pre-install all the R packages on the server! Right now we finished the top 5000 most frequently used R packages. Chances are that your favorite package is already installed.

14. Can I upload big files to the site?

Not if it is more than 10MB. Try to get a small portion of your data. Upload it to the site to get the code, which can be run locally on your laptop. Alternatively, download RTutor R package, and use it from your own computer.

15. Voice input does not work!

One of the main reason is that your browser block the website site from accessing the microphone. Make sure you access the site using https://RTutor.ai. With http, mic access is automatically blocked in Chrome. Speak closer to the mic. Make sure there is only one browser tab using the mic.

16. Is that your photo?

No. I am an old guy. The photo was synthesized by AI. Using prompts 'statistics tutor', the image was generated by Stable Diffusion 2.0. If you look carefully, you can see that her fingers are messed up.

Update log:

April 26, 2024: Defaults to the latest GPT-4V model of 4/09.
v0.98.4 3/2/2024. Add a few rows of data in prompt.
v0.98.3 11/1/2023. Fix issue with EDA report when the target variable is categorical or not specified.
v0.98.2 11/1/2023. Comprehensive EDA report!
v 0.98 10/28/2023. Ask questions about code, error. Second data file upload.
v 0.97 10/23/2023. GPT-4 becomes the default. Make ggplot2 a preferred method for plotting. Use R environment to enable successive data manipulation.
v 0.96 9/26/2023. Include column names in all requests. GPT-4 is available.
v 0.95 6/11/2023. ChatGPT(gpt-3.5-turbo) becomes default model.
v 0.94 4/21/2023. Interactive plots using CanvasXpress.
v 0.93 3/26/2023. Change data types. Add data description. Improve voice input.
v 0.92 3/8/2023. Includes description of data structure in prompt.
v 0.91 2/6/2023. Voice input is improved. Just enable micphone and say Tutor...
v 0.90 1/15/2023. Generates and runs Pyton code in addition to R!
v 0.8.6 1/8/2023. Add description of the levels in factors.
v 0.8.5 1/6/2023. Demo in many foreign languages.
v 0.8.4 1/5/2023. Collect user feedback.
v 0.8.3 1/5/2023. Collect some user data for improvement.
v 0.8.2 1/4/2023. Auto convert first column as row names.
v 0.8.1 1/3/2023. Option to convert some numeric columns with few unique levels to factors.
v 0.8.0 1/3/2023. Add description of columns (numeric vs. categorical).
v 0.7.6 12/31/2022. Add RNA-seq data and example requests.
v 0.7.5 12/31/2022. Redesigned UI.
v 0.7 12/27/2022. Add EDA tab.
v 0.6 12/27/2022. Keeps record of all code chunks for resue and report.
v 0.5 12/24/2022. Keep current code and continue.
v 0.4 12/23/2022. Interactive plot. Voice input optional.
v0.3 12/20/2022. Add voice recognition.
V0.2 12/16/2022. Add temperature control. Server reboot reminder.
V0.1 12/11/2022. Initial launch