R Shiny for Data Science Tutorial – Build Interactive Data-Driven Web Apps

Ecommerce Empire Academy

Learn how to build interactive data-driven web apps in R using the Shiny package.

✏️ Course developed by Chanin Nantasenamat (aka Data Professor). Check out his YouTube
channel for more bioinformatics and data science tutorials:

⭐️ Code ⭐️
💻 Apps 1-5:
💻 Deploy Shiny App:

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⭐️ Course Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:01:13) Introduction to Shiny
⌨️ (0:08:24) App 1 – Print User Input
⌨️ (0:21:12) App 2 – Display Histogram
⌨️ (0:32:07) App 3 – Machine Learning (Weather Dataset)
⌨️ (0:47:51) App 4 – Machine Learning (Iris Dataset)
⌨️ (1:05:03) App 5 – BMI Calculator
⌨️ (1:19:18) Deploy Shiny Apps to Heroku

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25 thoughts on “R Shiny for Data Science Tutorial – Build Interactive Data-Driven Web Apps”

  1. Sir, please make a tutorial that how can we make a web admin panel for our app.

    I’m using Kotlin, mvvm architecture and Firebase for the app, but don’t know how to make web admin panel so please help us with this…🙏

  2. Looks interesting and far less intimidating than I thought!
    Thanks for the very clear video, have only watched the first couple of apps but I already like the way you instruct this course,
    thank you so much!

  3. Entertainment kamaal

    It was a useful information on R shiny. Can you please show us how to work on if the dynamic content.

  4. Thanks @Data Professor for your tutorial, it is really amazing. I am running the IRIS dataset app on some other model ( data set) where all the columns are numeric, there are four columns open,low,high,volume , but while running the app it is showing error : variables ‘open’, ‘low’, ‘Volume’, ‘high’ were specified with different types from the fit, Request you to please help on this……. thanks

  5. Vishwaraj Sankla

    Hi, can someone tell me what is the source of airquality data that is been loaded?
    I have an csv file and i want to load that instead of airquality data. pls help

  6. Thanks a lot Data Professor. I learned Shiny in just two hours with you and I am very happy to find the simple way of deploying my ML credit risk model. God bless you.

  7. Really very much useful video. Thanks a lot. Can we try this for fuzzy c means with 4 cluster probabilty and prediction also

  8. Sir, Can you please dmonstrate how to make shiny standalone apps. like with .exe extension!! Help is much appreciated.

  9. Great tutorial, made it very easy to understand. Is there a link the slides mentioned in the tutorial? Thanks!

  10. Ksingh Imtnag

    Hi Prof. Your tutorial is great. I am getting following error in both Play-Golf and IRIS programs related to randomForest.
    Error in y – ymean : non-numeric argument to binary operator
    In addition: Warning messages:
    1: In randomForest.default(m, y, …) :
    The response has five or fewer unique values. Are you sure you want to do regression?
    2: In mean.default(y) : argument is not numeric or logical: returning NA

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