Back to Course

R MASTERCLASS | Q4 2024 (Oct-Dec)

0% Complete
0/0 Steps
  1. WEEK 1 (PREWORK DUE BEFORE FIRST CLASS)

    Welcome to the Masterclass
    2 Topics
    |
    2 Quizzes
  2. Using ChatGPT
    1 Quiz
  3. R basics revision
    3 Quizzes
  4. Learn to Type Fast! (optional)
  5. WORKSHOP 1 | Tidyverse and R Markdown Revision | RMC Q4 2024
  6. WEEK 2 (PREWORK DUE WED, 9 OCT)
    Cohort Notes on the Git Lesson
  7. Git & GitHub for R Users
    1 Topic
  8. WORKSHOP 2 | GitHub Practice | RMC Q4 2024
  9. WEEK 3 (PREWORK DUE WED, 16 OCT)
    HTML Documents & Quarto
    1 Topic
  10. Publishing HTMLs with GitHub Pages
    1 Topic
  11. Creating a Personal Website (optional)
  12. WORKSHOP 3 | Build your own Data Report | RMC Q4 2024
  13. WEEK 4 (PREWORK DUE WED, 23 OCT)
    Joining 1: Intro to Joining Datasets
    1 Topic
  14. Joining 2: Mismatched Values, One-to-Many & Multi-Key Joins
    1 Topic
  15. WORKSHOP 4 | Joining Datasets | RMC Q4 2024
  16. WEEK 5 (PREWORK DUE WED, 30 OCT)
    Recognizing and Formatting Dates
    1 Topic
  17. String Manipulation
    1 Topic
  18. WORKSHOP 5 | Dates & Strings | RMC Q4 2024
  19. WEEK 6 (PREWORK DUE WED, 6 NOV)
    Snippet | The dplyr::across function
  20. Data Cleaning 1: Data Diagnostics
    1 Topic
  21. Data Cleaning 2: Fixing Inconsistencies
    1 Topic
  22. WORKSHOP 6 | Data Cleaning | RMC Q4 2024
  23. WEEK 7 (PREWORK DUE WED, 13 NOV)
    For Loops
    1 Topic
  24. Functions and Conditionals
    1 Topic
  25. WORKSHOP 7 | For Loops & Functions | RMC Q4 2024
  26. WEEK 8 (PREWORK DUE WED, 20 NOV)
    Snippet | Intro to Simple Features Data
  27. Thematic Maps
    1 Topic
  28. Physical Features
    1 Topic
  29. Density Maps
    1 Topic
  30. WORKSHOP 8 | Geospatial Visualization | RMC Q4 2024
  31. WORKSHOP 9 (PREWORK DUE WED, 27 NOV)
    Snippet | Sources of Map Data
  32. Shapefile Data
    1 Topic
  33. Boundary Data
    1 Topic
  34. Layers
    1 Topic
  35. WORKSHOP 9 | Advanced Geospatial Visualization | RMC Q4 2024
  36. WORKSHOP 10 (PREWORK DUE WED, 4 DEC)
    Dashboards with Quarto
    1 Topic
  37. WORKSHOP 10 | Dashboards with Quarto | RMC Q4 2024
  38. FINAL PROJECT (DUE SUN, 12 JAN)
    Final Project | RMC Q4 2024
  39. WORKSHOP 11 | Progress Check | RMC Q4 2024
Lesson 10 of 39
In Progress

Publishing HTMLs with GitHub Pages

Please watch the video below and code along as you do so. By the end of the video, you should have deployed an HTML page to GitHub pages.

🚗 Video too fast or too slow? Click the gear icon ⚙️ at the bottom-right to change the speed!

👋 Before you go, leave an anonymous rating & feedback

Average rating 4.8 / 5. Vote count: 28

No votes so far! Be the first to rate this post.

Please share any positive or negative feedback you may have.

Feedback is completely anonymous

7 Comments
Newest
Oldest Most Voted
Inline Feedbacks
View all comments
Shikha

I confirm

Haruna

I have been getting this error message while trying to render my .qmd file. @Kene, kindly assist.

Screenshot-333
Haruna


title: “HTML Intro”
subtitle: “Introduction to using HTML documents”
author: “Haruna Aremu”
date: “2025-04-09”
theme: yeti

{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

pacman::p_load(reactable, tidyverse, plotly)

# What makes HTML reports so great?

## Interactive tables

For example, reactable.

{r}
reactable(infert)

## Interactive plots

{r}
education_plot <- ggplot(data = infert, aes(x=education,
             fill= education))+
 geom_bar() 
  
education_plot %>% 
 ggplotly()

# Why are HTML reports so rich?

Leverage the full power of web technologies.

– HTML: HyperText Markup Language
– CSS: Cascading Style Sheet
– Javascript

Haruna

Thank you very much for this Kene. Appreciate

7
0
Questions or comments?x