The objective of today’s lab is to create a website using the
rmarkdown package and deploy it using GitHub pages. We
will include interactive visualizations (e.g. plot_ly()
output) on the website.
For this lab, we have created some initial content for you to work with for an example website: https://github.com/JSC370/jsc370-2023/tree/main/labs/lab12
Your objective will be to create your own personal project website using this as a reference.
Building websites uses the same reproducible workflow you can use for your analyses and collaborations. It is very iterative. You can do it all from RStudio, with a combination of clicking or typing commands as you feel comfortable.
There are two main steps for creating a personal website that will be hosted on GitHub:
I. Local setup
The basic workflow is as follows:
.Rproj
)_site.yml
and index.Rmd
file in
your new directory.Rmd
filesrmarkdown::render_site()
This creates
the output: index.html
Clone the website repository at https://github.com/JSC370/jsc370-2022/tree/main/labs/lab12
with example project website content into a directory for the lab,
e.g. "lab-12"
.
Note: we are not initializing this as a git repository, we will do that in Step 1. We are just downloading the contents.
mkdir ~/week12-lab
git clone https://github.com/JSC370/jsc370-2023/tree/main/labs/lab12
open JSC370-final-project.Rproj
Create and go to the directory you want to create your website in,
e.g. "my-website"
, and initialize git.
In command line:
mkdir ~/my-website
cd ~/my-website
git init
Recall from lecture that the minimum requirements for an R Markdown website are:
index.Rmd
: contains the content for the website
homepage_site.yml
: contains metadata for the websiteCreate these essential files, as well as a README.md
,
add all to git queue, and commit to your website repository.
Note: Use the touch
command from
command line to initialize empty files:
echo My JSC370 Final Project Website > README.md
touch _site.yml
touch index.Rmd
git add --all
git commit -m "initalizing repository"
.Rproj
fileCreate an R Project file using RStudio IDE:
Go to RStudio IDE > File > New Project > Existing Directory
The R Project is useful because RStudio will recognize your project as a website, and provide appropriate build tools.
Note: After creating the R Project and initial files, you may need to close the project and reopen it before R will recognize it as a website and show the appropriate build tools.
Edit the _site.yml
file to include the metadata, layout,
and theme you want for your website.
First let’s take a look at a basic example of a
_site.yml
file for a website with one page:
name: "my-website"
navbar:
title: "My Website"
left:
- text: "Home"
href: index.html
This is the minimum you need to include in your
_site.yml
.
Now let’s take a look at the _site.yml
from the website
repository you downloaded into "lab-12"
. It looks like
this:
name: "my-website"
output_dir: "."
navbar:
title: "JSC370 Final Project"
left:
- text: "Home"
href: index.html
right:
- icon: fa-github fa-lg
href: https://github.com/JSC370/jsc370-2023/
- text: "JSC370 Home"
href: https://jsc370.github.io/jsc370-2023/
output:
html_document:
theme: cosmo
include:
after_body: footer.html
css: styles.css
Inspecting this, how do you add links to internal webpages? How do you add links to external websites? How do you add icons?
Note: recall that the output_dir
field
indicates which directory to copy site content into
("_site"
is the default if none is specified). It can be
"."
to keep all content within the root website directory
alongside the source code.
Note: Preview themes here and play around with different options. Themes are easy to change even after you have added content.
Now your task is to create a YAML for your website that includes only
the essential components for your website. Either copy the content of
the simple _site.yml
into your own _site.yml
file in your website directory my-website
, or replicate it
yourself line by line.
.Rmd
filesEdit and create .Rmd
files that contain your website
content, which will produce the html pages of your website when you knit
them.
For example, the index.Rmd
could look like this:
---
title: "JSC370 Final Project"
author: "Your Name"
output:
html_document:
toc: TRUE
toc_float: TRUE
---
This is my JSC370 Final Project website.
Recall that the toc
specifies whether there is a table
of contents, and toc_float
provides the option to float the
table of contents to the left of the main document content. The floating
table of contents will always be visible even when the document is
scrolled. There are other options for how to display the
toc
in R Markdown HTML output which you can read about here.
After you are done with your index.Rmd
file, knit it to
check the output. Either click the Knit
option in the
toolbar or in the console type
rmarkdown::render_site("index.Rmd")
. This will render the
output into a file index.html
which you can check out by
opening the file in your directory:
Now we have the content and layout setup, we can build the website! This can be done in two ways:
rmarkdown::render_site()
rmarkdown has created all the additional files you
need for your website. Check them out in your directory. Most
importantly, the index.html
file provides with a preview of
the site, which you can look at in a browser as above:
Create an online (remote) repository for your project using GitHub
In command line:
Add the remote using git remote add
git remote add origin https://github.com/YOUR_GITHUB_NAME/YOUR_PROJECT_NAME.git
Optionally, use the commands git status
and
git remote -v
to check out the status.
Push the changes to the remote using git push
git push -u origin master
Enable GitHub pages for the repository by going to the repository’s Settings > GitHub Pages, where you’ll select the “master branch” folder and hit Save:
It’s live! Go to the website at www.YOUR_GH_NAME.github.io/YOUR_PROJECT_NAME/ (the website should appear to you when you click the appropriate setting in GitHub Pages)
Your task here is to create 2 interactive visuals, using
plotly, leaflet, DT,
or anything else you have explored, and post them on your website at
index.Rmd
.
First you can source any necessary code, meaning run it. For example,
let’s use the COVID-19 data from the NYT we explored in week 11. In the
example repository you downloaded into "week12-lab"
, we
have provided the code process_covid_data.R
which goes
through the first steps we carried out in the lab of downloading and
processing the data. To source this code:
Recall that echo=FALSE
means the code itself will not
appear in the HTML output. You can also set this globally in
opts_chunk$set(echo=FALSE)
(see above for this lab)
Then you can add some code chunks to create the interactive visuals you want to include. I will add some code to create a couple of the plotly figures we created in lab. I am naming each plot but not outputting them here, because I will want to do that in independent code chunks as we will see in the next step.
Note: Code chunks cannot have the same name, so if
you do name them (like this one: plot1
), you will need to
be sure to give each an independent name.
p1_scatter <- cv_states_today %>%
plot_ly(x = ~pop_density, y = ~deathsper100k,
type = 'scatter', mode = 'markers', color = ~state,
size = ~population, sizes = c(5, 70), marker = list(sizemode='diameter', opacity=0.5),
hoverinfo = 'text',
text = ~paste( paste(state, ":", sep=""), paste(" Cases per 100k: ", per100k, sep="") , paste(" Deaths per 100k: ",
deathsper100k, sep=""), sep = "<br>")) %>%
layout(title = "Population-normalized COVID-19 deaths vs. population density",
yaxis = list(title = "Deaths per 100k"), xaxis = list(title = "Population Density"),
hovermode = "compare")
# filter out "District of Columbia"
cv_states_today_scatter <- cv_states_today %>% filter(state!="District of Columbia")
p2_scatter <- cv_states_today_scatter %>%
plot_ly(x = ~pop_density, y = ~deathsper100k,
type = 'scatter', mode = 'markers', color = ~state,
size = ~population, sizes = c(5, 70), marker = list(sizemode='diameter', opacity=0.5),
hoverinfo = 'text',
text = ~paste( paste(state, ":", sep=""), paste(" Cases per 100k: ", per100k, sep="") , paste(" Deaths per 100k: ",
deathsper100k, sep=""), sep = "<br>")) %>%
layout(title = "Population-normalized COVID-19 deaths vs. population density",
yaxis = list(title = "Deaths per 100k"), xaxis = list(title = "Population Density"),
hovermode = "compare")
Now, please create 2 figures of your own, either using the code from
last week’s lab, or creating new figures based on the data created by
the process_COVID_data.R
code.
Create tabs to display each figure. We do that using the following R Markdown language:
## Showcasing plots {.tabset}
### Figure 1
```{r echo=FALSE}
p1_scatter
```
### Figure 2
```{r echo=FALSE}
p2_scatter
```
{-}
The output will look like this:
Knit the page index.Rmd
to check the output. It may take
a bit longer now that we’re also processing the data from the NYT.
(Recall from lecture we can do that once per session by inputting the
global option opts_chunk$set(cache=TRUE)
).
You’ve now made some edits to your website. To get the updates onto
the live webpage, you need to re-render the site to create the HTML
output from your .Rmd
file edits, and push the updates to
the remote GitHub repository:
In the R console: rmarkdown::render_site()
Preview contents by looking at the index.html
file
in a browser
Add and push changes to remote from your website project
repository locally (e.g. JSC370-final-project
):
git add --all
git commit -m "interactive visuals"
git push -u origin master
Preview your changes online at your website! Note that it may take up to 10 minutes for the content to render.
Add the online link to your website in your README.md
file, e.g.
This is my JSC370 Final Project website home. The website is online at https://github.com/meredithfranklin/my-website.
Then please submit your lab by submitting the link to your github site on Quercus.
This lab pulled from: