Today we will finish talking about GitHub, RMarkdown, and the first project.
GitHub (part 2)
You should now all having working GitHub repositories for your work. You can reach the page through this link (you’ll have to sign into your GitHub account):
Now, take the photo you brought to class. Put it in the
img directory on the
GitHub repository (I recommend giving it a short name with no spaces).
Next, click on the file
index.html in the repository. Then click on the
pencil button on the right hand side to the right of the Raw/Blame/History
buttons. You can now edit the file. Change my name on line 16 to your name.
Then, on line 17, change the link
figure.jpg to the name of your figure.
Scroll down and click “Commit changes”.
If you followed along with the instructions for today, you should be able to see the website at this link with your username filled in:
But now, your name and photo will appear. If you put the
first.html file on
the site correctly, you will also be able to click on the first link and see
One element of our current pipeline prohibits our analysis from being completely reproducible. While someone that finds the repository would have our code and analysis together, they cannot actually run the script without our data. Even if they had the data, they would need to figure out how to download it and change the path the to data to the correct link.
To fix this, verify that you have uploaded the class dataset to your GitHub
repository. Then, we need to re-access the
first.Rmd file. This is
trickier than it should be because the GitHub assumes that you want all of
the files downloaded. That’s okay though, at least for now. Click on the green
Clone or Download button on the repository page and select Download ZIP.
Unzip the file and you’ll see the
first.Rmd file there which you should be
able to double click on.
Once you have the markdown file re-opened, scroll down to where you loaded the dataset into R. Modify this line to read it in from your website
Verify that this produces the data you were expecting.
I have expanded on only a few elements of the RMarkdown format. Several others will be useful in preparing your data projects.
Notice that the first chunk of code includes the option
makes it so that, while the code runs when knit, the code and any output is
not included in the text. Other options include:
echo=FALSE, echo refers to whether the code should be shown; this turns it off for a particular chunk but unlike
include=FALSEplots and other output are still shown
message=FALSEto suppress any messages; note that messages are still shown with
include=FALSE, so you’ll probably want this in the first chunk as well
warning=FALSEto suppress any warnings; similar to messages, these are included even when
Experiment with setting this options and note the differences in the output.
You can also use special markings to make words in bold (put them between
* symbols) or italics (put them between single
* symbols). Try this
will two things in the report. For a complete reference see the RMarkdown
These are great references for all of the possible things we can do with RMarkdown.
Finally, re-knit the RMarkdown file and re-upload both the HTML and Rmd file.
Note: It is essential that you do this correctly and give the exact correct name of the file. Some of your have not been doing the assignments that I give at the end of class. I will start verifying that you have done these and, as explained in the syllabus, will consider this equivalent to an absence.
Details for the first project are now available on the website. The project is due at the start of class on Tuesday, February 20th. Note that the instructions are spread across three documents: a webpage with a the basic outline, an RMarkdown file to be used as a template, and a rubric with a detailed breakdown of the expected elements.
Please do not wait until the last minute to work on this project and also please make sure to triple check that you are following the instructions as specified.