To add images, replace tutheaderbl1.png with the file name of any image you upload to your GitHub repository.
You can read this text, then delete it and replace it with your text about your tutorial: what are the aims, what code do you need to achieve them?
We are using <a href="#section_number">text</a> to create anchors within our text. For example, when you click on section one, the page will automatically go to where you have put <a name="section_number"></a>.
To create subheadings, you can use #, e.g. # Subheading 1 creates a subheading with a large font size. The more hashtags you add, the smaller the text becomes. If you want to make text bold, you can surround it with __text__, which creates text. For italics, use only one understore around the text, e.g. _text_, text.
This is some introductory text for your tutorial. Explain the skills that will be learned and why they are important. Set the tutorial in context.
You can get all of the resources for this tutorial from this GitHub repository. Clone and download the repo as a zip file, then unzip it.
At the beginning of your tutorial you can ask people to open RStudio, create a new script by clicking on File/ New File/ R Script set the working directory and load some packages, for example ggplot2 and dplyr. You can surround package names, functions, actions ("File/ New...") and small chunks of code with backticks, which defines them as inline code blocks and makes them stand out among the text, e.g. ggplot2.
When you have a larger chunk of code, you can paste the whole code in the Markdown document and add three backticks on the line before the code chunks starts and on the line after the code chunks ends. After the three backticks that go before your code chunk starts, you can specify in which language the code is written, in our case R.
To find the backticks on your keyboard, look towards the top left corner on a Windows computer, perhaps just above Tab and before the number one key. On a Mac, look around the left Shift key. You can also just copy the backticks from below.
# Set the working directory
setwd("your_filepath")
# Load packages
library(ggplot2)
library(dplyr)You can add more text and code, e.g.
# Create fake data
x_dat <- rnorm(n = 100, mean = 5, sd = 2) # x data
y_dat <- rnorm(n = 100, mean = 10, sd = 0.2) # y data
xy <- data.frame(x_dat, y_dat) # combine into data frameHere you can add some more text if you wish.
xy_fil <- xy %>% # Create object with the contents of `xy`
filter(x_dat < 7.5) # Keep rows where `x_dat` is less than 7.5And finally, plot the data:
ggplot(data = xy_fil, aes(x = x_dat, y = y_dat)) + # Select the data to use
geom_point() + # Draw scatter points
geom_smooth(method = "loess") # Draw a loess curveAt this point it would be a good idea to include an image of what the plot is meant to look like so students can check they've done it right. Replace IMAGE_NAME.png with your own image file:
More text, code and images.
This is the end of the tutorial. Summarise what the student has learned, possibly even with a list of learning outcomes. In this tutorial we learned:
We can also provide some useful links, include a contact form and a way to send feedback.
For more on ggplot2, read the official ggplot2 cheatsheet.
Everything below this is footer material - text and links that appears at the end of all of your tutorials.