iris <- read.csv("./iris.csv", stringsAsFactors = TRUE) #read in fileModule 6 Exercise 1
Module 6 Exercise
GEOG 5680, Summer 2025
This is an example of using Quarto! It’s super cool. Here’s a list of things that are cool about it: - It updates based when you press Render - It’s an easy way to collaborate with colleagues on projects - You can publish it online - It can update your figures automatically if you change your data. All you have to do is render it - People will think you are way cooler than them–and you will be.
Example
Here’s an example. We can use chunks of code like this.
Next, we can get some summary statistics.
##Summary statistics
print("mean")[1] "mean"
print(mean(iris$Sepal.Width))[1] 3.057333
print("s.d.")[1] "s.d."
print("range")[1] "range"
print(range(iris$Sepal.Width))[1] 2.0 4.4
And we can plot the petal values.
plot(iris$Petal.Length, iris$Petal.Width, pch=16, col=as.factor(iris$Species))Conclusion
Here is a conclusion. Yay