diff --git a/a3.r b/a3.r
new file mode 100644
index 0000000000000000000000000000000000000000..6b0367782b4fcab69af21d3a82d476d67ce06c96
--- /dev/null
+++ b/a3.r
@@ -0,0 +1,56 @@
+###
+ # R code for assignment.
+ ##
+
+
+# Clear console.
+cat('\014')
+
+
+# install.packages('arules', dependencies=TRUE)
+library(arules)
+
+
+###
+ # The "cat" function seems to be an all around better alternative to "print".
+ # ("print" has a tendency to add extra, frivilous output that makes it look dirty and difficult to read.)
+ #
+ # This wrapper for "cat" then automatically adds a newline to the end of the message, effectively accomplishing
+ # what you would intuitively expect "print" to do.
+ #
+ # See references.md file for source of idea.
+ ##
+catn <- function(message, trailing='\n') {
+    cat(message)
+    cat(trailing)
+}
+
+
+###
+ # Tests the build-in R "apriori" function using the in class example from the powerpoints.
+ ##
+in_class_example <- function() {
+    # Create our initial dataset.
+    # Note that we use True/False so R knows that each value is either present or not.
+    items <-    c(  "A",    "B",    "C",    "D",    "E")
+    values <-   c(  TRUE,   FALSE,  TRUE,   TRUE,   FALSE,
+                    FALSE,  TRUE,   TRUE,   FALSE,  TRUE,
+                    TRUE,   TRUE,   TRUE,   FALSE,  TRUE,
+                    FALSE,  TRUE,   FALSE,  FALSE,  TRUE)
+
+    # Create our dataset in the format the apriori function wants.
+    dataset <- data.frame(matrix(values, nrow=4, byrow=TRUE))
+    colnames(dataset) <- items
+
+    # Generate rules from apriori function.
+    rules <- apriori(dataset, parameter=list(supp=0.4, conf=0))
+
+    # Display all rules.
+    catn('')
+    catn('')
+    print(rules)
+    inspect(rules)
+}
+
+
+in_class_example()
diff --git a/documents/references.md b/documents/references.md
index c6822a2cf63873118a5a4d5752a98ddb0d691b9c..d49cd6b6604835c54cd5bac4e1b80d83ed598625 100644
--- a/documents/references.md
+++ b/documents/references.md
@@ -11,6 +11,7 @@ All references to external logic. Includes anything from stack overflow links to
 Turns out that R has "packages", and they already have an implementation of Apriori. Hours wasted trying to implement it myself, rip.<br>
 * <https://datascienceplus.com/implementing-apriori-algorithm-in-r/>
 * <https://www.rdocumentation.org/packages/arules/versions/1.6-5/topics/apriori>
+* <https://www.rdocumentation.org/packages/arules/versions/1.6-5/topics/rules-class>
 
 ### Run Entire Script in R Studio
 <https://stackoverflow.com/a/12766667>