1. R Course 3rd lecture

2. Topics to cover
Last class we covered creating and naming vectors and using vectors for operations
This class we will cover: Vector Subsetting, Matrices, dataframes and arrays

3. Vector subsetting
> remain <- c(spades = 11, hearts = 12,diamonds = 11, clubs = 13)
> remain[1]
Spades 11
> remain[3] diamonds 11

4. Further subsetting > Remain["spades"] spades 11 remain[c(1, 4)]
spades clubs
remain[c(4, 1)]
Clubs spades
13 11

5. > remain[-1] All but index 1 are returned
>remain[-c(1,2)]
> remain[-"spades"]
Error in -"spades" : invalid argument to unary operator

6. Subsetting using logical vectors
> remain <- c(spades = 11, hearts = 12,
diamonds = 11, clubs = 13)
> remain[c(FALSE, TRUE, FALSE, TRUE)]
hearts clubs
12 13
> selection_vector <- c(FALSE, TRUE, FALSE, TRUE)
> remain[selection_vector]

7. poker_vector <- c(140, -50, 20, -120, 240)
roulette_vector <- c(-24, -50, 100, -350, 10)
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
names(poker_vector) <- days_vector
names(roulette_vector) <- days_vector
# Poker results of Wednesday: poker_wednesday
# Roulette results of Friday: roulette_friday

8. Task # Casino winnings from Monday to Friday
poker_vector <- c(140, -50, 20, -120, 240)
roulette_vector <- c(-24, -50, 100, -350, 10)
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
names(poker_vector) <- days_vector
names(roulette_vector) <- days_vector
# Poker results of Wednesday: poker_wednesday
# Roulette results of Friday: roulette_friday

9. # Casino winnings from Monday to Friday
poker_vector <- c(140, -50, 20, -120, 240)
roulette_vector <- c(-24, -50, 100, -350, 10)
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
names(poker_vector) <- days_vector
names(roulette_vector) <- days_vector
# Mid-week poker results: poker_midweek
# End-of-week roulette results: roulette_endweek

10. poker_vector <- c(140, -50, 20, -120, 240)
roulette_vector <- c(-24, -50, 100, -350, 10)
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
names(poker_vector) <- days_vector
names(roulette_vector) <- days_vector
# Create logical vector corresponding to profitable poker days: selection_vector
# Select amounts for profitable poker days: poker_profits

11. More advanced subsetting
Player: House:
# Select the player's score for the third game: player_third
# Select the scores where player exceeds house: winning_scores
# Count number of times player < 18: n_low_score
Hints:With square brackets, select the player's score for the third game, using any of the techniques that you've learned about. Store the result in player_third. Subset the player vector to only select the scores that exceeded the scores of house, so the scores that had the player win. Use subsetting in combination with the relational operator >. Assign the subset to the variable winning_scores. Count the number of times the score inside player was lower than 18. This time, you should use a relational operator in combination with sum(). Save the resulting value in a new variable, n_low_score.

12. Matrix One Two Alpha 245 304 Bravo 178 257 Charlie 314 260
2-dimensional, 1 type
We briefly looked at creating a matrix using the method matrix(data=c(1:9),nrow=3,ncol=3)
Now we’ll look at creating
One
Two
Alpha
245
304
Bravo
178
257
Charlie
314
260

13. Alpha<- c(245,304)
Bravo<-c(178,257)
Charlie<-c(314,260)
ABCmatrix<-rbind(Alpha,Bravo,Charlie)
colnames(ABCmatrix)<-c("one","two")
Another way of naming is dimnames(ABCmatrix)<-list(rowname,colname) where rowname/colname are vectors representing the names

14. Subsetting matrices Matrix[row,col] E.g. ABCmatrix[1,] ABCmatrix[2,2]
ABCmatrix[c(1,3),]
ABCmatrix[-3,]

15. Task
A vector box is defined that represents the box office numbers from the first three Star Wars movies (A New Hope, Empire Strikes Back, and Return of the Jedi). The first, third and fifth element correspond to the US box office revenue for the movies, the second, fourth and sixth element represent the non-US box office revenue.
box <- c( , 314.4, , , , 165.8)
Construct a matrix with one row for each movie. The first column is for the US box office revenue, and the second column for the non-US box office revenue. Name the matrix star_wars_matrix

16. Another method new_hope <- c(460.998, 314.4)
empire_strikes <- c( , )
return_jedi <- c( , 165.8)
Use rbind() to create star_wars_matrix, and name the columns and rows

17. Which options are correct
Which options are correct? Hint: If you’re stuck try them out to see what they do
A A & C B&D D
# option A star_wars_matrix <- rbind(new_hope, empire_strikes, return_jedi) rownames(star_wars_matrix) <- c("US", "non-US") colnames(star_wars_matrix) <- c("A New Hope", "The Empire Strikes Back", "Return of the Jedi") # option B col <- c("US", "non-US") row <- c("A New Hope", "The Empire Strikes Back", "Return of the Jedi") rbind(new_hope, empire_strikes, return_jedi, names = c(col, row)) # option C col <- c("US", "non-US") row <- c("A New Hope", "The Empire Strikes Back", "Return of the Jedi") star_wars_matrix <- matrix(c(new_hope, empire_strikes, return_jedi), byrow = TRUE, nrow = 3, dimnames = list(col, row)) # option D col <- c("US", "non-US") row <- c("A New Hope", "The Empire Strikes Back", "Return of the Jedi") star_wars_matrix <- matrix(c(new_hope, empire_strikes, return_jedi), byrow = TRUE, nrow = 3, dimnames = list(row, col))

18. The answer was D!
Both option A and C have switched rows and column, so these generate an error.
Option B is completely invalid syntax. rbind() has no names argument!

19. Practicing subsetting
Using Star_wars_matrix:
# Select all US box office revenue
# Select revenue for "A New Hope"
# Calculate the average non-US revenue per movie: non_us_all
# Calculate the average non-US revenue of first two movies: non_us_some
# Create a submatrix for all figures for "A New Hope" and "Return of the Jedi"

20. Using names and logical vectors to subset
Using names, select the US revenues for "A New Hope" and "The Empire Strikes Back".
Using logical vectors, select the last two rows and both columns from star_wars_matrix.
Finally, select the non-US revenue for "The Empire Strikes Back" with whatever technique you like.

21. Which one of these calls selects the total revenue for the 2nd, 4th and 6th movie in the matrix?
A&B All 4 A&D C&D Only B
All_wars_matrix US
non-US
total
ANH
314.4
ESB
247.9
ROTJ
165.8
TPM
552.5
AOTC
338.7
ROTS
468.5
# option A: all_wars_matrix[seq(2, 6, by = 2), "total"] # option B: all_wars_matrix[c(F,T,F,T,F,T), c(F,T)] # option C: all_wars_matrix[c("The Empire Strikes Back", 4, 6), c(T,T,F)] # option D: all_wars_matrix[c(F,T), "total"]

22. The answer was A & D!

23. Dataframe 2-dimensional, any type
df <- data.frame(name = c("Matt", "Joe", "Chris"),
age = c(52, 29, 25),
relationshipStatus = c("married", "single", "married"))

24. Task
planets <- c("Mercury", "Venus", "Earth", "Mars", "Jupiter", "Saturn", "Uranus", "Neptune")
type <- c("Terrestrial planet", "Terrestrial planet", "Terrestrial planet", "Terrestrial planet", "Gas giant", "Gas giant", "Gas giant", "Gas giant")
diameter <- c(0.382, 0.949, 1, 0.532, , 9.449, 4.007, 3.883)
rotation <- c(58.64, , 1, 1.03, 0.41, 0.43, -0.72, 0.67)
rings <- c(FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE)
Create a dataframe from these vectors
Make sure that you've actually created a data frame with 8 observations and 5 variables with str()

25. Array n-dimensional, same type
a <- array(data=c(1:6), dim = c(2,2,2)) gives a 2x2x2 array

26. Factors
Factors
> blood <- c("B", "AB", "O", "A", "O", "O", "A", "B")
> blood_factor <- factor(blood)
[1] B AB O A O O A B
Levels: A AB B O
> str(blood_factor)
Factor w/ 4 levels "A","AB","B","O":
Can also do various things such as renaming levels and ordering

27. Lists - Used to store R objects with no coercion, but some loss of functionality
> song <- list("Rsome times", 190, 5)
> names(song) <- c("title", "duration", "track")
> song <- list(title = "Rsome times",duration = 190,track = 5)
Extending lists
friends <- c("Kurt", "Florence","Patti", "Dave")
song$sent <- friends
Can also subset lists, [ (incl. names) vs [[:
song[1] vs song[[1]]

28. Transposing A very useful command is t()
This transposes data and can be very useful when manipulating data sets