Getting Started with R

#Subtraction
2-3

[1] -1

#Addition
9+6

[1] 15

#Division
2/5

[1] 0.4

#Exponentiation
4^5

[1] 1024

#Square root
sqrt(2)

[1] 1.414214

#Logarithms
log(4) #Natural log

[1] 1.386294

Question_1: Compute the log base 5 of 10 and the log of 10.

#Answers: Question 1
log(10,5)# Log of 5, Base 10
log(10,10)# Log of 10, Base 10
log(100,4) # Log of 100, Base 4

Computing some offensive metrics in Baseball

#Batting Average=(No. of hits)/(No. of At Bats)
#What is the batting average of a player that bats 29 hits in 112 at bats?
BA=29/112
BA

[1] 0.2589286

#Alternative Solution
N_Hits=29
At_Bats=112
BA<-N_Hits/At_Bats
BA

[1] 0.2589286

Batting_Average=round(BA,digits = 3)
Batting_Average

[1] 0.259

Question_2: What is the batting average of a player that bats 42 hits in 212 at bats?

#Answers
N_Hits=42
At_Bats1=212
Bat_Average<-N_Hits/At_Bats1
BattingAverage=round(Bat_Average,digits = 3)
BattingAverage

[1] 0.198

#On Base Percentage
#OBP=(H+BB+HBP)/(At Bats+BB+HBP+SF)
#Let us compute the OBP for a player with the following general stats
#AB=515,H=172,BB=84,HBP=5,SF=6
OBP=(172+84+5)/(515+84+5+6)
OBP

[1] 0.4278689

OBP_Adj=round(OBP,digits = 3)
OBP_Adj

[1] 0.428

Question_3:Compute the OBP for a player with the following general stats

#AB=565,H=156,BB=65,HBP=3,SF=7
OBP=(156+65+3)/(565+65+3+156+7)
OBP

[1] 0.281407

OBP_ad=round(OBP,digits=3)
OBP_ad

[1] 0.281

Often you will want to test whether something is less than, greater than or equal to something.

3==8

[1] FALSE

3!=8

[1] TRUE

3<=8

[1] TRUE

3>4

[1] FALSE

# Logical Disjunction (or)
FALSE|FALSE # False OR False

[1] FALSE

TRUE&FALSE

[1] FALSE

!FALSE

[1] TRUE

# Combination of statements
2<3|1==5 # 2<3 is True, 1==5 is False, True OR False is True

[1] TRUE

Assigning Values to Variables

#In R, you create a variable and assign it a value using <- as follow
Total_Bases<-6+5
Total_Bases*3

[1] 33

#To see the variables that are currently defined, use ls (as in “list”)

ls()

 [1] "At_Bats"         "At_Bats1"       
 [3] "BA"              "Bat_Average"    
 [5] "Batting_Average" "BattingAverage" 
 [7] "N_Hits"          "OBP"            
 [9] "OBP_ad"          "OBP_adj"        
[11] "OBP_Adj"         "Total_Bases"    

#To delete a variable, use rm (as in “remove”)
rm(Total_Bases)

Vectors

pitches_by_innings<-c(12,15,10,20,10) 
pitches_by_innings

[1] 12 15 10 20 10

strikes_by_innings<-c(9,12,6,14,9)
strikes_by_innings

[1]  9 12  6 14  9

Question_4: Define two vectors,runs_per_9innings and hits_per_9innings, each with five elements.

rep(2,5)

[1] 2 2 2 2 2

rep(3,3)

[1] 3 3 3

1:6

[1] 1 2 3 4 5 6

2:7

[1] 2 3 4 5 6 7

#sequence from 1 to 10 with a step of 2
seq(1,10,by=2)

[1] 1 3 5 7 9

seq(2,13,by=3)

[1]  2  5  8 11

#add vectors
pitches_by_innings+strikes_by_innings

[1] 21 27 16 34 19

#compare two vectors
pitches_by_innings

[1] 12 15 10 20 10

strikes_by_innings

[1]  9 12  6 14  9

pitches_by_innings==strikes_by_innings

[1] FALSE FALSE FALSE FALSE FALSE

# find length of vector
length(pitches_by_innings)

[1] 5

# find minimum value in vector
min(pitches_by_innings)

[1] 10

mean(pitches_by_innings)

[1] 13.4

pitches_by_innings[1]

[1] 12

pitches_by_innings[length(pitches_by_innings)]

[1] 10

pitches_by_innings

[1] 12 15 10 20 10

pitches_by_innings[c(1:3)]

[1] 12 15 10

player_positions <- c("catcher","pitcher","infielders","outfielders")
player_positions

[1] "catcher"     "pitcher"     "infielders" 
[4] "outfielders"

Data Frames

data.frame(bonus=c(2,3,1),active_roster=c("yes","no","yes"), 
salary=c(1.5,2.5,1))

Using Tables

x<-c("Yes","No","No","Yes","Yes")
table(x)

x
 No Yes 
  2   3 

Numerical measures and center of spread

ceo_salaries<-c(12,.4,2,50,8,3,1,4,.25)
mean(ceo_salaries)

[1] 8.961111

var(ceo_salaries)

[1] 251.9386

sd(ceo_salaries)

[1] 15.87257

median(ceo_salaries)

[1] 3

fivenum(ceo_salaries)

[1]  0.25  1.00  3.00  8.00 50.00

#12,.4,2,15,8,3,1,4,.25

getMode<-function(x) {
  ux<-unique(x)
  ux[which.max(tabulate(match(x,ux)))]
}

pitches_by_innings

[1] 12 15 10 20 10

getMode(pitches_by_innings)

[1] 10

strikes_by_innings

[1]  9 12  6 14  9

getMode(strikes_by_innings)

[1] 9

game_day<-c("Saturday","Saturday","Sunday","Monday","Saturday","Tuesday","Sunday","Friday","Friday","Monday")
table(game_day)

game_day
  Friday   Monday Saturday   Sunday  Tuesday 
       2        2        3        2        1 

getMode(game_day)

[1] "Saturday"