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7.1. Operations on Vectors

In this section you will find more information about how to compose operations with vectors.

7.1.1. Select elements

# define persons
> persons <- c("John", "Jack", "Bill", "Kim", "Jason", "Michael", "Britney", "Julia")
> length(persons)
[1] 8
 
# select persons from numeric index 4 to 6
> persons[c(4:6)]
[1] "Kim"     "Jason"   "Michael"
 
# select using a vector of booleans
# here NA (Not Available) tells us that we have tried to select more
# data than available: persons contains 8 values and the boolean 
# selection uses 10 values
> persons[c(rep(TRUE,2),rep(FALSE,3),rep(T,5))]
[1] "John"    "Jack"    "Michael" "Britney" "Julia"   NA        NA

7.1.2. Name elements

> weights <- c(77, 58, 66, 82)
 
# assign names to numeric values
> names(weights) <- c("John", "Jack", "Bill", "Kim")
 
> weights
John Jack Bill  Kim 
  77   58   66   82 
 
# select using one name
> weights["Bill"]
Bill 
  66 
 
# select using several names  
> weights[c("John","Bill")]
John Bill 
  77   66

7.1.3. Arithmetic operations and comparisons

> weights <- c(77, 58, 66, 82)
> names(weights) <- c("John", "Jack", "Bill", "Kim")
> weights
John Jack Bill  Kim 
  77   58   66   82 
 
# add one to all values of weight
> weights+1
John Jack Bill  Kim 
  78   59   67   83 
 
# add vector (10,20) 
# so we get 77+10, 58+20, 66+10, 82+20  
> weights+c(10,20)
John Jack Bill  Kim 
  87   78   76  102 
 
# which values are greater than 68  
> weights > 68
 John  Jack  Bill   Kim 
 TRUE FALSE FALSE  TRUE
 
# use operator x %in% v (is x inside vector v) 
> 77 %in% weights        
[1] TRUE

7.1.4. Sort, order

The function sort() will sort the data and order() will return the order of the index if the data are sorted.

> weights <- c(85,78,54,98,66,78,77,62,89,92,76,77,55,68);
> sort(weights)
 [1] 54 55 62 66 68 76 77 77 78 78 85 89 92 98
> sort(weights[3:8])
[1] 54 62 66 77 78 98
> order(weights)
 [1]  3 13  8  5 14 11  7 12  2  6  1  9 10  4

7.1.5. Sum, mean, median, min, max, quantile, var, sd, summary

> weights <- c(85,78,54,98,66,78,77,62,89,92,76,77,55,68);
> sum(weights)
[1] 1055
> mean(weights)
[1] 75.35714
> var(weights)     # variance
[1] 175.3242
> sd(weights)      # standard deviation
[1] 13.241
> median(weights)
[1] 77
> min(weights)
[1] 54
> max(weights)
[1] 98
> quantile(weights)
   0%   25%   50%   75%  100% 
54.00 66.50 77.00 83.25 98.00 
> summary(weights)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  54.00   66.50   77.00   75.36   83.25   98.00