CALCULADORA

sqrt(4)
## [1] 2
log10(8)
## [1] 0.90309
(9*3)^(1+3)
## [1] 531441
1:50
##  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## [26] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
seq(2.5,10.5,2)
## [1]  2.5  4.5  6.5  8.5 10.5

MANEJO Y TIPO DE DATOS R

a<-1.7
b<-c(10,11,15,19)

Asignar valores a letras

a
## [1] 1.7
1/b
## [1] 0.10000000 0.09090909 0.06666667 0.05263158
b<-(a>5)
a[a>5] 
## numeric(0)
x<-1.5
y<--3.5
paste("El punto es (",x,",",y,")", sep="")
## [1] "El punto es (1.5,-3.5)"
a<- "Esto es un ejemplo"
substr(a,6,11) 
## [1] "es un "

MATRICES

matrix <- matrix(3:32, nrow=6, ncol=5) 
matrix
##      [,1] [,2] [,3] [,4] [,5]
## [1,]    3    9   15   21   27
## [2,]    4   10   16   22   28
## [3,]    5   11   17   23   29
## [4,]    6   12   18   24   30
## [5,]    7   13   19   25   31
## [6,]    8   14   20   26   32
cells = c(1.2,26,24,68)
namesf = c("F1", "F2") 
namesc = c("C1", "C2") 
matrix2 <- matrix(cells, nrow=2, ncol=2, byrow=TRUE,dimnames=list(namesf, namesc))
matrix2
##      C1 C2
## F1  1.2 26
## F2 24.0 68

DATA FRAMES (VARIABLES)

size <- c(173,176,180,165,185,175,186,160,160,172,177,175,176)
age <- c(23,24,20,22,23,24,25,28,21,21,31,24,26)
sex <- c(1,1,0,1,1,1,1,0,1,1,0,1,1)
str(sex)
##  num [1:13] 1 1 0 1 1 1 1 0 1 1 ...
str(size)
##  num [1:13] 173 176 180 165 185 175 186 160 160 172 ...
is.numeric(sex)
## [1] TRUE
is.factor(sex) 
## [1] FALSE
sex <- as.factor(sex) 
sex = factor(sex)
str(sex)
##  Factor w/ 2 levels "0","1": 2 2 1 2 2 2 2 1 2 2 ...

PARA CAMBIAR UNA VARIABLE A FACTOR SEGUIR LOS PASES DE ARRIBA 67-71

gl(4,2)
## [1] 1 1 2 2 3 3 4 4
## Levels: 1 2 3 4
 ?gl
## starting httpd help server ... done
data <- data.frame(size,sex,age)
data
##    size sex age
## 1   173   1  23
## 2   176   1  24
## 3   180   0  20
## 4   165   1  22
## 5   185   1  23
## 6   175   1  24
## 7   186   1  25
## 8   160   0  28
## 9   160   1  21
## 10  172   1  21
## 11  177   0  31
## 12  175   1  24
## 13  176   1  26
head(data)
##   size sex age
## 1  173   1  23
## 2  176   1  24
## 3  180   0  20
## 4  165   1  22
## 5  185   1  23
## 6  175   1  24
tail(data) 
##    size sex age
## 8   160   0  28
## 9   160   1  21
## 10  172   1  21
## 11  177   0  31
## 12  175   1  24
## 13  176   1  26

JUGADORES

read.table("jugadores.txt")
##         V1   V2       V3
## 1  lateral edad estatura
## 2        1   27   178,56
## 3        1   22    181,5
## 4        2   23      183
## 5        1   24      162
## 6        2   26      172
## 7        1   26    171,5
## 8        1   33      160
## 9        1   26      163
## 10       1   29      167
## 11       1   24    161,2
## 12       2   25      170
## 13       2   26      187
## 14       1   23      166
## 15       1   27      162
## 16       2   25      194
## 17       1   24      160
## 18       2   22      185
## 19       1   21      155
## 20       1   21      175
## 21       2   22      183
## 22       1   22      167
## 23       1   30      172
## 24       1   25      163
## 25       1   24      172
## 26       1   23      161
## 27       2   33      182
data$estatura + 10
## numeric(0)
str(data) 
## 'data.frame':    13 obs. of  3 variables:
##  $ size: num  173 176 180 165 185 175 186 160 160 172 ...
##  $ sex : Factor w/ 2 levels "0","1": 2 2 1 2 2 2 2 1 2 2 ...
##  $ age : num  23 24 20 22 23 24 25 28 21 21 ...
data<-read.table("jugadores.txt",head=T) #
head(data)
##   lateral edad estatura
## 1       1   27   178,56
## 2       1   22    181,5
## 3       2   23      183
## 4       1   24      162
## 5       2   26      172
## 6       1   26    171,5