
Asignación de Variables
x <- (3)
y <- (2)
Impresión de Resultados
x
## [1] 3
y
## [1] 2
Operaciones Aritméticas
suma <- x+y
suma
## [1] 5
resta <- x-y
resta
## [1] 1
multiplicacion <- x*y
multiplicacion
## [1] 6
division <- x/y
division
## [1] 1.5
division_entera <- x%/%y
division_entera
## [1] 1
residuo <- x%%y
residuo
## [1] 1
potencia <- x^2 # cambien con **
potencia
## [1] 9
Funciones matemáticas
raiz_cuadrada <- sqrt(x)
raiz_cuadrada
## [1] 1.732051
raiz_cubica <- x^(1/3)
raiz_cubica
## [1] 1.44225
exponencial <- exp(1)
exponencial
## [1] 2.718282
absoluto <- abs(x)
absoluto
## [1] 3
signo <-(x)
signo
## [1] 3
redondeo_arriba <- ceiling(division)
redondeo_arriba
## [1] 2
redondeo_abajo <- floor(division)
redondeo_abajo
## [1] 1
truncar <- trunc(division)
truncar
## [1] 1
Constantes
pi
## [1] 3.141593
radio <- 5
area_circulo <- pi*radio^2
area_circulo
## [1] 78.53982
Vectores
a <- c(1,2,3,4,5) # Juntarlos
a
## [1] 1 2 3 4 5
b <- c(1:100) # Secuencia de enteros
b
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100
c <- seq(2,5,by=0.5) # Secuencia específica
c
## [1] 2.0 2.5 3.0 3.5 4.0 4.5 5.0
d <- rep(1:2, times=3) # Repertir vector
d
## [1] 1 2 1 2 1 2
e <- rep(1:2, each=3) # Repetir elementos
e
## [1] 1 1 1 2 2 2
f <- c("pera", "manzana", "kiwi", "fresa")
f
## [1] "pera" "manzana" "kiwi" "fresa"
longitud <- length(a)
longitud
## [1] 5
promedio <- mean(a)
promedio
## [1] 3
rango <- max(a)-min(a)
rango
## [1] 4
resumen <- summary(a)
resumen
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1 2 3 3 4 5
orden_ascendente <- sort(a)
orden_ascendente
## [1] 1 2 3 4 5
orden_descendente <- sort(a, decreasing=TRUE)
orden_descendente
## [1] 5 4 3 2 1
g <- c(1,2,3,4,5)
suma_vectores <- a+g
suma_vectores
## [1] 2 4 6 8 10
# Tipos de Datos
# Caracter: Palabras, van siempre entre comillas.
# Numericos: Números.
# Lógicos: TRUE, FALSE.
# Factorers: Niveles preestablecidos '1' '0'
# Para convertir Ej: as.numeric
Graficar
plot(a,g, main="Ventas por Mes", xlab="Mes", ylab="M USD", type="b")

# Operadores Relacionales
# Igual a==b
# Desigual a!=b
# Mayor que a>b
# Menos que a<b
# Mayor o igual que a>=b
# Menor o igual que a<=b
Condicionales
calificacion <- 71
if (x>=70){
print("Pasa")
} else {
print("No pasa")
}
## [1] "No pasa"
Tabla
tabla <- data.frame(x,g)
tabla
## x g
## 1 3 1
## 2 3 2
## 3 3 3
## 4 3 4
## 5 3 5
Ejercicio 1
# Registra el nombre, peso, altura de alumnos.
# calcula su IMC y asigna su categoria
nombre <- c("Elisa", "Dayra", "Isabel")
altura <- c(1.66, 1.78, 1.64)
peso <- c(50, 83, 55)
df <- data.frame(nombre,altura,peso)
df$IMC <- df$peso/df$altura**2
df$clasificacion <- ifelse(df$IMC<18.5, "Peso Bajo",
ifelse(df$IMC<25,"Normal",
ifelse(df$IMC<30,"Sobrepeso",
ifelse(df$IMC<35,"Obesidad Grado 1",
ifelse(df$IMC<40,"Obesidad Grado 2", "Obesidad Grado 3")))))
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