# Asignar Variable
x <-3
y <-2

# Imprimir Resultado
x
## [1] 3
y
## [1] 2
# Operaciones Basicas
suma <- x+y
suma
## [1] 5
# Resta -, Multiplicacion *, Division /

division_entera <- x %/% y
division_entera
## [1] 1
redondear_arriba <- ceiling(x/y)
redondear_arriba
## [1] 2
redondear_abajo <- floor(x/y)
redondear_abajo
## [1] 1
residuo <- x%%y
residuo
## [1] 1
potencia <- x**2
potencia
## [1] 9
raiz <- x**(1/2)
raiz
## [1] 1.732051
exponencial <- exp(1)
exponencial
## [1] 2.718282
absoluto <- abs(x)
absoluto
## [1] 3
signo<- sign(x)
signo
## [1] 1
# Constantes
pi
## [1] 3.141593
radio<- 10
area_circulo <- pi*radio**2
area_circulo
## [1] 314.1593
#Vectores
a<-c(1,2,3,4,5)

b<-c(1:100)

c<- seq(1,100,by= .5)
c
##   [1]   1.0   1.5   2.0   2.5   3.0   3.5   4.0   4.5   5.0   5.5   6.0   6.5
##  [13]   7.0   7.5   8.0   8.5   9.0   9.5  10.0  10.5  11.0  11.5  12.0  12.5
##  [25]  13.0  13.5  14.0  14.5  15.0  15.5  16.0  16.5  17.0  17.5  18.0  18.5
##  [37]  19.0  19.5  20.0  20.5  21.0  21.5  22.0  22.5  23.0  23.5  24.0  24.5
##  [49]  25.0  25.5  26.0  26.5  27.0  27.5  28.0  28.5  29.0  29.5  30.0  30.5
##  [61]  31.0  31.5  32.0  32.5  33.0  33.5  34.0  34.5  35.0  35.5  36.0  36.5
##  [73]  37.0  37.5  38.0  38.5  39.0  39.5  40.0  40.5  41.0  41.5  42.0  42.5
##  [85]  43.0  43.5  44.0  44.5  45.0  45.5  46.0  46.5  47.0  47.5  48.0  48.5
##  [97]  49.0  49.5  50.0  50.5  51.0  51.5  52.0  52.5  53.0  53.5  54.0  54.5
## [109]  55.0  55.5  56.0  56.5  57.0  57.5  58.0  58.5  59.0  59.5  60.0  60.5
## [121]  61.0  61.5  62.0  62.5  63.0  63.5  64.0  64.5  65.0  65.5  66.0  66.5
## [133]  67.0  67.5  68.0  68.5  69.0  69.5  70.0  70.5  71.0  71.5  72.0  72.5
## [145]  73.0  73.5  74.0  74.5  75.0  75.5  76.0  76.5  77.0  77.5  78.0  78.5
## [157]  79.0  79.5  80.0  80.5  81.0  81.5  82.0  82.5  83.0  83.5  84.0  84.5
## [169]  85.0  85.5  86.0  86.5  87.0  87.5  88.0  88.5  89.0  89.5  90.0  90.5
## [181]  91.0  91.5  92.0  92.5  93.0  93.5  94.0  94.5  95.0  95.5  96.0  96.5
## [193]  97.0  97.5  98.0  98.5  99.0  99.5 100.0
d<- rep(0,times =50)
d
##  [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [39] 0 0 0 0 0 0 0 0 0 0 0 0
nombre<-c("pepe","pancho","juan","luis","roberto")
nombre
## [1] "pepe"    "pancho"  "juan"    "luis"    "roberto"
edad<-c(20,40,19,89,30)
edad
## [1] 20 40 19 89 30
tabla<- data.frame(nombre,edad)
tabla
##    nombre edad
## 1    pepe   20
## 2  pancho   40
## 3    juan   19
## 4    luis   89
## 5 roberto   30
summary(tabla)
##     nombre               edad     
##  Length:5           Min.   :19.0  
##  Class :character   1st Qu.:20.0  
##  Mode  :character   Median :30.0  
##                     Mean   :39.6  
##                     3rd Qu.:40.0  
##                     Max.   :89.0
str(tabla)
## 'data.frame':    5 obs. of  2 variables:
##  $ nombre: chr  "pepe" "pancho" "juan" "luis" ...
##  $ edad  : num  20 40 19 89 30
tabla$edad
## [1] 20 40 19 89 30
tabla$meses<- tabla$edad*12
tabla
##    nombre edad meses
## 1    pepe   20   240
## 2  pancho   40   480
## 3    juan   19   228
## 4    luis   89  1068
## 5 roberto   30   360
#Ejericio 1
#Generar una tabla con los pacientes, su peso, su IMC, y clasificacion.

altura<-c(1.69,1.75,1.82,1.54,1.66)
peso<-c(88,56,68,90,64)

tabla_imc<- data.frame(nombre,edad,altura,peso)
tabla_imc
##    nombre edad altura peso
## 1    pepe   20   1.69   88
## 2  pancho   40   1.75   56
## 3    juan   19   1.82   68
## 4    luis   89   1.54   90
## 5 roberto   30   1.66   64
imc<-c(peso/altura**2)


tabla_imc$imc<-round(imc, digits = 2)

tabla_imc
##    nombre edad altura peso   imc
## 1    pepe   20   1.69   88 30.81
## 2  pancho   40   1.75   56 18.29
## 3    juan   19   1.82   68 20.53
## 4    luis   89   1.54   90 37.95
## 5 roberto   30   1.66   64 23.23
tabla_imc$clasificacion<- ifelse(tabla_imc$imc<18.5,"bajo peso", ifelse(tabla_imc$imc<24.9,"normal",
                                                                        ifelse(tabla_imc$imc<29.9,"sobrepeso","obesidad")))
tabla_imc
##    nombre edad altura peso   imc clasificacion
## 1    pepe   20   1.69   88 30.81      obesidad
## 2  pancho   40   1.75   56 18.29     bajo peso
## 3    juan   19   1.82   68 20.53        normal
## 4    luis   89   1.54   90 37.95      obesidad
## 5 roberto   30   1.66   64 23.23        normal
#Continuacion Vectores

longitud<- length(a)
longitud
## [1] 5
orden_ascendente<-sort(tabla_imc$imc)
orden_ascendente
## [1] 18.29 20.53 23.23 30.81 37.95
orden_decendente<-sort(tabla_imc$imc, decreasing = TRUE)
orden_decendente
## [1] 37.95 30.81 23.23 20.53 18.29
#Graficas

plot(altura,peso, main = "Grafica Altura y Peso")

tabla_imc
##    nombre edad altura peso   imc clasificacion
## 1    pepe   20   1.69   88 30.81      obesidad
## 2  pancho   40   1.75   56 18.29     bajo peso
## 3    juan   19   1.82   68 20.53        normal
## 4    luis   89   1.54   90 37.95      obesidad
## 5 roberto   30   1.66   64 23.23        normal

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