Asignación de Variables

x <- 3
y <- 2

Impresion 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^y
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 <- sign(x)
signo
## [1] 1
redondeo_arriba <- ceiling(division)
redondeo_arriba
## [1] 2
redondeo_abajo <- floor(division)
redondeo_abajo
## [1] 1
truncar <- trunc(division) #TRUNCAR ignora los decimales, sólo considera el número entero
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)
a
## [1] 1 2 3 4 5
b <- c(1:100)
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 <- c("pera","mango","manzana","kiwi","fresa")
c
## [1] "pera"    "mango"   "manzana" "kiwi"    "fresa"
longitud <- length(a)
longitud
## [1] 5
promedio <- mean(a)
promedio
## [1] 3
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
d <- c(1,2,3,4,5)
d
## [1] 1 2 3 4 5
suma_vectores <- a+d
suma_vectores
## [1]  2  4  6  8 10

Graficar

plot(a,d, main = "Ventas por mes", xlab = "Mes", ylab = "Millones USD", type = "b")

plot
## function (x, y, ...) 
## UseMethod("plot")
## <bytecode: 0x000001ff156dbd30>
## <environment: namespace:base>
LS0tDQp0aXRsZTogIkNvbWFuZG8gQmFzaWNvcyINCmF1dGhvcjogIkZhYmlhbmEgTWVkaW5hY2VsbGkgQTAwODM1ODYiDQpkYXRlOiAiMjAyMy0wOS0xMSINCm91dHB1dDogDQogIGh0bWxfZG9jdW1lbnQ6DQogICAgdG9jOiBUUlVFDQogICAgdG9jX2Zsb2F0OiBUUlVFDQogICAgY29kZV9kb3dubG9hZDogVFJVRQ0KICAgIHRoZW1lOiAiY2VydWxlYW4iDQogICAgaGlnaGxpZ2h0OiAidGFuZ28iDQotLS0NCg0KIVtdKGM6XFxVc2Vyc1xcSFBcXERlc2t0b3BcXEJvb3RjYW1wIGRlIFByb2dyYW1hY2nDs25cXGFyaXRtZXRpY2EtNS1ncmFkby5naWYpDQoNCiMjIyBBc2lnbmFjacOzbiBkZSBWYXJpYWJsZXMNCmBgYHtyfQ0KeCA8LSAzDQp5IDwtIDINCmBgYA0KIyMjIEltcHJlc2lvbiBkZSBSZXN1bHRhZG9zDQpgYGB7cn0NCngNCnkNCmBgYA0KIyMjIE9wZXJhY2lvbmVzIEFyaXRtw6l0aWNhcw0KYGBge3J9DQpzdW1hIDwtIHgreQ0Kc3VtYQ0KDQpyZXN0YSA8LSB4LXkNCnJlc3RhDQoNCm11bHRpcGxpY2FjaW9uIDwtIHgqeQ0KbXVsdGlwbGljYWNpb24gDQoNCmRpdmlzaW9uIDwtIHgveQ0KZGl2aXNpb24NCg0KZGl2aXNpb25fZW50ZXJhIDwtIHglLyV5DQpkaXZpc2lvbl9lbnRlcmENCg0KcmVzaWR1byA8LSB4JS8leQ0KcmVzaWR1bw0KDQpwb3RlbmNpYSA8LSB4XnkNCnBvdGVuY2lhDQpgYGANCiMjIyBGdW5jaW9uZXMgbWF0ZW3DoXRpY2FzDQpgYGB7cn0NCnJhaXpfY3VhZHJhZGEgPC0gc3FydCh4KQ0KcmFpel9jdWFkcmFkYQ0KDQpyYWl6X2N1YmljYSA8LSB4XigxLzMpDQpyYWl6X2N1YmljYQ0KDQpleHBvbmVuY2lhbCA8LSBleHAoMSkNCmV4cG9uZW5jaWFsDQoNCmFic29sdXRvIDwtIGFicyh4KQ0KYWJzb2x1dG8NCg0Kc2lnbm8gPC0gc2lnbih4KQ0Kc2lnbm8NCg0KcmVkb25kZW9fYXJyaWJhIDwtIGNlaWxpbmcoZGl2aXNpb24pDQpyZWRvbmRlb19hcnJpYmENCg0KcmVkb25kZW9fYWJham8gPC0gZmxvb3IoZGl2aXNpb24pDQpyZWRvbmRlb19hYmFqbw0KDQp0cnVuY2FyIDwtIHRydW5jKGRpdmlzaW9uKSAjVFJVTkNBUiBpZ25vcmEgbG9zIGRlY2ltYWxlcywgc8OzbG8gY29uc2lkZXJhIGVsIG7Dum1lcm8gZW50ZXJvDQp0cnVuY2FyDQpgYGANCiMjIyBDb25zdGFudGVzDQpgYGB7cn0NCnBpDQpyYWRpbyA8LSA1DQphcmVhX2NpcmN1bG8gPC0gcGkqcmFkaW9eMg0KYXJlYV9jaXJjdWxvDQpgYGANCiMjIyBWZWN0b3Jlcw0KYGBge3J9DQphIDwtIGMoMSwyLDMsNCw1KQ0KYQ0KDQpiIDwtIGMoMToxMDApDQpiDQoNCmMgPC0gYygicGVyYSIsIm1hbmdvIiwibWFuemFuYSIsImtpd2kiLCJmcmVzYSIpDQpjDQoNCmxvbmdpdHVkIDwtIGxlbmd0aChhKQ0KbG9uZ2l0dWQNCg0KcHJvbWVkaW8gPC0gbWVhbihhKQ0KcHJvbWVkaW8NCg0KcmVzdW1lbiA8LSBzdW1tYXJ5KGEpDQpyZXN1bWVuDQoNCm9yZGVuX0FzY2VuZGVudGUgPC0gc29ydChhKQ0Kb3JkZW5fQXNjZW5kZW50ZQ0KDQpvcmRlbl9kZXNjZW5kZW50ZSA8LSBzb3J0KGEsZGVjcmVhc2luZyA9IFRSVUUpDQpvcmRlbl9kZXNjZW5kZW50ZQ0KDQpkIDwtIGMoMSwyLDMsNCw1KQ0KZA0KDQpzdW1hX3ZlY3RvcmVzIDwtIGErZA0Kc3VtYV92ZWN0b3Jlcw0KDQpgYGANCiMjIyBHcmFmaWNhcg0KYGBge3J9DQpwbG90KGEsZCwgbWFpbiA9ICJWZW50YXMgcG9yIG1lcyIsIHhsYWIgPSAiTWVzIiwgeWxhYiA9ICJNaWxsb25lcyBVU0QiLCB0eXBlID0gImIiKQ0KcGxvdA0KYGBgDQo=