From b64d75084a681c24357b7ac0a2f1ebf389240dca Mon Sep 17 00:00:00 2001
From: leiton68 <69021140+leiton68@users.noreply.github.com>
Date: Sun, 2 Aug 2020 23:26:45 -0500
Subject: [PATCH] solution #1

---
 .Rhistory     | 512 ++++++++++++++++++++++++++++++++++++++++++++++++++
 cachematrix.R |  15 --
 2 files changed, 512 insertions(+), 15 deletions(-)
 create mode 100644 .Rhistory

diff --git a/.Rhistory b/.Rhistory
new file mode 100644
index 00000000000..08b529beb71
--- /dev/null
+++ b/.Rhistory
@@ -0,0 +1,512 @@
+x
+x <- c(3,5,1,10,12,6)
+x[x!=6] <- 0
+x
+x <- c(3,5,1,10,12,6)
+x[x>=6] <- 0
+x
+x <- c(3,5,1,10,12,6)
+x[x%in% 1:5] <- 0
+x
+x <- c(3,5,1,10,12,6)
+x[x==6] <- 0
+x
+data <- read.table("C:\Users\LEITON\Desktop\CURSO R COURSERA\01SEMANA\hw1_data.csv")
+getwd()
+getwd()
+data <- read.table("hw1_data.csv")
+data <- read.csv("hw1_data.csv")
+data
+data[1]
+data[,1]
+data
+data[Ozone]
+data['Ozone']
+data['Ozone',47]
+data['Ozone',153]
+data['Ozone'][47]
+data['Ozone']
+data['Ozone'].mean()
+data[[1][1]]
+data[[1]][[1]]
+data[['Oxone']][[1]]
+data[['Oxone']][[2]]
+data[['Ozone']][[2]]
+data[['Ozone']][[47]]
+data[['Ozone']]
+is.na(data[['Ozone']])
+zz1 <- is.na(data[['Ozone']])
+zz1
+u <- zz1==TRUE
+u
+zz1[u]
+data[u]
+u1 <- zz1==FALSE
+u1
+zz <- (data[['Ozone']])
+zz
+zz[u1]
+mean(zz[u1])
+zz2 <- (zz[u1] >31 & zz[u1] <90)
+zz2
+zz[zz2]
+data
+zz5 <- (data[['Month']]==5)
+zz5
+data[zz5]
+uu1 <- data
+uu1[zz5]
+uu1
+data[['Month']]==5
+uu2 <- uu1==TRUE
+uu1[uu2]
+uu1
+zz1 <- is.na(data[['Ozone']])
+zz1
+u <- zz1 = TRUE
+u <- zz1 == TRUE
+data[u]
+zz <- (data[['Ozone']])
+zz[u]
+(data[['Ozone']])
+oz <- (data[['Ozone']])
+zz1 <- is.na(data[['Ozone']])
+zz1
+u <- zz1 == TRUE
+u
+oz[u]
+zz1[u]
+data[u]
+data
+data %>% filter(Monh == 6)
+data %>% filter(Month == 6)
+data
+data['Month']
+f1 <- data['Month']
+f2 <- f1 == 6
+f2
+f3 <- f2==TRUE
+f1[f3]
+data[f1[f3]]
+data
+f1 <- is.na(data['Ozone'])
+data[!['Ozone']]
+data[!f1]
+f1
+u1 <- data['Ozone']
+u1[!f2]
+u1[!f3]
+data
+data[32:61]
+data[32,61]
+data[,,,,32:61,,]
+data[32:61,32:61,32:61,32:61,32:6132:61]
+filter(data,"Ozone"=na)
+filter(data,"Ozone"==na)
+filter(data,"Month"==69
+filter(data,"Ozone"==na)
+filter(data,"Month"==6)
+filter(data,Month==6)
+data
+d1 <- filter(data,Month==6)
+d1 <- filter(data,"Month"==6)
+d1
+data %>% filter(Month==6)
+library(dplyr)
+data[,[1:3]]
+data[1]
+data[,3]
+data[,1]
+data
+data[,4]
+data[,4][1_6]
+data[,4][1:6]
+data[,4]["Month"==6]
+data[,4][32:61]
+mean(data[,4][32:61])
+x <- c(1,3, 5)
+y <- c(3, 2, 10)
+rbind(x,y)
+add2(3,5)
+x+y
+add2(3,5)
+add2 <- function(x,y){
+x + y
+}
+add2(3,5)
+above <- function(x,n) {
+use <- x > n
+x[use]
+x <- 1:20
+above(x)
+above(x,12)
+above(x,12)
+above <- function(x,n=10) {
+use <- x > n
+x[use]
+}
+above(x,12)
+above(x)
+x <- 1:20
+above(x)
+above <- function(x, n = 10) {
+use <- x > n
+x[use]
+}
+1+1
+1+1
+add2(3,5)
+add2(3,5)
+add2(3,5)
+1+1
+0
+1+1
+x <- 1
+x
+above <- function(x, n = 10) {
+use <- x > n
+x[use]
+}
+x <- 1:20
+above(x)
+above(x,12)
+columnmean <- function(y) {
+nc <- ncol(y)
+means <- numeric(nc)
+for(i in 1:nc) {
+means[i] <-mean(y[,i])
+}
+means
+}
+columnmean(airequality)
+columnmean(airquality)
+columnmean <- function(y, removeNA = TRUE) {
+nc <- ncol(y)
+means <- numeric(nc)
+for(i in 1:nc) {
+means[i] <-mean(y[,i], na.rm =removeNA)
+}
+means
+}
+columnmean(airquality)
+columnmean(airquality,FALSE)
+swirl()
+install.packages("swirl")
+packageVersion("swirl")
+library(swirl)
+swirl()
+library("swirl")
+install_course("Notificaciones
+R Programming")
+install_from_swirl("R Programming")
+x <- list(a = 1:5, b = rnorm(10))
+lapply(x, mean)
+x
+rnorm(10)
+lapply(x, mean)
+x <- list(a = 1:4, b = rnorm(10), c = rnorm(20,1), d = rnorm(100,5))
+lapply(x, mean)
+c
+d
+x
+x <- 1:4
+lapply(x, runif)
+x <- 1:4
+lapply(x, runif, min = 0, max = 10)
+x <- list(a = matrix(1:4, 2, 2), b = matrix(1:6, 3, 2))
+x
+lapply(x, function(elt) elt[,1])
+x <- list(a = 1:4, b = rnorm(10), c = rnorm(20,1), d = rnorm(100,5))
+sapply(x, mean)
+mean(x)
+x <- matrix(rnorm(200), 20, 10)
+x
+apply(x, 2, mean)
+apply(x, 1, sum)
+x <- matrix(rnorm(200), 20, 10)
+apply(x, 1, quantile, probs = c(0.25, 0.75))
+a <- array(rnorm(2*2*10),c(2,2,10))
+apply(a, c(1,2), mean)
+rowMeans(a, dims = 2)
+a
+rowMeans(a, dims = 2)
+mapply(rep, 1:4, 4:1)
+noise <- function(n, mean, sd){}
+noise <- function(n, mean, sd){ rnorm(n,mean,sd)}
+noise(5,1,2)
+noise(1:5,1:5,2)
+mapply(noise, 1:5,1:5,2)
+x <- c(rnorm(10), runif(10), rnorm(10,1))
+f <- gl(3, 10)
+f
+tapply(x,f,mean)
+x
+f
+tapply(x,f,mean, simplify=FALSE)
+tapply(x,f,range)
+x <- c(rnorm(10), runif(10), rnorm(10,1))
+x
+f <- gl(3,10)
+f
+split(x,f)
+lapply(split(X,f), mean)
+log(-1)
+printmessage <- function(x){
+if(x>0)
+print("x is greater than zero")
+else
+print("x es less than or equal to zero")
+invisible(x)
+}
+printmessage(1)
+printmessage(NA)
+printmessage2 <- function(x){
+if(is.na(x))
+print("x is a missing value!")
+else if(x>0)
+print("x is greater than zero")
+else
+print("x es less than or equal to zero")
+invisible(x)
+}
+printmessage2(x)
+x <- log(-1)
+printmessage2(x)
+mean(x)
+clear all
+clear
+mean(x)
+mean(x)
+x
+x
+x
+mean(x)
+traceback()
+lm(y-x)
+traceback()
+help lm
+debug(lm)
+lm(y-x)
+option(error = recover)
+read.csv("nosuchfile")
+options(error = recover)
+read.csv("nosuchfile")
+library(datasets)
+data(iris)
+?iris
+iris
+mean(Sepal.Length)
+library(datasets)
+data(iris)
+library(datasets)
+data(iris)
+?iris
+iris
+iris[1]
+iris[1,101:150]
+2
+apply(iris,1,mean)
+apply(iris,2,mean)
+iris
+apply(iris,1,mean)
+apply(iris,3,mean)
+apply(iris, 1, mean)
+library(datasets)
+data("iris")
+?iris
+iris_dt <- as.data.table(iris)
+iris_dt[Species == "virginica", round(mean(Sepal.Length))]
+iris
+install.packages("data.table")
+iris_dt <- as.data.table(iris)
+iris_dt[Species == "virginica", round(mean(Sepal.Length))]
+iris_dt <- as.data.table(iris)
+iris_dt[Species == "virginica", round(mean(Sepal.Length))]
+iris_dt <- as.data.table(iris)
+library(datasets)
+data(iris)
+iris
+library(data.table)
+iris_dt <- as.data.table(iris)
+iris_dt[Species == "virginica", round(mean(Sepal.Length))]
+iris_dt[Species == "virginica", round(mean(Sepal.Length))]
+iris_dt[Species == "virginica", round(mean(Sepal.Length),3)]
+iris_dt[Species == "virginica", round(mean(Sepal.Length),4)]
+apply(iris,1,mean)
+apply(iris[,1:4],2,mean)
+apply(iris, 2, mean)
+apply(iris[,1:4],1,mean)
+colMeans(iris)
+rowMeans(iris[,1:4])
+library(datasets)
+data(mtcars)
+?mtcars
+mtcars
+with(mtcars, tapply(mpg, cyl, mean))
+sapply(mtcars, cyl, mean)
+split(mtcars, mtcars$cyl)
+lapply(mtcars, mean)
+apply(mtcars, 2, mean)}
+apply(mtcars, 2, mean)
+tapply(mtcars$cyl, mtcars$mpg, mean)
+sapply(split(mtcars$mpg, mtcars$cyl),mean)
+tapply(mtcars$mpg, mtcars$cyl, mean)
+mean(mtcars$mpg, mtcars$cyl)
+mtcars
+with(mtcars, tapply(hp, cyl, mean))
+209.21429-82.63636
+debug(ls)
+x <<- 1
+x
+setwd
+dir
+getwd
+getwd()
+s <- NULL
+set <- function(y) {
+x <<- y
+s <<- NULL
+}
+getwd()
+load("C:/Users/LEITON/ProgrammingAssignment2/ProgrammingAssignment2/cachematrix.R")
+getwd()
+setwd("C:/Users/LEITON/ProgrammingAssignment2/ProgrammingAssignment2")
+getwd()
+my_matrix <- makeCacheMatrix(matrix(1:4, 2, 2))
+## This function creates a matrix object that can cache its inverse
+makeCacheMatrix <- fucntion(x=matrix()){
+inv <- NULL
+set <- function(y){
+x <<- y
+inv <<- NULL
+}
+get <- function() x
+setInverse <- function(inverse) inv <<- inverse
+getInverse <- function() inv
+list(set = set, get = get,
+setInverse = setInverse,
+getInverse = getInverse)
+}
+## This function computes the inverse of the matrix created in the function
+## above.
+cacheSolve <- function(x, ...){
+## Return inverse matrix of x
+inv <- x$getInverse()
+if (!is.null(j)){
+message("getting cached data")
+return(inv)
+}
+mat <- x$get()
+j <- solve(mat, ...)
+x$setInverse(inv)
+inv
+}
+## This function creates a matrix object that can cache its inverse
+makeCacheMatrix <- function(x=matrix()){
+inv <- NULL
+set <- function(y){
+x <<- y
+inv <<- NULL
+}
+get <- function() x
+setInverse <- function(inverse) inv <<- inverse
+getInverse <- function() inv
+list(set = set, get = get,
+setInverse = setInverse,
+getInverse = getInverse)
+}
+## This function computes the inverse of the matrix created in the function
+## above.
+cacheSolve <- function(x, ...){
+## Return inverse matrix of x
+inv <- x$getInverse()
+if (!is.null(j)){
+message("getting cached data")
+return(inv)
+}
+mat <- x$get()
+j <- solve(mat, ...)
+x$setInverse(inv)
+inv
+}
+getwd()
+my_matrix <- makeCacheMatrix(matrix(1:4),2,2))
+my_matrix <- makeCacheMatrix(matrix(1:4,2,2))
+my_matrix$get()
+my_matrix$getInerse()
+my_matrix$getInverse()
+cacheSolve(my_matrix)
+## This function creates a matrix object that can cache its inverse
+makeCacheMatrix <- function(x=matrix()){
+inv <- NULL
+set <- function(y){
+x <<- y
+inv <<- NULL
+}
+get <- function() x
+setInverse <- function(inverse) inv <<- inverse
+getInverse <- function() inv
+list(set = set, get = get,
+setInverse = setInverse,
+getInverse = getInverse)
+}
+## This function computes the inverse of the matrix created in the function
+## above.
+cacheSolve <- function(x, ...){
+## Return inverse matrix of x
+inv <- x$getInverse()
+if (!is.null(j)){
+message("getting cached data")
+return(inv)
+}
+mat <- x$get()
+inv <- solve(mat, ...)
+x$setInverse(inv)
+inv
+}
+getwd()
+my_matrix <- makeCacheMatrix(matrix(1:4,2,2))
+my_matrix$get()
+my_matrix$getInverse()
+cacheSolve(my_matrix)
+## This function creates a matrix object that can cache its inverse
+makeCacheMatrix <- function(x=matrix()){
+inv <- NULL
+set <- function(y){
+x <<- y
+inv <<- NULL
+}
+get <- function() x
+setInverse <- function(inverse) inv <<- inverse
+getInverse <- function() inv
+list(set = set, get = get,
+setInverse = setInverse,
+getInverse = getInverse)
+}
+## This function computes the inverse of the matrix created in the function
+## above.
+cacheSolve <- function(x, ...){
+## Return inverse matrix of x
+inv <- x$getInverse()
+if (!is.null(inv)){
+message("getting cached data")
+return(inv)
+}
+mat <- x$get()
+inv <- solve(mat, ...)
+x$setInverse(inv)
+inv
+}
+my_matrix <- makeCacheMatrix(matrix(1:4,2,2))
+my_matrix$get()
+my_matrix$getInverse()
+cacheSolve(my_matrix)
+cacheSolve(my_matrix)
+cacheSolve(my_matrix)
+my_matrix$getInverse()
+my_matrix <- makeCacheMatrix(matrix(c(2,2,1,4),2,2))
+my_matrix$get()
+my_matrix$getInverse()
+cacheSolve(my_matrix)
+cacheSolve(my_matrix)
+my_matrix$getInverse()
diff --git a/cachematrix.R b/cachematrix.R
index a50be65aa44..e69de29bb2d 100644
--- a/cachematrix.R
+++ b/cachematrix.R
@@ -1,15 +0,0 @@
-## Put comments here that give an overall description of what your
-## functions do
-
-## Write a short comment describing this function
-
-makeCacheMatrix <- function(x = matrix()) {
-
-}
-
-
-## Write a short comment describing this function
-
-cacheSolve <- function(x, ...) {
-        ## Return a matrix that is the inverse of 'x'
-}