R Notebook

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if(!require(paqueteMETODOS)){
  install.packages(paqueteMETODOS)
  
}

## Loading required package: paqueteMETODOS

## Loading required package: cubature

## Loading required package: GGally

## Loading required package: ggplot2

## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2

## Loading required package: MASS

## Loading required package: summarytools

## Loading required package: psych

## 
## Attaching package: 'psych'

## The following objects are masked from 'package:ggplot2':
## 
##     %+%, alpha

## Loading required package: tidyverse

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.2     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ lubridate 1.9.2     ✔ tibble    3.2.1
## ✔ purrr     1.0.1     ✔ tidyr     1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ psych::%+%()    masks ggplot2::%+%()
## ✖ psych::alpha()  masks ggplot2::alpha()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ✖ dplyr::select() masks MASS::select()
## ✖ tibble::view()  masks summarytools::view()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(paqueteMETODOS)

if(!require(tidyverse)){
  install.packages(tidyverse)
  
}
library(tidyverse)

# Instalaremos y cargaremos la librería devtools si aún no está instalada
if (!require(devtools)) {
  install.packages("devtools")
}

## Loading required package: devtools
## Loading required package: usethis

library(ggplot2)

if(!require(dplyr)){
  install.packages(dplyr)
  
}
library(dplyr)

if(!require(tidyr)){
  install.packages(tidyr)
  
}
library(tidyr)

# Instalaremos y cargaremos la librería ggplot2 si aún no está instalada
if (!require(ggplot2)) {
  install.packages("ggplot2")
}
library(ggplot2)

devtools::install_github("dgonxalex80/paqueteMETODOS")

library(paqueteMETODOS)

Realice un análisis exploratorio de las variables precio de vivienda (millones de pesos COP) y área de la vivienda (metros cuadrados) - incluir gráficos e indicadores apropiados interpretados.

data(vivienda4)
Apto <- filter(vivienda4, tipo == "Apartamento")
chuck(Apto)