Titanic

Importar base de datos

base_de_datos <- read.csv("/Users/andreapaolasosa/Desktop/titanic.csv")

Entender base de datos

summary (base_de_datos)

##      pclass         survived         name               sex           
##  Min.   :1.000   Min.   :0.000   Length:1310        Length:1310       
##  1st Qu.:2.000   1st Qu.:0.000   Class :character   Class :character  
##  Median :3.000   Median :0.000   Mode  :character   Mode  :character  
##  Mean   :2.295   Mean   :0.382                                        
##  3rd Qu.:3.000   3rd Qu.:1.000                                        
##  Max.   :3.000   Max.   :1.000                                        
##  NA's   :1       NA's   :1                                            
##       age              sibsp            parch          ticket         
##  Min.   : 0.1667   Min.   :0.0000   Min.   :0.000   Length:1310       
##  1st Qu.:21.0000   1st Qu.:0.0000   1st Qu.:0.000   Class :character  
##  Median :28.0000   Median :0.0000   Median :0.000   Mode  :character  
##  Mean   :29.8811   Mean   :0.4989   Mean   :0.385                     
##  3rd Qu.:39.0000   3rd Qu.:1.0000   3rd Qu.:0.000                     
##  Max.   :80.0000   Max.   :8.0000   Max.   :9.000                     
##  NA's   :264       NA's   :1        NA's   :1                         
##       fare            cabin             embarked             boat          
##  Min.   :  0.000   Length:1310        Length:1310        Length:1310       
##  1st Qu.:  7.896   Class :character   Class :character   Class :character  
##  Median : 14.454   Mode  :character   Mode  :character   Mode  :character  
##  Mean   : 33.295                                                           
##  3rd Qu.: 31.275                                                           
##  Max.   :512.329                                                           
##  NA's   :2                                                                 
##       body        home.dest        
##  Min.   :  1.0   Length:1310       
##  1st Qu.: 72.0   Class :character  
##  Median :155.0   Mode  :character  
##  Mean   :160.8                     
##  3rd Qu.:256.0                     
##  Max.   :328.0                     
##  NA's   :1189

Filtrar base de datos

Titanic<-base_de_datos[,c("pclass", "age" ,"sex","survived")]

Titanic$survived<-as.factor(ifelse(Titanic$survived==0,"Murio","Sobrevivio"))
Titanic$pclass<-as.factor(Titanic$sex)
Titanic$sex<-as.factor(Titanic$sex)
str (Titanic)

## 'data.frame':    1310 obs. of  4 variables:
##  $ pclass  : Factor w/ 3 levels "","female","male": 2 3 2 3 2 3 2 3 2 3 ...
##  $ age     : num  29 0.917 2 30 25 ...
##  $ sex     : Factor w/ 3 levels "","female","male": 2 3 2 3 2 3 2 3 2 3 ...
##  $ survived: Factor w/ 2 levels "Murio","Sobrevivio": 2 2 1 1 1 2 2 1 2 1 ...

sum (is.na(Titanic))

## [1] 265

Titanic<-na.omit(Titanic)

Crear arbol de decision

library (rpart)
arbol <-rpart(formula=survived ~., data = Titanic)
arbol

## n= 1046 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
## 1) root 1046 427 Murio (0.5917782 0.4082218)  
##   2) pclass=male 658 135 Murio (0.7948328 0.2051672)  
##     4) age>=9.5 615 110 Murio (0.8211382 0.1788618) *
##     5) age< 9.5 43  18 Sobrevivio (0.4186047 0.5813953) *
##   3) pclass=female 388  96 Sobrevivio (0.2474227 0.7525773) *

#install.packages("rpart.plot")
#install.packages ("rpart.plot")
library(rpart.plot)

rpart.plot(arbol)

prp(arbol,extra=7,prefix="fraccion\n")

##Conclusiones En este ejercicio se puede obersvar como se utilizaron datos correspondienntes a los sobrevivientes del titanic, de esta manera se pudo crear un arbol de decisiones para visualizacion de que segmentos de personas sobrevivieron.