Análisis exploratorio de Toyota Corolla

El presente análisis considera como insumo la data obtenida de Toyota en el siguiente link:https://www.kaggle.com/code/janakitruno/mlr-toyota-corolla-dataset

##      Price            Age              KM           FuelType        
##  Min.   : 4350   Min.   : 1.00   Min.   :     1   Length:1436       
##  1st Qu.: 8450   1st Qu.:44.00   1st Qu.: 43000   Class :character  
##  Median : 9900   Median :61.00   Median : 63390   Mode  :character  
##  Mean   :10731   Mean   :55.95   Mean   : 68533                     
##  3rd Qu.:11950   3rd Qu.:70.00   3rd Qu.: 87021                     
##  Max.   :32500   Max.   :80.00   Max.   :243000                     
##        HP           MetColor        Automatic             CC      
##  Min.   : 69.0   Min.   :0.0000   Min.   :0.00000   Min.   :1300  
##  1st Qu.: 90.0   1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:1400  
##  Median :110.0   Median :1.0000   Median :0.00000   Median :1600  
##  Mean   :101.5   Mean   :0.6748   Mean   :0.05571   Mean   :1567  
##  3rd Qu.:110.0   3rd Qu.:1.0000   3rd Qu.:0.00000   3rd Qu.:1600  
##  Max.   :192.0   Max.   :1.0000   Max.   :1.00000   Max.   :2000  
##      Doors           Weight    
##  Min.   :2.000   Min.   :1000  
##  1st Qu.:3.000   1st Qu.:1040  
##  Median :4.000   Median :1070  
##  Mean   :4.033   Mean   :1072  
##  3rd Qu.:5.000   3rd Qu.:1085  
##  Max.   :5.000   Max.   :1615

Análisis visual

You can also embed plots, for example:

BDN <- NULL
BDC <- NULL
column <- dim(Data)[2]
par(mfrow = c(2,column/2))

for (i in 1:column)
    {x <- Data[ ,i]
      if (is.numeric(x)==TRUE)
      {hist(x,
            main = paste("Histograma de", names(Data)[i]))
        BDN <- c(BDN,i)
      } else
      {
        pie (table(x),
             main = paste("Pie de", names(Data)[i]))
        BDC <- c(BDC,i)
      }
    }

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.