Examine the data

str

str(CARROS)
## 'data.frame':    32 obs. of  11 variables:
##  $ Kmporlitro             : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ Cilindros              : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ Preco                  : num  160 160 108 258 360 ...
##  $ HP                     : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ Amperagem_circ_eletrico: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ Peso                   : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ RPM                    : num  16.5 17 18.6 19.4 17 ...
##  $ Tipodecombustivel      : Factor w/ 2 levels "Gasolina","Álcool": 1 1 2 2 1 2 1 2 2 2 ...
##  $ TipodeMarcha           : Factor w/ 2 levels "Automático","Manual": 2 2 2 1 1 1 1 1 1 1 ...
##  $ NumdeMarchas           : num  4 4 4 3 3 3 3 4 4 4 ...
##  $ NumdeValvulas          : num  4 4 1 1 2 1 4 2 2 4 ...
##  - attr(*, "variable.labels")= chr  "Km por litro" "Número de Cilindros" "Preço" "HP = Horse Power (potência do motor)" ...

describe

library(psych)
describe(CARROS)
##                         vars  n   mean     sd median trimmed    mad   min
## Kmporlitro                 1 32  20.09   6.03  19.20   19.70   5.41 10.40
## Cilindros                  2 32   6.19   1.79   6.00    6.23   2.97  4.00
## Preco                      3 32 230.72 123.94 196.30  222.52 140.48 71.10
## HP                         4 32 146.69  68.56 123.00  141.19  77.10 52.00
## Amperagem_circ_eletrico    5 32   3.60   0.53   3.70    3.58   0.70  2.76
## Peso                       6 32   3.22   0.98   3.33    3.15   0.77  1.51
## RPM                        7 32  17.85   1.79  17.71   17.83   1.42 14.50
## Tipodecombustivel*         8 32   1.44   0.50   1.00    1.42   0.00  1.00
## TipodeMarcha*              9 32   1.41   0.50   1.00    1.38   0.00  1.00
## NumdeMarchas              10 32   3.69   0.74   4.00    3.62   1.48  3.00
## NumdeValvulas             11 32   2.81   1.62   2.00    2.65   1.48  1.00
##                            max  range  skew kurtosis    se
## Kmporlitro               33.90  23.50  0.61    -0.37  1.07
## Cilindros                 8.00   4.00 -0.17    -1.76  0.32
## Preco                   472.00 400.90  0.38    -1.21 21.91
## HP                      335.00 283.00  0.73    -0.14 12.12
## Amperagem_circ_eletrico   4.93   2.17  0.27    -0.71  0.09
## Peso                      5.42   3.91  0.42    -0.02  0.17
## RPM                      22.90   8.40  0.37     0.34  0.32
## Tipodecombustivel*        2.00   1.00  0.24    -2.00  0.09
## TipodeMarcha*             2.00   1.00  0.36    -1.92  0.09
## NumdeMarchas              5.00   2.00  0.53    -1.07  0.13
## NumdeValvulas             8.00   7.00  1.05     1.26  0.29
library(dplyr)
## Warning: package 'dplyr' was built under R version 3.5.3
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
glimpse(CARROS)
## Observations: 32
## Variables: 11
## $ Kmporlitro              <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14...
## $ Cilindros               <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8,...
## $ Preco                   <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225...
## $ HP                      <dbl> 110, 110, 93, 110, 175, 105, 245, 62, ...
## $ Amperagem_circ_eletrico <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3....
## $ Peso                    <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.4...
## $ RPM                     <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20....
## $ Tipodecombustivel       <fct> Gasolina, Gasolina, Álcool, Álcool, Ga...
## $ TipodeMarcha            <fct> Manual, Manual, Manual, Automático, Au...
## $ NumdeMarchas            <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3,...
## $ NumdeValvulas           <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3,...

summary

summary(CARROS)
##    Kmporlitro      Cilindros         Preco             HP       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##  Amperagem_circ_eletrico      Peso            RPM        Tipodecombustivel
##  Min.   :2.760           Min.   :1.513   Min.   :14.50   Gasolina:18      
##  1st Qu.:3.080           1st Qu.:2.581   1st Qu.:16.89   Álcool  :14      
##  Median :3.695           Median :3.325   Median :17.71                    
##  Mean   :3.597           Mean   :3.217   Mean   :17.85                    
##  3rd Qu.:3.920           3rd Qu.:3.610   3rd Qu.:18.90                    
##  Max.   :4.930           Max.   :5.424   Max.   :22.90                    
##      TipodeMarcha  NumdeMarchas   NumdeValvulas  
##  Automático:19    Min.   :3.000   Min.   :1.000  
##  Manual    :13    1st Qu.:3.000   1st Qu.:2.000  
##                   Median :4.000   Median :2.000  
##                   Mean   :3.688   Mean   :2.812  
##                   3rd Qu.:4.000   3rd Qu.:4.000  
##                   Max.   :5.000   Max.   :8.000

data

library(dataMaid)
## 
## Attaching package: 'dataMaid'
## The following object is masked from 'package:dplyr':
## 
##     summarize
#Visualize a variable
#visualize(CARROS$am)

#Visualize a dataset
visualize(CARROS)