INTRODUÇÃO
1º FASE-IMPORTAR DADOS
library(readxl)
BasesEstados <- read_excel("C:/Users/welington/Desktop/MESTRADO_2021/Base_de_dados-master/BasesEstados.xlsx",
sheet = "dados")
library(readr)
Fifa <- read_csv("C:/Users/welington/Desktop/MESTRADO_2021/Base_de_dados-master/FifaData.csv")
##
## -- Column specification --------------------------------------------------------
## cols(
## .default = col_double(),
## Name = col_character(),
## Nationality = col_character(),
## National_Position = col_character(),
## Club = col_character(),
## Club_Position = col_character(),
## Club_Joining = col_character(),
## Height = col_character(),
## Weight = col_character(),
## Preffered_Foot = col_character(),
## Birth_Date = col_character(),
## Preffered_Position = col_character(),
## Work_Rate = col_character()
## )
## i Use `spec()` for the full column specifications.
load("C:/Users/welington/Desktop/MESTRADO_2021/Base_de_dados-master/CARROS.RData")
2ª FASE-MANIPULAR O BANCO DE DADOS
summary(CARROS$Kmporlitro)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 10.40 15.43 19.20 20.09 22.80 33.90
summary(Fifa$Nationality)
## Length Class Mode
## 17588 character character
summary(BasesEstados$PIB)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 7.314e+06 2.945e+07 8.083e+07 1.627e+08 1.695e+08 1.409e+09
summary(CARROS$Tipodecombustivel)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.4375 1.0000 1.0000
summary(CARROS$TipodeMarcha)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.4062 1.0000 1.0000
summary(Fifa$Nationality)
## Length Class Mode
## 17588 character character
class(CARROS$Tipodecombustivel)
## [1] "numeric"
class(CARROS$TipodeMarcha)
## [1] "numeric"
class(Fifa$Nationality)
## [1] "character"
CARROS$Tipodecombustivel<-as.factor(CARROS$Tipodecombustivel)
CARROS$TipodeMarcha<-as.factor(CARROS$TipodeMarcha)
Fifa$Nationality<-as.factor(Fifa$Nationality)
CARROS$Tipodecombustivel_2 <- ifelse(CARROS$Tipodecombustivel=="0","Gas","Alc")
CARROS$TipodeMarcha_2 <- ifelse(CARROS$TipodeMarcha=="0","Auto","Manual")
CARROS$Tipodecombustivel_2<- as.factor(CARROS$Tipodecombustivel_2)
CARROS$TipodeMarcha_2<- as.factor(CARROS$TipodeMarcha_2)
summary(CARROS$TipodeMarcha_2)
## Auto Manual
## 19 13
tabela_combustivel<-table(CARROS$Tipodecombustivel_2)
tabela_combustivel
##
## Alc Gas
## 14 18
prop.table(tabela_combustivel)*100 #Abs
##
## Alc Gas
## 43.75 56.25
pie(tabela_combustivel)

vet1<-c(1,2,3,4,5)
vet1
## [1] 1 2 3 4 5
vet2<-c(T,T,T,F,F)
vet2
## [1] TRUE TRUE TRUE FALSE FALSE
vet3<-c("carlos","paulo","carla","paula")
vet3
## [1] "carlos" "paulo" "carla" "paula"
vet4<-c("red","yellow","blue","green")
pie(tabela_combustivel,col =c("red","blue"))

pie(tabela_combustivel,col =c("#60a397" , "#28249c"),main ="Meu Primeiro Gráfico no R!")

tabela_fifa<-table(Fifa$Nationality)
pie(tabela_fifa)

barplot(tabela_combustivel,col = c("#60a397","#28249c"),main ="Meu Primeiro Gráfico no R!",ylim = c(0,20))
