graficos

library(readxl)
global_shark_attack <- read_excel("C:/Users/Gabriela/Downloads/global-shark-attack.xlsx")
library(readxl)
CODIGO_PARA_MAPA <- read_excel("C:/Users/Gabriela/Downloads/CODIGO_PARA_MAPA.xlsx")

## New names:
## • `Country` -> `Country...2`
## • `` -> `...3`
## • `Country` -> `Country...4`

gráfico 1

library(rworldmap)

## Warning: package 'rworldmap' was built under R version 4.3.2

## Carregando pacotes exigidos: sp

## The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
## which was just loaded, were retired in October 2023.
## Please refer to R-spatial evolution reports for details, especially
## https://r-spatial.org/r/2023/05/15/evolution4.html.
## It may be desirable to make the sf package available;
## package maintainers should consider adding sf to Suggests:.

## ### Welcome to rworldmap ###

## For a short introduction type :   vignette('rworldmap')

tub <- joinCountryData2Map(CODIGO_PARA_MAPA
                             , joinCode = "ISO3"
                             , nameJoinColumn = "ISO3V10" )

## 149 codes from your data successfully matched countries in the map
## 0 codes from your data failed to match with a country code in the map
## 94 codes from the map weren't represented in your data

cor <- RColorBrewer::brewer.pal(5,'RdPu')

mapCountryData( tub, nameColumnToPlot="n",colourPalette =cor,
                mapTitle ="Ataque de Tubarão")

## You asked for 7 quantiles, only 3 could be created in quantiles classification

## Warning in rwmGetColours(colourPalette, numColours): 5 colours specified and 3
## required, using interpolation to calculate colours

tabela de lesões

library(forcats)

## Warning: package 'forcats' was built under R version 4.3.2

global_shark_attack$lesao = global_shark_attack$Injury %>%
  fct_lump_n(5)

table(global_shark_attack$lesao)

## 
##       FATAL Foot bitten  Leg bitten   No injury    Survived       Other 
##         862         100          82          89          97        5623

tabela de atividades

global_shark_attack$atividade = global_shark_attack$Activity %>%
  fct_lump_n(5)

table(global_shark_attack$atividade)

## 
##      Fishing Spearfishing      Surfing     Swimming       Wading        Other 
##          498          387         1112         1009          171         3127

#Gráfico 2

tabela = table(global_shark_attack$lesao,global_shark_attack$atividade)
barplot(tabela,beside = T,legend.text = rownames(tabela),args.legend = list(x = "topleft"),
        col=c("red","tomato3","tomato2","skyblue","blue","darkblue"))

tabela fatal ou não fatal

global_shark_attack$fatal = ifelse(global_shark_attack$`Fatal (Y/N)`=="y","Sim",
                            ifelse(global_shark_attack$`Fatal (Y/N)`=="Y","Sim",
                            ifelse(global_shark_attack$`Fatal (Y/N)`=="n","Não",
                            ifelse(global_shark_attack$`Fatal (Y/N)`=="N","Não",NA))))

table(global_shark_attack$fatal)

## 
##  Não  Sim 
## 4805 1448

Tabela sexo

global_shark_attack$Sexo= ifelse(global_shark_attack$Sex=="F","feminino",
                                 ifelse(global_shark_attack$Sex=="M","masculino",NA))

table(global_shark_attack$Sexo)

## 
##  feminino masculino 
##       768      5545

Gráfico 3

library(forcats)

global_shark_attack$especie = global_shark_attack$Species %>%
  fct_lump_n(5)


pie(table(global_shark_attack$especie))

chisq.test(global_shark_attack$atividade,global_shark_attack$lesao)

## Warning in chisq.test(global_shark_attack$atividade,
## global_shark_attack$lesao): Aproximação do qui-quadrado pode estar incorreta

## 
##  Pearson's Chi-squared test
## 
## data:  global_shark_attack$atividade and global_shark_attack$lesao
## X-squared = 270.77, df = 25, p-value < 2.2e-16