q1-4markdown

Q 1-4

VADeaths

head(VADeaths)

##       Rural Male Rural Female Urban Male Urban Female
## 50-54       11.7          8.7       15.4          8.4
## 55-59       18.1         11.7       24.3         13.6
## 60-64       26.9         20.3       37.0         19.3
## 65-69       41.0         30.9       54.6         35.1
## 70-74       66.0         54.3       71.1         50.0

cores_va <- c("green", "orange", "magenta", "pink", "blue")

barplot(
  VADeaths,
  beside = TRUE,
  col = cores_va,
  main = "Taxas de mortalidade na virgínia (1940)",
  xlab = "grupos populacionais",
  ylab = "Taxa de Mortalidade (por 1000  habitantes)",
  ylim = c(0, 80)
)

legend(
  "topleft",
  legend = rownames(VADeaths),
  fill = cores_va,
  title = "Faixa etaria",
  bty = "n"
)

ClassificaçãoDoença

pacientes <- c(
  "moderado", "leve", "leve", "severo", "leve",
  "moderado", "moderado", "moderado", "leve", "leve",
  "severo", "leve", "moderado", "moderado", "leve",
  "severo", "moderado", "moderado", "moderado", "leve"
)

pacientes <- factor(pacientes, levels = c("leve", "moderado", "severo"))

contagem <- table(pacientes)
porcentagens <- round(prop.table(contagem) * 100, 1)
rotulos_fatias <- paste0(porcentagens, "%")

cores_doenca <- c("cyan", "brown", "purple")

pie(
  contagem,
  labels = rotulos_fatias,
  col = cores_doenca,
  main = "Distribuição dos estagios da doenca (n = 20)"
)
legend(
  "topright",
  legend = c("Leve", "Moderado", "Severo"),
  fill = cores_doenca,
  title = "Estágio clínico"
)

USArrests

top5_crimes <- USArrests %>% mutate(City = rownames(.)) %>% arrange(desc(Murder)) %>% slice(1:5)

top5_longo <- top5_crimes %>%
  select(City, Murder, Assault, Rape) %>%
  pivot_longer(
    cols = c(Murder, Assault, Rape),
    names_to = "Crime",
    values_to = "Taxa"
  ) %>% mutate(City = factor(City, levels = top5_crimes[["City"]]))

plot_ly(
  data = top5_longo,
  x = ~City,
  y = ~Taxa,
  color = ~Crime,
  colors = c(Murder = "red", Assault = "blue", Rape = "black"),
  type = "bar"
) %>%
  layout(
    title = "5 estados mais violentos (por murder)",
    xaxis = list(title = "Estado (City)"),
    yaxis = list(title = "Prisões (por 100000 habitantes)"),
    barmode = "group",
    legend = list(title = list(text = "<b>Tipo de Crime</b>"))
  )

Orange

dados_orange <- Orange %>%
  mutate(Tree = factor(Tree, levels = c("1", "2", "3", "4", "5")))

plot_ly(
  data = dados_orange,
  x = ~age,
  y = ~circumference,
  color = ~Tree,
  colors = "Set1",
  type = "scatter",
  mode = "lines+markers",
  text = ~paste0("Arvore ", Tree, " — idade: ", age, " dias — circ.: ", circumference, " mm"),
  hoverinfo = "text"
) %>%
  layout(
    title = "Crescimento da circunferência das laranjeiras ao longo do tempo",
    xaxis = list(title = "Idade (dias)"),
    yaxis = list(title = "Circunferência (mm)"),
    legend = list(title = list(text = "<b>Árvore</b>"))
  )