# Analise de dados no R
# 1 Covid-19 Analytics ------------------------------------------

# Pacote:
# install.packages("covid19.analytics")
library(covid19.analytics)
library (RCurl)

library(ggplot2)

# obtencao de dados
obitos <- covid19.data("ts-deaths")
confirmados <- covid19.data("ts-confirmed")

# casos confirmados, tendencia
single.trend(confirmados[ confirmados$Country.Region=="Brazil",])
single.trend(confirmados[ confirmados$Country.Region=="US",])

# casos obitos, tendencia
single.trend(obitos[ obitos$Country.Region=="Brazil",])
single.trend(obitos[ obitos$Country.Region=="US",])

mtrends(obitos, geo.loc = c("US","Brazil"), confBnd = TRUE, info = "")


# Mapeamento
live.map(
  data = covid19.data(),
  select.projctn = TRUE,
  projctn = "orthographic",
  title = "",
  no.legend = FALSE,
  szRef = 0.2,
  fileName = NULL
)

# Total plot
totals.plt(
  data0 = NULL,
  geo.loc0 = NULL,
  one.plt.per.page = FALSE,
  log.plt = TRUE,
  with.totals = FALSE,
  interactive.fig = TRUE,
  fileName = NULL
)

totals.plt(
  data0 = NULL,
  geo.loc0 = "Brazil",
  one.plt.per.page = FALSE,
  log.plt = TRUE,
  with.totals = FALSE,
  interactive.fig = TRUE,
  fileName = NULL
)

# Modelo SIR
generate.SIR.model(data = confirmados,geo.loc = "Brazil",
                   t0 = NULL,t1 = NULL,deltaT = NULL,tfinal = 90,
                   fatality.rate = 0.02,tot.population = 1.4e+09,
                   staticPlt = TRUE,interactiveFig = TRUE)

# 2 Bases de dados no Kaggle ------------------------------------

# 2.1 New York City Airbnb Open Data
#     Airbnb listings and metrics in NYC, NY, USA (2019)
#     https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data

d.airbnb <- read.csv("../000_Dados/Airbnb_NYC_2019/AB_NYC_2019.csv")
#write.csv2(file = "AB_NYC_2019.csv",d.airbnb)

t.grupo <- table(d.airbnb$neighbourhood_group)
t.grupo
sort(t.grupo,decreasing = TRUE)

t.price <- tapply(d.airbnb$price,d.airbnb$neighbourhood_group, FUN = mean)
t.price
sort(t.price)

### Gráficos
fill <- "#4271AE"
lines <- "#1F3552"

ggplot(d.airbnb, aes(x = neighbourhood_group, y = price)) +
  geom_boxplot(colour = lines, fill = fill,size = 1) +
  scale_y_continuous(name = "Preço",
                     breaks = seq(0, 200, 50),limits=c(0, 200)) +
  scale_x_discrete(name = "Bairros") +
  ggtitle("Boxplot do preço") +
  theme_bw() +
  theme(panel.grid.major = element_line(colour = "#d3d3d3"),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.title = element_text(face="bold"),
        axis.text.x = element_text(colour="black", size = 11),
        axis.text.y = element_text(colour="black", size = 9),
        axis.line = element_line(size=0.5, colour = "black"))