In esppk/noaatk: Clean and Plot earthquake data

vis_data <- noaa %>% 
  select(EQ_MAG_MW, DEATHS, DATE, LOCATION_NAME_,
         COUNTRY, LONGITUDE, LATITUDE)

vis_data <- vis_data %>% na.omit()


countries <- vis_data$COUNTRY %>% unique()

countries <- vis_data %>% group_by(COUNTRY) %>% 
  summarise(n = n()) %>% arrange(desc(n)) %>% 
  filter(n >= 5) %>% select(COUNTRY) %>% 
  purrr::flatten_chr()


countries


vis_data <- vis_data %>% filter(COUNTRY %in% countries)
vis_data$DATE %>% range()

library(lubridate)
library(plotly)

gg <- vis_data %>% filter(COUNTRY %in% c("CHINA", "ITALY", "TURKEY", "JAPAN")) %>% 
  filter(DATE > ymd('1900-01-01')) %>% 
  ggplot(aes(x = DATE, y = COUNTRY)) +
  geom_segment(aes(x = min(DATE), y = COUNTRY, xend = max(DATE), yend = COUNTRY), alpha = 0.5, color = "tan") + 
  geom_point(aes(size = EQ_MAG_MW, alpha = DEATHS, text = paste('LOCATION:', LOCATION_NAME_)), color = "red") + 
  theme(axis.title.y = element_blank(), axis.ticks.y = element_blank()) +
  theme_minimal() + 
  scale_alpha()

ggplotly(gg)

eq_create_label <- function(dat){
  loc <- dat$LOCATION_NAME_
  mag <- dat$EQ_MAG_MW
  dea <- dat$DEATHS
  paste("<b>Location: </b>", loc,"<br>",
        "<b>Magnitude: </b>", mag,"<br>",
        "<b>Total deaths: </b>", dea)
}

vis_data <- vis_data %>% mutate(pop_text = eq_create_label(.))
vis_data

save(vis_data, file = "./shinyApp/vis_data.rda")
save(countries, file = "./shinyApp/countries.rda")

leaflet::leaflet() %>%
    leaflet::addTiles() %>%
    leaflet::addCircleMarkers(data = vis_data %>% filter(COUNTRY == "CHINA"), 
                              color = "red",
                              radius = ~ EQ_MAG_MW,
                     lng = ~ LONGITUDE, lat = ~ LATITUDE,
                     popup = ~ pop_text)