winter-olympics • apply303

Total Medals

total_medals |>
  plot_ly(x = ~Country, y = ~totals) %>%
  plotly::add_bars() |>
  layout(title = "Norway has more Winter Olympic Medals than All Other Countries<br> (1924 - 2014)")

Medals by Place

medal_counts |>
  mutate(Medal = forcats::fct_relevel(Medal,'bronze','silver','gold'),
                Country = reorder(Country, totals, sum)) |>
  plot_ly(x = ~Country, y = ~totals, color = ~Medal) %>%
  plotly::add_bars() |>
  layout(barmode = "stack",
         hovermode = "x") |>
  layout(title = "Norway Has the Most Gold, Silver, <br> and Bronze Winter Olympic Medals <br> (1924 - 2014)")

medal_counts2 |>
  mutate(Medal = forcats::fct_relevel(Medal,'bronze','silver','gold'),
                Country = reorder(Country, totals, sum)) |>
  plot_ly() %>%
  plotly::add_bars(x = ~Country, y = ~totals, color = ~Medal, colors = c("#CD7F32", "#C0C0C0", "#FFD700")) |>
  layout(hovermode = "x") |>
  layout(title = "Norway Has the Most Gold, Silver, <br> and Bronze Winter Olympic Medals <br> (1924 - 2014)") |> 
 layout(
         yaxis = list(title = "Total Medals"),
         xaxis = list(rangeslider = list(type = "date")),
         updatemenus = list(list(type = "buttons", direction = "right", x = 0.9, y = 0.98,
                                 buttons = list(
                                   list(method = "relayout", args = list("barmode", "group"), 
                                        label = "Dodge"),
                                   list(method = "relayout", args = list("barmode", "stack"),
                                        label = "Stack")
                                 ))))

Medals by Event

medals_per_event$Medal <- factor(medals_per_event$Medal,                 # Relevel group factor
                         levels = c("gold", "silver", "bronze"))

require(crosstalk)
shared_medals <- SharedData$new(medals_per_event)

bscols(widths = c(2,NA),
  list(
    filter_select("Sport", "Sport", shared_medals, ~Sport)
  ),
  ggplotly(shared_medals %>% 
  ggplot(aes(Country, totals)) +
  geom_point(aes(color = Medal, label = Sport))  +
  theme(axis.text.x = element_blank(), axis.ticks.x = element_blank()) +
  scale_color_manual(values=c("#FFD700", "#C0C0C0", "#CD7F32")) + 
  labs(x = "Country <br> (alphabetical)", y = "Medals Won", size = "", 
       title = "Medals per Country <br> Split by Event")))

Sport

Choropleth of Medals

medal_location2$hover <- with(medal_location2, paste(name, '<br>', 
                                                     "Gold:", gold, "<br>", 
                                                     "Silver:", silver, "<br>", 
                                                     "Bronze:", bronze))

plot_ly(medal_location2, 
        type='choropleth', 
        locations=medal_location2$iso_a3, 
        z=medal_location2$total, text=medal_location2$hover, colorscale="Blues",
        reversescale = TRUE) |> # make darker countries = more medals
  plotly::layout(title = "Winter Olympic Medals Won per Country <br> (1924 - 2014)") |>
  plotly::colorbar(title = "Total Medals")