Himalayan Peak Expeditions

An interactive visual of expeditions to the four most popular peaks in a given year

library(tidyverse)
library(plotly)
library(leaflet)
expeditions <- read_csv("expeditions.csv")
peaks <- read_csv("himalayan_peaks.csv")

expeditions <- expeditions |>
  left_join(
    peaks |>
      select(PEAKID, PKNAME),
    by=join_by(PEAKID))

most_pop_yearly <- expeditions |>
  group_by(YEAR, PKNAME) |>
  count() |>
  ungroup() |>
  group_by(YEAR) |>
  slice_max(n, n=4) |>
  mutate(
    YEAR = as.factor(YEAR)
  ) |>
  rename(
    Expeditions = n
  )

most_pop_yearly$YEAR <- factor(most_pop_yearly$YEAR, levels = c("2024", "2023", "2022", "2021", "2020"))

plot <- most_pop_yearly |>
  ggplot(aes(x = Expeditions, 
             y = PKNAME, 
             fill = YEAR)) +
  geom_bar(stat = "identity") +
  labs(
    x = "Number of Expeditions",
    y = "Peak Name",
    title = "Yearly Expeditions to Himalayan Peaks",
    fill = "Year"
  ) +
  scale_fill_viridis_d(option = "C", end = 0.8) +
  theme_minimal()

ggplotly(plot, tooltip = "x")

leaflet() |> 
  addTiles() |>
  addPopups(lng = 84.5597,
             lat = 28.5497,
             popup = "Manaslu"
  ) |>
  addPopups(lng = 87.0876,
             lat = 27.8857,
             popup = "Makalu"
  ) |>
  addPopups(lng = 86.9336,
             lat = 27.9626,
             popup = "Lhotse"
  ) |>
  addPopups(lng = 84.416667,
             lat = 28.735,
             popup = "Himlung Himal"
  ) |>
  addPopups(lng = 86.9250,
             lat = 27.9881,
             popup = "Everest"
  ) |>
  addPopups(lng = 86.8612,
             lat = 27.8619,
             popup = "Ama Damblam"
  )