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tidytuesday_2020_39.R
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tidytuesday_2020_39.R
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library(tidyverse)
# Data
tuesdata <- tidytuesdayR::tt_load("2020-09-22")
climb_data <- tuesdata$expeditions %>%
left_join(tuesdata$peaks, by = "peak_name") %>%
select(peak = peak_name, year, height = height_metres) %>%
arrange(-height) %>%
mutate(height_group = fct_inorder(case_when(peak == "Everest" ~ "Mt. Everest (8850m)",
between(height, 8000, 8849) ~ "> 8000m",
between(height, 7000, 7999) ~ "7999m ~ 7000m",
between(height, 6000, 6999) ~ "6999m ~ 6000m",
TRUE ~ "< 6000m"))
) %>%
count(five_years = round(year/5) * 5, height_group) %>%
filter(five_years >= 1920) %>%
complete(five_years, height_group, fill = list(n = 0)) %>%
group_by(five_years) %>%
mutate(prop = n / sum(n)) %>%
ungroup()
# Plot
mountain_palette <- c("#6E86A6", "#95A2B3", "#5C606A", "#44464E", "#3D3737")
climb_plot <- climb_data %>%
ggplot(aes(five_years, prop)) +
geom_area(aes(fill = height_group, color = height_group)) +
scale_fill_manual(values = mountain_palette) +
scale_color_manual(values = mountain_palette) +
coord_cartesian(xlim = c(1920, 2020), expand = FALSE) +
scale_x_continuous(breaks = scales::pretty_breaks(11)) +
scale_y_continuous(labels = scales::percent) +
labs(
title = "Himalayan Peaks Attempted Over Time",
subtitle = "Over 1/4th of all expeditions were to Mount Everest",
x = NULL, y = NULL, fill = NULL, color = NULL,
caption = "By: @yjunechoe | Source: The Himalayan Database"
) +
theme_classic(base_family = "Futura Hv BT", base_size = 16) +
theme(
plot.title.position = "plot",
plot.title = element_text(size = 28, color = "white", family = "Lora", face = "bold"),
plot.subtitle = element_text(size = 14, color = "white", face = "italic"),
plot.margin = margin(2, 2.5, 2, 2, 'cm'),
plot.caption = element_text(color = "white", family = "Roboto Mono", hjust = 1.15, vjust = -13),
legend.position = "top",
legend.direction = "horizontal",
legend.text = element_text(color = "white"),
legend.background = element_rect(fill = NA),
axis.text = element_text(color = "white"),
axis.text.y = element_text(vjust = -.1),
axis.text.x = element_text(vjust = -2),
axis.ticks = element_blank(),
axis.line = element_blank(),
panel.background = element_blank(),
plot.background = element_rect(fill = "#606F84", color = NA)
)
# Save
pngfile <- fs::path(getwd(), "plot.png")
ragg::agg_png(
pngfile,
width = 60,
height = 36,
units = "cm",
res = 300,
scaling = 2
)
plot(climb_plot); invisible(dev.off())
tuesdata$expeditions %>%
left_join(tuesdata$peaks, by = "peak_name") %>%
select(peak = peak_name, year, height = height_metres) %>%
arrange(-height) %>%
mutate(height_group = fct_inorder(case_when(peak == "Everest" ~ "Mt. Everest (8850m)",
between(height, 8000, 8849) ~ "8000m and up",
between(height, 7000, 7999) ~ "7500m ~ 7999m",
between(height, 6000, 6999) ~ "8500m ~ 8849m",
TRUE ~ "Under 6000m"))
) %>%
count(decade = floor(year/10) * 10, height_group) %>%
filter(decade >= 1920) %>%
group_by(decade) %>%
mutate(prop = n / sum(n)) %>%
ungroup() %>%
complete(decade, height_group, fill = list(prop = 0)) %>%
ggplot(aes(decade, prop)) +
geom_area(aes(fill = height_group, color = height_group)) +
scale_fill_manual(values = mountain_palette) +
scale_color_manual(values = mountain_palette)
## Replace PLOT_NAME and PLOT_OBJECT
pngfile <- fs::path(
getwd(), #knitr::fig_path(),
"plot.png"
)
ragg::agg_png(
pngfile,
width = 60,
height = 36,
units = "cm",
res = 300,
scaling = 2
)
plot(p) ; invisible(dev.off())
magick::image_read(pngfile) #knitr::include_graphics(pngfile)
df %>%
ggplot(aes(year, cut))
first_successes <- tuesdata$expeditions %>%
filter(str_detect(termination_reason, "Success")) %>%
group_by(peak_name) %>%
slice_min(highpoint_date, n = 1)
tuesdata$expeditions %>%
filter(str_detect(termination_reason, "Success")) %>%
group_by(peak_name) %>%
slice_min(highpoint_date - basecamp_date, n = 1) %>%
ggplot(aes(highpoint_date, highpoint_date - basecamp_date)) +
geom_point()
tuesdata$expeditions %>%
group_by(peak_name, heighpoint_metres) %>%
filter(n() > 1) %>%
summarize(accidents = sum(!str_detect(termination_reason, "Accident"))) %>%
arrange(-accidents)
tuesdata$expeditions %>%
filter(peak_name == "Everest") %>%
mutate(highpoint_group = cut(highpoint_metres, breaks = 5)) %>%
ggplot(aes(highpoint_date, group = highpoint_group)) +
geom_freqpoly(bins = 20)
tuesdata$expeditions %>%
filter(peak_name == "Everest") %>%
ggplot(aes(highpoint_date, highpoint_metres)) +
geom_area()
peaks_clean <- tuesdata$peaks %>%
filter(first_ascent_year > 1000, climbing_status == "Climbed") %>%
filter(!str_detect(first_ascent_country, ",|Inida|W Germany")) %>%
rename(year = contains("year"),
country = contains("country"),
height = contains("height"))
peaks_clean %>%
group_by(country) %>%
arrange(height) %>%
slice(1) %>%
ggplot(aes(year, height)) +
geom_point(size = 2)
## Replace PLOT_NAME and PLOT_OBJECT
pngfile <- fs::path(
getwd(), #knitr::fig_path(),
"plot.png"
)
ragg::agg_png(
pngfile,
width = 80,
height = 100,
units = "cm",
res = 300,
scaling = 3
)
plot(p) ; invisible(dev.off())
magick::image_read(pngfile) #knitr::include_graphics(pngfile)