Status Quo
library(tidyverse)
library(legendry)
## Warning: package 'legendry' was built under R version 4.4.1
gapminder::gapminder %>%
filter(continent == "Europe") %>%
filter(year %in% c(1957, 2002)) %>%
ggplot() +
facet_wrap(~year) +
aes(y = country, weight = pop) +
geom_bar()
gapminder::gapminder %>%
filter(continent == "Europe") %>%
filter(year %in% c(1957, 2002)) %>%
ggplot() +
facet_wrap(~year) +
aes(y = country, weight = pop) +
geom_bar()
last_plot() +
aes(y = tidytext::reorder_within(country, pop, year))
last_plot() +
tidytext::scale_y_reordered()
last_plot() +
scale_y_discrete()
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
last_plot() +
aes(y = fct_reorder(country, pop))
last_plot() +
aes(y = interaction(year, country, sep = "___") |> fct_infreq(w = 1/pop))
last_plot() +
tidytext::scale_y_reordered()
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
last_plot() +
aes(y = interaction(year, country, sep = "___") |> fct_infreq(w = 1/pop)) +
scale_y_discrete(labels = function(x) str_remove(x, "^.+___"))
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
last_plot() +
aes(y = interaction(year, country) |> fct_infreq(w = 1/pop)) + scale_y_discrete()
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
last_plot() +
scale_y_discrete(labels = function(x) str_remove(x, ".+\\."))
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
last_plot() +
facet_wrap(~ year, scales = "free_y")
gapminder::gapminder %>%
filter(continent == "Oceania") %>%
filter(year %in% c(1957, 2002)) %>%
ggplot() +
facet_wrap(~ year) +
aes(y = country, weight = pop) +
geom_bar()
last_plot() +
aes(y = fct_infreq(interaction(year, country), w = pop))
last_plot() +
facet_wrap(~ year, scales = "free_y")
last_plot() +
scale_y_discrete(labels = function(x) str_remove(x, ".+\\."))
last_plot() +
aes(y = fct_infreq(interaction(year, country), w = 1/pop))
gapminder::gapminder %>%
filter(continent == "Americas") %>%
filter(year %in% c(1957, 2002)) %>%
ggplot() +
facet_wrap(~ year) +
aes(x = pop, y = interaction(year, country, sep = "___") |> fct_reorder(pop)) +
geom_col()
last_plot() +
facet_wrap(~ year, scales = "free_y")
last_plot() +
scale_y_discrete(labels = function(x) str_remove(x, ".+___")) + # don't show year part of factor
labs(y = NULL)
read.csv("https://raw.githubusercontent.com/EvaMaeRey/mytidytuesday/refs/heads/main/2024-11-19-gg-prefixes/exported_funs_exts_ggplot2_tidyverse_org.csv") |>
mutate(prefix_short = fun_exported |> str_extract(".+?_")) |>
filter(prefix_short %in% c("geom_", "scale_", "stat_", "theme_", "layer_", "coord_", "position_")) |>
group_by(user) |>
filter(n() >= 70) |>
filter(!is.na(prefix_short)) |>
ggplot() +
facet_wrap(~user, scales = "free_y") +
aes(y = interaction(user, prefix_short) |> fct_infreq()) +
geom_bar() +
scale_y_discrete(labels = function(x) str_remove(x, ".+\\.")) +
coord_trans(y = "reverse", ylim = c(1,6)) +
labs(y = NULL) +
theme_gray(paper = ggplot2:::col_mix("lavender", "white", .9),
ink = "grey10") +
theme(axis.ticks = element_blank())
compute_panel_rank <- function(data, scales, width = .7, n = 5){
data |>
mutate(x = rank(y)) |>
arrange(x) |>
slice(1:n)
}
ggplot(palmerpenguins::penguins) +
aes(y = bill_length_mm) +
geom_bar(stat = statexpress::qstat(compute_panel_rank))
compute_panel_rank <- function(data, scales, width = .7, n = 5){
data|>
mutate(xmax = x,
xmin = 0,
ymin = rank(-x, ties.method = "random") - width/2,
ymax = ymin + width,
label = ranked) |>
arrange(ymin) |>
dplyr::select(-x) |>
slice(1:n)
}
compute_panel_rank_label <- function(data, scales, width = .7, y_nudge = -.05, n = 5){
data|>
mutate(y = rank(-x, ties.method = "random") - width/2 + y_nudge,
x = 0,
label = ranked) |>
arrange(y) |>
slice(1:n)
}
compute_panel_rank_value_label <- function(data, scales, width = .7, n = 5){
data|>
mutate(y = rank(-x, ties.method = "random"),
x = x,
label = x) |>
arrange(y) |>
slice(1:n) |>
mutate(large = x > quantile(range(x), .5) ) |>
mutate(hjust = large)
}
library(statexpress)
contrast <- function(colour) {
out <- rep("grey20", length(colour))
light <- farver::get_channel(colour, "l", space = "hcl")
out[light < 50] <- "grey80"
out
}
# from https://github.com/teunbrand/ggplot_tricks
# aes_autocontrast <- aes(colour = after_scale(contrast(large)))
gapminder::gapminder |>
filter(year > 2000) |>
ggplot() +
aes(ranked = country, x = pop) +
geom_rect(stat = qstat_panel(compute_panel_rank)) + # geom_rbar
qlayer(stat = qstat_panel(compute_panel_rank_label),
geom = qproto_update(GeomText, aes(hjust = 0, vjust = 0,
fill = "transparent",
linewidth = 0,
color = from_theme(ink)))) + #geom_rbar_text
qlayer(geom = qproto_update(GeomLabel,
aes(fill = "transparent",
linewidth = 0)),
stat = qstat_panel(compute_panel_rank_value_label)) +
facet_wrap(~year) +
coord_trans(y = "reverse")
last_plot() +
ggchalkboard::theme_chalkboard(base_size = 13)
last_plot() +
ggchalkboard::theme_chalkboard(base_size = 13, base_theme = theme_gray) +
theme(axis.text = element_blank(),
axis.ticks = element_blank()) +
labs(title = "Top 5 populations among countries, 2002 & 2007",
x = NULL)
fct_rank <- function(x, by){
rank(-by) |> interaction(x, lex.order = T)
}
fct_rank_within <- function(x, by, within){
data.frame(x, by, within) |>
mutate(rank = fct_rank(x, by), .by = within) |>
mutate(ranked = interaction(within, rank)) |>
pull(ranked)
}
gapminder::gapminder |>
filter(continent == "Oceania") |>
filter(year > 2000) |>
select(country, pop, year) |>
mutate(ranked = fct_rank(country, pop))
## # A tibble: 4 × 4
## country pop year ranked
## <fct> <int> <int> <fct>
## 1 Australia 19546792 2002 2.Australia
## 2 Australia 20434176 2007 1.Australia
## 3 New Zealand 3908037 2002 4.New Zealand
## 4 New Zealand 4115771 2007 3.New Zealand
gapminder::gapminder |>
filter(continent == "Oceania") |>
filter(year > 2000) |>
select(country, pop, year) |>
mutate(ranked = fct_rank_within(country, pop, year))
## # A tibble: 4 × 4
## country pop year ranked
## <fct> <int> <int> <fct>
## 1 Australia 19546792 2002 2002.1.Australia
## 2 Australia 20434176 2007 2007.1.Australia
## 3 New Zealand 3908037 2002 2002.2.New Zealand
## 4 New Zealand 4115771 2007 2007.2.New Zealand
# fct_rank_within <- function(x, by, within){
#
# for(i in 1:len)
# rank(-by) |> interaction(x) |> fct_reorder(by) |> interaction(within)
#
# }
gapminder::gapminder |>
filter(continent == "Americas") |>
filter(year > 2000) |>
ggplot() +
aes(y = fct_rank(country, pop),
x = pop) +
geom_col() +
coord_trans(y = "reverse") # coord_page
last_plot() +
facet_wrap(~year, scales = "free_y")
last_plot() +
scale_y_discrete(labels = function(x) str_remove(x, "\\d+\\."))
gapminder::gapminder |>
filter(continent == "Americas") |>
filter(year > 2000) |>
ggplot() +
aes(y = fct_rank_within(country, pop, year),
x = pop) +
geom_col() +
coord_trans(y = "reverse") # coord_page
last_plot() +
facet_wrap(~year, scales = "free_y")
last_plot() +
scale_y_discrete(labels = function(x) str_remove(x, ".+\\."))
