本节我们通过tidytuesday 2021年第24周的数据集来可视化密西根州五大湖的鲑鱼产量
library(tidyverse)
library(ggfx)
library(ggtext)
library(packcircles)
library(systemfonts)
library(patchwork)
fishing <- read_csv("fishing.csv")
fishing %>%
count(lake, sort = T)
fishing %>%
filter(lake == "Michigan") %>%
count(species, sort = T)
fishing %>%
count(species, sort = T)
fishing %>%
select(lake, species, year, values) %>%
mutate(
species = fct_lump(species, n = 2)
) %>%
filter(lake == "Michigan", species != "Other") %>%
group_by(lake, species, year) %>%
summarise(values = sum(values, na.rm = TRUE)) %>%
ggplot(aes(year, values)) +
geom_line() +
facet_wrap(~species)
king_salmon <-
fishing %>%
filter(species == "Chinook Salmon", region == "MI State Total") %>%
count(year, wt = values) %>%
mutate(
fill = if_else(n <= lead(n), "#457b9d", "#a8dadc"),
year_next = lead(year),
nmax = max(n)
)
p_main <- ggplot(king_salmon, aes(year, n)) +
as_reference(
geom_ribbon(aes(xmin = year, xmax =year, ymin = 0, ymax = n)),
id = "bg"
) +
with_blend(
geom_rect(aes(xmin = year, xmax = year_next, ymin = 0,
ymax = nmax,fill = fill), alpha = 0.8),
bg_layer = "bg",
blend_type = "in"
) +
geom_line(color = "#1d3557") +
geom_richtext(aes(x = 2005, y = 47,
label = "The <span style='color: #457b9d'>RISE</span> and <span style='color: #a8dadc'>FALL</span> of King Salmon Prodcution<br>in the Great Lakes"),
family = "Limelight", size = 7, label.color = NA, fill = NA, lineheight = 1.2) +
scale_y_continuous(limits = c(0, NA)) +
scale_fill_identity() +
labs(x = "", y = "Production Amounts (in '000 pounds)")+
coord_cartesian(expand = c(0,0), clip = "off") +
theme_minimal(base_family = "Inter", base_size = 16) +
theme(
plot.margin = margin(10, 25, 10, 15),
plot.caption.position = "plot",
plot.caption = element_markdown(size = 14, hjust = 0.5),
panel.grid.minor = element_blank(),
axis.line = element_line(size = 0.5),
axis.title.y.left = element_text(size = 11, face = "bold",
margin = margin(r = 10), color = "grey40")
)
set.seed(100)
p_inset <-
king_salmon %>%
filter(year %in% c(1992, 1995, 1998, 2012)) %>%
rowwise() %>%
mutate(
fish_total = list(circleProgressiveLayout(rep(1, nmax))),
fish_present = list(
c(rep("#1d3557", n), rep("grey85", nmax - n)) %>% sample()
)
) %>%
unnest(cols = c("fish_total", "fish_present")) %>%
ggplot(aes(x, y)) +
geom_text(aes(label = "\uf578", color = fish_present), size = 4, family = "Font Awesome") +
scale_color_identity() +
facet_wrap(~year) +
theme_void() +
theme(
plot.margin = margin(15, 15, 15, 15),
strip.text = element_text(family = "Limelight", size = 12, margin = margin(b = 10)),
panel.spacing = unit(1, "lines")
)
p_final <- p_main + inset_element(p_inset, 0.4, 0.1, 0.9, 0.75)
p_final
喜欢的小伙伴欢迎关注我的公众号
R语言数据分析指南,持续分享数据可视化的经典案例及一些生信知识,希望对大家有所帮助
网友评论