如何调整饼图上的 ggrepel 标签?
How to adjust ggrepel label on pie chart?
我正在尝试创建一个饼图来可视化 9 个属的丰度百分比。然而,标签都聚集在一起。我该如何补救?代码如下:
generaabundance2020 <- c(883, 464, 1948, 1177, 2607, 962, 2073, 620, 2670)
genera2020 <- c("Andrena", "Ceratina", "Halictus",
"Hesperapis", "Lasioglossum", "Melissodes",
"Osmia", "Panurginus", "Other")
generabreakdown2020 <- data.frame(group = genera2020, value = generaabundance2020)
gb2020label <- generabreakdown2020 %>%
group_by(value) %>% # Variable to be transformed
count() %>%
ungroup() %>%
mutate(perc = `value` / sum(`value`)) %>%
arrange(perc) %>%
mutate(labels = scales::percent(perc))
generabreakdown2020 %>%
ggplot(aes(x = "", y = value, fill = group)) +
geom_col() +
coord_polar("y", start = 0) +
theme_void() +
geom_label_repel(aes(label = gb2020label$labels), position = position_fill(vjust = 0.5),
size = 5, show.legend = F, max.overlaps = 50) +
guides(fill = guide_legend(title = "Genera")) +
scale_fill_manual(values = c("brown1", "chocolate1",
"darkgoldenrod1", "darkgreen",
"deepskyblue", "darkslateblue",
"darkorchid4", "hotpink1",
"lightpink"))
产生以下内容:
您没有向我们提供您的工作数据,所以我在这里使用 ggplot2::mpg
。
library(tidyverse)
library(ggrepel)
mpg_2 <-
mpg %>%
slice_sample(n = 20) %>%
count(manufacturer) %>%
mutate(perc = n / sum(n)) %>%
mutate(labels = scales::percent(perc)) %>%
arrange(desc(manufacturer)) %>%
mutate(text_y = cumsum(n) - n/2)
没有极坐标的图表
mpg_2 %>%
ggplot(aes(x = "", y = n, fill = manufacturer)) +
geom_col() +
geom_label(aes(label = labels, y = text_y))
带有极坐标和 geom_label_repel
的图表
mpg_2 %>%
ggplot(aes(x = "", y = n, fill = manufacturer)) +
geom_col() +
geom_label_repel(aes(label = labels, y = text_y),
force = 0.5,nudge_x = 0.6, nudge_y = 0.6) +
coord_polar(theta = "y")
但也许您的数据不够密集,需要排斥?
mpg_2 %>%
ggplot(aes(x = "", y = n, fill = manufacturer)) +
geom_col() +
geom_label(aes(label = labels, y = text_y), nudge_x = 0.6) +
coord_polar(theta = "y")
由 reprex package (v2.0.1)
于 2021-10-26 创建
感谢您添加数据。
您的代码中存在一些错误。最主要的是您没有预先计算放置标签的位置(在 text_y
变量中完成)。该变量需要作为 geom_label_repel
.
的 y 美学传递
第二个是你不再需要
group_by(value) %>% count() %>% ungroup()
因为您提供的数据已经汇总。
library(tidyverse)
library(ggrepel)
generaabundance2020 <- c(883, 464, 1948, 1177, 2607, 962, 2073, 620, 2670)
genera2020 <- c("Andrena", "Ceratina", "Halictus", "Hesperapis", "Lasioglossum", "Melissodes", "Osmia", "Panurginus", "Other")
generabreakdown2020 <- data.frame(group = genera2020, value = generaabundance2020)
gb2020label <-
generabreakdown2020 %>%
mutate(perc = value/ sum(value)) %>%
mutate(labels = scales::percent(perc)) %>%
arrange(desc(group)) %>% ## arrange in the order of the legend
mutate(text_y = cumsum(value) - value/2) ### calculate where to place the text labels
gb2020label %>%
ggplot(aes(x = "", y = value, fill = group)) +
geom_col() +
coord_polar(theta = "y") +
geom_label_repel(aes(label = labels, y = text_y),
nudge_x = 0.6, nudge_y = 0.6,
size = 5, show.legend = F) +
guides(fill = guide_legend(title = "Genera")) +
scale_fill_manual(values = c("brown1", "chocolate1",
"darkgoldenrod1", "darkgreen",
"deepskyblue", "darkslateblue",
"darkorchid4", "hotpink1",
"lightpink"))
如果要按频率降序排列,请记住将组变量的因子水平也设置为相同的顺序。
gb2020label <-
generabreakdown2020 %>%
mutate(perc = value/ sum(value)) %>%
mutate(labels = scales::percent(perc)) %>%
arrange(desc(perc)) %>% ## arrange in descending order of frequency
mutate(group = fct_rev(fct_inorder(group))) %>% ## also arrange the groups in descending order of freq
mutate(text_y = cumsum(value) - value/2) ### calculate where to place the text labels
gb2020label %>%
ggplot(aes(x = "", y = value, fill = group)) +
geom_col() +
coord_polar(theta = "y") +
geom_label_repel(aes(label = labels, y = text_y),
nudge_x = 0.6, nudge_y = 0.6,
size = 5, show.legend = F) +
guides(fill = guide_legend(title = "Genera")) +
scale_fill_manual(values = c("brown1", "chocolate1",
"darkgoldenrod1", "darkgreen",
"deepskyblue", "darkslateblue",
"darkorchid4", "hotpink1",
"lightpink"))
由 reprex package (v2.0.1)
于 2021-10-27 创建
我正在尝试创建一个饼图来可视化 9 个属的丰度百分比。然而,标签都聚集在一起。我该如何补救?代码如下:
generaabundance2020 <- c(883, 464, 1948, 1177, 2607, 962, 2073, 620, 2670)
genera2020 <- c("Andrena", "Ceratina", "Halictus",
"Hesperapis", "Lasioglossum", "Melissodes",
"Osmia", "Panurginus", "Other")
generabreakdown2020 <- data.frame(group = genera2020, value = generaabundance2020)
gb2020label <- generabreakdown2020 %>%
group_by(value) %>% # Variable to be transformed
count() %>%
ungroup() %>%
mutate(perc = `value` / sum(`value`)) %>%
arrange(perc) %>%
mutate(labels = scales::percent(perc))
generabreakdown2020 %>%
ggplot(aes(x = "", y = value, fill = group)) +
geom_col() +
coord_polar("y", start = 0) +
theme_void() +
geom_label_repel(aes(label = gb2020label$labels), position = position_fill(vjust = 0.5),
size = 5, show.legend = F, max.overlaps = 50) +
guides(fill = guide_legend(title = "Genera")) +
scale_fill_manual(values = c("brown1", "chocolate1",
"darkgoldenrod1", "darkgreen",
"deepskyblue", "darkslateblue",
"darkorchid4", "hotpink1",
"lightpink"))
产生以下内容:
您没有向我们提供您的工作数据,所以我在这里使用 ggplot2::mpg
。
library(tidyverse)
library(ggrepel)
mpg_2 <-
mpg %>%
slice_sample(n = 20) %>%
count(manufacturer) %>%
mutate(perc = n / sum(n)) %>%
mutate(labels = scales::percent(perc)) %>%
arrange(desc(manufacturer)) %>%
mutate(text_y = cumsum(n) - n/2)
没有极坐标的图表
mpg_2 %>%
ggplot(aes(x = "", y = n, fill = manufacturer)) +
geom_col() +
geom_label(aes(label = labels, y = text_y))
带有极坐标和 geom_label_repel
的图表
mpg_2 %>%
ggplot(aes(x = "", y = n, fill = manufacturer)) +
geom_col() +
geom_label_repel(aes(label = labels, y = text_y),
force = 0.5,nudge_x = 0.6, nudge_y = 0.6) +
coord_polar(theta = "y")
但也许您的数据不够密集,需要排斥?
mpg_2 %>%
ggplot(aes(x = "", y = n, fill = manufacturer)) +
geom_col() +
geom_label(aes(label = labels, y = text_y), nudge_x = 0.6) +
coord_polar(theta = "y")
由 reprex package (v2.0.1)
于 2021-10-26 创建感谢您添加数据。
您的代码中存在一些错误。最主要的是您没有预先计算放置标签的位置(在 text_y
变量中完成)。该变量需要作为 geom_label_repel
.
第二个是你不再需要
group_by(value) %>% count() %>% ungroup()
因为您提供的数据已经汇总。
library(tidyverse)
library(ggrepel)
generaabundance2020 <- c(883, 464, 1948, 1177, 2607, 962, 2073, 620, 2670)
genera2020 <- c("Andrena", "Ceratina", "Halictus", "Hesperapis", "Lasioglossum", "Melissodes", "Osmia", "Panurginus", "Other")
generabreakdown2020 <- data.frame(group = genera2020, value = generaabundance2020)
gb2020label <-
generabreakdown2020 %>%
mutate(perc = value/ sum(value)) %>%
mutate(labels = scales::percent(perc)) %>%
arrange(desc(group)) %>% ## arrange in the order of the legend
mutate(text_y = cumsum(value) - value/2) ### calculate where to place the text labels
gb2020label %>%
ggplot(aes(x = "", y = value, fill = group)) +
geom_col() +
coord_polar(theta = "y") +
geom_label_repel(aes(label = labels, y = text_y),
nudge_x = 0.6, nudge_y = 0.6,
size = 5, show.legend = F) +
guides(fill = guide_legend(title = "Genera")) +
scale_fill_manual(values = c("brown1", "chocolate1",
"darkgoldenrod1", "darkgreen",
"deepskyblue", "darkslateblue",
"darkorchid4", "hotpink1",
"lightpink"))
如果要按频率降序排列,请记住将组变量的因子水平也设置为相同的顺序。
gb2020label <-
generabreakdown2020 %>%
mutate(perc = value/ sum(value)) %>%
mutate(labels = scales::percent(perc)) %>%
arrange(desc(perc)) %>% ## arrange in descending order of frequency
mutate(group = fct_rev(fct_inorder(group))) %>% ## also arrange the groups in descending order of freq
mutate(text_y = cumsum(value) - value/2) ### calculate where to place the text labels
gb2020label %>%
ggplot(aes(x = "", y = value, fill = group)) +
geom_col() +
coord_polar(theta = "y") +
geom_label_repel(aes(label = labels, y = text_y),
nudge_x = 0.6, nudge_y = 0.6,
size = 5, show.legend = F) +
guides(fill = guide_legend(title = "Genera")) +
scale_fill_manual(values = c("brown1", "chocolate1",
"darkgoldenrod1", "darkgreen",
"deepskyblue", "darkslateblue",
"darkorchid4", "hotpink1",
"lightpink"))
由 reprex package (v2.0.1)
于 2021-10-27 创建