平时我们做柱状图或饼图都会用彩色进行填充，但是文章有时候为了节约成本采用黑白印刷时候，图形一般都会做成各种阴影线条填充模式来进行区分(如下图)，R中的ggpattern包刚好可以满足了我们的需求，若有需要就来学习下吧~该包也给出了详细的文档适合初学者跟着学习，地址：https://coolbutuseless.github.io/package/ggpattern/index.html
特点总结：
- 几乎满足所有来自ggplot2拥有填充特性的geoms (如bar、boxplot等)
- 一套控制图案外观的aesthetics
- 包含了用户定义模式的能力
安装
# install.packages("remotes")
remotes::install_github("coolbutuseless/ggpattern")
library(ggpattern)
这里就演示常见的7\8 种图形，详细内容自行阅读源文档~~
绘图
1. geom_col_pattern
df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))
ggplot(df) +
geom_col_pattern(
aes(level, outcome, pattern_fill = level),
pattern = 'stripe',
fill = 'white',## 填充色
colour = 'black'## 边框
) +
theme_bw(18) +
theme(legend.position = 'none') +
labs(
title = "ggpattern::geom_pattern_col()",
subtitle = "pattern = 'stripe'"
) +
coord_fixed(ratio = 1/2)
主要函数为geom_col_pattern,pattern提供形状，fill填充色，colour边框颜色
不同分组映射不同形状
p <- ggplot(df, aes(level, outcome)) +
geom_col_pattern(
aes(pattern = level, fill = level, pattern_fill = level),
colour = 'black',
pattern_density = 0.35,
pattern_key_scale_factor = 1.3) +
theme_bw() +
labs(
title = "ggpattern::geom_col_pattern()",
subtitle = 'geometry-based patterns'
) +
scale_pattern_fill_manual(values = c(a='blue', b='red', c='yellow', d='darkgreen')) +
theme(legend.position = 'none') +
coord_fixed(ratio = 1)
p
这里我们多加了个参数pattern_density = 0.35, 作用改变图案密度即改变元素向邻近元素延伸的距离。它是一个分数，通常要求取值范围为[0,1]。
自定义颜色
利用scale_pattern_fill_manual函数
p <- ggplot(df, aes(level, outcome)) +
geom_col_pattern(
aes(pattern = level, fill = level, pattern_fill = level),
colour = 'black',
pattern_density = 0.35,
pattern_key_scale_factor = 1.3) +
theme_bw() +
labs(
title = "ggpattern::geom_col_pattern()",
subtitle = 'geometry-based patterns'
) +
scale_pattern_fill_manual(values = c(a='blue', b='red', c='yellow', d='darkgreen')) +
theme(legend.position = 'none') +
coord_fixed(ratio = 1)
p
2. geom_bar_pattern()
p <- ggplot(mpg, aes(class)) +
geom_bar_pattern(
aes(
pattern = class,
pattern_angle = class
),
fill = 'white',
colour = 'black',
pattern_spacing = 0.025
) +
theme_bw(18) +
labs(title = "ggpattern::geom_bar_pattern()") +
theme(legend.position = 'none') +
coord_fixed(ratio = 1/15) +
scale_pattern_discrete(guide = guide_legend(nrow = 1))
p
其中参数
pattern_spacing 代表元素之间的距离
pattern_angle代表元素旋转角度
利用geom_bar_pattern()绘制饼图
df <- data.frame(
group = factor(c("Cool", "But", "Use", "Less"), levels = c("Cool", "But", "Use", "Less")),
value = c(10, 20, 30, 40)
)
p <- ggplot(df, aes(x="", y = value, pattern = group, pattern_angle = group))+
geom_bar_pattern(
width = 1,
stat = "identity",
fill = 'white',
colour = 'black',
pattern_aspect_ratio = 1,
pattern_density = 0.3
) +
coord_polar("y", start=0) +
theme_void(20) +
theme(
legend.key.size = unit(2, 'cm')
) +
labs(title = "ggpattern::geom_bar_pattern() + coord_polar()")
p
饼图
3.geom_bin2d_pattern()
p <- ggplot(diamonds, aes(x, y)) +
xlim(4, 10) + ylim(4, 10) +
geom_bin2d_pattern(aes(pattern_spacing = ..density..), fill = 'white', bins = 6, colour = 'black', size = 1) +
theme_bw(18) +
theme(legend.position = 'none') +
labs(title = "ggpattern::geom_bin2d_pattern()")
p
#> Warning: Removed 478 rows containing non-finite values (stat_bin2d).
二维封箱热图
4. geom_boxplot_pattern() 箱线图
p <- ggplot(mpg, aes(class, hwy)) +
geom_boxplot_pattern(
aes(
pattern = class,
pattern_fill = class
),
pattern_spacing = 0.03
) +
theme_bw(18) +
labs(title = "ggpattern::geom_boxplot_pattern()") +
theme(legend.position = 'none') +
coord_fixed(1/8)
p
5. geom_crossbar_pattern()
df <- data.frame(
trt = factor(c(1, 1, 2, 2)),
resp = c(1, 5, 3, 4),
group = factor(c(1, 2, 1, 2)),
upper = c(1.1, 5.3, 3.3, 4.2),
lower = c(0.8, 4.6, 2.4, 3.6)
)
p <- ggplot(df, aes(trt, resp, colour = group)) +
geom_crossbar_pattern(
aes(
ymin = lower,
ymax = upper,
pattern_angle = trt,
pattern = group
), width = 0.2,
pattern_spacing = 0.02
) +
theme_bw(18) +
labs(title = "ggpattern::geom_crossbar_pattern()") +
theme(legend.position = 'none') +
coord_fixed(ratio = 1/3)
p
crossbar
6. geom_density_pattern()
p <- ggplot(mtcars) +
geom_density_pattern(
aes(
x = mpg,
pattern_fill = as.factor(cyl),
pattern = as.factor(cyl)
),
fill = 'white',
pattern_key_scale_factor = 1.2,
pattern_density = 0.4
) +
theme_bw(18) +
labs(title = "ggpattern::geom_density_pattern()") +
theme(legend.key.size = unit(2, 'cm')) +
coord_fixed(ratio = 100)
p
密度图
7. geom_map_pattern()
library(maps)
crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests)
crimesm <- reshape2::melt(crimes, id = 1)
states_map <- map_data("state")
p <- ggplot(crimes, aes(map_id = state)) +
geom_map_pattern(
aes(
# fill = Murder,
pattern_fill = Murder,
pattern_spacing = state,
pattern_density = state,
pattern_angle = state,
pattern = state
),
fill = 'white',
colour = 'black',
pattern_aspect_ratio = 1.8,
map = states_map
) +
expand_limits(x = states_map$long, y = states_map$lat) +
coord_map() +
theme_bw(18) +
labs(title = "ggpattern::geom_map_pattern()") +
scale_pattern_density_discrete(range = c(0.01, 0.3)) +
scale_pattern_spacing_discrete(range = c(0.01, 0.03)) +
theme(legend.position = 'none')
p
map
8. geom_violin_pattern()
p <- ggplot(mtcars, aes(as.factor(cyl), mpg)) +
geom_violin_pattern(aes(pattern = as.factor(cyl))) +
theme_bw(18) +
labs(title = "ggpattern::geom_violin_pattern()") +
theme(
legend.key.size = unit(2, 'cm')
) +
coord_fixed(1/15)
p
Violin
其它好玩的
-
结合gganimate包绘制动态的条形图
- 以图片形式填充你的图形，这里利用
pattern= 'placeholder'模式，类型pattern_type选择kitten, 填充个几个噬元兽试试
p <- ggplot(mpg, aes(class)) +
geom_bar_pattern(
aes(
pattern_angle = class
),
pattern = 'placeholder',
pattern_type = 'kitten',
fill = 'white',
colour = 'black',
pattern_spacing = 0.025
) +
theme_bw(18) +
labs(
title = "ggpattern::geom_bar_pattern()",
subtitle = "pattern = 'placeholder', pattern_type = 'kitten'"
) +
theme(legend.position = 'none') +
coord_fixed(ratio = 1/15) +
scale_pattern_discrete(guide = guide_legend(nrow = 1))
p
改变pattern_type=murray
哈哈，更多好玩的图形自己摸索吧，当然也支持自定义图片呦： 提供图片给一个向量后， 结合pattern = 'image' 模式和scale_pattern_filename_discrete()函数轻松绘制，很是easy！！
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