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！！
