如何在 ggplot 的条形图中添加影线、条纹或其他图案或纹理? [英] How can I add hatches, stripes or another pattern or texture to a barplot in ggplot?

问题描述

假设我有一个带有序数变量和一个分类变量的数据:

set.seed(35)df <- data.frame(Class = factor(rep(c(1,2),times = 80), labels = c("Math","Science")),StudyTime = factor(sort(sample(1:4, 16, prob = c(0.25,0.3,0.3,0.15), replace = TRUE)),labels = c("<5","5-10","10-20",">20")),书呆子 = factor(sapply(rep(c(0.1,0.3,0.5,0.8),c(30,50,50,30)), function(x)sample(c("Nerd","NotNerd"),size =1, prob = c(x,1-x))),levels = c("NotNerd","Nerd")))

可以将 ggplot 和 geom_bar 与 x、fill 和 alpha 一起使用(或 color)美学映射来可视化这些变量之间的关系.

ggplot(data = df, aes(x = Class, fill = StudyTime, alpha = Nerd)) +geom_bar(position = "dodge", color = "black") +scale_alpha_manual(values = c(Nerd = 0.5, NotNerd = 1)) +scale_fill_manual(values = colorRampPalette(c("#0066CC","#FFFFFF","#FF8C00"))(4)) +实验室(x =班级"，y =学生人数"，alpha =书呆子?")+主题(legend.key.height = unit(1，cm"))

然而，alpha 和 color 并不理想.更好的选择可能是应用条纹或交叉影线等图案.

对

解决方案

一种方法是使用

该软件包似乎支持许多常见的几何图形.以下是使用 geom_tile 将连续变量与分类变量组合的示例:

set.seed(40)df2 <- data.frame(Row = rep(1:9,times=9), Column = rep(1:9,each=9),蒸发 = runif(81,50,100),TreeCover = sample(c("Yes", "No"), 81, prob = c(0.3,0.7), replace = TRUE))ggplot(data=df2, aes(x=as.factor(Row), y=as.factor(Column),模式 = TreeCover, 填充 = 蒸发)) +geom_tile_pattern(pattern_color = NA，pattern_fill = "黑色",模式角度= 45，模式密度 = 0.5，模式间距 = 0.025，pattern_key_scale_factor = 1) +scale_pattern_manual(values = c(Yes = "circle", No = "none")) +scale_fill_gradient(low="#0066CC", high="#FF8C00") +coord_equal() +实验室(x =行"，y =列")+指南(模式 = guide_legend(覆盖.aes = 列表(填充 = 白色")))

Suppose I have data with both an ordinal variable and a categorical variable:

set.seed(35)
df <- data.frame(Class = factor(rep(c(1,2),times = 80), labels = c("Math","Science")),
                 StudyTime = factor(sort(sample(1:4, 16, prob = c(0.25,0.3,0.3,0.15), replace = TRUE)),labels = c("<5","5-10","10-20",">20")),
                 Nerd = factor(sapply(rep(c(0.1,0.3,0.5,0.8),c(30,50,50,30)), function(x)sample(c("Nerd","NotNerd"),size = 1, prob = c(x,1-x))),levels = c("NotNerd","Nerd")))

One could use ggplot and geom_bar with x, fill and alpha (or color) aesthetic mappings to visualize the relationship between these variables.

ggplot(data = df, aes(x = Class, fill = StudyTime, alpha = Nerd)) + 
  geom_bar(position = "dodge", color = "black") + 
  scale_alpha_manual(values = c(Nerd = 0.5, NotNerd = 1)) +
  scale_fill_manual(values = colorRampPalette(c("#0066CC","#FFFFFF","#FF8C00"))(4)) +
  labs(x = "Class", y = "Number of Students", alpha = "Nerd?") +
  theme(legend.key.height = unit(1, "cm"))

However, alpha and color are not ideal. A better alternative might be to apply a pattern such as stripes or a crosshatch.

The accepted answer to this question from over 10 years ago says to use colors, and the most upvoted answer (while clever) uses over 100 lines of code.

This question received some upvotes but no new answers.

Is there any better alternative to adding a pattern such as can be seen here?

解决方案

One approach is to use the ggpattern package written by Mike FC (no affiliation):

library(ggplot2)
#remotes::install_github("coolbutuseless/ggpattern")
library(ggpattern)
ggplot(data = df, aes(x = Class, fill = StudyTime, pattern = Nerd)) +
  geom_bar_pattern(position = position_dodge(preserve = "single"),
                   color = "black", 
                   pattern_fill = "black",
                   pattern_angle = 45,
                   pattern_density = 0.1,
                   pattern_spacing = 0.025,
                   pattern_key_scale_factor = 0.6) + 
  scale_fill_manual(values = colorRampPalette(c("#0066CC","#FFFFFF","#FF8C00"))(4)) +
  scale_pattern_manual(values = c(Nerd = "stripe", NotNerd = "none")) +
  labs(x = "Class", y = "Number of Students", pattern = "Nerd?") + 
  guides(pattern = guide_legend(override.aes = list(fill = "white")),
         fill = guide_legend(override.aes = list(pattern = "none")))

The package appears to support a number of common geometries. Here is an example of using geom_tile to combine a continuous variable with a categorical variable:

set.seed(40)
df2 <- data.frame(Row = rep(1:9,times=9), Column = rep(1:9,each=9),
                   Evaporation = runif(81,50,100),
                   TreeCover = sample(c("Yes", "No"), 81, prob = c(0.3,0.7), replace = TRUE))

ggplot(data=df2, aes(x=as.factor(Row), y=as.factor(Column),
                     pattern = TreeCover, fill= Evaporation)) +
  geom_tile_pattern(pattern_color = NA,
                    pattern_fill = "black",
                    pattern_angle = 45,
                    pattern_density = 0.5,
                    pattern_spacing = 0.025,
                    pattern_key_scale_factor = 1) +
  scale_pattern_manual(values = c(Yes = "circle", No = "none")) +
  scale_fill_gradient(low="#0066CC", high="#FF8C00") +
  coord_equal() + 
  labs(x = "Row",y = "Column") + 
  guides(pattern = guide_legend(override.aes = list(fill = "white")))

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