我有一個包含變數值的資料集，每個資料集分為 3 個觀察類別。
下面是一個最小的作業示例：
library(dplyr)
library(ggplot2)
Test.df <-c()
Test.df$Value <- runif(51)
Test.df <- as.data.frame(Test.df)
Test.df$Category <- as.factor(c("A", "B", "C"))
Test.df <- arrange(Test.df, Category)
Test.df$Variable <- c("ZA", "ZB", "ZC", "ZD", "ZE", "ZF", "ZF", "ZH", "ZI", "ZJ", "ZK", "ZL", "ZM", "ZN", "ZO", "ZP", "ZQ")
Colors <- c("#E8223D","#E4B533","#4BA046","#C7202F","#EF402C","#27BFE5","#FBC413","#A21C43","#F26A2D","#DE1768","#F99D29","#BF8D2C","#407F46","#1E97D4","#5ABA47","#136A9F","#15496B")
Bar.Plot <-
ggplot(Test.df, aes(x = Variable, y = Value))
geom_bar(stat="identity",
width = 0.9,
position = position_dodge(width = 1),
aes(fill = Category))
scale_fill_manual(Test.df$Variable, values=Colors)
Bar.Plot
這將輸出以下圖：
顏色如何按變數交替，以便變數 ZA 的 3 個觀察值是相同的顏色，變數 ZB 的 3 個觀察值是下一個顏色，并且每個變數向下迭代顏色串列？
此外，是否可以為每個觀察添加一個 alpha 以增加一些透明度，例如為三個 ZA 觀察中的每一個添加不同的 alpha？
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library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(ggplot2)
Test.df <- c()
Test.df$Value <- runif(51)
Test.df <- as.data.frame(Test.df)
Test.df$Category <- as.factor(c("A", "B", "C"))
Test.df <- arrange(Test.df, Category)
Test.df$Variable <- c("ZA", "ZB", "ZC", "ZD", "ZE", "ZF", "ZF", "ZH", "ZI", "ZJ", "ZK", "ZL", "ZM", "ZN", "ZO", "ZP", "ZQ")
Colors <- c("#E8223D", "#E4B533", "#4BA046", "#C7202F", "#EF402C", "#27BFE5", "#FBC413", "#A21C43", "#F26A2D", "#DE1768", "#F99D29", "#BF8D2C", "#407F46", "#1E97D4", "#5ABA47", "#136A9F", "#15496B")
Bar.Plot <-
ggplot(Test.df, aes(x = Variable, y = Value))
geom_bar(
stat = "identity",
width = 0.9,
position = position_dodge(width = 1),
aes(fill = Variable, group = Category, alpha = Category)
)
scale_fill_manual(Test.df$Variable, values = Colors)
guides(alpha = FALSE)
#> Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
#> "none")` instead.
Bar.Plot
#> Warning: Using alpha for a discrete variable is not advised.
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