我的目标是重现这个图,我的问题是重现每个条中的渐变填充。
评论后添加 @PavoDive 的好评将我们引向了一个问题,基本上是说“你不能用 ggplot2 做到这一点,而且即使你能做到,这也是一个坏主意。”同意这是一个糟糕的图形选择,但出于教学目的,我想重新创建原始版本,然后展示改进。那么,有没有编程解决方案呢?
使用
ggplot
代码后面的数据,除了每个条形(以及微小的刻度线)相同的一致渐变颜色之外,我已经接近了。但我的努力导致条形图被填充以匹配 y 值,而在原始图中,每个条形图都填充了相同的模式。怎样才能达到这样的效果呢?
ggplot(df, aes(x = x, y = y, fill = y)) +
geom_hline(yintercept = seq(0, .35, .05), color = "grey30", size = 0.5, linetype = "solid") +
geom_bar(stat = "identity", width = 0.4) +
scale_fill_gradient(low='green4', high='green1', guide = FALSE) +
theme(legend.position = "none") +
theme_minimal() +
geom_text(data = df, aes(label = scales::percent(y), vjust = -.5)) +
theme(axis.text.y = element_blank()) +
theme(axis.ticks = element_blank()) +
labs(y = "", x = "") +
ggtitle("Question 15: Do you feel prepared to comply with the upcoming December
2015 updated requirements of the FRCP that relate to ediscovery") +
theme(plot.title = element_text(face = "bold", size = 18)) +
theme(panel.border = element_blank())
数据
df <- data.frame(x = c("Prepared", "Somewhat\nprepared", "Not prepared", "Very prepared"),
y = c(.32, .31, .20, .17))
df$x <- factor(df$x, levels = c("Prepared", "Somewhat\nPrepared", "Not Prepared", "Very Prepared"))
这可以通过包
gridSVG
中的功能来实现。我使用您示例的精简版本,仅包含实际问题最必要的部分:
# load additional packages
library(grid)
library(gridSVG)
# create a small data set
df <- data.frame(x = factor(1:3), y = 1:3)
# a basic bar plot to be modified
ggplot(data = df, aes(x = x, y = y)) +
geom_bar(stat = "identity")
# create a linear color gradient
cols <- linearGradient(col = c("green4", "green1"),
x0 = unit(0.5, "npc"), x1 = unit(0.5, "npc"))
# create a definition of a gradient fill
registerGradientFill(label = "cols", gradient = cols)
# list the names of grobs and look for the relevant geometry
grid.ls()
# GRID.gTableParent.76
# ...snip...
# panel.3-4-3-4
# geom_rect.rect.2 # <~~~~ this is the grob! Note that the number may differ
# apply the gradient to each bar
grid.gradientFill("geom_rect.rect", label = rep("cols", length(unique(df$x))),
group = FALSE, grep = TRUE)
# generate SVG output from the grid graphics
grid.export("myplot.svg")
您可以在
此处、此处和此处找到更多
gridSVG
示例。
这里有一个选项,使用
geom_path
和缩放的 y 代替条形来着色。这会创建一些新数据 (dat
),从 0 到每个 df$y
值的序列(此处长度为 100,在列 dat$y
中)。然后,创建每个序列的缩放版本(从 0 到 1),用作颜色渐变(称为 dat$scaled
)。只需将每个序列除以其最大值即可完成缩放。
## Make the data for geom_path
mat <- mapply(seq, 0, df$y, MoreArgs = list(length=100)) # make sequences 0 to each df$y
dat <- stack(data.frame(lapply(split(mat, col(mat)), function(x) x/tail(x,1)))) # scale each, and reshape
dat$x <- rep(df$x, each=100) # add the x-factors
dat$y <- stack(as.data.frame(mat))[,1] # add the unscaled column
names(dat)[1] <- "scaled" # rename
## Make the plot
ggplot(dat, aes(x, y, color=scaled)) + # use different data
## *** removed some code here ***
geom_hline(yintercept = seq(0, .35, .05), color = "grey30", size = 0.5, linetype = "solid") +
theme(legend.position = "none") +
theme_minimal() +
geom_text(data = df, aes(label = scales::percent(y), vjust = -.5), color="black") +
theme(axis.text.y = element_blank()) +
theme(axis.ticks = element_blank()) +
labs(y = "", x = "") +
ggtitle("Question 15: Do you feel prepared to comply with the upcoming December
2015 updated requirements of the FRCP that relate to ediscovery") +
theme(plot.title = element_text(face = "bold", size = 18)) +
theme(panel.border = element_blank()) +
## *** Added this code ***
geom_path(lwd=20) +
scale_color_continuous(low='green4', high='green1', guide=F)
使用
ggplot2 >= 3.5.0
(和 R >= 4.2.0
)增加了对渐变填充的支持,现在可以更轻松地实现这一点。
与@Henrik 的方法类似,这需要首先使用例如创建渐变填充
grid::linearGradient
然后可以传递给 fill=
的 geom_bar
参数:
library(ggplot2)
packageVersion("ggplot2")
#> [1] '3.5.0'
grad_ungroup <- grid::linearGradient(c("green4", "green1"), group = FALSE)
ggplot(df, aes(x = x, y = y, fill = y)) +
geom_hline(
yintercept = seq(0, .35, .05),
color = "grey30", size = 0.5, linetype = "solid"
) +
geom_bar(stat = "identity", width = 0.4, fill = grad_ungroup) +
theme(legend.position = "none") +
theme_minimal() +
geom_text(data = df, aes(label = scales::percent(y), vjust = -.5)) +
theme(axis.text.y = element_blank()) +
theme(axis.ticks = element_blank()) +
labs(y = "", x = "") +
ggtitle("Question 15: Do you feel prepared to comply with the upcoming December
2015 updated requirements of the FRCP that relate to ediscovery") +
theme(plot.title = element_text(face = "bold", size = 18)) +
theme(panel.border = element_blank())