相对于每个条缩放的geom_bar的渐变填充，未映射到变量 [英] Gradient fill for geom_bar scaled relative to each bar and not mapped to a variable

问题描述

我的目标是重现此图，而我的问题是重现每个条形图中的渐变填充.

My goal is to reproduce this plot, and my problem is reproducing the gradient fill in each bar.

在COMMENT之后添加 @PavoDive的好评论将我们引至一个问题，其内容基本上是您无法使用ggplot2做到这一点，而且即使您可以做到，这也不是一个好主意."同意它是一个不好的图形选择，但是出于教学目的，我想重新创建原始图形，然后显示改进之处.那么，是否仍然有一个编程解决方案?

ADDED after COMMENT The good comment of @PavoDive directs us to a question that basically says "You can't do it with ggplot2 and furthermore it is a bad idea even if you could do it." Agreed as to it being a poor graphical choice, but for didactic purposes I wanted to re-create the original and then show improvements. So, is there a programming solution nevertheless?

使用ggplot代码之后的数据，除了每个条形图(和微小的刻度线)相同的一致渐变色以外，我已经接近了.但是我的努力导致填充的条形与y值匹配，而在原始图中，每个条形都填充有相同的图案.我如何实现这种效果?

With the data that follows the ggplot code I have gotten close, other than the consistent gradient coloring that is the same for each bar (and the tiny tick marks). But my efforts result in bars that are filled to match the y value, while in the original plot each bar is filled with the same pattern. How do I achieve that effect?

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"))

推荐答案

这里是一个选项，使用带缩放y的geom_path代替条形进行着色.这将创建一些新数据(dat)，其顺序是从0到每个df$y值(此处为长度100，在dat$y列中).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).通过简单地将每个序列除以其最大值即可完成缩放.

Here is an option, using geom_path with a scaled y to color by instead of bars. This creates some new data (dat), sequences from 0 to each df$y value (length 100 here, in column dat$y). Then, a scaled version of each sequence is created (from 0 to 1), that is used as the color gradient (called dat$scaled). The scaling is done by simply dividing each sequence by its maximum value.

## 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)

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