如何将ggplot生成的分位数税率柱状图转换为Plotly对象？

我看到你已经成功用ggplot绘制了分组均值柱状图，但在转换为Plotly交互式图表时遇到了问题。这个问题通常是因为ggplotly对ggplot中某些非数据绑定的美学设置兼容性不好，比如你直接用外部向量color_code设置fill颜色，以及x轴的手动标签设置方式，都会导致转换异常。

下面是调整后的完整代码，能顺利完成ggplot到Plotly的转换：

# 先加载必要的包（确保plotly已安装）
library("rJava")
library("xlsxjars")
library("xlsx")
require(tidyr)
require(plyr)
library("ggplot2")
library("plotly")

# 你的数据处理部分（保持不变）
g4_data_ext<-data.frame(structure(list(Centile.threshold = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100), Effective.tax.rates = c(11.4875111183361, 8.07673874931679, 7.8639563682086, 6.84656368538612, 6.8383437884744, 5.83532681932012, 5.11955857753708, 4.68757220539562, 4.66492423437793, 4.63051650494602, 4.71570390296145, 4.4419481131279, 4.16374366969064, 4.4424750798236, 4.2633646392858, 4.10185821346884, 2.29819561722, 2.01895390855722, 0, 0, 2.80530318111453, 2.83367683951859, 3.03173307975026, 3.58758933227946, 3.05869003045607, 3.59225918463074, 3.01588015121759, 3.55943967998446, 3.6220565232692, 3.40885422585891, 3.51447401518606, 3.68902868712004, 3.77018314638409, 3.72783452684771, 3.80791342516448, 3.99449874248864, 4.08421307782513, 4.07517557211112, 4.19659018929637, 4.22887420998102, 4.25529382081159, 4.36205679154288, 4.40690982734329, 4.33909305037396, 4.45990415426276, 4.59436808108174, 4.6831546716255, 4.73811656768519, 4.75412915916737, 4.84778797281815, 4.94690785473091, 5.06784298188807, 5.1769208879221, 5.2520552039406, 5.33650672817794, 5.43499638671921, 5.52400199193912, 5.58169115527766, 5.70509046165446, 5.76549758450655, 5.86333222670147, 5.87097687497217, 5.98729128544292, 6.07397530734785, 6.15030076581313, 6.21615540600908, 6.28135059352123, 6.38292345287997, 6.43416757218245, 6.5863284138631, 6.63365437304645, 6.70316768627345, 6.7816891944299, 6.85128738244695, 6.94261253911407, 7.01673024329712, 7.11081973369591, 7.18077796481166, 7.26197149513331, 7.32607460317916, 7.39638728837014, 7.47062968448649, 7.55194205005014, 7.64318101794584, 7.73728594723894, 7.79092205170689, 7.88152530983832, 7.97428540786095, 8.09278589483141, 8.20373396784042, 8.27757060469128, 8.40889176349213, 8.50851684368756, 8.64124701008068, 8.72559960562268, 8.85276486059087, 9.06564270204267, 9.26861906650096, 9.43047799204161, 10.2298639144453), grp_id = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 7, 8), grp_label = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 3L), .Label = c("<=50%", "=99%", ">99%", "51%-60%", "61%-70%", "71%-80%", "81%-90%", "91%-98%" ), class = "factor"), row.names = c(NA, -100L), class = "data.frame"))

# 计算分组均值（保持不变）
means_g4<-data.frame(ddply(g4_data_ext,~grp_id+grp_label,summarise,mean=mean(Effective.tax.rates),sd=sd(Effective.tax.rates)))

# 定义颜色映射，和分组标签绑定
color_map <- c(
  "<=50%" = "darkturquoise",
  "51%-60%" = "darkturquoise",
  "61%-70%" = "darkturquoise",
  "71%-80%" = "darkturquoise",
  "81%-90%" = "darkturquoise",
  "91%-98%" = "darkturquoise",
  "=99%" = "tomato",
  ">99%" = "orangered"
)

# 重构ggplot代码，让美学映射基于数据
p <- ggplot(data = means_g4, aes(x = grp_label, y = mean, fill = grp_label, label = round(mean, 2))) +
  labs(x = "Group", y = "Mean Effective Tax Rates") +
  coord_cartesian(ylim = c(-3, 12)) +
  geom_bar(stat = "identity") +
  geom_text(aes(y = mean * 1.1), position = position_dodge(width = 0.9), size = 3) +
  scale_fill_manual(values = color_map) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 0, hjust = 0.5))

# 转换为Plotly对象
ggplotly(p, tooltip = c("x", "y"))

关键调整点说明： #

1. 颜色映射绑定到数据：之前直接用外部向量color_code设置fill，ggplotly无法识别这种非数据关联的颜色设置。现在把颜色和grp_label绑定，用scale_fill_manual定义，让ggplotly能正确解析颜色信息。
2. x轴直接使用分组标签：不再手动用grp_id转factor后设置标签，直接用grp_label作为x轴变量，简化代码同时提升兼容性。
3. 美学映射统一放在aes内部：所有需要被ggplotly识别的属性（比如fill、label）都放到aes()里，确保Plotly能读取到完整的图层数据。
4. 优化tooltip显示：通过tooltip参数指定Plotly悬停时显示的内容，提升交互体验。

这样修改后，你应该能顺利得到交互式的Plotly柱状图，保留原ggplot的所有视觉样式，同时支持悬停查看详细数值等交互功能。

内容的提问来源于stack exchange，提问作者silent_hunter