Scatterpie：如何在连接饼图的线上添加注释以标记饼图之间 y 值的百分比变化
Scatterpie: How to add annotation over line connecting pies to mark percent change in y-values between pies
我有一个散点图，其中饼图绘制在 x 轴和 y 轴上，还有一条连接它们的“趋势线”。本着 的精神，我想在每一行上添加一个注释，以标记每个相邻饼图下的 y 值之间的百分比 increase/decrease。
我的数据
library(tidyverse)
library(scatterpie)
my_df <- structure(list(day_in_july = 13:20, yes_and_yes = c(0.611814345991561,
0.574750830564784, 0.593323216995448, 0.610539845758355, 0.650602409638554,
0.57429718875502, 0.575971731448763, 0.545454545454545), yes_but_no = c(0.388185654008439,
0.425249169435216, 0.406676783004552, 0.389460154241645, 0.349397590361446,
0.42570281124498, 0.424028268551237, 0.454545454545455), y = c(0.388185654008439,
0.425249169435216, 0.406676783004552, 0.389460154241645, 0.349397590361446,
0.42570281124498, 0.424028268551237, 0.454545454545455)), row.names = c(NA,
-8L), class = c("tbl_df", "tbl", "data.frame"))
我目前的可视化
p <- ggplot(data = my_df) +
geom_path(aes(x=day_in_july, y = y*50)) +
geom_scatterpie(aes(x = day_in_july, y = y*50, r = 0.3),
data = my_df,
cols = colnames(my_df)[2:3],
color = "red") +
geom_text(aes(y = y*50, x = day_in_july,
label = paste0(formatC(y*100, digits = 3), "%")),
nudge_y = 0.07, nudge_x = -0.25, size = 3) +
geom_text(aes(y = y*50, x = day_in_july,
label = paste0(formatC((1-y)*100, digits = 3), "%")),
nudge_y = -0.07, nudge_x = 0.25, size = 3) +
scale_fill_manual(values = c("pink", "seagreen3")) +
scale_x_continuous(labels = xvals, breaks = xvals) +
scale_y_continuous(name = "yes but no",
labels = function(x) x/50) +
coord_fixed()
> p
我想在相邻饼图
的 y 值之间添加百分比 increase/decrease
第一个饼图（在 day_in_july = 13）的 y 值为 0.388。从这个 y 值到下一个饼图的 y 值 (0.425)，增加了 9.53%。因此，我想用标签 +9.53% 标记连接两个馅饼的线。
最后，我希望情节看起来像这样：
在寻找解决方案的路上
已经有了相关的机制来获得我正在寻找的东西。
这个想法是使用 ggplot_build() 访问图下的数据，然后计算两个连续值之间的百分比变化，然后用相应注释的线条重建图。但是，此解决方案不适用于散点图，因为从 ggplot_build 输出的基础数据属于它自己的类型。
plot_data <- ggplot_build(p) %>% ggplot_build(p)$data[[1]] %>% as.tibble()
> plot_data
## # A tibble: 2,904 x 13
## fill group index amount PANEL stringsAsFactors nControl x y colour size linetype alpha
## <chr> <chr> <dbl> <dbl> <fct> <lgl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <lgl>
## 1 pink 1 0 0.612 1 FALSE 221 13 19.7 red 0.5 1 NA
## 2 pink 1 0.00452 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 3 pink 1 0.00905 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 4 pink 1 0.0136 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 5 pink 1 0.0181 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 6 pink 1 0.0226 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 7 pink 1 0.0271 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 8 pink 1 0.0317 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 9 pink 1 0.0362 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 10 pink 1 0.0407 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## # ... with 2,894 more rows
计算饼图 y 值之间百分比变化所需的实际 y 值在哪里？显然，我可以从数据中获取 y 值。但是为了重建情节，来自 ggplot_build() 的这些数据对我来说没有意义，我不知道如何利用该技术将饼图之间的百分比变化添加到情节线。
这是我对 ggrepel 包的尝试。我基本上创建了一个包含 geom_label_repel() 必要信息的新数据框。我省略了创建 foo 的详细信息。但我认为你可以阅读它。我花了一些时间来找到标签的最佳位置，这就是我现在能为你做的。位置不满意就自己玩吧
foo <- tibble(day_in_july = my_df$day_in_july + 0.5,
y = my_df$y * 50 + (((lead(my_df$y * 50) - (my_df$y * 50))) / 2),
gap = ((lead(my_df$yes_but_no) / my_df$yes_but_no) - 1) * 100) %>%
mutate(gap = paste(round(gap, digits = 2), "%", sep = ""),
hue = ifelse(gap > 0, "green", "red"))
p <- ggplot(data = my_df) +
geom_path(aes(x = day_in_july, y = y*50)) +
geom_scatterpie(aes(x = day_in_july, y = y*50, r = 0.3),
data = my_df,
cols = colnames(my_df)[2:3],
color = "red") +
geom_text(aes(y = y * 50, x = day_in_july,
label = paste0(formatC(y * 100, digits = 3), "%")),
nudge_y = 0.07, nudge_x = -0.25, size = 3) +
geom_text(aes(y = y * 50, x = day_in_july,
label = paste0(formatC((1-y) * 100, digits = 3), "%")),
nudge_y = -0.07, nudge_x = 0.25, size = 3) +
scale_fill_manual(values = c("pink", "seagreen3")) +
geom_label_repel(data = foo,
aes(x = day_in_july, y = y,
color = hue, label = as.character(gap)),
show.legend = FALSE,
nudge_x = 0.3,
direction = "y",
vjust = -1.0) +
scale_color_manual(values = c("green", "red"))
我有一个散点图，其中饼图绘制在 x 轴和 y 轴上，还有一条连接它们的“趋势线”。本着
我的数据
library(tidyverse)
library(scatterpie)
my_df <- structure(list(day_in_july = 13:20, yes_and_yes = c(0.611814345991561,
0.574750830564784, 0.593323216995448, 0.610539845758355, 0.650602409638554,
0.57429718875502, 0.575971731448763, 0.545454545454545), yes_but_no = c(0.388185654008439,
0.425249169435216, 0.406676783004552, 0.389460154241645, 0.349397590361446,
0.42570281124498, 0.424028268551237, 0.454545454545455), y = c(0.388185654008439,
0.425249169435216, 0.406676783004552, 0.389460154241645, 0.349397590361446,
0.42570281124498, 0.424028268551237, 0.454545454545455)), row.names = c(NA,
-8L), class = c("tbl_df", "tbl", "data.frame"))
我目前的可视化
p <- ggplot(data = my_df) +
geom_path(aes(x=day_in_july, y = y*50)) +
geom_scatterpie(aes(x = day_in_july, y = y*50, r = 0.3),
data = my_df,
cols = colnames(my_df)[2:3],
color = "red") +
geom_text(aes(y = y*50, x = day_in_july,
label = paste0(formatC(y*100, digits = 3), "%")),
nudge_y = 0.07, nudge_x = -0.25, size = 3) +
geom_text(aes(y = y*50, x = day_in_july,
label = paste0(formatC((1-y)*100, digits = 3), "%")),
nudge_y = -0.07, nudge_x = 0.25, size = 3) +
scale_fill_manual(values = c("pink", "seagreen3")) +
scale_x_continuous(labels = xvals, breaks = xvals) +
scale_y_continuous(name = "yes but no",
labels = function(x) x/50) +
coord_fixed()
> p
我想在相邻饼图
的 y 值之间添加百分比 increase/decrease第一个饼图（在 day_in_july = 13）的 y 值为 0.388。从这个 y 值到下一个饼图的 y 值 (0.425)，增加了 9.53%。因此，我想用标签 +9.53% 标记连接两个馅饼的线。
最后，我希望情节看起来像这样：
在寻找解决方案的路上
ggplot_build() 访问图下的数据，然后计算两个连续值之间的百分比变化，然后用相应注释的线条重建图。但是，此解决方案不适用于散点图，因为从 ggplot_build 输出的基础数据属于它自己的类型。
plot_data <- ggplot_build(p) %>% ggplot_build(p)$data[[1]] %>% as.tibble()
> plot_data
## # A tibble: 2,904 x 13
## fill group index amount PANEL stringsAsFactors nControl x y colour size linetype alpha
## <chr> <chr> <dbl> <dbl> <fct> <lgl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <lgl>
## 1 pink 1 0 0.612 1 FALSE 221 13 19.7 red 0.5 1 NA
## 2 pink 1 0.00452 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 3 pink 1 0.00905 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 4 pink 1 0.0136 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 5 pink 1 0.0181 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 6 pink 1 0.0226 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 7 pink 1 0.0271 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 8 pink 1 0.0317 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 9 pink 1 0.0362 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## 10 pink 1 0.0407 0.612 1 FALSE 221 13.0 19.7 red 0.5 1 NA
## # ... with 2,894 more rows
计算饼图 y 值之间百分比变化所需的实际 y 值在哪里？显然，我可以从数据中获取 y 值。但是为了重建情节，来自 ggplot_build() 的这些数据对我来说没有意义，我不知道如何利用该技术将饼图之间的百分比变化添加到情节线。
这是我对 ggrepel 包的尝试。我基本上创建了一个包含 geom_label_repel() 必要信息的新数据框。我省略了创建 foo 的详细信息。但我认为你可以阅读它。我花了一些时间来找到标签的最佳位置，这就是我现在能为你做的。位置不满意就自己玩吧
foo <- tibble(day_in_july = my_df$day_in_july + 0.5,
y = my_df$y * 50 + (((lead(my_df$y * 50) - (my_df$y * 50))) / 2),
gap = ((lead(my_df$yes_but_no) / my_df$yes_but_no) - 1) * 100) %>%
mutate(gap = paste(round(gap, digits = 2), "%", sep = ""),
hue = ifelse(gap > 0, "green", "red"))
p <- ggplot(data = my_df) +
geom_path(aes(x = day_in_july, y = y*50)) +
geom_scatterpie(aes(x = day_in_july, y = y*50, r = 0.3),
data = my_df,
cols = colnames(my_df)[2:3],
color = "red") +
geom_text(aes(y = y * 50, x = day_in_july,
label = paste0(formatC(y * 100, digits = 3), "%")),
nudge_y = 0.07, nudge_x = -0.25, size = 3) +
geom_text(aes(y = y * 50, x = day_in_july,
label = paste0(formatC((1-y) * 100, digits = 3), "%")),
nudge_y = -0.07, nudge_x = 0.25, size = 3) +
scale_fill_manual(values = c("pink", "seagreen3")) +
geom_label_repel(data = foo,
aes(x = day_in_july, y = y,
color = hue, label = as.character(gap)),
show.legend = FALSE,
nudge_x = 0.3,
direction = "y",
vjust = -1.0) +
scale_color_manual(values = c("green", "red"))