我有 ggPlotly 可視化的水平點圖。3個數值變數被放在圖上。一切正常：
library(ggplot2)
df <- data.frame (origin = c("A","B","C","D","E","F","G","H","I","J"),
Percentage = c(23,16,32,71,3,60,15,21,44,60),
rate = c(10,12,20,200,-25,12,13,90,-105,23),
change = c(10,12,-5,12,6,8,0.5,-2,5,-2))
plt <- ggplot(df, aes(x = rate, y = factor(origin, rev(origin))))
geom_segment(aes(x = (min(rate,change)-4), xend = (max(rate,change) 4),
y = origin, yend = origin), color = 'gray')
geom_vline(xintercept = 0, linetype = 2, color = 'gray')
#geom_vline(xintercept =17, linetype = 1, color = 'black')
geom_point(aes(fill = 'rate'), shape = 21, size = 10, color = NA)
geom_text(aes(label = rate, color = 'rate'))
geom_point(aes(x = change, fill = 'change'),
color = NA, shape = 21, size = 10)
geom_text(aes(label = change, x = change, color = "change"))
geom_point(aes(x = (max(rate,change) 5.5), fill = "Percentage"), color = "gray",
size = 10, shape = 21)
geom_text(aes(x = (max(rate,change) 5.5), label = paste0(Percentage, "%")),size=3)
theme_minimal(base_size = 16)
scale_x_continuous(labels = ~paste0(.x, '%'), name = NULL)
scale_fill_manual(values = c('#aac7c4', '#5f9299','black'))
scale_color_manual(values = c("black", "white"))
theme(panel.grid = element_blank(),
axis.text.y = element_text(color = 'gray50'))
labs(color = NULL, y = NULL, fill = NULL)
theme(axis.title = element_text(size=15), legend.title = element_text(size=2))
plt <- ggplotly(plt)
#customize legend
plt$x$data[[3]]$name <- plt$x$data[[3]]$legendgroup <-
plt$x$data[[4]]$name <- plt$x$data[[4]]$legendgroup <- "rate"
plt$x$data[[5]]$name <- plt$x$data[[5]]$legendgroup <-
plt$x$data[[6]]$name <- plt$x$data[[6]]$legendgroup <- "change"
plt$x$data[[7]]$name <- plt$x$data[[7]]$legendgroup <-
plt$x$data[[8]]$name <- plt$x$data[[8]]$legendgroup <- "Percentage"
plt
但是，當我激活（洗掉＃）geom_vline(xintercept =17, linetype = 1, color = 'black')代碼行時，為了在繪圖上添加垂直線，從圖例中隱藏變數無法正常作業。例如，如果我們隱藏 'change' 變數：'rate' 的數字消失了，而其中一些仍然顯示。我認為解決方案應該在plt$x$data. 另外，我想按百分比從上到下對分類變數“原點”進行排序，例如，如果J 的百分比最高，它應該在頂部，而且，如果可能的話，我不這樣做，但我想保留A在排名中總是墊底。
uj5u.com熱心網友回復：
如果您仍然希望 A 在底部（盡管@Allan Cameron 的答案看起來很棒！），這將按百分比排序，并將 A 保持在底部。
保持你的情節和資料在你的問題中，我開始構建情節。
plt2 <- plotly_build(plt)
要按百分比重新排序值，而不是“A”，我通過Percentage添加的行號對資料重新排序，并對其進行排序以匹配圖中的順序。然后我用它來重新排列圖中的 y 軸。我在這段代碼中留下了我的檢查和平衡，所以它可能看起來很多，但其中很多是驗證。
# determine the rearrangement
nOrder = df %>%
filter(origin != "A") %>%
arrange(Percentage) %>% # desired order (other than A*)
mutate(rn = 2:nrow(df)) %>%
arrange(origin)
# add A as last
nOrder = rbind(c(unlist(df[df$origin == "A", ], use.names = F),
1), nOrder) %>%
mutate(across(c(Percentage, rn), as.integer))
# take a look
str(nOrder)
# create the vector with the order modifier
gimme <- unlist(nOrder$rn, use.names = F)
# expected order
(eo = append("A", df[df$origin != "A", ] %>% arrange(Percentage) %>%
select(origin) %>% unlist(use.names = F)))
# validgate gimme is set correctly
plt2$x$layout$yaxis$categoryarray
# check
plt2$x$layout$yaxis$categoryarray[order(gimme)]
all.equal(plt2$x$layout$yaxis$ticktext[order(gimme)], eo) # TRUE
現在是時候重新排列 y 軸了。由于翻譯的原因，有一些事情必須改變ggplot <-> plotly。range（或者它會隱藏 A 并在頂部添加無用的空格）以及type需要更改的順序以及順序。順序是用引數設定的categoryarray。
# finally change the plot's y-axis
plt2 %>% layout(yaxis = list(range = c(-.5, 10),
categoryarray = (1:10)[order(gimme)],
type = "category")) -> plt2
plt2
添加重新排序后，我注意到垂直線不再可見。我再次創建了線條。（這是由于 y 軸的變化。）
lines <- function(x = 0, dash = "solid", color = "black"){
list(type = "line",
x0 = x, x1 = x, y0 = 0, y1 = 1,
xref = "x", yref = "paper",
layer = "below",
line = list(color = color,
dash = dash))
}
plt2$x$layout$shapes <- list(plt2$x$layout$shapes,
lines(17),
lines(dash = "longdash",
color = "gray"))
現在為傳奇名稱。有很多方法可以做到這一點。我注意到你做對了，添加了一個圖層，然后出現了問題。您可以使用正則運算式，而不是挑選。另一種選擇是檢查以找到要更改的痕跡。
# change the applicable traces with conditions and regex
# fixes legend regardless of where or what order the traces fall in
invisible(
lapply(1:length(plt2$x$data),
function(j) {
i = plt2$x$data[[j]]$name
if(!is.null(i)){
i = sub(".([[:alpha:]] ).*", "\\1", i)
plt2$x$data[[j]]$name <<-
plt2$x$data[[j]]$legendgroup <<- i
}
})
)
# if you just wanted to investigate
invisible(
lapply(1:length(plt2$x$data),
function(k) {
message(k, ' ', plt2$x$data[[k]]$name)
}
))
現在你只需要呼叫情節。
plt2
uj5u.com熱心網友回復：
origin按百分比對列進行排序很簡單。這是在資料級別完成的，通過轉換origin為一個因子，其級別由 的值確定 Percentage：
df$origin <- factor(df$origin, df$origin[order(df$Percentage)])
您的自定義圖例發生奇怪事情的原因是您在某些現有圖層之前添加了一個圖層，這會導致您在最后修改圖例組時使用的索引無效。最簡單的解決方法是在現有圖層之后畫線：
plt <- ggplot(df, aes(x = rate, y = factor(origin, rev(origin))))
geom_segment(aes(x = (min(rate,change)-4), xend = (max(rate,change) 4),
y = origin, yend = origin), color = 'gray')
geom_vline(xintercept = 0, linetype = 2, color = 'gray')
geom_point(aes(fill = 'rate'), shape = 21, size = 10, color = NA)
geom_text(aes(label = rate, color = 'rate'))
geom_point(aes(x = change, fill = 'change'),
color = NA, shape = 21, size = 10)
geom_text(aes(label = change, x = change, color = "change"))
geom_point(aes(x = (max(rate,change) 5.5), fill = "Percentage"),
color = "gray", size = 10, shape = 21)
geom_text(aes(x = (max(rate,change) 5.5), label = paste0(Percentage, "%")),
size = 3)
geom_vline(xintercept =17, linetype = 1, color = 'black')
theme_minimal(base_size = 16)
scale_x_continuous(labels = ~paste0(.x, '%'), name = NULL)
scale_fill_manual(values = c('#aac7c4', '#5f9299','black'))
scale_color_manual(values = c("black", "white"))
theme(panel.grid = element_blank(),
axis.text.y = element_text(color = 'gray50'))
labs(color = NULL, y = NULL, fill = NULL)
theme(axis.title = element_text(size=15), legend.title = element_text(size=2))
plt <- ggplotly(plt)
現在您可以像以前一樣自定義圖例組：
#customize legend
plt$x$data[[3]]$name <- plt$x$data[[3]]$legendgroup <-
plt$x$data[[4]]$name <- plt$x$data[[4]]$legendgroup <- "rate"
plt$x$data[[5]]$name <- plt$x$data[[5]]$legendgroup <-
plt$x$data[[6]]$name <- plt$x$data[[6]]$legendgroup <- "change"
plt$x$data[[7]]$name <- plt$x$data[[7]]$legendgroup <-
plt$x$data[[8]]$name <- plt$x$data[[8]]$legendgroup <- "Percentage"
plt
如果您希望線條位于所有點和文本的后面，請保持現有的繪圖代碼不變，并增加圖例分組代碼中的所有索引：
#customize legend
plt$x$data[[4]]$name <- plt$x$data[[4]]$legendgroup <-
plt$x$data[[5]]$name <- plt$x$data[[5]]$legendgroup <- "rate"
plt$x$data[[6]]$name <- plt$x$data[[6]]$legendgroup <-
plt$x$data[[7]]$name <- plt$x$data[[7]]$legendgroup <- "change"
plt$x$data[[8]]$name <- plt$x$data[[8]]$legendgroup <-
plt$x$data[[9]]$name <- plt$x$data[[9]]$legendgroup <- "Percentage"
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標籤：r ggplot2 情节地 tidyverse 数据可视化
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