在 r plotly 中不使用“變換”的多組分組條形圖（在同一圖上）

Question

代碼：

library(plotly)
library(tidyverse)

df <- data.frame(protein = c("Chicken", "Beef", "Pork", "Fish",
                             "Chicken", "Beef", "Pork", "Fish"),
                 y1 = c(3, 24, 36, 49, 7, 15, 34, 49),
                 y2 = c(9, 28, 40, 47, 8, 20, 30, 40 ), 
                 gender = c("Male", "Male", "Male", "Male",
                            "Female", "Female", "Female", "Female"))

df %>%
  plot_ly() %>% 
  add_bars (y = ~y1, x = ~protein,
            name = 'y1.male') %>% add_bars(y = ~y2,
               x=~protein, color = I("green"),name = "y2.male")%>%
  add_bars(y = ~y1, x = ~protein, color = I("black"),
           name = 'y1.female') %>% add_bars(y = ~y2,
                x=~protein, color = I("red"), name = "y2.female")

我想要的結果是創建類似這樣的東西：

但是，當您運行代碼時，您會看到它在每個欄中堆疊了“男性”和“女性”值。 我希望“y1.male”在 y = y1 時代表“男性”數據，“y2.male”在 y = y2 時代表“男性”數據，“y1.female”在 y = y2 時代表“女性”數據y = y1 和“y2.female”分別表示 y = y2 時的“女性”數據。 我怎樣才能 go 做到這一點而不必在 r-plotly 中通過“轉換”使用過濾器？

Answer 1

我們可以將數據重新排列為長格式，然后是 plot：

df %>% 
  pivot_longer(cols = c(y1, y2)) %>% 
  unite(gender_var, c(gender, name)) %>% 
 plot_ly() %>% 
  add_bars (x = ~protein, y = ~value,
            name = ~gender_var)