在R中以绘图方式共享子图之间共享轴和图例（ggplot2中的构面和使用ggplotly不起作用）

Question

我有以下数据：

df <- data.frame(numbers = rep(1:3, 30),
                 letter = sample(c("A", "B", "C", "D"), 90, replace = TRUE),
                 status = sample(c("good", "bad", "ugly"), 90, replace = TRUE))

我正在尝试复制此ggplot2图，但使其具有交互性：

ggplot(df, aes(letter, fill = status)) + geom_bar() + facet_wrap(.~numbers)

如果我使用ggplotly，则可以选择和取消选择变量，但是条形图不会重新调整，因此我得到的内容如下：

所以我的想法是转换数据，然后创建单个绘图并使用子图：

df_group <- df %>% group_by(numbers, letter, status) %>% tally()
df_group_cast <- dcast(df_group, numbers + letter ~ status)

p1 <- df_group_cast %>% 
    filter(numbers == 1) %>%
    plot_ly(x = ~letter, y = ~good, type = 'bar', name = 'good') %>%
    add_trace(y = ~bad, name = 'bad') %>%
    add_trace(y = ~ugly, name = 'ugly') %>%
    layout(yaxis = list(title = 'Count'), barmode = 'stack')

p2 <- df_group_cast %>% 
    filter(numbers == 2) %>%
    plot_ly(x = ~letter, y = ~good, type = 'bar', name = 'good') %>%
    add_trace(y = ~bad, name = 'bad') %>%
    add_trace(y = ~ugly, name = 'ugly') %>%
    layout(yaxis = list(title = 'Count'), barmode = 'stack')

p3 <- df_group_cast %>% 
    filter(numbers == 3) %>%
    plot_ly(x = ~letter, y = ~good, type = 'bar', name = 'good') %>%
    add_trace(y = ~bad, name = 'bad') %>%
    add_trace(y = ~ugly, name = 'ugly') %>%
    layout(yaxis = list(title = 'Count'), barmode = 'stack')

subplot(p1, p2, p3)

这是交互式的，但看起来也很糟糕。我希望他们共享一个比例，有一个图例，并对每个数字组都有标题。

这可能吗？

（我想将这样的交互式图形嵌入slidify中，如果有更好的库可以使用它们。到目前为止，rCharts使我失败了，所以我要作图）

Answer 1

我知道了！不需要最后投放我的数据。我什至还添加了添加子组标题的步骤。

df_group <- df %>% group_by(numbers, letter, status) %>% tally()

将注释文本放在一起以添加到图中：

a <- list(
    text = sprintf("<b>1</b>"),
    xref = "paper",
    yref = "paper",
    yanchor = "bottom",
    xanchor = "center",
    align = "center",
    x = 0.5,
    y = 1,
    showarrow = FALSE)

b <- list(
    text = sprintf("<b>2</b>"),
    xref = "paper",
    yref = "paper",
    yanchor = "bottom",
    xanchor = "center",
    align = "center",
    x = 0.5,
    y = 1,
    showarrow = FALSE)

c <- list(
    text = sprintf("<b>3</b>"),
    xref = "paper",
    yref = "paper",
    yanchor = "bottom",
    xanchor = "center",
    align = "center",
    x = 0.5,
    y = 1,
    showarrow = FALSE)

将实际图放在一起，请注意布局下的“注释”选项。我也不需要添加所有的废话，按状态着色可以帮我完成工作。

p1 <- df_group %>% 
    filter(numbers == 1) %>% 
    group_by(letter) %>% 
    plot_ly(x = ~letter, y= ~n, color = ~status, type = 'bar', legendgroup = ~status) %>% 
    layout(barmode = 'stack', annotations = a)

p2 <- df_group %>% 
    filter(numbers == 2) %>% 
    group_by(letter) %>% 
    plot_ly(x = ~letter, y= ~n, color = ~status, type = 'bar', legendgroup = ~status, showlegend = FALSE) %>% 
    layout(barmode = 'stack', annotations = b)

p3 <- df_group %>% 
    filter(numbers == 3) %>% 
    group_by(letter) %>% 
    plot_ly(x = ~letter, y= ~n, color = ~status, type = 'bar', legendgroup = ~status, showlegend = FALSE) %>% 
    layout(barmode = 'stack', annotations = c)

绘图：

subplot(p1, p2, p3, shareY = TRUE)

Imgur无法显示交互性，因此您只需要相信它是交互式的，就可以通过单击所有图的标签来选择所有图中的类别。