我在使用ggvis的add_tooltip时遇到了麻烦。
我只是想通过源码为我的情节提供一个工具提示。
我很难理解需要为add_tooltip（）创建的html函数
我知道我需要一个＆＃34; ID＆＃34;在我的数据中（你可以在底部看到我的数据）。请，有人可以解释这一部分。我不明白ggvis如何使用ID作为情节。
Visitas_Por_Fuente$id <- 1:nrow(Visitas_Por_Fuente) #Create the ID column.
Visitas_Por_Fuente %>%
ggvis(~Fuentes, ~sessions) %>%
layer_bars(width = 0.8, fill = ~Fuentes) %>%
add_tooltip(mysessions ,"hover")
mysessions <- function(x) {
if(is.null(x)) return(NULL)
#notice below the id column is how ggvis can understand which session to show
row <- Visitas_Por_Fuente[Visitas_Por_Fuente$id == x$id, ]
#prettyNum shows the number with thousand-comma separator
paste0("Sessions:", " ",prettyNum(row$sessions, big.mark=",",scientific=F))
}
显示图表，但悬停时说：
Warning: Unhandled error in observer: non-character argument
observe({
value <- session$input[[id]]
if (is.null(value))
return()
if (!is.list(value$data))
return()
df <- value$data
class(df) <- "data.frame"
attr(df, "row.names") <- .set_row_names(1L)
fun(data = df, location = list(x = value$pagex, y = value$pagey),
session = session)
})
我的数据：
structure(list(Fuentes = structure(c(3L, 5L, 6L, 6L, 4L, 5L,
5L, 5L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 6L, 7L, 3L, 5L, 6L, 6L, 5L, 6L, 5L, 5L, 5L, 5L, 7L, 7L, 6L,
1L, 6L, 5L, 5L, 4L, 5L, 5L, 4L, 6L, 5L, 5L, 5L, 5L, 7L, 3L, 5L,
6L, 6L, 4L, 6L, 5L, 5L, 4L, 4L, 5L, 7L, 7L, 6L, 7L, 5L, 4L, 5L,
4L, 2L, 2L, 6L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L, 4L, 5L, 5L,
5L, 5L, 4L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 2L,
2L, 5L, 5L, 5L, 4L, 5L, 4L, 5L, 6L, 7L, 3L, 6L, 6L, 5L, 5L, 5L,
5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 7L, 5L, 4L, 2L, 2L, 5L, 5L, 5L,
5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L, 4L, 4L, 5L, 5L, 7L, 7L, 1L,
6L, 5L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 2L, 5L, 5L, 5L, 4L, 5L,
6L, 7L, 3L, 5L, 6L, 6L, 5L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L,
1L, 6L, 5L, 5L, 5L, 7L, 5L, 5L, 7L, 4L, 5L, 5L, 4L, 2L, 2L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 4L, 4L,
4L, 6L, 4L, 4L, 4L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 5L, 7L, 7L, 1L,
6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L,
7L, 3L, 6L, 6L, 4L, 4L, 6L, 4L, 4L, 5L, 4L, 5L, 5L, 7L, 7L, 5L,
6L, 5L, 5L, 7L, 7L, 5L, 5L, 5L, 5L, 6L, 4L, 5L, 2L, 2L, 5L, 5L,
5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 5L, 6L, 4L, 6L, 4L, 4L, 4L, 5L,
4L, 5L, 4L, 5L, 7L, 7L, 6L, 6L, 7L, 5L, 5L, 5L, 5L, 4L, 2L, 5L,
5L, 5L, 4L, 4L, 5L, 5L, 6L, 7L, 3L, 5L, 5L, 6L, 6L, 6L, 5L, 5L,
5L, 5L, 4L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 7L, 5L, 4L, 5L, 4L, 2L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 6L, 6L,
4L, 4L, 5L, 5L, 4L, 5L, 7L, 7L, 1L, 6L, 5L, 7L, 5L, 5L, 4L, 5L,
5L, 4L, 6L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 6L, 6L, 4L, 6L,
5L, 4L, 5L, 4L, 5L, 7L, 7L, 4L, 5L, 7L, 7L, 5L, 1L, 6L, 5L, 7L,
5L, 5L, 4L, 5L, 4L, 2L, 2L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L,
7L, 3L, 6L, 4L, 6L, 4L, 4L, 5L, 5L, 4L, 4L, 5L, 4L, 5L, 7L, 7L,
1L, 6L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 6L, 5L, 5L, 5L, 5L, 5L,
6L, 7L, 3L, 6L, 6L, 5L, 5L, 4L, 5L, 4L, 5L, 7L, 7L, 6L, 5L, 5L,
7L, 5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 6L,
4L, 6L, 4L, 4L, 5L, 5L, 5L, 7L, 1L, 6L, 5L, 5L, 5L, 5L, 5L, 5L,
4L, 6L, 5L, 5L, 4L, 5L, 6L, 3L, 6L, 6L, 4L, 6L, 5L, 4L, 4L, 5L,
4L, 5L, 5L, 7L, 7L, 6L, 1L, 6L, 5L, 5L, 7L, 5L, 5L, 4L, 2L, 5L,
5L, 5L, 5L, 5L, 4L, 6L, 7L, 3L, 6L, 4L, 4L, 6L, 4L, 4L, 5L, 5L,
5L, 5L, 5L, 4L, 5L, 7L, 1L, 6L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L,
4L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 5L, 5L, 5L, 6L, 7L, 3L,
6L, 6L, 4L, 6L, 4L, 4L, 5L, 5L, 7L, 4L, 5L, 7L, 7L, 1L, 6L, 5L,
5L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 5L, 5L, 2L, 2L, 6L, 5L, 5L,
5L, 5L, 5L, 6L, 3L, 5L, 6L, 4L, 4L, 4L, 6L, 4L, 4L, 4L, 5L, 5L,
4L, 5L, 7L, 7L, 5L, 1L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 5L,
5L, 5L, 4L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 5L, 5L, 6L, 7L,
3L, 5L, 6L, 6L, 4L, 5L, 4L, 5L, 7L, 7L, 6L, 5L, 7L, 5L, 5L, 4L,
2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 6L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 5L, 5L, 7L, 1L, 6L, 5L, 5L, 5L, 5L, 4L, 5L, 5L,
4L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 6L, 3L, 5L, 5L, 6L, 5L, 5L,
5L, 4L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 7L, 5L, 5L, 7L, 5L, 5L, 6L,
4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 4L, 6L, 5L, 4L,
5L, 5L, 7L, 7L, 5L, 1L, 6L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 2L,
5L, 5L, 5L, 5L, 4L, 4L, 5L, 2L, 4L, 5L, 4L, 6L, 3L, 5L, 6L, 6L,
5L, 5L, 5L, 5L, 7L, 7L, 6L, 5L, 7L, 5L, 7L, 5L, 5L, 5L, 2L, 5L,
2L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 5L, 5L, 4L, 5L, 7L, 7L, 1L,
6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 2L, 2L, 5L, 6L, 7L, 3L, 6L, 6L,
5L, 5L, 5L, 7L, 5L, 7L, 7L, 5L, 5L, 6L, 5L, 5L, 5L, 5L, 5L, 4L,
5L, 5L, 4L, 5L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
6L, 5L, 3L, 6L, 6L, 4L, 6L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 5L, 1L,
6L, 5L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 5L, 6L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 4L, 6L, 5L, 5L, 7L, 7L, 6L, 5L,
5L, 7L, 5L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L,
6L, 7L, 3L, 6L, 4L, 6L, 5L, 4L, 5L, 5L, 4L, 5L, 7L, 7L, 5L, 1L,
6L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 4L,
5L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 2L, 2L,
5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 6L, 5L, 5L, 5L, 5L, 7L, 7L, 5L,
6L, 7L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 5L, 5L, 4L,
5L, 6L, 3L, 6L, 6L, 4L, 6L, 4L, 5L, 5L, 5L, 5L, 7L, 6L, 6L, 5L,
5L, 7L, 5L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 6L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 6L, 7L, 3L, 5L, 6L, 4L, 4L, 4L, 5L, 6L, 4L, 4L, 5L, 4L,
5L, 4L, 5L, 7L, 7L, 1L, 6L, 5L, 5L, 5L, 5L, 7L, 5L, 5L, 5L, 5L,
5L, 5L, 4L, 4L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L,
5L, 6L, 6L, 5L, 4L, 5L, 5L, 7L, 6L, 5L, 5L, 5L, 5L, 2L, 2L, 5L,
6L, 3L, 5L, 5L, 6L, 4L, 6L, 5L, 4L, 5L, 7L, 7L, 1L, 6L, 5L, 7L,
5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 6L,
6L, 4L, 5L, 5L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 5L, 5L, 5L, 2L, 2L,
6L, 3L, 6L, 4L, 6L, 4L, 5L, 4L, 5L, 7L, 1L, 6L, 5L, 5L, 5L, 5L,
5L, 4L, 5L, 5L, 5L, 2L, 5L, 6L, 7L, 3L, 6L, 6L, 5L, 5L, 5L, 7L,
7L, 6L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 2L, 2L, 5L, 5L, 5L, 6L, 3L,
6L, 4L, 6L, 4L, 5L, 5L, 4L, 4L, 5L, 5L, 7L, 7L, 5L, 1L, 6L, 5L,
5L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 5L, 6L, 5L, 5L, 6L, 7L, 3L, 6L,
4L, 5L, 6L, 5L, 5L, 5L, 5L, 4L, 5L, 7L, 7L, 6L, 5L, 5L, 7L, 5L,
5L, 5L, 4L, 5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 4L, 6L, 3L, 6L,
6L, 6L, 4L, 5L, 5L, 5L, 4L, 5L, 7L, 7L, 6L, 5L, 5L, 5L, 4L, 5L,
5L, 4L, 5L, 5L, 5L, 6L, 3L, 5L, 5L, 6L, 6L, 5L, 4L, 5L, 5L, 7L,
7L, 6L, 5L, 5L, 5L, 5L, 4L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L,
6L, 5L, 3L, 6L, 4L, 5L, 5L, 5L, 7L, 7L, 5L, 1L, 6L, 5L, 5L, 5L,
5L, 4L, 5L, 5L, 5L, 4L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 6L, 5L, 5L,
5L, 5L, 7L, 6L, 7L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 5L, 7L, 3L, 6L,
4L, 5L, 6L, 5L, 5L, 5L, 7L, 6L, 5L, 5L, 5L, 4L, 5L, 5L, 4L, 5L,
5L, 6L, 3L, 6L, 6L, 5L, 1L, 6L, 5L, 5L, 4L, 5L, 4L, 2L, 2L, 5L,
5L, 5L, 5L, 6L, 3L, 6L, 6L, 5L, 5L, 5L, 7L, 7L, 5L, 6L, 5L, 5L,
5L, 5L, 5L, 4L, 6L, 3L, 6L, 6L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 5L,
5L, 5L, 4L, 2L, 2L, 6L, 3L, 6L, 5L, 6L, 4L, 4L, 5L, 7L, 7L, 1L,
6L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 3L, 6L, 6L, 5L, 5L, 5L, 5L,
7L, 6L, 5L, 5L, 4L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 4L, 6L, 7L, 3L, 5L, 6L, 6L, 4L, 5L, 5L, 5L, 4L, 4L, 5L, 7L,
7L, 6L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 2L, 5L, 5L, 5L, 4L, 4L,
5L, 5L, 4L, 6L, 3L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 7L, 5L, 6L, 5L,
5L, 7L, 5L, 5L, 5L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 4L,
4L, 5L, 4L, 5L, 6L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 2L, 5L,
5L, 4L, 4L, 6L, 3L, 6L, 6L, 5L, 5L, 5L, 7L, 6L, 5L, 5L, 5L, 5L,
5L, 4L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L, 5L, 5L,
5L, 7L, 5L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 5L, 5L, 5L, 6L,
7L, 3L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 6L, 5L, 5L, 5L, 5L, 4L, 5L,
2L, 5L, 5L, 5L, 5L, 6L, 3L, 5L, 4L, 4L, 6L, 4L, 5L, 5L, 5L, 7L,
6L, 5L, 5L, 4L, 5L, 5L, 4L, 4L, 5L, 5L, 5L, 3L, 6L, 6L, 5L, 5L,
7L, 6L, 5L, 5L, 5L, 5L, 7L, 5L, 4L, 2L, 5L, 5L, 5L, 5L, 5L, 6L,
7L, 3L, 4L, 6L, 5L, 5L, 4L, 5L, 5L, 7L, 1L, 6L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 4L, 4L, 5L, 6L, 3L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 7L,
6L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 4L, 6L, 5L, 5L, 7L, 7L,
5L, 6L, 5L, 5L, 5L, 5L), .Label = c("Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media"), class = "factor"),
sessions = c(197L, 1L, 7L, 13L, 1L, 1L, 10L, 1L, 3L, 3L,
5L, 3L, 566L, 1L, 27L, 159L, 7L, 1L, 6L, 1L, 1L, 4L, 1L,
6L, 10L, 129L, 1L, 7L, 2L, 1L, 10L, 1L, 5L, 6L, 9L, 1L, 28L,
1L, 7L, 386L, 1L, 146L, 1L, 89L, 41L, 9L, 1L, 1L, 1L, 6L,
3L, 4L, 182L, 1L, 5L, 8L, 2L, 1L, 1L, 4L, 1L, 1L, 2L, 3L,
2L, 524L, 4L, 26L, 1L, 152L, 4L, 2L, 3L, 1L, 2L, 2L, 1L,
5L, 10L, 142L, 1L, 1L, 8L, 1L, 3L, 1L, 1L, 1L, 1L, 7L, 4L,
13L, 3L, 375L, 3L, 2L, 147L, 1L, 101L, 29L, 4L, 1L, 1L, 2L,
3L, 1L, 1L, 2L, 1L, 7L, 5L, 5L, 224L, 3L, 12L, 1L, 7L, 2L,
1L, 4L, 141L, 4L, 632L, 2L, 2L, 32L, 1L, 138L, 1L, 1L, 9L,
5L, 1L, 1L, 1L, 2L, 1L, 6L, 3L, 139L, 4L, 1L, 9L, 1L, 1L,
5L, 9L, 8L, 36L, 1L, 537L, 1L, 2L, 5L, 3L, 174L, 1L, 106L,
39L, 9L, 2L, 2L, 2L, 3L, 1L, 6L, 3L, 2L, 689L, 1L, 14L, 2L,
2L, 35L, 1L, 15L, 1L, 1L, 1L, 3L, 20L, 465L, 1L, 3269L, 1L,
2L, 1L, 9L, 1L, 32L, 6L, 2L, 293L, 1L, 3L, 1L, 11L, 2L, 1L,
9L, 10L, 1L, 1L, 1L, 1L, 1L, 2L, 7L, 2L, 433L, 1L, 4L, 1L,
1L, 3L, 19L, 1L, 2L, 1L, 1L, 12L, 1L, 4L, 1L, 1L, 3L, 37L,
10L, 88L, 6L, 1808L, 5L, 4L, 451L, 5L, 219L, 112L, 4L, 3L,
1L, 6L, 1L, 2L, 3L, 5L, 10L, 2L, 264L, 8L, 1L, 1L, 1L, 17L,
1L, 1L, 7L, 1L, 1L, 4L, 6L, 516L, 1L, 948L, 2L, 1L, 2L, 1L,
33L, 1L, 1L, 133L, 1L, 2L, 1L, 5L, 11L, 1L, 4L, 1L, 1L, 1L,
6L, 10L, 5L, 168L, 1L, 1L, 5L, 1L, 10L, 1L, 1L, 3L, 9L, 1L,
2L, 1L, 8L, 3L, 98L, 1L, 548L, 1L, 1L, 177L, 97L, 17L, 4L,
1L, 6L, 2L, 1L, 2L, 1L, 1L, 5L, 4L, 5L, 235L, 1L, 2L, 9L,
2L, 19L, 1L, 2L, 2L, 1L, 1L, 3L, 6L, 5L, 396L, 1209L, 1L,
2L, 1L, 41L, 1L, 125L, 3L, 5L, 1L, 4L, 1L, 1L, 4L, 1L, 3L,
1L, 1L, 5L, 2L, 121L, 2L, 1L, 1L, 10L, 1L, 1L, 4L, 1L, 2L,
10L, 3L, 75L, 5L, 632L, 1L, 2L, 2L, 178L, 1L, 67L, 33L, 6L,
1L, 1L, 1L, 2L, 1L, 12L, 3L, 194L, 1L, 1L, 1L, 1L, 1L, 20L,
1L, 1L, 6L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 296L, 1L, 1L, 979L,
6L, 4L, 1L, 33L, 1L, 109L, 5L, 2L, 6L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 6L, 3L, 118L, 1L, 1L, 15L, 1L, 1L, 1L, 1L, 1L,
4L, 2L, 1L, 18L, 6L, 53L, 3L, 584L, 2L, 1L, 2L, 172L, 2L,
100L, 27L, 9L, 2L, 1L, 2L, 1L, 1L, 1L, 11L, 3L, 202L, 6L,
20L, 2L, 1L, 1L, 4L, 1L, 8L, 2L, 292L, 719L, 2L, 1L, 2L,
29L, 106L, 7L, 3L, 8L, 2L, 2L, 1L, 1L, 1L, 7L, 3L, 139L,
4L, 1L, 2L, 17L, 1L, 2L, 3L, 2L, 20L, 53L, 3L, 530L, 2L,
1L, 1L, 172L, 113L, 23L, 2L, 1L, 4L, 2L, 2L, 1L, 7L, 891L,
10L, 1L, 1L, 12L, 1L, 1L, 1L, 1L, 1L, 4L, 5L, 6L, 1312L,
1L, 1L, 1168L, 1L, 4L, 2L, 39L, 133L, 3L, 13L, 5L, 2L, 6L,
1L, 1L, 1L, 13L, 3L, 297L, 4L, 1L, 1L, 9L, 1L, 1L, 1L, 1L,
2L, 1L, 2L, 1L, 25L, 182L, 1L, 776L, 2L, 1L, 1L, 260L, 2L,
115L, 52L, 14L, 2L, 4L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 14L, 2L, 731L, 7L, 2L, 1L, 16L, 1L, 1L, 3L, 2L, 1L,
1L, 11L, 6L, 294L, 1L, 1135L, 1L, 3L, 1L, 6L, 1L, 36L, 1L,
1L, 126L, 4L, 1L, 1L, 4L, 11L, 1L, 2L, 1L, 2L, 2L, 1L, 6L,
355L, 3L, 9L, 1L, 4L, 1L, 13L, 2L, 1L, 1L, 7L, 1L, 1L, 22L,
5L, 67L, 1L, 2L, 926L, 1L, 1L, 1L, 1L, 2L, 1L, 208L, 1L,
1L, 136L, 44L, 12L, 1L, 1L, 2L, 2L, 4L, 2L, 1L, 1L, 1L, 1L,
8L, 9L, 1L, 198L, 1L, 8L, 13L, 2L, 4L, 1L, 4L, 2L, 205L,
568L, 1L, 1L, 19L, 94L, 2L, 3L, 8L, 1L, 1L, 1L, 1L, 1L, 1L,
8L, 157L, 4L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 12L,
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"sessions"), class = "data.frame", row.names = c(NA, -1724L))
答案 0 :(得分：1)
一般来说，你需要给图层一个＆＃34;键＆＃34;在悬停或单击时返回，然后将其用作工具提示功能的输入。
我在这里看到的一个问题是你正在制作一个条形图（即每个＆＃34; Fuente＆＃34;类型总结了值）但是你想为每个单独的观察使用工具提示 （行）在您的数据中。所以问题是在你的图表中你没有显示每个数据点（观察）是分开的，因此当悬停在一个条形图上时，要知道你想要返回的特定数据点（观察）是很困难的。工具提示。
为了展示layer_points如何通过特定于观察的工具提示，我可以像这样修改你的代码：
Visitas_Por_Fuente$id <- 1:nrow(Visitas_Por_Fuente) #Create the ID column.
mysessions <- function(x) {
if(is.null(x)) return(NULL)
# get the current session info, based on "id" that is hovered over:
current_session <- Visitas_Por_Fuente[Visitas_Por_Fuente$id == x$id, "sessions"]
# format the value with prettyNum if you like:
paste0("Sessions:", " ",prettyNum(current_session, big.mark=",",scientific=F))
}
Visitas_Por_Fuente %>%
ggvis(~Fuentes, ~sessions) %>%
layer_points(fill = ~Fuentes, key := ~id) %>% # define a key
add_tooltip(mysessions ,"hover")
这是另一个版本，其中包含条形图的工具提示，显示每个＆＃34; Fuente＆＃34;的会话总数。将鼠标悬停在条形图上时键入（这是可能的，因为它不需要知道使用了哪个单一数据点 - 而是使用＆＃34; Fuente＆＃34;作为键）：
mysessions <- function(x) {
if(is.null(x)) return(NULL)
# compute the total number of sessions of the "Fuente" type that is hovered over
total_sessions <-
sum(Visitas_Por_Fuente[Visitas_Por_Fuente$Fuentes == x$Fuentes, "sessions"])
# format the value with prettyNum if you like:
paste0("Total number of Sessions:", " ",
prettyNum(total_sessions, big.mark=",",scientific=F))
}
Visitas_Por_Fuente %>%
ggvis(~Fuentes, ~sessions) %>%
layer_bars(width = 0.8, fill = ~Fuentes, key := ~Fuentes) %>%
add_tooltip(mysessions ,"hover")