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我正在尝试使用 mapbox ( plotly::plot_mapbox()) 在绘图中创建地图可视化，其中地图中的点属于不同的地理区域 (“comunas”)，用户可以在由crosstalk::filter_select().

预期的行为是，当在小部件中选择地理区域时，它应触发地图中的过滤器，该过滤器应仅显示属于所选区域的点。

但是，我无法使其工作（我正在按照此处提供的说明进行操作）。我写的代码成功创建了1）地图和2）过滤小部件，但是组件之间没有交互/对话，即当我在下拉列表中选择一个区域时，在地图，它会不断显示所有的点，而不仅仅是那些属于所选区域的点。

难道我做错了什么？我怎样才能使这项工作按预期进行？

下面是一个包含原始数据子集的可重现示例（它需要 Mapbox 令牌才能运行）：

library(tidyverse)
library(plotly)
library(crosstalk)

data <- 
  tibble::tribble(
    ~Comuna,         ~Latitude,        ~Longitude, ~id,
    "Alhué", -34.0227777777778, -71.0994444444444,  1L,
    "Alhué", -34.0958333333333,          -71.1825,  2L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  1L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  2L,
    "Alhué", -34.0227777777778, -71.0994444444444,  3L,
    "Alto Biobío", -37.8830555555556, -71.6280555555555,  1L,
    "Alto Biobío", -37.8830555555556, -71.6280555555555,  2L,
    "Alhué", -33.4430555555556, -70.7488888888889,  4L,
    "Alhué",           -33.445,          -70.6475,  5L,
    "Alhué",           -33.445,          -70.6475,  6L,
    "Algarrobo", -33.4136111111111, -71.4827777777778,  3L,
    "Alto Biobío", -37.8866666666667,            -71.63,  3L,
    "Alto Biobío", -38.0883333333333, -71.3458333333333,  4L,
    "Alto Biobío", -38.0913888888889, -71.4113888888889,  5L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  4L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  5L
  )

plot_example <- 
  data %>%
  plot_mapbox(
    lat = ~ Latitude,
    lon = ~ Longitude,
    text = ~ Comuna,
    mode = "markers",
    hoverinfo = "text") %>%  
  layout(mapbox = list(
    style = "dark",
    center = list(
      lat = ~ median(Latitude),
      lon = ~ median(Longitude)
    ),
    zoom = 6
  )) %>% 
  group_by(Comuna)

shared_key_cells <- highlight_key(data, ~Comuna)

bscols(
  filter_select("Comuna", "Comuna", shared_key_cells, ~Comuna,
                multiple = FALSE),
  plot_example
)
4

1 回答 1

1

您plot_example需要使用共享数据。这应该有效：

library(tidyverse)
library(plotly)
library(crosstalk)

data <- 
  tibble::tribble(
    ~Comuna,         ~Latitude,        ~Longitude, ~id,
    "Alhué", -34.0227777777778, -71.0994444444444,  1L,
    "Alhué", -34.0958333333333,          -71.1825,  2L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  1L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  2L,
    "Alhué", -34.0227777777778, -71.0994444444444,  3L,
    "Alto Biobío", -37.8830555555556, -71.6280555555555,  1L,
    "Alto Biobío", -37.8830555555556, -71.6280555555555,  2L,
    "Alhué", -33.4430555555556, -70.7488888888889,  4L,
    "Alhué",           -33.445,          -70.6475,  5L,
    "Alhué",           -33.445,          -70.6475,  6L,
    "Algarrobo", -33.4136111111111, -71.4827777777778,  3L,
    "Alto Biobío", -37.8866666666667,            -71.63,  3L,
    "Alto Biobío", -38.0883333333333, -71.3458333333333,  4L,
    "Alto Biobío", -38.0913888888889, -71.4113888888889,  5L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  4L,
    "Algarrobo", -33.3827777777778, -71.4163888888889,  5L
  )

shared_key_cells <- highlight_key(data, ~Comuna)

plot_example <- 
  shared_key_cells %>%
  plot_mapbox(
    lat = ~ Latitude,
    lon = ~ Longitude,
    text = ~ Comuna,
    mode = "markers",
    hoverinfo = "text") %>%  
  layout(mapbox = list(
    style = "dark",
    center = list(
      lat = ~ median(Latitude),
      lon = ~ median(Longitude)
    ),
    zoom = 6
  )) %>% 
  group_by(Comuna)


bscols(
  filter_select("Comuna", "Comuna", shared_key_cells, ~Comuna,
                multiple = FALSE),
  plot_example
)
于 2020-07-18T04:15:27.510 回答