如何使用串扰小部件过滤 plot_mapbox() 中的点?

How to filter points in plot_mapbox() using crosstalk widget?

我正在尝试使用 mapbox (plotly::plot_mapbox()) 在 plotly 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”),用户可以选择一个地理区域在 crosstalk::filter_select().

创建的下拉小部件中

预期的行为是,当一个地理区域在小部件中 selected 时,它应该在地图中触发一个过滤器,它应该只显示属于 select 的点ed区.

但是,我无法让它工作(我正在按照提供的说明进行操作 here)。我成功编写的代码创建了 1) 地图和 2) 过滤小部件,但这些组件不会 interact/talk 彼此,即当我 select 下拉列表中的一个区域时,那里地图上没有过滤效果,它一直显示所有的点,而不仅仅是那些属于selected区的点。

我是不是做错了什么?我怎样才能使这项工作按预期进行?

下面是一个带有原始数据子集的可重现示例(它需要一个 Mapbox 令牌 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
)

您的 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
)