R - plotly - 结合气泡和等值线图

Question

我想在 plotly 中将两种类型的地图组合在一张地图中，即气泡图和等值线图。 objective 是通过将鼠标悬停在地图上来显示国家级别（等值线）和城市级别（气泡）的人口规模。

等值线图的绘图示例代码如下：

library(plotly)
    df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_world_gdp_with_codes.csv')

    # light grey boundaries
    l <- list(color = toRGB("grey"), width = 0.5)

    # specify map projection/options
    g <- list(
      showframe = FALSE,
      showcoastlines = FALSE,
      projection = list(type = 'Mercator')
    )

    plot_ly(df, z = GDP..BILLIONS., text = COUNTRY, locations = CODE, type = 'choropleth',
            color = GDP..BILLIONS., colors = 'Blues', marker = list(line = l),
            colorbar = list(tickprefix = '$', title = 'GDP Billions US$'),
            filename="r-docs/world-choropleth") %>%
      layout(title = '2014 Global GDP<br>Source:<a href="https://www.cia.gov/library/publications/the-world-factbook/fields/2195.html">CIA World Factbook</a>',
             geo = g)

气泡图的绘图示例代码如下：

library(plotly)
    df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')
    df$hover <- paste(df$name, "Population", df$pop/1e6, " million")

    df$q <- with(df, cut(pop, quantile(pop)))
    levels(df$q) <- paste(c("1st", "2nd", "3rd", "4th", "5th"), "Quantile")
    df$q <- as.ordered(df$q)

    g <- list(
      scope = 'usa',
      projection = list(type = 'albers usa'),
      showland = TRUE,
      landcolor = toRGB("gray85"),
      subunitwidth = 1,
      countrywidth = 1,
      subunitcolor = toRGB("white"),
      countrycolor = toRGB("white")
    )

    plot_ly(df, lon = lon, lat = lat, text = hover,
            marker = list(size = sqrt(pop/10000) + 1),
            color = q, type = 'scattergeo', locationmode = 'USA-states',
            filename="r-docs/bubble-map") %>%
      layout(title = '2014 US city populations<br>(Click legend to toggle)', geo = g)

怎么可能将两种类型的地图合二为一呢？

Answer 1

好问题！这是一个简单的例子。注：

使用add_trace在绘图之上添加另一个图表类型图层
绘图的 layout 在所有轨迹之间共享。 layout 键描述了地图的 scope、坐标轴、title 等内容。See more layout keys.

简单气泡图

lon = c(-73.9865812, -118.2427266, -87.6244212, -95.3676974)
pop = c(8287238, 3826423, 2705627, 2129784)
df_cities = data.frame(cities, lat, lon, pop)

plot_ly(df_cities, lon=lon, lat=lat, 
        text=paste0(df_cities$cities,'<br>Population: ', df_cities$pop),
        marker= list(size = sqrt(pop/10000) + 1), type="scattergeo",
        filename="Whosebug/simple-scattergeo") %>%
  layout(geo = list(scope="usa"))

Interactive version

简单等值线图

state_codes = c("NY", "CA", "IL", "TX")
pop = c(19746227.0, 38802500.0, 12880580.0, 26956958.0)
df_states = data.frame(state_codes, pop)

plot_ly(df_states, z=pop, locations=state_codes, text=paste0(df_states$state_codes, '<br>Population: ', df_states$pop), 
        type="choropleth", locationmode="USA-states", colors = 'Purples', filename="Whosebug/simple-choropleth") %>%
  layout(geo = list(scope="usa"))

Interactive version

综合等值线图和气泡图

plot_ly(df_cities, lon=lon, lat=lat, 
        text=paste0(df_cities$cities,'<br>Population: ', df_cities$pop), 
        marker= list(size = sqrt(pop/10000) + 1), type="scattergeo",
        filename="Whosebug/choropleth+scattergeo") %>%
  add_trace(z=df_states$pop,
            locations=df_states$state_codes, 
            text=paste0(df_states$state_codes, '<br>Population: ', df_states$pop),
            type="choropleth", 
            colors = 'Purples', 
            locationmode="USA-states") %>%
  layout(geo = list(scope="usa"))

Interactive version with hover text

请注意，第二条轨迹中的 z 和 locations 列明确来自 df_states 数据框。如果它们来自与第一条轨迹相同的数据帧（df_cities 在 plot_ly 中声明），那么我们可以只写 z=state_codes 而不是 z=df_states$state_codes（如第二个示例中所示） ).

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