Package 'leafdown'

Title: Provides Drill Down Functionality for 'leaflet' Choropleths
Description: Provides drill down functionality for 'leaflet' choropleths in 'shiny' apps.
Authors: Andreas Hofheinz [cre], Peter Gandenberger [aut]
Maintainer: Andreas Hofheinz <[email protected]>
License: GPL-3
Version: 1.2.0
Built: 2026-05-21 09:26:18 UTC
Source: https://github.com/cran/leafdown

Help Index

Check whether the given join_map_levels_by is valid

Description

The join_map_levels_by must be a named vector of at most one element. The columns specified in the vector must be data slots of the spdfs in the spdfs_list.

Usage

assert_join_map_levels_by(join_map_levels_by, spdfs_list)

Arguments

join_map_levels_by

A named vector with the columns to join the map levels by.
spdfs_list

A list with the spdfs of all map levels.

Value

the join_map_levels_by in the right order

Check whether the given spdf_list is a valid spdf_list and has all the required params.

Description

The spdf_list must be a list of at most two elements. All elements must be a s4 class of type SpatialPolygonsDataFrame.

Usage

assert_spdf_list(spdfs_list)

Arguments

spdfs_list

A list with the spdfs of all map levels

Value

TRUE if spdf_list is valid.

Checks for undesired arguments in ellipsis in $draw_leafdown method

Description

Checks arguments in ellipsis for undesired inputs such as 'layerId' which may collide with internal structure of leafdown and returns a "cleaned" version of the arguments by removing or redefining problematic inputs. e.g. 'layerId' is removed from arg_list when set.

Usage

check_draw_ellipsis(...)

Arguments

...

Additional arguments given to leaflet::addPolygons

Value

List containing arguments in ... as elements

GPD for administrative districts of Germany for 2014.

Description

A dataset containing the GPD (gross domestic product) for 402 administrative districts of Germany for the year 2014.

Usage

gdp_2014_admin_districts

Format

A data frame with 402 rows and 2 variables:

Admin_District

Name of the administrative district

GDP_2014

GDP for the year 2014, in euro

Source

Landatlas (www.landatlas.de). Ausgabe 2018. Hrsg.: Thuenen-Institut fuer Laendliche Raeume - Braunschweig 2018.

Note that in this package we have slightly adapted some names of the administrative districts for a better match.

GPD for federal states of Germany for 2014.

Description

A dataset containing the GPD (gross domestic product) for all 16 federal states of Germany for the year 2014.

Usage

gdp_2014_federal_states

Format

A data frame with 16 rows and 2 variables:

Federal_State

Name of the federal state

GDP_2014

GDP for the year 2014, in euro

Source

Arbeitskreis Volkswirtschaftliche Gesamtrechnungen der Laender: https://www.deutschlandinzahlen.de

Leafdown R6 Class

Description

This class acts as a wrapper around a leafdown map.

Active bindings

curr_sel_data

A reactiveValue containing a data.frame with the metadata and (if available) the corresponding values of all currently selected shapes.

curr_data

The metadata and (if available) the corresponding values of all currently displayed shapes.

curr_map_level

Index of the current map level. This corresponds to the position of the shapes in the spdfs_list. (i.e The highest-level is 1, the next is 2 and so on...).

curr_poly_ids

The ids of all polygons of the current map level.

Methods

Public methods

Method new()

Initializes the leafdown object.

Usage
Leafdown$new(spdfs_list, map_output_id, input, join_map_levels_by = NULL)
Arguments
spdfs_list

A list with the spdfs of all map levels. This cannot be changed later.

map_output_id

The id from the shiny-ui used in the leafletOutput("<<id>>"). Used to observe for _shape_click events.

input

The input from the shiny app.

join_map_levels_by

A named vector of length length(spdfs_list) - 1 with the columns by which the map levels should be joined. The first element defines how the first and second map levels should be joined, the second element does the same for the second and third map levels and so on. The name of an element defines the name of the join column in the upper map level and the actual element the join column of the lower map level. By default this is set to c("GID_0" = "GID_0", "GID_1" = "GID_1", ..., "GID_n" = "GID_n"), where n is length(spdfs_list) - 1.

Method draw_leafdown()

Draws the leaflet map on the current map level. All unselected parents will be drawn in gray.

Usage
Leafdown$draw_leafdown(...)
Arguments
...

Additional arguments given to leaflet::addPolygons

Method keep_zoom()

Keeps the zoom after drill_down and drill_up events.

Usage
Leafdown$keep_zoom(map, input)
Arguments
map

the map output from draw_leafdown

input

the input object from the shiny app

Method add_data()

Adds the data to the currently displayed shapes. This includes the meta-data AND the values to be visualized in the map.

Usage
Leafdown$add_data(data)
Arguments
data

The new data existing of the meta-data and the values to display in the map(color)

Method drill_down()

Drills down to the lower level if:

  • there is a lower level (for now there are only two levels)

  • at least one shape is selected to drill down on

This will not redraw the map. Also call add_data to add data for the new level and then draw_leafdown to redraw the map on the new level.

Usage
Leafdown$drill_down()

Method drill_up()

Drills up to the higher level if:

  • there is a higher level (for now there are only two levels)

This will not redraw the map. Also call add_data to add data for the new level and then draw_leafdown to redraw the map on the new level.

Usage
Leafdown$drill_up()

Method toggle_shape_select()

Selects the shape with the given shape id, or unselects it if it was already selected.

Usage
Leafdown$toggle_shape_select(shape_id)
Arguments
shape_id

the id of the shape to select, has to be a character and in the current map-level.

Method clone()

The objects of this class are cloneable with this method.

Usage
Leafdown$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

## Not run: 

library(leafdown)
library(leaflet)
library(shiny)
library(dplyr)
library(shinyjs)

ger1 <- raster::getData(country = "Germany", level = 1)
ger2 <- raster::getData(country = "Germany", level = 2)
spdfs_list <- list(ger1, ger2)

ui <- shiny::fluidPage(
  useShinyjs(),
  actionButton("drill_down", "Drill Down"),
  actionButton("drill_up", "Drill Up"),
  leafletOutput("leafdown")
)

server <- function(input, output) {
  my_leafdown <- Leafdown$new(spdfs_list, "leafdown", input)
  update_leafdown <- reactiveVal(0)

  observeEvent(input$drill_down, {
    my_leafdown$drill_down()
    update_leafdown(update_leafdown() + 1)
  })

  observeEvent(input$drill_up, {
    my_leafdown$drill_up()
   update_leafdown(update_leafdown() + 1)
 })

  output$leafdown <- renderLeaflet({
    update_leafdown()
    meta_data <- my_leafdown$curr_data
    curr_map_level <- my_leafdown$curr_map_level
    if (curr_map_level == 1) {
      data <- meta_data %>%
        left_join(gdp_2014_federal_states, by = c("NAME_1" = "Federal_State"))
    } else {
      data <- meta_data %>%
        left_join(gdp_2014_admin_districts, by = c("NAME_2" = "Admin_District"))
    }

    my_leafdown$add_data(data)
    my_leafdown$draw_leafdown(
      fillColor = ~ colorNumeric("Greens", GDP_2014)(GDP_2014), weight = 2, color = "grey"
    )
  })
}

shinyApp(ui, server)


## End(Not run)

Results of the 2016 US Presidential Election - County Level

Description

A dataset containing the results of the presidential election and census data (e.g. racial makeup, unemployment)

Usage

us_election_counties

Format

A data frame with 3,143 rows and 17 total columns

State

Name of the State

ST

Abbreviation of the State name

County

Name of the County

Votes

Total number of votes cast

Republicans2016

Percent of votes for the Republican Party

Democrats2016

Percent of votes for the Democratic Party

Green2016

Percent of votes for the Green Party

Libertarians2016

Percent of votes for the Libertarian Party

TotalPopulation

Total Population of the county

Unemployment

Percent of unemployment

White

Percentage of Whites

Black

Percentage of Blacks

Hispanic

Percentage of Hispanics

Asian

Percentage of Asians

Amerindian

Percentage of Amerindians

Other

Percentage of Other Races

NAME_2

The short County name, used for matching with the map

Source

https://github.com/Deleetdk/USA.county.data

Results of the 2016 US Presidential Election - State Level

Description

A dataset containing the results of the presidential election and census data (e.g. racial makeup, unemployment)

Usage

us_election_states

Format

A data frame with 51 rows and 15 total columns

State

Name of the State

ST

Abbreviation of the State name

Votes

Total number of votes cast

Republicans2016

Percent of votes for the Republican Party

Democrats2016

Percent of votes for the Democratic Party

Green2016

Percent of votes for the Green Party

Libertarians2016

Percent of votes for the Libertarian Party

TotalPopulation

Total Population of the county

Unemployment

Percent of unemployment

White

Percentage of Whites

Black

Percentage of Blacks

Hispanic

Percentage of Hispanics

Asian

Percentage of Asians

Amerindian

Percentage of Amerindians

Other

Percentage of Other Races

Source

https://github.com/Deleetdk/USA.county.data

Note: The data was aggregated from the county level