dreamrs / topogram

R htmlwidget for cartogram-chart

topogram

Cartogram htmlwidget for visualizing geographical data by distorting a TopoJson topology, using cartogram-chart

Installation

Install from GitHub:

remotes::install_github("dreamRs/topogram")

Overview

Created with:

library(topogram)
world %>% 
  topogram( 
    value = "pop_est", 
    label = "{name}: {format(pop_est, big.mark = ',')}",
    palette = scales::col_bin("viridis", bins = 20, domain = NULL)
  ) %>% 
  topogram_legend(
    title = "Population",
    formatter = scales::label_comma()
  ) %>% 
  topogram_labs(
    title = "World population",
    subtitle = "Population estimate for 2017",
    caption = "Data source: NaturalEarth"
  )

More examples in the {pkgdown} website

Development

This package use {packer} to manage JavaScript assets, see packer's documentation for more.

Install nodes modules with:

packer::npm_install()

Modify srcjs/widgets/topogram.js, then run:

packer::bundle()

Re-install R package and try topogram() functions.

topogram's Issues

New Zealand maps

Would it be possible to add New Zealand maps? I tried to have a go myself, but the topojson files I created threw errors.

There are shape files available from Statistics NZ

I grabbed the "New Zealand 2017 clipped generalised" file to get territorial authorities (TA) and regional councils (REGC), and "New Zealand Electoral Districts 2014" to get the general (GED) and Māori (MED) electorates, as we've just had an election (though annoyingly these are to the 12 nautical mile boundary at the coast).

consider geojsonsf

I see you're using geojsonio to convert sf objects to GeoJSON. Would you consider using geojonsf to improve speed?

Hopefully in this benchmark I'm replicating what you're doing inside topogram

library(microbenchmark)
library(geojsonsf)
library(geojsonio)

microbenchmark(
  
  geojsonsf = {
    shape$id <- 1:nrow(shape)
    sf_geojson( shape )
  },
  geojsonio = {
    geo_list <- geojson_list(input = shape)
    for (i in seq_along(geo_list$features)) {
      geo_list$features[[i]]$id <- i - 1
      geo_list$features[[i]]$properties$id <- i - 1
    }
    geo_json <- geojson_json(input = geo_list)
  },
  times = 5
  
)
# Unit: milliseconds
# expr        min         lq       mean     median         uq        max neval
# geojsonsf   1.955478   2.078431   2.172361   2.126749   2.226844   2.474302     5
# geojsonio 235.419525 239.354627 241.348199 240.610821 242.299392 249.056631     5

Note, I'm planning an update to geojsonsf by the end of October with some important fixes & updates.

---

You can also specify package version dependencies inside the DESCRIPTION in place of inside functions

  if (packageVersion("geojsonio") < "0.6.0.9100")
    stop("You need geojsonio >= 0.6.0.9100 to use this function.", call. = FALSE)

vs

Imports: 
    htmlwidgets,
    geojsonio (>=0.6.09100),
    htmltools,
    shiny,
    rmarkdown,
    jsonlite,
    magrittr

This way you don't have to implement the version check inside each function which may require it.

Only france-reg, france-reg-2016, france-dep, usa-states are available?

Any chance more regions will be included?
Thank you.