plotly / plotly/plotly.R

Strange results with GeoJSON

Open
#1,778 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
R
Stars
2.7k
Forks
641
PR merge metrics
No merged PRs in 30d

Description

I tried plot choropleth with Highcharts GeoJSON.

Code to reproduce:

# packages ----------------------------------------------------------------
library(jsonlite)
library(plotly)

# prepare data ------------------------------------------------------------
# read geo data
map_data <- read_json(path = "https://raw.githubusercontent.com/highcharts/map-collection-dist/master/countries/es/es-all.geo.json")
# fill values to draw
df <- data.frame(
  id = unlist(lapply(map_data$features, "[[", "id")),
  name = unlist(lapply(map_data$features, "[[", c("properties", "name")))
)
df$value <- as.integer(runif(NROW(df), 0, 100))

# plotly ------------------------------------------------------------------
plotly_plt <- plot_ly() %>%
  add_trace(
    type = "choropleth",
    geojson = map_data,
    locations = df[["id"]],
    z = df[["value"]]
  ) %>%
  layout(
    geo = list(
      fitbounds = "locations"
    )
  )
plotly_plt

Screenshot of the result:
image

P.S.: This issue is repost SO question. Posted here because no responses on the SO.

Additional information:

─ Session info ────────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 4.0.0 (2020-04-24)
 os       Arch Linux                  
 system   x86_64, linux-gnu           
 ui       RStudio                     
 language                             
 collate  ru_RU.UTF-8                 
 ctype    ru_RU.UTF-8                 
 tz       Asia/Novokuznetsk           
 date     2020-05-24                  

─ Packages ────────────────────────────────────────────────────────────────────
 package     * version date       lib source        
 assertthat    0.2.1   2019-03-21 [1] CRAN (R 4.0.0)
 cli           2.0.2   2020-02-28 [1] CRAN (R 4.0.0)
 colorspace    1.4-1   2019-03-18 [1] CRAN (R 4.0.0)
 crayon        1.3.4   2017-09-16 [1] CRAN (R 4.0.0)
 crosstalk     1.1.0.1 2020-03-13 [1] CRAN (R 4.0.0)
 data.table    1.12.8  2019-12-09 [1] CRAN (R 4.0.0)
 digest        0.6.25  2020-02-23 [1] CRAN (R 4.0.0)
 dplyr         0.8.5   2020-03-07 [1] CRAN (R 4.0.0)
 ellipsis      0.3.1   2020-05-15 [1] CRAN (R 4.0.0)
 fansi         0.4.1   2020-01-08 [1] CRAN (R 4.0.0)
 farver        2.0.3   2020-01-16 [1] CRAN (R 4.0.0)
 ggplot2     * 3.3.0   2020-03-05 [1] CRAN (R 4.0.0)
 glue          1.4.1   2020-05-13 [1] CRAN (R 4.0.0)
 gtable        0.3.0   2019-03-25 [1] CRAN (R 4.0.0)
 htmltools     0.4.0   2019-10-04 [1] CRAN (R 4.0.0)
 htmlwidgets   1.5.1   2019-10-08 [1] CRAN (R 4.0.0)
 httr          1.4.1   2019-08-05 [1] CRAN (R 4.0.0)
 jsonlite    * 1.6.1   2020-02-02 [1] CRAN (R 4.0.0)
 lazyeval      0.2.2   2019-03-15 [1] CRAN (R 4.0.0)
 lifecycle     0.2.0   2020-03-06 [1] CRAN (R 4.0.0)
 magrittr      1.5     2014-11-22 [1] CRAN (R 4.0.0)
 munsell       0.5.0   2018-06-12 [1] CRAN (R 4.0.0)
 pillar        1.4.4   2020-05-05 [1] CRAN (R 4.0.0)
 pkgconfig     2.0.3   2019-09-22 [1] CRAN (R 4.0.0)
 plotly      * 4.9.2.1 2020-04-04 [1] CRAN (R 4.0.0)
 purrr         0.3.4   2020-04-17 [1] CRAN (R 4.0.0)
 R6            2.4.1   2019-11-12 [1] CRAN (R 4.0.0)
 Rcpp          1.0.4.6 2020-04-09 [1] CRAN (R 4.0.0)
 rlang         0.4.6   2020-05-02 [1] CRAN (R 4.0.0)
 rstudioapi    0.11    2020-02-07 [1] CRAN (R 4.0.0)
 scales        1.1.1   2020-05-11 [1] CRAN (R 4.0.0)
 sessioninfo   1.1.1   2018-11-05 [1] CRAN (R 4.0.0)
 tibble        3.0.1   2020-04-20 [1] CRAN (R 4.0.0)
 tidyr         1.1.0   2020-05-20 [1] CRAN (R 4.0.0)
 tidyselect    1.1.0   2020-05-11 [1] CRAN (R 4.0.0)
 vctrs         0.3.0   2020-05-11 [1] CRAN (R 4.0.0)
 viridisLite   0.3.0   2018-02-01 [1] CRAN (R 4.0.0)
 withr         2.2.0   2020-04-20 [1] CRAN (R 4.0.0)
 yaml          2.2.1   2020-02-01 [1] CRAN (R 4.0.0)

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by running the reproducible R example using the Highcharts Spain GeoJSON and inspect how the choropleth trace handles geojson, locations, and fitbounds. Compare the rendered map with the supplied screenshot; done means the GeoJSON regions and generated values are displayed in the expected locations without the reported strange result.

Written by the indexing model from the issue text.

Assessment

Tech stack
r
Domain
data-visualization
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.