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https://github.com/symbolixau/geojsonsf

Conversion between sf and geojson

https://github.com/symbolixau/geojsonsf

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
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    DOI references
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    Academic publication links
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    Committers with academic emails
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  • ○
    Scientific vocabulary similarity
    Low similarity (15.8%) to scientific vocabulary

Keywords

geojson geospatial gis r rstats simplefeature well-known-text

Keywords from Contributors

google-map geo mapbox-gl-js mapbox-gl deckgl spatial-analysis google-maps-javascript-api google-maps-api rspatial proj
Last synced: 5 months ago · JSON representation

Repository

Conversion between sf and geojson

Basic Info
  • Host: GitHub
  • Owner: SymbolixAU
  • License: other
  • Language: R
  • Default Branch: master
  • Size: 11.2 MB
Statistics
  • Stars: 84
  • Watchers: 5
  • Forks: 7
  • Open Issues: 8
  • Releases: 9
Topics
geojson geospatial gis r rstats simplefeature well-known-text
Created almost 8 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License

README.Rmd 

---
title: geojsonsf
output: github_document
always_allow_html: yes
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "# ",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/geojsonsf)](https://CRAN.R-project.org/package=geojsonsf)
![downloads](http://cranlogs.r-pkg.org/badges/grand-total/geojsonsf)
[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/geojsonsf)](https://CRAN.R-project.org/package=geojsonsf)
[![Github Stars](https://img.shields.io/github/stars/SymbolixAU/geojsonsf.svg?style=social&label=Github)](https://github.com/SymbolixAU/geojsonsf)
[![R build status](https://github.com/symbolixau/geojsonsf/workflows/R-CMD-check/badge.svg)](https://github.com/symbolixau/geojsonsf/actions)
[![Coverage Status](https://codecov.io/github/SymbolixAU/geojsonsf/coverage.svg?branch=master)](https://codecov.io/github/SymbolixAU/geojsonsf?branch=master)

--

## geojsonsf

A simple, low-dependency and **fast** converter between GeoJSON and Simple Feature objects in R. 

---

**v1.3.2** 

Converts

- GeoJSON --> `sf`
- GeoJSON --> `sfc`
- `sf`    --> GeoJSON
- `sfc`   --> GeoJSON
- GeoJSON --> Well-known text
- data.frame --> GeoJSON (POINT only)

As per GeoJSON ([RFC 7946 specification)](https://tools.ietf.org/html/rfc7946#page-11), foreign members are ignored, and nested objects and arrays inside the `properties` object are converted to string/characters. 

Also, as per the specification, **CRS** 

> The coordinate reference system for all GeoJSON coordinates is a
geographic coordinate reference system, using the World Geodetic
System 1984 (WGS 84) [WGS84] datum, with longitude and latitude units
of decimal degrees. This is equivalent to the coordinate reference
system identified by the Open Geospatial Consortium (OGC) URN
urn:ogc:def:crs:OGC::CRS84

From **v1.3.2**, if your coordinates are in a different CRS you can specify the CRS & proj4string values in the `geojson_sf()` and `geojson_sfc()` functions. 

## Installation

Install the CRAN version with


```{r, eval = F}
install.packages("geojsonsf")
```


To install the development version

```{r gh-installation, eval = FALSE}
# install.packages("devtools")
devtools::install_github("SymbolixAU/geojsonsf")
```

## Why did you build it?

To quickly parse between GeoJSON and `sf` objects, and to handle cases not supported by `sf`, e.g. arrays of geometries

```{r, echo=FALSE, warning=FALSE, message=FALSE}
library(geojsonsf)
library(sf)        ## Loaded for sf print methods
```


## What do you mean, 'cases not supported'

For example, `sf` can't read an array of GeoJSON objects, so I wanted to make this work

```{r}
js <- c(
	'[
	  {"type":"Point","coordinates":[0,0]},
	  {"type":"LineString","coordinates":[[-1,-1],[1,1]]},
		{
      "type": "FeatureCollection",
      "features": [
      {
        "type": "Feature",
        "properties": {"id":1},
        "geometry": {"type": "Point", "coordinates": [100.0, 0.0]}
      }
    ]
  }
	]'
)

sf <- geojson_sf( js )
sf
```


And going the other way you can also return a vector of GeoJSON

```{r}
js <- sf_geojson( sf, atomise = T )
js
```

### What's the benefit of 'atomising'?

It's useful for when you work with geospatial databases and want an individual record for each individual feature. 

### What happens if you don't `atomise`?

You get a single GeoJSON object

```{r}
sf_geojson( sf )
```


### Can you remove the properites and just return the geometries

Yes. Call `sfc_geojson()` on the `sfc` object.

```{r}
sfc_geojson( sf$geometry )
```

### If I have an `sf` object without any properties, why does it 'atomise' by default?

```{r}
sf$id <- NULL
sf_geojson( sf )
```

The `simplify` argument is `TRUE` by default, and it will try and 'simplify' the GeoJSON. If there are no properties in the `sf` object, then the GeoJSON won't have any properties.

However, if you set `simplify = FALSE` you'll get a FeatureCollection with an empty properties field.

```{r}
sf_geojson(sf, simplify = F)
```


### How fast is it?

This benchmark shows a comparison with `library(sf)` for converting a string of GeoJSON of 3,221 counties in the US in to an `sf` object

```{r,eval= FALSE}
myurl <- "http://eric.clst.org/assets/wiki/uploads/Stuff/gz_2010_us_050_00_500k.json"
geo <- readLines(myurl)
geo <- paste0(geo, collapse = "")

library(microbenchmark)

microbenchmark(
    geojsonsf = {
        geojson_sf(geo)
    },
    sf = {
        sf::st_read(geo, quiet = T)
    },
    times = 2
)

#Unit: milliseconds
#      expr       min        lq      mean    median        uq       max  neval
# geojsonsf  709.2268  709.2268  722.0626  722.0626  734.8984  734.8984      2
#        sf 1867.6840 1867.6840 1958.7968 1958.7968 2049.9097 2049.9097      2
```

Owner

  • Name: SymbolixAU
  • Login: SymbolixAU
  • Kind: organization
  • Location: Melbourne, Australia

GitHub Events

Total
  • Issues event: 2
  • Watch event: 3
  • Issue comment event: 1
Last Year
  • Issues event: 2
  • Watch event: 3
  • Issue comment event: 1

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 350
  • Total Committers: 7
  • Avg Commits per committer: 50.0
  • Development Distribution Score (DDS): 0.177
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
SymbolixAU d****y@s****u 288
David d****1@g****m 52
SymbolixAU d****y@S****u 4
Andy Teucher a****r@g****m 3
blacklime a****s@b****o 1
dcooley = 1
SymbolixAU d****t@s****u 1
Committer Domains (Top 20 + Academic)
symbolix.com.au: 3 blacklime.io: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 79
  • Total pull requests: 23
  • Average time to close issues: about 2 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 27
  • Total pull request authors: 4
  • Average comments per issue: 2.32
  • Average comments per pull request: 0.3
  • Merged pull requests: 21
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: about 3 hours
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • SymbolixAU (43)
  • dcooley (6)
  • layik (5)
  • lorenzwalthert (2)
  • coolbutuseless (1)
  • mpadge (1)
  • ateucher (1)
  • cywhale (1)
  • frabau1 (1)
  • mem48 (1)
  • RobertMyles (1)
  • aoles (1)
  • SimonGoring (1)
  • etiennekintzler (1)
  • clozanoruiz (1)
Pull Request Authors
  • SymbolixAU (19)
  • layik (2)
  • ateucher (2)
  • techisdead (1)
Top Labels
Issue Labels
bug (4) enhancement (4) invalid (1) wontfix (1) help wanted (1)
Pull Request Labels

Packages

  • Total packages: 4
  • Total downloads:
    • cran 135,973 last-month
  • Total docker downloads: 951,508
  • Total dependent packages: 40
    (may contain duplicates)
  • Total dependent repositories: 65
    (may contain duplicates)
  • Total versions: 26
  • Total maintainers: 1
proxy.golang.org: github.com/symbolixau/geojsonsf
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 7 months ago
proxy.golang.org: github.com/SymbolixAU/geojsonsf
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
cran.r-project.org: geojsonsf

GeoJSON to Simple Feature Converter

  • Versions: 11
  • Dependent Packages: 37
  • Dependent Repositories: 63
  • Downloads: 135,973 Last month
  • Docker Downloads: 951,508
Rankings
Dependent packages count: 2.1%
Downloads: 2.5%
Dependent repos count: 3.1%
Stargazers count: 4.6%
Average: 6.3%
Forks count: 8.0%
Docker downloads count: 17.6%
Maintainers (1)
dcooley@symbolix.com.au
Last synced: 6 months ago
conda-forge.org: r-geojsonsf
  • Versions: 5
  • Dependent Packages: 3
  • Dependent Repositories: 2
Rankings
Dependent packages count: 15.6%
Dependent repos count: 20.3%
Average: 29.9%
Stargazers count: 36.1%
Forks count: 47.5%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.3.0 depends
  • Rcpp * imports
  • covr * suggests
  • jsonify * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • tinytest * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/cache v1 composite
  • actions/checkout v2 composite
  • actions/upload-artifact master composite
  • r-lib/actions/setup-pandoc master composite
  • r-lib/actions/setup-r master composite