arcgisplaces is an R package to interface with ArcGIS Places Service.
The places service is a ready-to-use location service that can search for businesses and geographic locations around the world. It allows you to find, locate, and discover detailed information about each place.
In order to use {arcgisplaces}
you will need an ArcGIS Developers
account. Get started
here.
You can install a binary of the development version of arcgisplaces from r-universe with:
install.packages("arcgisgeocode", repos = "https://r-arcgis.r-universe.dev")
You will also need the development version of
{arcgisutils}
if (!requireNamespace("pak")) install.packages("pak")
pak::pak("r-arcgis/arcgisutils")
Or, you can install the development version from GitHub. Note the development version requires an installation of Rust. See rustup for instructions to install Rust.
if (requireNamespace("pak")) install.packages("pak")
pak::pak("r-arcgis/arcgisplaces")
Finding places:
near_point()
: search for places near a location.within_extent()
: search for places within an extent.place_details()
: get detailed information about the places returned fromnear_point()
orwithin_extent()
.- Note: see
fields
for the possible attributes to return for place details.
- Note: see
Understanding categories:
-
categories()
: find categories by name or ID. -
category_details()
: get detailed information about the categories returned fromcategories()
. -
Find place attributes such as name, address, description, opening hours, price ratings, user ratings, and social links.
arcgisutils
is needed for authentication. The Places API supports
either using an API key via auth_key()
or one generated via OAuth2
using either auth_client()
or auth_code()
. See API
documentation
for more.
library(arcgisutils)
#>
#> Attaching package: 'arcgisutils'
#> The following object is masked from 'package:base':
#>
#> %||%
library(arcgisplaces)
# Authenticate with a Developer Account API Key
token <- auth_key()
set_arc_token(token)
You can search for places near a location with near_point()
.
coffee <- near_point(x = -122.334, y = 47.655, search_text = "Coffee")
coffee
#> Simple feature collection with 6 features and 5 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -1122.334 ymin: -952.345 xmax: 877.666 ymax: 1047.655
#> Geodetic CRS: WGS 84
#> place_id name
#> 1 f6059fc575735b5e3f558c96ab69e6f6 Irwin's Neighborhood Bakery and Cafe
#> 2 88a10ccf031f02ef2697591f72e1e169 Fuel Coffee
#> 3 a8c6da1aa0d08fe96e5d80d0f3b3de03 Friday Afternoon
#> 4 906da2fe5164619199a2f2ba9c99a650 Starbucks
#> 5 d49bac9ae79ebfc88dc2c070ad0ee91c HHD Heuk Hwa Dang
#> 6 4bdfa82268e67a698d0b8ea3d2df3853 A Muddy Cup
#> distance categories icon geometry
#> 1 97.0 c("13002.... <NA> POINT (-122.3328 47.65539)
#> 2 723.8 c("13035.... <NA> POINT (-122.3369 47.66122)
#> 3 740.8 c("13036.... <NA> POINT (-122.342 47.65895)
#> 4 767.3 13035, C.... <NA> POINT (-122.3361 47.66175)
#> 5 964.1 13033, B.... <NA> POINT (-122.3425 47.66153)
#> 6 964.2 c("13035.... <NA> POINT (-122.3255 47.66149)
Locations are returned as an sf object with the place ID, the place name, distance from the search point, a character vector of categories.
Tip
arcgisplaces
will return an sf object, but the sf package is not
required to work with the package. The sf
print method will not be
used unless the package is loaded. If package size is a
consideration—i.e. deploying an app in a Docker container—consider
using wk
or rsgeo
.
Details for the places can be fetched using place_details()
. The
possible fields are documented
online
as well as contained in the exported vector fields
. Because pricing is
dependent upon which fields are requested, it is a required argument.
To get the add requested_fields = "hours"
. Note, that the other
possible fields will still be present in the result, but completely
empty.
details <- place_details(
coffee$place_id,
requested_fields = "rating",
.progress = FALSE # remove progress bar
)
details[c("price", "user")]
#> Simple feature collection with 6 features and 2 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: Inf ymin: Inf xmax: -Inf ymax: -Inf
#> Geodetic CRS: WGS 84
#> price user location
#> 1 Cheap 4.0 POINT EMPTY
#> 2 Cheap 3.9 POINT EMPTY
#> 3 Moderate NA POINT EMPTY
#> 4 Cheap 3.4 POINT EMPTY
#> 5 <NA> NA POINT EMPTY
#> 6 Cheap 3.9 POINT EMPTY
Or, you can search for places within a bounding box using
within_extent()
. This could be quite handy for searching within
current map bounds, for example.
bakeries <- within_extent(
-70.356, 43.588, -70.176, 43.7182,
category_id = "13002"
)
bakeries[c("name")]
#> Simple feature collection with 29 features and 1 field
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -70.356 ymin: 43.588 xmax: -70.176 ymax: 43.7182
#> Geodetic CRS: WGS 84
#> First 10 features:
#> name geometry
#> 1 Crumbl Cookies POINT (-70.33067 43.67675)
#> 2 Electric Bike Cafe POINT (-70.2864 43.63655)
#> 3 Gross Confection Bakery POINT (-70.25428 43.65763)
#> 4 Dina’s Cuisine POINT (-70.28725 43.67695)
#> 5 Lolli and Pops POINT (-70.33512 43.63377)
#> 6 C Salt Gourmet Market POINT (-70.2271 43.59174)
#> 7 Bread & Friends POINT (-70.25693 43.65514)
#> 8 BenReuben’s Knishery POINT (-70.25299 43.63748)
#> 9 Katie Made Bakery POINT (-70.24992 43.66449)
#> 10 Cinnamon Girl POINT (-70.27412 43.68086)