🚧 Warning! The `notaurin` package is not affiliated with AURIN in
any way. 🚧
The official AURIN R tutorial can be found here. Want to know a more convenient way to access the AURIN data portal from R which AURIN simply doesn’t seem to offer? Maybe give {notaurin} a try. 😬
The goal of {notaurin} is to provide an easy way for R users to access MORE THAN 5000 OPEN DATASETS on AURIN using their Data Portal. You can request an API key from:
AURIN is “Australia’s 🦘 single largest resource for accessing clean, integrated, spatially enabled and research-ready data on issues surrounding health and wellbeing, socio-economic metrics, transportation, and land-use.”
Here are ways you can install notaurin:
# from CRAN for the latest version
install.packages("notaurin")
# from GitHub for the latest development version
install.packages("remotes")
remotes::install_github("asiripanich/notaurin")This package requires the sf package. Please see the sf package’s GitHub page to install its non R dependencies.
First, you must add your AURIN API username and
password as an R
environment variable to your .Renviron file. notaurin provides
aur_register() function to help you with this step. If you choose to
set add_to_renviron = TRUE you won’t need to run this step again on
current machine after you restart your R session.
library(notaurin)
# add_to_renviron = TRUE, so you won't need to run this step again on current machine.
aur_register(username = "your-username", password = "your-password", add_to_renviron = T) aur_browse() opens the data catalogue of
AURIN on your default browser.
aur_browse()Identify the ‘AURIN Open API ID’ field on the ‘Additional Info’
table of the dataset that you want to download. For example, for this
public toilet 2017
dataset
its ‘AURIN Open API ID’ field is
"aurin:datasource-UQ_ERG-UoM_AURIN_DB_public_toilets".
Note that, some datasets on AURIN may not have ‘AURIN Open API ID’, meaning that it cannot be downloaded via their API.
Alternatively, you may use aur_meta to search datasets without leaving
your R console.
meta <- aur_meta()
#> ℹ Creating AURIN WFS Client...
#> ℹ Fetching available datasets...
# print out the first five rows
knitr::kable(head(meta))| aurin_open_api_id | title |
|---|---|
| datasource-NSW_Govt_DPE-UoM_AURIN_DB:nsw_srlup_additional_rural_2014 | Additional Rural Village Land 18/01/2014 for NSW |
| datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:aus_2016_aust | ABS - ASGS - Country (AUS) 2016 |
| datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:gccsa_2011_aust | ABS - ASGS - Greater Capital City Statistical Area (GCCSA) 2011 |
| datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:gccsa_2016_aust | ABS - ASGS - Greater Capital City Statistical Area (GCCSA) 2016 |
| datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:mb_2016_aust | ABS - ASGS - Mesh Block (MB) 2016 |
| datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:mb_2011_act | ABS - ASGS - Mesh Block (MB) ACT 2011 |
Use aur_get() to download the dataset.
# download this public toilet dataset.
open_api_id <- "datasource-AU_Govt_DSS-UoM_AURIN:national_public_toilets_2017"
public_toilets <- aur_get(open_api_id = open_api_id)
#> ℹ Downloading 'datasource-AU_Govt_DSS-UoM_AURIN:national_public_toilets_2017'...�[K✔ Downloading 'datasource-AU_Govt_DSS-UoM_AURIN:national_public_toilets_2017'... [2.6s]�[K
state_polygons <- aur_get(open_api_id = "datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:ste_2016_aust")
#> ℹ Downloading 'datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:ste_2016_aust'...�[K✔ Downloading 'datasource-AU_Govt_ABS-UoM_AURIN_DB_GeoLevel:ste_2016_aust'... [6.6s]�[K
state_polygons <- state_polygons[state_polygons$state_code_2016 %in% 1:8, ]Let’s visualise the data using the ggplot2 package.
# If you don't have the package you can install it with `install.packages("ggplot2")`.
library(ggplot2)
ggplot(public_toilets) +
geom_sf(data = state_polygons, fill = "antiquewhite") +
geom_sf(alpha = 0.05, aes(color = status)) +
labs(title = "Public toilets in Australia, 2017") +
scale_color_brewer(palette = "Dark2") +
theme_bw() +
guides(colour = guide_legend(override.aes = list(alpha = 1))) +
theme(panel.background = element_rect(fill = "aliceblue"))
See here to find available datasets.
When there are many datasets that you need to download, you may want to put all of your CPUs to work. The code chucks below show how you can download multiple datasets in parallel using the {furrr} and {future} packages.
First, setup the workers - this affects how many datasets you can
download in parallel at the same time. The maximum number of workers of
your machine can be determined using future::availableCores().
library(furrr)
library(future)
future::plan(future::multiprocess, workers = 2)
#> Warning: Strategy 'multiprocess' is deprecated in future (>= 1.20.0) [2020-10-30]. Instead, explicitly specify either 'multisession' (recommended) or 'multicore'. In the current R session,
#> 'multiprocess' equals 'multicore'.Let’s assume you want the first 10 rows of all datasets on AURIN with the word “toilet” in their title.
knitr::kable(meta[grepl("toilet", meta$title, ignore.case = T), ])| aurin_open_api_id | title | |
|---|---|---|
| 1519 | datasource-AU_Govt_DSS-UoM_AURIN:national_public_toilets_2017 | DSS - National Public Toilets (Point) 2017 |
| 1579 | datasource-AU_Govt_Doh-UoM_AURIN_DB_1:national_toilet_map_2018_06 | Department of Health - National Toilet Map - June 2018 |
| 3117 | datasource-UQ_ERG-UoM_AURIN_DB:public_toilets | Public Toilets 2004-2014 for Australia |
Extract their AURIN open API ids and download all of them in parallel.
toilet_datasets_ids <- meta$aurin_open_api_id[grepl("toilet", meta$title, ignore.case = T)]
data_lst <- furrr::future_map(toilet_datasets_ids, ~ aur_get(.x, params = list(maxFeatures = 10)))
#> ℹ Downloading 'datasource-AU_Govt_DSS-UoM_AURIN:national_public_toilets_2017'...�[K✔ Downloading 'datasource-AU_Govt_DSS-UoM_AURIN:national_public_toilets_2017'... [2.7s]�[K
#> ℹ Downloading 'datasource-AU_Govt_Doh-UoM_AURIN_DB_1:national_toilet_map_2018_06'...�[K✔ Downloading 'datasource-AU_Govt_Doh-UoM_AURIN_DB_1:national_toilet_map_2018_06'... [2.7s]�[K
#> ℹ Downloading 'datasource-UQ_ERG-UoM_AURIN_DB:public_toilets'...�[K✔ Downloading 'datasource-UQ_ERG-UoM_AURIN_DB:public_toilets'... [2s]�[K
data_lst
#> [[1]]
#> Simple feature collection with 18789 features and 46 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 113.4102 ymin: -43.582 xmax: 153.6263 ymax: -10.57019
#> Geodetic CRS: WGS 84
#> # A tibble: 18,789 × 47
#> id toile…¹ url name addre…² town state postc…³ addre…⁴ male female unisex dump_…⁵ facil…⁶ toile…⁷ acces…⁸ payme…⁹ key_r…˟ acces…˟ parking parki…˟ acces…˟ acces…˟ acces…˟ acces…˟ mlak
#> <chr> <int> <chr> <chr> <chr> <chr> <chr> <int> <chr> <lgl> <lgl> <lgl> <lgl> <chr> <chr> <lgl> <lgl> <lgl> <chr> <lgl> <chr> <lgl> <lgl> <lgl> <chr> <lgl>
#> 1 national_p… 341 http… Elsi… Alden … Clif… Quee… 4361 <NA> TRUE TRUE FALSE FALSE Park o… <NA> FALSE FALSE FALSE <NA> FALSE <NA> TRUE TRUE FALSE <NA> FALSE
#> 2 national_p… 418 http… Luck… Lucky … Luck… Sout… 5602 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> TRUE <NA> FALSE FALSE FALSE <NA> FALSE
#> 3 national_p… 634 http… Olds… Holley… Mort… New … 2223 <NA> TRUE TRUE FALSE FALSE Park o… <NA> FALSE FALSE FALSE <NA> FALSE <NA> TRUE TRUE FALSE <NA> TRUE
#> 4 national_p… 1150 http… Jaeg… Hill S… Oran… New … 2800 <NA> TRUE TRUE FALSE FALSE Park o… <NA> FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE FALSE <NA> FALSE
#> 5 national_p… 1207 http… Lake… Evans … Shen… West… 6008 <NA> FALSE FALSE TRUE FALSE Park o… Automa… FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE TRUE <NA> FALSE
#> 6 national_p… 1535 http… Earl… Earl S… Coff… New … 2450 <NA> TRUE TRUE FALSE FALSE Sporti… Sewera… FALSE FALSE FALSE <NA> TRUE <NA> FALSE FALSE FALSE <NA> FALSE
#> 7 national_p… 1590 http… Truc… Davids… Deni… New … 2710 <NA> TRUE TRUE FALSE FALSE Car pa… Sewera… FALSE FALSE FALSE <NA> TRUE <NA> FALSE FALSE FALSE <NA> FALSE
#> 8 national_p… 1913 http… Hemi… High S… Belm… Vict… 3216 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> FALSE <NA> TRUE TRUE FALSE <NA> FALSE
#> 9 national_p… 2081 http… Eden… Eden V… Keyn… Sout… 5353 The to… TRUE TRUE FALSE FALSE Park o… Septic FALSE FALSE FALSE <NA> FALSE <NA> TRUE TRUE FALSE <NA> FALSE
#> 10 national_p… 2377 http… Wils… Wilson… Watt… Vict… 3096 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE FALSE <NA> FALSE
#> # … with 18,779 more rows, 21 more variables: parking_accessible <lgl>, access_parking_note <chr>, ambulant <lgl>, lh_transfer <lgl>, rh_transfer <lgl>, adult_change <lgl>, is_open <chr>,
#> # opening_hours <chr>, openinghours_note <chr>, baby_change <lgl>, showers <lgl>, drinking_water <lgl>, sharps_disposal <lgl>, sanitary_disposal <lgl>, icon_url <chr>, icon_alt_text <chr>,
#> # notes <chr>, status <chr>, latitude <dbl>, longitude <dbl>, geometry <POINT [°]>, and abbreviated variable names ¹toilet_id, ²address1, ³postcode, ⁴address_note, ⁵dump_point, ⁶facility_type,
#> # ⁷toilet_type, ⁸access_limited, ⁹payment_required, ˟key_required, ˟access_note, ˟parking_note, ˟accessible_male, ˟accessible_female, ˟accessible_unisex, ˟accessible_note
#>
#> [[2]]
#> Simple feature collection with 19034 features and 47 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 113.4102 ymin: -43.58278 xmax: 153.6263 ymax: -10.57019
#> Geodetic CRS: WGS 84
#> # A tibble: 19,034 × 48
#> id toile…¹ url name addre…² town state postc…³ addre…⁴ male female unisex dump_…⁵ facil…⁶ toile…⁷ acces…⁸ payme…⁹ key_r…˟ acces…˟ parking parki…˟ acces…˟ acces…˟ acces…˟ acces…˟ mlak
#> <chr> <int> <chr> <chr> <chr> <chr> <chr> <int> <chr> <lgl> <lgl> <lgl> <lgl> <chr> <chr> <lgl> <lgl> <lgl> <chr> <lgl> <chr> <lgl> <lgl> <lgl> <chr> <lgl>
#> 1 national_t… 272 http… Bris… Brisba… Merr… New … 2329 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE FALSE <NA> FALSE
#> 2 national_t… 578 http… Nati… Wimmer… Nati… Vict… 3409 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> FALSE <NA> TRUE TRUE FALSE <NA> FALSE
#> 3 national_t… 628 http… Brid… Bridge… Pens… New … 2222 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE FALSE <NA> FALSE
#> 4 national_t… 868 http… Sand… Oroya … Sand… West… 6639 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> TRUE <NA> TRUE TRUE FALSE <NA> FALSE
#> 5 national_t… 1300 http… Murr… Ravens… Rave… West… 6208 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> TRUE <NA> FALSE FALSE FALSE <NA> FALSE
#> 6 national_t… 1461 http… Menz… Purslo… Moun… West… 6016 <NA> TRUE TRUE FALSE FALSE Park o… Sewera… FALSE FALSE FALSE <NA> FALSE <NA> TRUE TRUE FALSE <NA> FALSE
#> 7 national_t… 1638 http… Roy … Warreg… Dula… Quee… 4425 <NA> TRUE TRUE FALSE FALSE Park o… Sewera… FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE TRUE <NA> FALSE
#> 8 national_t… 1750 http… Meri… Tagger… Meri… Vict… 3496 <NA> TRUE TRUE FALSE FALSE <NA> <NA> FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE FALSE <NA> FALSE
#> 9 national_t… 2520 http… Show… Evans … Wang… Vict… 3677 <NA> TRUE TRUE FALSE FALSE Sporti… <NA> FALSE FALSE FALSE <NA> FALSE <NA> FALSE FALSE FALSE <NA> FALSE
#> 10 national_t… 2725 http… Haro… Paxton… Clev… Quee… 4163 <NA> TRUE TRUE FALSE FALSE Park o… Sewera… FALSE FALSE FALSE <NA> TRUE <NA> FALSE FALSE FALSE <NA> FALSE
#> # … with 19,024 more rows, 22 more variables: parking_accessible <lgl>, access_parking_note <chr>, ambulant <lgl>, lh_transfer <lgl>, rh_transfer <lgl>, adult_change <lgl>, changing_places <lgl>,
#> # is_open <chr>, opening_hours <chr>, openinghours_note <chr>, baby_change <lgl>, showers <lgl>, drinking_water <lgl>, sharps_disposal <lgl>, sanitary_disposal <lgl>, icon_url <chr>,
#> # icon_alt_text <chr>, notes <chr>, status <chr>, latitude <dbl>, longitude <dbl>, geometry <POINT [°]>, and abbreviated variable names ¹toilet_id, ²address1, ³postcode, ⁴address_note, ⁵dump_point,
#> # ⁶facility_type, ⁷toilet_type, ⁸access_limited, ⁹payment_required, ˟key_required, ˟access_note, ˟parking_note, ˟accessible_male, ˟accessible_female, ˟accessible_unisex, ˟accessible_note
#>
#> [[3]]
#> Simple feature collection with 16737 features and 39 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 113.4102 ymin: -43.582 xmax: 153.6222 ymax: -10.57119
#> Geodetic CRS: WGS 84
#> # A tibble: 16,737 × 40
#> id ogc_fid status lastupdate name addre…¹ town state postc…² addre…³ male female unisex facil…⁴ toile…⁵ acces…⁶ payme…⁷ keyre…⁸ acces…⁹ parking parki…˟ yeari…˟ acces…˟ acces…˟ acces…˟ acces…˟
#> <chr> <int> <chr> <date> <chr> <chr> <chr> <chr> <chr> <chr> <int> <int> <chr> <chr> <chr> <int> <int> <int> <chr> <int> <chr> <chr> <int> <int> <int> <chr>
#> 1 publ… 28 Verif… 2008-02-13 Flyi… Esplan… Flyi… Quee… 4860 <NA> 1 1 <NA> <NA> <NA> 0 0 0 <NA> 0 <NA> <NA> 0 0 0 <NA>
#> 2 publ… 301 Verif… 2009-03-25 Tour… Leslie… Stan… Quee… 4380 <NA> 1 1 <NA> <NA> <NA> 0 0 0 <NA> 0 <NA> <NA> 1 1 0 <NA>
#> 3 publ… 381 Verif… 2010-03-24 Pinn… Day St… Pinn… Sout… 5304 <NA> 1 1 <NA> <NA> <NA> 0 0 0 <NA> 1 <NA> <NA> 0 0 0 <NA>
#> 4 publ… 500 Verif… 2008-01-30 Rive… <NA> Waik… Sout… 5330 <NA> 1 1 <NA> Park o… <NA> 0 0 0 <NA> 0 <NA> <NA> 0 0 0 <NA>
#> 5 publ… 612 Verif… 2008-02-18 Kend… <NA> Kend… West… 6323 <NA> 1 1 <NA> <NA> <NA> 0 0 0 <NA> 0 <NA> <NA> 0 0 0 <NA>
#> 6 publ… 620 Verif… 2006-02-10 Shen… 124 Sh… Menz… West… 6436 Toilet… 1 1 <NA> Other Sewera… 0 0 0 <NA> 0 <NA> <NA> 0 0 0 <NA>
#> 7 publ… 673 Verif… 2008-02-18 Rota… 1836 N… Sout… West… 6701 Near 1… 1 1 <NA> Park o… Septic 0 0 0 <NA> 0 <NA> <NA> 0 0 0 Access…
#> 8 publ… 708 Verif… 2009-02-24 Sand… Oroya … Sand… West… 6639 <NA> 1 1 <NA> <NA> <NA> 0 0 0 <NA> 1 <NA> <NA> 1 1 0 <NA>
#> 9 publ… 734 Verif… 2009-02-18 McIn… Bent S… Leon… Vict… 3953 <NA> 1 1 <NA> Park o… <NA> 0 0 0 <NA> 1 <NA> <NA> 1 1 0 <NA>
#> 10 publ… 847 Verif… 2008-02-18 Libr… Civic … Aubu… New … 2144 <NA> 1 1 <NA> Other Sewera… 0 0 0 <NA> 0 <NA> <NA> 0 0 0 <NA>
#> # … with 16,727 more rows, 14 more variables: mlak <int>, parkingaccessible <int>, accessibleparkingnote <chr>, isopen <chr>, openinghoursschedule <chr>, openinghoursnote <chr>, babychange <int>,
#> # showers <int>, drinkingwater <int>, sharpsdisposal <int>, sanitarydisposal <int>, iconalttext <chr>, notes <chr>, geometry <POINT [°]>, and abbreviated variable names ¹address1, ²postcode,
#> # ³addressnote, ⁴facilitytype, ⁵toilettype, ⁶accesslimited, ⁷paymentrequired, ⁸keyrequired, ⁹accessnote, ˟parkingnote, ˟yearinstalled, ˟accessiblemale, ˟accessiblefemale, ˟accessibleunisex,
#> # ˟accessiblenote