Explore Socrata data with ease.
socratadata provides an easy-to-use interface for
downloading data from Socrata
open data portals powered by Rust. socratadata improves
upon the existing RSocrata
package by introducing support for the Socrata
Discovery API and all Socrata
datatypes.
Unlike RSocrata, socratadata does not
support uploading or editing existing datasets.
You can install socratadata from CRAN.
install.packages("socratadata")You can install the development version of socratadata from GitHub with:
# install.packages("pak")
pak::pak("ryanzomorrodi/socratadata")Use soc_discover() to explore the datasets with a
domain.
library(socratadata)
soc_discover(domains = "data.cityofchicago.org")
#> # A tibble: 879 × 21
#> id name attribution owner_name provenance description created
#> <chr> <chr> <chr> <chr> <chr> <chr> <dttm>
#> 1 xzkq… Curr… City of Ch… cocadmin official "This data… 2011-09-27 00:00:00
#> 2 ijzp… Crim… Chicago Po… cocadmin official "This data… 2011-09-30 00:00:00
#> 3 ydr8… Buil… City of Ch… cocadmin official "This data… 2011-09-30 00:00:00
#> 4 85ca… Traf… City of Ch… Jonathan … official "Crash dat… 2017-10-19 00:00:00
#> 5 s6ha… Affo… City of Ch… cocadmin official "The renta… 2013-03-14 00:00:00
#> 6 4ijn… Food… City of Ch… cocadmin official "This info… 2011-08-08 00:00:00
#> 7 2ft4… Lobb… City of Ch… cocadmin official "All lobby… 2011-06-07 00:00:00
#> 8 i6bp… Chic… City of Ch… cocadmin official "List of a… 2010-12-22 00:00:00
#> 9 kn9c… Cens… U.S. Censu… Jamyia official "This data… 2012-01-05 00:00:00
#> 10 z8bn… Poli… Chicago Po… cocadmin official "Chicago P… 2010-12-22 00:00:00
#> # ℹ 869 more rows
#> # ℹ 14 more variables: data_last_updated <dttm>, metadata_last_updated <dttm>,
#> # categories <list>, tags <list>, domain_category <chr>, domain_tags <list>,
#> # domain_metadata <list>, column_names <list>, column_labels <list>,
#> # column_datatypes <list>, column_descriptions <list>, permalink <chr>,
#> # link <chr>, license <chr>Or with a query.
soc_discover(query = "bus")
#> # A tibble: 875 × 21
#> id name attribution owner_name provenance description created
#> <chr> <chr> <chr> <chr> <chr> <chr> <dttm>
#> 1 ez4e… Bus … Department… NYC OpenD… official "The Bus B… 2015-09-30 00:00:00
#> 2 6qat… DART… Department… Delaware … official "This cont… 2017-07-28 00:00:00
#> 3 bd2s… KCAT… KCATA Tran… DataKC official "This data… 2013-04-23 00:00:00
#> 4 wgnh… Capi… Capital Di… NY Open D… official "Bus stops… 2013-05-22 00:00:00
#> 5 s5c7… Bus … <NA> Karl Suey… official "" 2015-05-23 00:00:00
#> 6 eqmj… Bron… mta.info Elkin official "Bronx Tra… 2012-10-06 00:00:00
#> 7 ycrg… Bus … Department… NYC OpenD… official "Bus lanes… 2020-12-04 00:00:00
#> 8 nmjv… Bus … Transit Se… City of M… official "***NOTE: … 2019-06-03 00:00:00
#> 9 cudb… MTA … Metropolit… NY Open D… official "Bus Speed… 2021-12-29 00:00:00
#> 10 6uva… CTA … City of Ch… Jonathan … official "Lines rep… 2024-07-31 00:00:00
#> # ℹ 865 more rows
#> # ℹ 14 more variables: data_last_updated <dttm>, metadata_last_updated <dttm>,
#> # categories <list>, tags <list>, domain_category <chr>, domain_tags <list>,
#> # domain_metadata <list>, column_names <list>, column_labels <list>,
#> # column_datatypes <list>, column_descriptions <list>, permalink <chr>,
#> # link <chr>, license <chr>Or with categories.
soc_discover(categories = "transportation")
#> # A tibble: 470 × 21
#> id name attribution owner_name provenance description created
#> <chr> <chr> <chr> <chr> <chr> <chr> <dttm>
#> 1 9mau… Vita… U.S. Censu… Raleigh M… official "VITAL SIG… 2020-04-09 00:00:00
#> 2 wdpr… Vita… Federal Tr… Raleigh M… official "VITAL SIG… 2017-05-24 00:00:00
#> 3 2tq4… Vita… Federal Tr… Raleigh M… official "VITAL SIG… 2017-05-22 00:00:00
#> 4 btc8… Citi… The City o… Calgary O… official "These are… 2021-06-10 00:00:00
#> 5 7y2e… Weig… New York S… NY Open D… official "This data… 2015-01-21 00:00:00
#> 6 pksj… Vita… Federal Tr… Raleigh M… official "VITAL SIG… 2017-05-24 00:00:00
#> 7 f57x… Vita… <NA> Raleigh M… official "VITAL SIG… 2018-08-20 00:00:00
#> 8 ei2q… Park… Division o… City of N… official "This data… 2018-09-20 00:00:00
#> 9 w96p… Dail… Maryland T… Titlow, K… official "The Daily… 2020-05-19 00:00:00
#> 10 muzh… Calg… The City o… Calgary O… official "Calgary T… 2018-09-07 00:00:00
#> # ℹ 460 more rows
#> # ℹ 14 more variables: data_last_updated <dttm>, metadata_last_updated <dttm>,
#> # categories <list>, tags <list>, domain_category <chr>, domain_tags <list>,
#> # domain_metadata <list>, column_names <list>, column_labels <list>,
#> # column_datatypes <list>, column_descriptions <list>, permalink <chr>,
#> # link <chr>, license <chr>
soc_discover(
domains = "data.cityofchicago.org",
domain_category = "Transportation"
)
#> # A tibble: 86 × 21
#> id name attribution owner_name provenance description created
#> <chr> <chr> <chr> <chr> <chr> <chr> <dttm>
#> 1 85ca… Traf… City of Ch… Jonathan … official "Crash dat… 2017-10-19 00:00:00
#> 2 i6bp… Chic… City of Ch… cocadmin official "List of a… 2010-12-22 00:00:00
#> 3 ygr5… Towe… Chicago Po… cocadmin official "This data… 2011-09-30 00:00:00
#> 4 6iiy… CTA … Chicago Tr… CTA official "This data… 2011-08-12 00:00:00
#> 5 m6dm… Tran… City of Ch… Jonathan … official "<b>This d… 2018-10-02 00:00:00
#> 6 68nd… Traf… City of Ch… Jonathan … official "This data… 2018-01-04 00:00:00
#> 7 n4j6… Chic… City of Ch… cocadmin official "This data… 2011-11-20 00:00:00
#> 8 4i42… Spee… City of Ch… cocadmin official "This data… 2014-08-11 00:00:00
#> 9 t2qc… Chic… <NA> cocadmin official "This data… 2011-11-20 00:00:00
#> 10 pfsx… Aver… City of Ch… cocadmin official "This data… 2010-04-22 00:00:00
#> # ℹ 76 more rows
#> # ℹ 14 more variables: data_last_updated <dttm>, metadata_last_updated <dttm>,
#> # categories <list>, tags <list>, domain_category <chr>, domain_tags <list>,
#> # domain_metadata <list>, column_names <list>, column_labels <list>,
#> # column_datatypes <list>, column_descriptions <list>, permalink <chr>,
#> # link <chr>, license <chr>Or with tags.
soc_discover(
domains = "data.cityofchicago.org",
domain_tags = "public transit"
)
#> # A tibble: 12 × 21
#> id name attribution owner_name provenance description created
#> <chr> <chr> <chr> <chr> <chr> <chr> <dttm>
#> 1 6iiy… CTA … Chicago Tr… CTA official "This data… 2011-08-12 00:00:00
#> 2 pnau… CTA … Chicago Tr… CTA official "This list… 2011-08-12 00:00:00
#> 3 t2rn… CTA … Chicago Tr… CTA official "This data… 2011-08-05 00:00:00
#> 4 5neh… CTA … Chicago Tr… CTA official "This list… 2011-08-05 00:00:00
#> 5 bynn… CTA … Chicago Tr… CTA official "This data… 2011-08-05 00:00:00
#> 6 8pix… CTA … Chicago Tr… CTA official "This list… 2011-08-04 00:00:00
#> 7 w8km… CTA … Chicago Tr… CTA official "This data… 2011-08-11 00:00:00
#> 8 mq3i… CTA … Chicago Tr… CTA official "This data… 2011-08-11 00:00:00
#> 9 jyb9… CTA … Chicago Tr… CTA official "This data… 2011-08-05 00:00:00
#> 10 6uva… CTA … City of Ch… Jonathan … official "Lines rep… 2024-07-31 00:00:00
#> 11 xbyr… CTA … City of Ch… Jonathan … official "Lines rep… 2024-07-12 00:00:00
#> 12 3tzw… CTA … City of Ch… Jonathan … official "Points re… 2024-08-09 00:00:00
#> # ℹ 14 more variables: data_last_updated <dttm>, metadata_last_updated <dttm>,
#> # categories <list>, tags <list>, domain_category <chr>, domain_tags <list>,
#> # domain_metadata <list>, column_names <list>, column_labels <list>,
#> # column_datatypes <list>, column_descriptions <list>, permalink <chr>,
#> # link <chr>, license <chr>Or with ids.
soc_discover(ids = c("6iiy-9s97", "pnau-cf66"))
#> # A tibble: 2 × 21
#> id name attribution owner_name provenance description created
#> <chr> <chr> <chr> <chr> <chr> <chr> <dttm>
#> 1 6iiy-… CTA … Chicago Tr… CTA official This datas… 2011-08-12 00:00:00
#> 2 pnau-… CTA … Chicago Tr… CTA official This lists… 2011-08-12 00:00:00
#> # ℹ 14 more variables: data_last_updated <dttm>, metadata_last_updated <dttm>,
#> # categories <list>, tags <list>, domain_category <chr>, domain_tags <list>,
#> # domain_metadata <list>, column_names <list>, column_labels <list>,
#> # column_datatypes <list>, column_descriptions <list>, permalink <chr>,
#> # link <chr>, license <chr>Use soc_read() to read a socrata dataset into R.
soc_read(
"https://data.cityofchicago.org/Transportation/CTA-Ridership-Daily-Boarding-Totals/6iiy-9s97/about_data"
)
#> # A tibble: 8,886 × 5
#> service_date day_type bus rail_boardings total_rides
#> <dttm> <chr> <dbl> <dbl> <dbl>
#> 1 2001-01-01 00:00:00 U 297192 126455 423647
#> 2 2001-01-02 00:00:00 W 780827 501952 1282779
#> 3 2001-01-03 00:00:00 W 824923 536432 1361355
#> 4 2001-01-04 00:00:00 W 870021 550011 1420032
#> 5 2001-01-05 00:00:00 W 890426 557917 1448343
#> 6 2001-01-06 00:00:00 A 577401 255356 832757
#> 7 2001-01-07 00:00:00 U 375831 169825 545656
#> 8 2001-01-08 00:00:00 W 985221 590706 1575927
#> 9 2001-01-09 00:00:00 W 978377 599905 1578282
#> 10 2001-01-10 00:00:00 W 984884 602052 1586936
#> # ℹ 8,876 more rowsSpatial data will be read as an sf object.
soc_read(
"https://data.cityofchicago.org/Facilities-Geographic-Boundaries/Boundaries-Community-Areas/igwz-8jzy/about_data"
)
#> Simple feature collection with 77 features and 5 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -87.94011 ymin: 41.64454 xmax: -87.52414 ymax: 42.02304
#> Geodetic CRS: WGS 84
#> # A tibble: 77 × 6
#> the_geom area_numbe community area_num_1 shape_area
#> * <MULTIPOLYGON [°]> <dbl> <chr> <chr> <dbl>
#> 1 (((-87.65456 41.99817, -87.65574 … 1 ROGERS P… 1 51259902.
#> 2 (((-87.68465 42.01948, -87.68464 … 2 WEST RID… 2 98429095.
#> 3 (((-87.64102 41.9548, -87.644 41.… 3 UPTOWN 3 65095643.
#> 4 (((-87.67441 41.9761, -87.6744 41… 4 LINCOLN … 4 71352328.
#> 5 (((-87.67336 41.93234, -87.67342 … 5 NORTH CE… 5 57054168.
#> 6 (((-87.64102 41.9548, -87.64101 4… 6 LAKE VIEW 6 87214799.
#> 7 (((-87.63182 41.93258, -87.63182 … 7 LINCOLN … 7 88316400.
#> 8 (((-87.62446 41.91157, -87.62459 … 8 NEAR NOR… 8 76675896.
#> 9 (((-87.80676 42.00084, -87.80676 … 9 EDISON P… 9 31636314.
#> 10 (((-87.78002 41.99741, -87.78049 … 10 NORWOOD … 10 121959105.
#> # ℹ 67 more rows
#> # ℹ 1 more variable: shape_len <dbl>You can even perform complex queries using Socrata Query Language
(SoQL) via soc_query().
lower_west_side <- soc_read(
"https://data.cityofchicago.org/Facilities-Geographic-Boundaries/Boundaries-Community-Areas/igwz-8jzy/about_data",
query = soc_query(
where = "community LIKE 'LOWER WEST SIDE'"
)
)
print(lower_west_side)
#> Simple feature collection with 1 feature and 5 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -87.68807 ymin: 41.8348 xmax: -87.63516 ymax: 41.86002
#> Geodetic CRS: WGS 84
#> # A tibble: 1 × 6
#> the_geom area_numbe community area_num_1 shape_area shape_len
#> * <MULTIPOLYGON [°]> <dbl> <chr> <chr> <dbl> <dbl>
#> 1 (((-87.63516 41.85772, -… 31 LOWER WE… 31 81550724. 43229.
cta_ridership <- soc_read(
"https://data.cityofchicago.org/Transportation/Taxi-Trips-2013-2023-/wrvz-psew/about_data",
query = soc_query(
select = "pickup_community_area, count(*) as n",
where = glue::glue(
"within_polygon(dropoff_centroid_location, '{sf::st_as_text(lower_west_side$the_geom)}')"
),
group_by = "pickup_community_area",
order_by = "n DESC"
)
)
print(cta_ridership)
#> # A tibble: 78 × 2
#> pickup_community_area n
#> <dbl> <dbl>
#> 1 32 127474
#> 2 8 113797
#> 3 28 90983
#> 4 31 39509
#> 5 24 37789
#> 6 33 22793
#> 7 76 18006
#> 8 6 15160
#> 9 56 14142
#> 10 7 12191
#> # ℹ 68 more rowsAccess a dataset’s metadata using soc_metadata().
soc_metadata(cta_ridership)
#> ID: wrvz-psew
#> Name: Taxi Trips (2013-2023)
#> Attribution: City of Chicago
#> Owner: Jonathan Levy
#> Provenance: official
#> Description: <b>This dataset ends with 2023. Please see the Featured Content
#> link below for the dataset that starts in 2024.</b> Taxi trips from 2013 to
#> 2023 reported to the City of Chicago in its role as a regulatory agency. To
#> protect privacy but allow for aggregate analyses, the Taxi ID is consistent for
#> any given taxi medallion number but does not show the number, Census Tracts are
#> suppressed in some cases, and times are rounded to the nearest 15 minutes. Due
#> to the data reporting process, not all trips are reported but the City believes
#> that most are.
#> Created: 2016-05-27 21:27:48
#> Data last updated: 2024-02-07 20:40:12
#> Metadata last Updated: 2024-06-21 17:06:18
#> Domain Category: Transportation
#> Domain Tags: taxis, transportation, and historical
#> Domain fields:
#> • Time Period: 2013 - 2023
#> • Changes and Other Historical Information Useful to Understanding This
#> Dataset:
#> https://www.google.com/search?as_q="Related+dataset+ID+s"+"wrvz-psew"+inurl:stories&as_sitesearch=data.cityofchicago.org
#> • Data Owner: Department of Business Affairs & Consumer Protection
#> Columns:
#> # A tibble: 24 × 4
#> column_name column_label column_datatype column_description
#> <chr> <chr> <chr> <chr>
#> 1 trip_id Trip ID text A unique identifi…
#> 2 taxi_id Taxi ID text A unique identifi…
#> 3 trip_start_timestamp Trip Start Time… calendar_date When the trip sta…
#> 4 trip_end_timestamp Trip End Timest… calendar_date When the trip end…
#> 5 trip_seconds Trip Seconds number Time of the trip …
#> 6 trip_miles Trip Miles number Distance of the t…
#> 7 pickup_census_tract Pickup Census T… text The Census Tract …
#> 8 dropoff_census_tract Dropoff Census … text The Census Tract …
#> 9 pickup_community_area Pickup Communit… number The Community Are…
#> 10 dropoff_community_area Dropoff Communi… number The Community Are…
#> 11 fare Fare number The fare for the …
#> 12 tips Tips number The tip for the t…
#> 13 tolls Tolls number The tolls for the…
#> 14 extras Extras number Extra charges for…
#> 15 trip_total Trip Total number Total cost of the…
#> 16 payment_type Payment Type text Type of payment f…
#> 17 company Company text The taxi company.
#> 18 pickup_centroid_latitude Pickup Centroid… number The latitude of t…
#> 19 pickup_centroid_longitude Pickup Centroid… number The longitude of …
#> 20 pickup_centroid_location Pickup Centroid… point The location of t…
#> # ℹ 4 more rows
#> Permalink: https://data.cityofchicago.org/d/wrvz-psew
#> Link:
#> https://data.cityofchicago.org/Transportation/Taxi-Trips-2013-2023-/wrvz-psew
#> License: See Terms of UseOr explore a dataset’s metadata using it’s url.
soc_metadata(
"https://data.cityofchicago.org/Transportation/CTA-Ridership-Daily-Boarding-Totals/6iiy-9s97/about_data"
)
#> ID: 6iiy-9s97
#> Name: CTA - Ridership - Daily Boarding Totals
#> Attribution: Chicago Transit Authority
#> Owner: CTA
#> Provenance: official
#> Description: This dataset shows systemwide boardings for both bus and rail
#> services provided by CTA, dating back to 2001. Daytypes are as follows: W =
#> Weekday, A = Saturday, U = Sunday/Holiday. See attached readme file for
#> information on how these numbers are calculated.
#> Created: 2011-08-12 15:40:31
#> Data last updated: 2025-06-30 18:44:33
#> Metadata last Updated: 2025-06-30 18:44:32
#> Domain Category: Transportation
#> Domain Tags: cta, public transit, and ridership
#> Domain fields:
#> • Data Owner: Chicago Transit Authority
#> Columns:
#> # A tibble: 5 × 4
#> column_name column_label column_datatype column_description
#> <chr> <chr> <chr> <chr>
#> 1 service_date service_date calendar_date ""
#> 2 day_type day_type text ""
#> 3 bus bus number ""
#> 4 rail_boardings rail_boardings number ""
#> 5 total_rides total_rides number ""
#> Permalink: https://data.cityofchicago.org/d/6iiy-9s97
#> Link:
#> https://data.cityofchicago.org/Transportation/CTA-Ridership-Daily-Boarding-Totals/6iiy-9s97
#> License: See Terms of Use