nl2sqlproj/spider2-nl2sql huggingface dataset:
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.pancancer_atlas.Original_jhu_usc_edu_PANCAN_HumanMethylation27_betaValue_whitelisted`
(
  ID STRING OPTIONS(description="Unique probe identifier (eg cg04676771) from the Illumina Human Methylation array -- please refer to the annotation table (isb-cgc-bq.annotations.methylation_annotation_hg19_illumina_current) for more details about any particular probe"),
  AliquotBarcode STRING OPTIONS(description="TCGA aliquot barcode, eg TCGA-12-1089-01A-01D-0517-28"),
  Beta FLOAT64 OPTIONS(description="Normalized DNA methylation beta value (between 0 and 1, where 0 indicates completely un-methylated and 1 indicates fully methylated)")
)
OPTIONS(
  friendly_name="PanCancer DNA Methylation (27k Only)",
  description="Data loaded from the PanCancer Atlas initiative on the GDC in April 2018. Contains DNA Methylation data generated using Illumina Human Methylation 27k. Some samples were filtered using the PanCancer Atlas whitelist.  \n\nMore details: https://www.synapse.org/#!Synapse:syn4557792.10 and https://gdc.cancer.gov/about-data/publications/pancanatlas. \n\nFor data annotated with pertinent TCGA Barcodes and filtered by the barcode white list, table Filtered_jhu_usc_edu_PANCAN_HumanMethylation27_betaValue_whitelisted is recommended.",
  labels=[("category", "processed_-omics_data"), ("status", "current"), ("access", "open"), ("source_0", "gdc"), ("data_type", "dna_methylation"), ("program", "pancancer_atlas"), ("reference_genome", "hg19"), ("source_1", "literature")]
);

INSERT INTO `isb-cgc-bq.pancancer_atlas.Original_jhu_usc_edu_PANCAN_HumanMethylation27_betaValue_whitelisted` (ID, AliquotBarcode, Beta) VALUES ('cg05679521', 'TCGA-01-0628-11A-01D-0383-05', 0.0290592), ('cg04853151', 'TCGA-01-0628-11A-01D-0383-05', 0.029444), ('cg06162003', 'TCGA-01-0628-11A-01D-0383-05', 0.0111285), ('cg01136458', 'TCGA-01-0628-11A-01D-0383-05', 0.764987), ('cg02132188', 'TCGA-01-0628-11A-01D-0383-05', 0.31103400000000003);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.libraries_io.dependencies`
(
  id INT64 OPTIONS(description="The unique primary key of the dependency in the Libraries.io database."),
  platform STRING OPTIONS(description="The name of the Package manager the dependency is available on."),
  project_name STRING OPTIONS(description="The name of the project the dependency belongs to."),
  project_id INT64 OPTIONS(description="The unique primary key of the project for this dependency in the Libraries.io database."),
  version_number STRING OPTIONS(description="The number of the version that the dependency belongs to."),
  version_id INT64 OPTIONS(description="The unique primary key of the version for this dependency in the Libraries.io database."),
  dependency_name STRING OPTIONS(description="The name of the project that the dependency specifies."),
  dependency_platform STRING OPTIONS(description="The name of the package manager that the project that the dependency specifies is available from (only different for Atom)."),
  dependency_kind STRING OPTIONS(description="The type of dependency, often declared for the phase of usage, e.g. runtime, test, development, build."),
  optional_dependency STRING OPTIONS(description="Is the dependency optional?."),
  dependency_requirements STRING OPTIONS(description="The version or range of versions that the dependency specifies, resolution of that to a particular version is package manager specific."),
  dependency_project_id INT64 OPTIONS(description="The unique primary key of the project for this dependency in the Libraries.io database.")
);

INSERT INTO `bigquery-public-data.libraries_io.dependencies` (id, platform, project_name, project_id, version_number, version_id, dependency_name, dependency_platform, dependency_kind, optional_dependency, dependency_requirements, dependency_project_id) VALUES (63688894, 'Packagist', 'jackshadow/yii2-sentry', 2499997, '1.0.1', 10963540, 'codeception/verify', 'Packagist', 'Development', 'false', ' *', 48204), (93706523, 'Packagist', 'immediate/im-fabric-wordpress', 3261980, '1.2.3', 15670669, '10up/wp_mock', 'Packagist', 'Development', 'false', ' 0.3.0', 37460), (88984643, 'NPM', 'react-hig-datepicker', 3196162, '0.1.3-h', 15150299, 'react', 'NPM', 'runtime', 'false', ' ^15.4.1', 304875), (70881952, 'NPM', '@machinemode/cryptopia', 2619549, '0.1.0', 11984358, 'dotenv', 'NPM', 'Development', 'false', ' ^4.0.0', 142776), (85289846, 'Maven', 'de.taimos:dvalin-interconnect-core', 2673189, '1.20', 12274677, 'org.apache.activemq:activemq-client', 'Maven', 'runtime', 'false', '${activemq.version}', 359766);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.libraries_io.versions`
(
  id INT64 OPTIONS(description="The unique primary key of the version in the Libraries.io database."),
  platform STRING OPTIONS(description="The name of the Package manager the version is available on."),
  project_name STRING OPTIONS(description="The name of the project the version belongs to."),
  project_id INT64 OPTIONS(description="The unique primary key of the project for this version in the Libraries.io database."),
  number STRING OPTIONS(description="The number of the release often confirms to semantic versioning."),
  published_timestamp TIMESTAMP OPTIONS(description="The timestamp of when the version was published."),
  created_timestamp TIMESTAMP OPTIONS(description="The timestamp of when the version was first detected by Libraries.io."),
  updated_timestamp TIMESTAMP OPTIONS(description="The timestamp of when the version was last saved by Libraries.io.")
);

INSERT INTO `bigquery-public-data.libraries_io.versions` (id, platform, project_name, project_id, number, published_timestamp, created_timestamp, updated_timestamp) VALUES (3125634, 'Atom', 'webflow-to-wordpress', 802627, '0.0.0', '2015-05-23 19:19:04+00:00', '2015-05-23 19:19:04+00:00', '2015-05-23 19:19:04+00:00'), (3876666, 'Atom', 'nuclide-health', 994734, '0.0.0', '2015-09-28 20:18:41+00:00', '2015-09-28 20:18:41+00:00', '2015-09-28 20:18:41+00:00'), (4455398, 'Atom', 'fb-atom-snippets', 1112791, '0.0.0', '2015-12-07 21:28:37+00:00', '2015-12-07 21:28:37+00:00', '2015-12-07 21:28:37+00:00'), (4222891, 'Atom', 'nuclide-busy-signal', 1058135, '0.0.0', '2015-10-23 21:08:37+00:00', '2015-10-23 21:08:37+00:00', '2015-10-23 21:08:37+00:00'), (3459903, 'Atom', 'language-marasm', 929280, '0.0.0', '2015-08-13 21:38:51+00:00', '2015-08-13 21:38:51+00:00', '2015-08-13 21:38:51+00:00');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.libraries_io.tags`
(
  id INT64 OPTIONS(description="The unique primary key of the tag in the Libraries.io database."),
  host_type STRING OPTIONS(description="Which website the tags repository is hosted on, either GitHub, GitLab or Bitbucket."),
  repository_name_with_owner STRING OPTIONS(description="The repository name and owner seperated by a slash, also maps to the url slug on the given repository host e.g. librariesio/libraries.io."),
  repository_id INT64 OPTIONS(description="The unique primary key of the repository for this tag in the Libraries.io database."),
  tag_name STRING OPTIONS(description="The name of the tag often is a version number but could be any freeform string."),
  tag_git_sha STRING OPTIONS(description="Sha of the object that the tag is pointing at in the repository."),
  tag_published_timestamp TIMESTAMP OPTIONS(description="The timestamp of when the tag was published."),
  tag_created_timestamp TIMESTAMP OPTIONS(description="The timestamp of when the tag was first saved by Libraries.io."),
  tag_updated_timestamp TIMESTAMP OPTIONS(description="The timestamp of when the tag was last saved by Libraries.io.")
);

INSERT INTO `bigquery-public-data.libraries_io.tags` (id, host_type, repository_name_with_owner, repository_id, tag_name, tag_git_sha, tag_published_timestamp, tag_created_timestamp, tag_updated_timestamp) VALUES (52086629, 'GitHub', 'dmpriso/hunter', 23754342, 'v0.16.2', 'db87a6c907a822d2c0d3e5df01d74a11330e290d', '2016-10-01 00:27:25+00:00', '2017-05-11 12:17:06+00:00', '2017-05-11 12:17:06+00:00'), (52086654, 'GitHub', 'dmpriso/hunter', 23754342, 'v0.16.27', '4b9a51ac24f8c55d0dc28b617c4329f0db582b53', '2016-11-13 05:26:20+00:00', '2017-05-11 12:17:20+00:00', '2017-05-11 12:17:20+00:00'), (52086678, 'GitHub', 'dmpriso/hunter', 23754342, 'v0.17.14', 'ca3adc81c78cdba67bc1567088d0fba309df2fb8', '2017-01-15 04:57:59+00:00', '2017-05-11 12:17:27+00:00', '2017-05-11 12:17:27+00:00'), (52086709, 'GitHub', 'dmpriso/hunter', 23754342, 'v0.18.24', '65fce9666dcb02ac8fbc43bed10680dd86ab758b', '2017-03-21 10:26:17+00:00', '2017-05-11 12:17:36+00:00', '2017-05-11 12:17:36+00:00'), (52086694, 'GitHub', 'dmpriso/hunter', 23754342, 'v0.18.9', '87e8fb2e57f4a71b685270d053e94d8706da9bdb', '2017-03-04 03:46:31+00:00', '2017-05-11 12:17:32+00:00', '2017-05-11 12:17:32+00:00');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.libraries_io.repository_dependencies`
(
  id INT64 OPTIONS(description="The unique primary key of the repository dependency in the Libraries.io database."),
  host_type STRING OPTIONS(description="Which website the dependencys repository is hosted on, either GitHub, GitLab or Bitbucket."),
  repository_name_with_owner STRING OPTIONS(description="The repository name and owner seperated by a slash, also maps to the url slug on the given repository host e.g. librariesio/libraries.io."),
  repository_id INT64 OPTIONS(description="The unique primary key of the repository for this dependency in the Libraries.io database."),
  manifest_platform STRING OPTIONS(description="Which package manager the dependency listed in the manifest should use."),
  manifest_filepath STRING OPTIONS(description="Path to the file where the dependency is declared within the repository."),
  git_branch STRING OPTIONS(description="Which branch was the manifest loaded from the repository."),
  manifest_kind STRING OPTIONS(description="Either manifest or lockfile, manifests are written by humans, lockfiles contain full resolved dependency tree."),
  optional STRING OPTIONS(description="Is the dependency optional?."),
  dependency_project_name STRING OPTIONS(description="The name of the project that the dependency specifies."),
  dependency_requirements STRING OPTIONS(description="The version or range of versions that the dependency specifies, resolution of that to a particular version is package manager specific."),
  dependency_kind STRING OPTIONS(description="The type of dependency, often declared for the phase of usage, e.g. runtime, test, development, build."),
  dependency_project_id INT64 OPTIONS(description="The unique primary key of the project for this dependency in the Libraries.io database.")
);

INSERT INTO `bigquery-public-data.libraries_io.repository_dependencies` (id, host_type, repository_name_with_owner, repository_id, manifest_platform, manifest_filepath, git_branch, manifest_kind, optional, dependency_project_name, dependency_requirements, dependency_kind, dependency_project_id) VALUES (494629073, 'GitHub', 'stokesbga/react-native-step-indicator', 37320471, 'npm', 'example/yarn.lock', NULL, 'lockfile', NULL, 'debug', '3.1.0', 'runtime', 140871), (494629140, 'GitHub', 'stokesbga/react-native-step-indicator', 37320471, 'npm', 'example/yarn.lock', NULL, 'lockfile', NULL, 'fstream', '1.0.11', 'runtime', 149306), (494629180, 'GitHub', 'stokesbga/react-native-step-indicator', 37320471, 'npm', 'example/yarn.lock', NULL, 'lockfile', NULL, 'inquirer', '3.3.0', 'runtime', 159991), (494629193, 'GitHub', 'stokesbga/react-native-step-indicator', 37320471, 'npm', 'example/yarn.lock', NULL, 'lockfile', NULL, 'is-fullwidth-code-point', '2.0.0', 'runtime', 897326), (494629246, 'GitHub', 'stokesbga/react-native-step-indicator', 37320471, 'npm', 'example/yarn.lock', NULL, 'lockfile', NULL, 'jsesc', '2.5.1', 'runtime', 291676);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.covid19_nyt.us_states`
(
  date DATE OPTIONS(description="Date reported"),
  state_name STRING OPTIONS(description="State reported"),
  state_fips_code STRING OPTIONS(description="Standard geographic identifier for the state"),
  confirmed_cases INT64 OPTIONS(description="The total number of confirmed cases of COVID-19"),
  deaths INT64 OPTIONS(description="The total number of confirmed deaths of COVID-19")
)
OPTIONS(
  description="State-level data for the number of cases and deaths from The New York Times. Sourced from https://github.com/nytimes/covid-19-data."
);

INSERT INTO `bigquery-public-data.covid19_nyt.us_states` (date, state_name, state_fips_code, confirmed_cases, deaths) VALUES ('2020-03-13', 'Alabama', '01', 6, 0), ('2020-03-14', 'Alabama', '01', 12, 0), ('2020-03-15', 'Alabama', '01', 23, 0), ('2020-03-16', 'Alabama', '01', 29, 0), ('2020-03-17', 'Alabama', '01', 39, 0);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.covid19_nyt.mask_use_by_county`
(
  county_fips_code STRING OPTIONS(description="Standard geographic identifier for the county"),
  never FLOAT64 OPTIONS(description="The estimated share of people in this county who would say never in response to the question \"How often do you wear a mask in public when you expect to be within six feet of another person?\""),
  rarely FLOAT64 OPTIONS(description="The estimated share of people in this county who would say rarely"),
  sometimes FLOAT64 OPTIONS(description="The estimated share of people in this county who would say sometimes"),
  frequently FLOAT64 OPTIONS(description="The estimated share of people in this county who would say frequently"),
  always FLOAT64 OPTIONS(description="The estimated share of people in this county who would say always")
)
OPTIONS(
  description="This data comes from a large number of interviews conducted online by the global data and survey firm Dynata at the request of The New York Times. The firm asked a question about mask use to obtain 250,000 survey responses between July 2 and July 14, enough data to provide estimates more detailed than the state level. (Several states have imposed new mask requirements since the completion of these interviews.)\n\nSpecifically, each participant was asked: How often do you wear a mask in public when you expect to be within six feet of another person?\n\nThis survey was conducted a single time, and at this point we have no plans to update the data or conduct the survey again.\n\nSourced from https://github.com/nytimes/covid-19-data/tree/master/mask-use."
);

INSERT INTO `bigquery-public-data.covid19_nyt.mask_use_by_county` (county_fips_code, never, rarely, sometimes, frequently, always) VALUES ('08117', 0.0, 0.001, 0.064, 0.151, 0.784), ('48255', 0.0, 0.001, 0.104, 0.145, 0.75), ('48493', 0.0, 0.003, 0.072, 0.208, 0.716), ('36123', 0.0, 0.006, 0.023, 0.087, 0.884), ('48209', 0.0, 0.007, 0.022, 0.115, 0.855);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.covid19_nyt.us_counties`
(
  date DATE OPTIONS(description="Date reported"),
  county STRING OPTIONS(description="County in the specified state"),
  state_name STRING OPTIONS(description="State reported"),
  county_fips_code STRING OPTIONS(description="Standard geographic identifier for the county"),
  confirmed_cases INT64 OPTIONS(description="The total number of confirmed cases of COVID-19"),
  deaths INT64 OPTIONS(description="The total number of confirmed deaths of COVID-19")
)
OPTIONS(
  description="County-level data for the number of cases and deaths from The New York Times. Sourced from https://github.com/nytimes/covid-19-data."
);

INSERT INTO `bigquery-public-data.covid19_nyt.us_counties` (date, county, state_name, county_fips_code, confirmed_cases, deaths) VALUES ('2022-01-01', 'Autauga', 'Alabama', '01001', 11018, 160), ('2022-01-01', 'Baldwin', 'Alabama', '01003', 39911, 593), ('2022-01-01', 'Barbour', 'Alabama', '01005', 3860, 81), ('2022-01-01', 'Bibb', 'Alabama', '01007', 4533, 95), ('2022-01-01', 'Blount', 'Alabama', '01009', 11256, 198);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.san_francisco.film_locations`
(
  title STRING OPTIONS(description=""),
  release_year INT64 OPTIONS(description=""),
  locations STRING OPTIONS(description=""),
  fun_facts STRING OPTIONS(description=""),
  production_company STRING OPTIONS(description=""),
  distributor STRING OPTIONS(description=""),
  director STRING OPTIONS(description=""),
  writer STRING OPTIONS(description=""),
  actor_1 STRING OPTIONS(description=""),
  actor_2 STRING OPTIONS(description=""),
  actor_3 STRING OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.san_francisco.film_locations` (title, release_year, locations, fun_facts, production_company, distributor, director, writer, actor_1, actor_2, actor_3) VALUES ('A Jitney Elopement', 1915, '20th and Folsom Streets', '', 'The Essanay Film Manufacturing Company', 'General Film Company', 'Charles Chaplin', 'Charles Chaplin', 'Charles Chaplin', 'Edna Purviance', ''), ('A Jitney Elopement', 1915, 'Golden Gate Park', 'During San Francisco''s Gold Rush era, the Park was part of an area designated as the "Great Sand Waste".', 'The Essanay Film Manufacturing Company', 'General Film Company', 'Charles Chaplin', 'Charles Chaplin', 'Charles Chaplin', 'Edna Purviance', ''), ('San Francisco', 1936, 'The Barbary Coast', 'The Barbary Coast was a red-light district that was largely destroyed in the 1906 earthquake. Though some of the establishments were rebuilt after the earthquake, an anti-vice campaign put the establishments out of business.', 'Metro-Goldwyn Mayer', 'Metro-Goldwyn Mayer', 'W.S. Van Dyke', 'Anita Loos', 'Clark Gable', 'Jeanette MacDonald', 'Spencer Tracy'), ('San Francisco', 1936, 'City Hall', 'The dome of SF''s City Hall is almost a foot taller than that of the US Capitol Building. In 1954, Joe DiMaggio and Marilyn Monroe married at the Beaux Arts-style building.', 'Metro-Goldwyn Mayer', 'Metro-Goldwyn Mayer', 'W.S. Van Dyke', 'Anita Loos', 'Clark Gable', 'Jeanette MacDonald', 'Spencer Tracy'), ('After the Thin Man', 1936, 'Coit Tower', 'The Tower was funded by a gift bequeathed by Lillie Hitchcock Coit, a socialite who reportedly liked to chase fires. Though the tower resembles a firehose nozzle, it was not designed this way.', 'Metro-Goldwyn Mayer', 'Metro-Goldwyn Mayer', 'W.S. Van Dyke', 'Frances Goodrich', 'William Powell', 'Myrna Loy', 'James Stewart');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.san_francisco.bikeshare_stations`
(
  station_id INT64 NOT NULL OPTIONS(description="Station ID number"),
  name STRING OPTIONS(description="Name of station"),
  latitude FLOAT64 OPTIONS(description="Latitude"),
  longitude FLOAT64 OPTIONS(description="Longitude"),
  dockcount INT64 OPTIONS(description="Number of total docks at station"),
  landmark STRING OPTIONS(description="City (San Francisco, Redwood City, Palo Alto, Mountain View, San Jose)"),
  installation_date DATE OPTIONS(description="Original date that station was installed. If station was moved, it is noted below.")
);

INSERT INTO `bigquery-public-data.san_francisco.bikeshare_stations` (station_id, name, latitude, longitude, dockcount, landmark, installation_date) VALUES (4, 'Santa Clara at Almaden', 37.333988, -121.894902, 11, 'San Jose', '2013-08-06'), (84, 'Ryland Park', 37.342725, -121.895617, 15, 'San Jose', '2014-04-09'), (8, 'San Salvador at 1st', 37.330165, -121.885831, 15, 'San Jose', '2013-08-05'), (9, 'Japantown', 37.348742, -121.894715, 15, 'San Jose', '2013-08-05'), (3, 'San Jose Civic Center', 37.330698, -121.888979, 15, 'San Jose', '2013-08-05');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.san_francisco.bikeshare_status`
(
  station_id INT64 NOT NULL OPTIONS(description="Station ID number"),
  bikes_available INT64 OPTIONS(description="Number of available bikes"),
  docks_available INT64 OPTIONS(description="Number of available docks"),
  time TIMESTAMP OPTIONS(description="Date and time, PST")
);

INSERT INTO `bigquery-public-data.san_francisco.bikeshare_status` (station_id, bikes_available, docks_available, time) VALUES (2, 0, 26, '2014-09-10 09:25:02+00:00'), (2, 0, 26, '2015-09-12 02:07:02+00:00'), (2, 0, 26, '2015-09-11 11:05:02+00:00'), (2, 0, 27, '2016-08-30 15:13:47+00:00'), (2, 0, 27, '2015-09-24 13:31:02+00:00');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.san_francisco.bikeshare_trips`
(
  trip_id INT64 NOT NULL OPTIONS(description="Numeric ID of bike trip"),
  duration_sec INT64 OPTIONS(description="Time of trip in seconds"),
  start_date TIMESTAMP OPTIONS(description="Start date of trip with date and time, in PST"),
  start_station_name STRING OPTIONS(description="Station name of start station"),
  start_station_id INT64 OPTIONS(description="Numeric reference for start station"),
  end_date TIMESTAMP OPTIONS(description="End date of trip with date and time, in PST"),
  end_station_name STRING OPTIONS(description="Station name for end station"),
  end_station_id INT64 OPTIONS(description="Numeric reference for end station"),
  bike_number INT64 OPTIONS(description="ID of bike used"),
  zip_code STRING OPTIONS(description="Home zip code of subscriber (customers can choose to manually enter zip at kiosk however data is unreliable)"),
  subscriber_type STRING OPTIONS(description="Subscriber = annual or 30-day member; Customer = 24-hour or 3-day member")
);

INSERT INTO `bigquery-public-data.san_francisco.bikeshare_trips` (trip_id, duration_sec, start_date, start_station_name, start_station_id, end_date, end_station_name, end_station_id, bike_number, zip_code, subscriber_type) VALUES (1235850, 1540, '2016-06-11 08:19:00+00:00', 'San Jose Diridon Caltrain Station', 2, '2016-06-11 08:45:00+00:00', 'San Jose Diridon Caltrain Station', 2, 124, '15206', 'Customer'), (1219337, 6324, '2016-05-29 12:49:00+00:00', 'San Jose Diridon Caltrain Station', 2, '2016-05-29 14:34:00+00:00', 'San Jose Diridon Caltrain Station', 2, 174, '55416', 'Customer'), (793762, 115572, '2015-06-04 09:22:00+00:00', 'San Jose Diridon Caltrain Station', 2, '2015-06-05 17:28:00+00:00', 'San Jose Diridon Caltrain Station', 2, 190, '95391', 'Customer'), (453845, 54120, '2014-09-15 16:53:00+00:00', 'San Jose Diridon Caltrain Station', 2, '2014-09-16 07:55:00+00:00', 'San Jose Diridon Caltrain Station', 2, 127, '81', 'Customer'), (1245113, 5018, '2016-06-17 20:08:00+00:00', 'San Jose Diridon Caltrain Station', 2, '2016-06-17 21:32:00+00:00', 'San Jose Diridon Caltrain Station', 2, 153, '95070', 'Customer');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.san_francisco.sfpd_incidents`
(
  unique_key INT64 NOT NULL OPTIONS(description="The unique incident number for this accident"),
  category STRING OPTIONS(description=""),
  descript STRING OPTIONS(description=""),
  dayofweek STRING OPTIONS(description=""),
  pddistrict STRING OPTIONS(description="Police Department district"),
  resolution STRING OPTIONS(description="Whether there was an arrest, citation, booking, etc."),
  address STRING OPTIONS(description=""),
  longitude FLOAT64 OPTIONS(description=""),
  latitude FLOAT64 OPTIONS(description=""),
  location STRING OPTIONS(description="Latitude/Longitude"),
  pdid INT64 OPTIONS(description="Unique Identifier for use in update and insert operations"),
  timestamp TIMESTAMP OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.san_francisco.sfpd_incidents` (unique_key, category, descript, dayofweek, pddistrict, resolution, address, longitude, latitude, location, pdid, timestamp) VALUES (140841035, 'LARCENY/THEFT', 'PETTY THEFT FROM LOCKED AUTO', 'Saturday', 'PARK', 'NONE', '1400 Block of WALLER ST', -122.44796773714, 37.768862804, '(37.768862804, -122.44796773714)', 14084103506241, '2014-10-04 18:30:00+00:00'), (121031708, 'MISSING PERSON', 'MISSING ADULT', 'Saturday', 'PARK', 'NONE', '1400 Block of WALLER ST', -122.44796773714, 37.768862804, '(37.768862804, -122.44796773714)', 12103170874000, '2012-12-22 14:00:00+00:00'), (60771542, 'VANDALISM', 'MALICIOUS MISCHIEF, GRAFFITI', 'Wednesday', 'PARK', 'NONE', '1400 Block of WALLER ST', -122.44796773714, 37.768862804, '(37.768862804, -122.44796773714)', 6077154228165, '2006-07-19 10:00:00+00:00'), (50688521, 'VANDALISM', 'MALICIOUS MISCHIEF, GRAFFITI', 'Thursday', 'PARK', 'NONE', '1400 Block of WALLER ST', -122.44796773714, 37.768862804, '(37.768862804, -122.44796773714)', 5068852128165, '2005-06-16 00:01:00+00:00'), (150083471, 'NON-CRIMINAL', 'AIDED CASE -PROPERTY FOR DESTRUCTION', 'Tuesday', 'PARK', 'NONE', '1400 Block of WALLER ST', -122.44796773714, 37.768862804, '(37.768862804, -122.44796773714)', 15008347151041, '2015-01-27 20:40:00+00:00');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.san_francisco.street_trees`
(
  tree_id INT64 NOT NULL OPTIONS(description="Unique ID for Tree"),
  legal_status STRING OPTIONS(description="Legal staus: Permitted or DPW maintained"),
  species STRING OPTIONS(description="Species of tree"),
  address STRING OPTIONS(description="Address of Tree"),
  site_order INT64 OPTIONS(description="Order of tree at address where multiple trees are at same address. Trees are ordered in ascending address order"),
  site_info STRING OPTIONS(description="Description of location of tree"),
  plant_type STRING OPTIONS(description="Landscaping or Tree"),
  care_taker STRING OPTIONS(description="Agency or person that is primary caregiver to tree. Owner of Tree"),
  care_assistant STRING OPTIONS(description="Agency or person that is secondary caregiver to tree"),
  plant_date TIMESTAMP OPTIONS(description="Date tree was planted"),
  dbh STRING OPTIONS(description="depth, height"),
  plot_size STRING OPTIONS(description="dimension of tree plot"),
  permit_notes STRING OPTIONS(description="Tree permit number reference"),
  x_coordinate FLOAT64 OPTIONS(description="CA State Plane III"),
  y_coordinate FLOAT64 OPTIONS(description="CA State Plane III"),
  latitude FLOAT64 OPTIONS(description="WGS84"),
  longitude FLOAT64 OPTIONS(description="WGS84"),
  location STRING OPTIONS(description="Location formatted for mapping")
);

INSERT INTO `bigquery-public-data.san_francisco.street_trees` (tree_id, legal_status, species, address, site_order, site_info, plant_type, care_taker, care_assistant, plant_date, dbh, plot_size, permit_notes, x_coordinate, y_coordinate, latitude, longitude, location) VALUES (113066, '', 'Cupressus macrocarpa :: Monterey Cypress', '2X Cranleigh Dr', 7, ':', 'Tree', 'DPW', '', '2015-09-09 13:08:00+00:00', '3', '', '', 5991370.3, 2095943.7, 37.7345659248964, -122.472270103664, '(37.7345659248964, -122.472270103664)'), (97434, '', 'Ulmus parvifolia :: Chinese Elm', '1380x Newcomb Ave', 5, 'Median : Cutout', 'Tree', 'DPW', '', '2011-09-30 00:00:00+00:00', '3', '', '', 6016360.63733, 2094893.94179, 37.7330981190079, -122.385796183605, '(37.7330981190079, -122.385796183605)'), (91166, '', 'Cercis canadensis :: Eastern Redbud', '1548x Quesada Ave', 4, 'Median : Cutout', 'Tree', 'DPW', '', '2009-01-31 00:00:00+00:00', '3', '', '', 6015526.48125, 2094420.051093, 37.7317507154659, -122.388647039673, '(37.7317507154659, -122.388647039673)'), (87422, '', 'Lophostemon confertus :: Brisbane Box', '45X Jones St', 1, 'Sidewalk: Curb side : Cutout', 'Tree', 'DPW', '', '2008-04-22 00:00:00+00:00', '', '', '', 6009092.517834, 2112687.614007, 37.7815506408215, -122.412181237011, '(37.7815506408215, -122.412181237011)'), (87402, '', 'Prunus cerasifera :: Cherry Plum', '1300 Webster St', 7, 'Median : Cutout', 'Tree', 'DPW', '', '2008-04-21 00:00:00+00:00', '3', '3x3', '', 6003725.160049, 2113179.069411, 37.7825974263114, -122.430784800607, '(37.7825974263114, -122.430784800607)');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_images.labels`
(
  image_id STRING,
  source STRING,
  label_name STRING,
  confidence FLOAT64
);

INSERT INTO `bigquery-public-data.open_images.labels` (image_id, source, label_name, confidence) VALUES ('48a8ae7dcea2ee7b', 'human', '/m/0_k2', 0.0), ('03ebaa6691dd92b8', 'human', '/m/0_k2', 0.0), ('001fc547329866a1', 'human', '/m/0_k2', 0.0), ('03d684e10a2f30c3', 'human', '/m/0_k2', 0.0), ('073b4f8ab735456c', 'human', '/m/0h5k', 0.0);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_images.dict`
(
  label_name STRING,
  label_display_name STRING
);

INSERT INTO `bigquery-public-data.open_images.dict` (label_name, label_display_name) VALUES ('/m/01www', 'CD'), ('/m/0h989', 'Go'), ('/m/03bx7vb', 'Ox'), ('/m/01lgkm', 'RV'), ('/m/012wxt', 'Vj');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_images.images`
(
  image_id STRING,
  subset STRING,
  original_url STRING,
  original_landing_url STRING,
  license STRING,
  author_profile_url STRING,
  author STRING,
  title STRING,
  original_size INT64,
  original_md5 STRING,
  thumbnail_300k_url STRING
);

INSERT INTO `bigquery-public-data.open_images.images` (image_id, subset, original_url, original_landing_url, license, author_profile_url, author, title, original_size, original_md5, thumbnail_300k_url) VALUES ('4bc3355cee62c134', 'test', 'https://farm5.staticflickr.com/3298/4568682698_4934495448_o.jpg', 'https://www.flickr.com/photos/1la/4568682698', 'https://creativecommons.org/licenses/by/2.0/', 'https://www.flickr.com/people/1la/', 'ilaria', 'torta di mele e cannella#1', 1898324, 'N6igOnRKJx5oPmUZ5JLKeg==', 'https://c6.staticflickr.com/4/3298/4568682698_a108303ea2_z.jpg'), ('c5d3b4d316c5f4c5', 'test', 'https://farm6.staticflickr.com/1027/540292777_181e68eb01_o.jpg', 'https://www.flickr.com/photos/1la/540292777', 'https://creativecommons.org/licenses/by/2.0/', 'https://www.flickr.com/people/1la/', 'ilaria', 'prima del forno', 764512, 'zq/rYYk0K+VkCcl3SGShhA==', 'https://c2.staticflickr.com/2/1027/540292777_ae94892482_z.jpg'), ('8a5fa5652754f03c', 'test', 'https://c5.staticflickr.com/9/8300/8037336388_e2b170022d_o.jpg', 'https://www.flickr.com/photos/422/8037336388', 'https://creativecommons.org/licenses/by/2.0/', 'https://www.flickr.com/people/422/', 'Eli', 'Southern Cali Road Trip', 613137, 'ebYHfu22I9PfU89VB05Rmw==', 'https://c2.staticflickr.com/9/8300/8037336388_515c6efb5a_z.jpg'), ('57f2f8e2a31721e5', 'test', 'https://farm6.staticflickr.com/7215/7226943088_fbd6641ece_o.jpg', 'https://www.flickr.com/photos/ajy/7226943088/', 'https://creativecommons.org/licenses/by/2.0/', 'https://www.flickr.com/people/ajy/', 'Alistair Young', 'A Light Snack at the Gellert Restaurant', 941227, 'mWPkTJIAmNmPoOmYr1NheA==', 'https://c8.staticflickr.com/8/7215/7226943088_5e2e5a822f_z.jpg'), ('76c1552233203cef', 'test', 'https://c8.staticflickr.com/2/1081/737615063_5d381867ea_o.jpg', 'https://www.flickr.com/photos/aok/737615063', 'https://creativecommons.org/licenses/by/2.0/', 'https://www.flickr.com/people/aok/', 'Oskari Kettunen', 'Opening (2/4)', 2107296, 'Eeq+MST00TvWRAwMZvKgtw==', 'https://c1.staticflickr.com/2/1081/737615063_21403d1ec4_z.jpg');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_images.annotations_bbox`
(
  image_id STRING,
  source STRING,
  label_name STRING,
  confidence FLOAT64,
  x_min FLOAT64,
  x_max FLOAT64,
  y_min FLOAT64,
  y_max FLOAT64,
  is_occluded BOOL,
  is_truncated BOOL,
  is_group_of BOOL,
  is_depiction BOOL,
  is_inside BOOL
);

INSERT INTO `bigquery-public-data.open_images.annotations_bbox` (image_id, source, label_name, confidence, x_min, x_max, y_min, y_max, is_occluded, is_truncated, is_group_of, is_depiction, is_inside) VALUES ('036b24f92ed0d95e', 'human', '/m/0_k2', 1.0, 0.01, 0.404, 0.173, 0.416, NULL, NULL, NULL, NULL, NULL), ('d7f443439c6ffbfe', 'human', '/m/0_k2', 1.0, 0.318, 0.444, 0.016, 0.248, NULL, NULL, NULL, NULL, NULL), ('39808cdbf12eb7d0', 'human', '/m/0_k2', 1.0, 0.019, 0.966, 0.335, 0.751, NULL, NULL, NULL, NULL, NULL), ('5e85a77309b69a5f', 'human', '/m/0_k2', 1.0, 0.143, 0.345, 0.742, 0.925, NULL, NULL, NULL, NULL, NULL), ('540dc51c25dd244c', 'human', '/m/0_k2', 1.0, 0.21, 0.748, 0.189, 0.891, NULL, NULL, NULL, NULL, NULL);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.associationByDatatypeIndirect`
(
  diseaseId STRING,
  targetId STRING,
  datatypeId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `bigquery-public-data.open_targets_platform.associationByDatatypeIndirect` (diseaseId, targetId, datatypeId, score, evidenceCount) VALUES ('OTAR_0000006', 'ENSG00000117394', 'literature', 0.83349167092027, 256), ('MONDO_0006507', 'ENSG00000138449', 'genetic_association', 0.9257370696887254, 256), ('OTAR_0000020', 'ENSG00000138449', 'genetic_association', 0.9257370696887254, 256), ('EFO_0007318', 'ENSG00000105369', 'literature', 0.22489716308970872, 256), ('EFO_0005741', 'ENSG00000151623', 'literature', 0.26071459409866177, 256);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.go`
(
  id STRING,
  name STRING
);

INSERT INTO `bigquery-public-data.open_targets_platform.go` (id, name) VALUES ('GO:0030424', 'axon'), ('GO:0032059', 'bleb'), ('GO:0060417', 'yolk'), ('GO:0008623', 'CHRAC'), ('GO:0098986', 'T-bar');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.targetsPriorisation`
(
  targetId STRING,
  isInMembrane INT64,
  isSecreted INT64,
  hasSafetyEvent INT64,
  hasPocket INT64,
  hasLigand INT64,
  geneticConstraint FLOAT64,
  paralogMaxIdentityPercentage FLOAT64,
  mouseOrthologMaxIdentityPercentage FLOAT64,
  isCancerDriverGene INT64,
  hasTEP INT64,
  hasMouseKO INT64,
  hasHighQualityChemicalProbes INT64,
  maxClinicalTrialPhase FLOAT64,
  tissueSpecificity FLOAT64,
  tissueDistribution FLOAT64
);

INSERT INTO `bigquery-public-data.open_targets_platform.targetsPriorisation` (targetId, isInMembrane, isSecreted, hasSafetyEvent, hasPocket, hasLigand, geneticConstraint, paralogMaxIdentityPercentage, mouseOrthologMaxIdentityPercentage, isCancerDriverGene, hasTEP, hasMouseKO, hasHighQualityChemicalProbes, maxClinicalTrialPhase, tissueSpecificity, tissueDistribution) VALUES ('ENSG00000135747', NULL, NULL, NULL, 0, 0, 0.848822671389873, nan, nan, NULL, NULL, NULL, NULL, nan, nan, nan), ('ENSG00000175509', NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, NULL, NULL, nan, nan, nan), ('ENSG00000176752', NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, NULL, NULL, nan, nan, nan), ('ENSG00000176761', NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, NULL, NULL, nan, nan, nan), ('ENSG00000198217', NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, NULL, NULL, nan, nan, nan);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.diseaseToPhenotype`
(
  disease STRING,
  phenotype STRING,
  evidence STRUCT<list ARRAY<STRUCT<element STRUCT<aspect STRING, bioCuration STRING, diseaseFromSourceId STRING, diseaseFromSource STRING, diseaseName STRING, evidenceType STRING, frequency STRING, modifiers STRUCT<list ARRAY<STRUCT<element STRING>>>, onset STRUCT<list ARRAY<STRUCT<element STRING>>>, qualifier STRING, qualifierNot BOOL NOT NULL, references STRUCT<list ARRAY<STRUCT<element STRING>>>, sex STRING, resource STRING> NOT NULL>>> NOT NULL
);

INSERT INTO `bigquery-public-data.open_targets_platform.diseaseToPhenotype` (disease, phenotype, evidence) VALUES ('Orphanet_552', 'HP_0001520', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040283', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0004924', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040282', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0000831', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040283', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0000119', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040284', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0003076', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040282', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"});
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.associationByDatasourceDirect`
(
  datatypeId STRING,
  datasourceId STRING,
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64 NOT NULL
);

INSERT INTO `bigquery-public-data.open_targets_platform.associationByDatasourceDirect` (datatypeId, datasourceId, diseaseId, targetId, score, evidenceCount) VALUES ('genetic_association', 'eva', 'HP_0000011', 'ENSG00000141837', 0.19453785523571876, 1), ('genetic_association', 'eva', 'HP_0000023', 'ENSG00000166147', 0.5592963338026914, 1), ('genetic_association', 'eva', 'HP_0000029', 'ENSG00000162695', 0.4377101742803672, 1), ('genetic_association', 'eva', 'HP_0000029', 'ENSG00000171680', 0.19453785523571876, 1), ('genetic_association', 'eva', 'HP_0000062', 'ENSG00000196924', 0.19453785523571876, 1);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.associationByOverallDirect`
(
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `bigquery-public-data.open_targets_platform.associationByOverallDirect` (diseaseId, targetId, score, evidenceCount) VALUES ('EFO_0000198', 'ENSG00000108342', 0.05712528657623925, 256), ('EFO_0000400', 'ENSG00000169047', 0.21897639708803107, 256), ('EFO_0006790', 'ENSG00000142192', 0.3614410052684886, 256), ('EFO_1000684', 'ENSG00000105369', 0.09459043799521433, 256), ('OBI_1110021', 'ENSG00000183258', 0.06675469315003064, 256);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.associationByDatasourceIndirect`
(
  datatypeId STRING,
  datasourceId STRING,
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64 NOT NULL
);

INSERT INTO `bigquery-public-data.open_targets_platform.associationByDatasourceIndirect` (datatypeId, datasourceId, diseaseId, targetId, score, evidenceCount) VALUES ('genetic_association', 'eva', 'EFO_0002945', 'ENSG00000177628', 0.9429057941673307, 156), ('genetic_association', 'eva', 'MONDO_0004580', 'ENSG00000196189', 0.8343887095693674, 106), ('genetic_association', 'eva', 'MONDO_0010041', 'ENSG00000151835', 0.9480686371830984, 1125), ('genetic_association', 'eva', 'EFO_0000508', 'ENSG00000144488', 0.316739123497058, 61), ('genetic_association', 'eva', 'MONDO_0000591', 'ENSG00000139549', 0.8860192358280301, 69);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.significantAdverseDrugReactions`
(
  chembl_id STRING,
  event STRING,
  count INT64 NOT NULL,
  llr FLOAT64,
  critval FLOAT64,
  meddraCode STRING
);

INSERT INTO `bigquery-public-data.open_targets_platform.significantAdverseDrugReactions` (chembl_id, event, count, llr, critval, meddraCode) VALUES ('CHEMBL2', 'hypotension', 53, 91.35776972666008, 6.251299745844193, '10021097'), ('CHEMBL3', 'jaundice neonatal', 43, 155.15858689508605, 38.961201902675384, '10023138'), ('CHEMBL3', 'macular degeneration', 114, 388.47462428933795, 38.961201902675384, '10025409'), ('CHEMBL3', 'drug abuse', 83, 86.02875766474244, 38.961201902675384, '10013654'), ('CHEMBL3', 'premature baby', 150, 299.56098443422525, 38.961201902675384, '10036590');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.interaction`
(
  sourceDatabase STRING,
  targetA STRING,
  intA STRING,
  intABiologicalRole STRING,
  targetB STRING,
  intB STRING,
  intBBiologicalRole STRING,
  speciesA STRUCT<mnemonic STRING, scientific_name STRING, taxon_id INT64>,
  speciesB STRUCT<mnemonic STRING, scientific_name STRING, taxon_id INT64>,
  count INT64 NOT NULL,
  scoring FLOAT64
);

INSERT INTO `bigquery-public-data.open_targets_platform.interaction` (sourceDatabase, targetA, intA, intABiologicalRole, targetB, intB, intBBiologicalRole, speciesA, speciesB, count, scoring) VALUES ('intact', 'ENSG00000174132', 'Q8TBP5', 'unspecified role', 'ENSG00000111647', 'A0JNW5', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000274391', 'P56180-2', 'unspecified role', 'ENSG00000105135', 'A1L0T0', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000097096', 'Q5VT97-1', 'unspecified role', 'ENSG00000126822', 'A1L390', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000167770', 'Q96FW1', 'unspecified role', 'ENSG00000185888', 'A1L453', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000169951', 'Q96H86', 'unspecified role', 'ENSG00000174705', 'A1X283', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.hpo`
(
  dbXRefs STRUCT<list ARRAY<STRUCT<element STRING>>>,
  description STRING,
  id STRING,
  name STRING,
  namespace STRUCT<list ARRAY<STRUCT<element STRING>>>,
  obsolete_terms STRUCT<list ARRAY<STRUCT<element STRING>>>,
  parents STRUCT<list ARRAY<STRUCT<element STRING>>>
);

INSERT INTO `bigquery-public-data.open_targets_platform.hpo` (dbXRefs, description, id, name, namespace, obsolete_terms, parents) VALUES (NULL, NULL, 'CL_1001567', 'lung endothelial cell', {'list': "[{'element': 'cl'}]"}, NULL, {'list': "[{'element': 'b43134'} {'element': 'CL_0000082'} {'element': 'CL_0002139'}]"}), ({'list': "[{'element': 'BTO:0001141'}]"}, NULL, 'CL_1001568', 'pulmonary artery endothelial cell', {'list': "[{'element': 'cl'}]"}, NULL, {'list': "[{'element': 'b44524'} {'element': 'CL_1000413'}]"}), (NULL, 'The various hormone- or neurotransmitter-secreting cells present throughout the mucosa of the intestinal tract.', 'CL_1001516', 'intestinal enteroendocrine cell', {'list': "[{'element': 'cl'}]"}, NULL, {'list': "[{'element': 'CL_0002563'} {'element': 'CL_0000164'}]"}), (NULL, NULL, 'BFO_0000019', 'quality', {'list': "[{'element': 'bfo'}]"}, NULL, {'list': "[{'element': 'b24511'} {'element': 'BFO_0000020'}]"}), (NULL, 'An independent continuant that is spatially extended whose identity is independent of that of other entities and can be maintained through time.', 'BFO_0000040', 'material entity', {'list': "[{'element': 'bfo'}]"}, NULL, {'list': "[{'element': 'BFO_0000004'}]"});
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.indication`
(
  id STRING,
  indications STRUCT<list ARRAY<STRUCT<element STRUCT<disease STRING, efoName STRING, references STRUCT<list ARRAY<STRUCT<element STRUCT<source STRING, ids STRUCT<list ARRAY<STRUCT<element STRING>>> NOT NULL> NOT NULL>>> NOT NULL, maxPhaseForIndication FLOAT64> NOT NULL>>> NOT NULL,
  approvedIndications STRUCT<list ARRAY<STRUCT<element STRING NOT NULL>>> NOT NULL,
  indicationCount INT64 NOT NULL
);

INSERT INTO `bigquery-public-data.open_targets_platform.indication` (id, indications, approvedIndications, indicationCount) VALUES ('CHEMBL500826', {'list': "[{'element': {'disease': 'EFO_1001888', 'efoName': 'eye infection', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'S01AX10'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                             ]"}, {'list': '[]'}, 1), ('CHEMBL3989504', {'list': "[{'element': {'disease': 'EFO_0000771', 'efoName': 'bacterial disease', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'J01MA21'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                                 ]"}, {'list': '[]'}, 1), ('CHEMBL36633', {'list': "[{'element': {'disease': 'EFO_0003888', 'efoName': 'attention deficit hyperactivity disorder', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'N06BX07'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                                                        ]"}, {'list': '[]'}, 1), ('CHEMBL3989705', {'list': "[{'element': {'disease': 'EFO_1001888', 'efoName': 'eye infection', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'S01AX10'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                             ]"}, {'list': '[]'}, 1), ('CHEMBL3989444', {'list': "[{'element': {'disease': 'EFO_0000319', 'efoName': 'cardiovascular disease', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'C04AX24'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                                      ]"}, {'list': '[]'}, 1);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.open_targets_platform.associationByDatatypeDirect`
(
  diseaseId STRING,
  targetId STRING,
  datatypeId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `bigquery-public-data.open_targets_platform.associationByDatatypeDirect` (diseaseId, targetId, datatypeId, score, evidenceCount) VALUES ('HP_0011123', 'ENSG00000112115', 'literature', 0.257067389837001, 256), ('EFO_0000508', 'ENSG00000120802', 'genetic_association', 0.31858841318116704, 256), ('EFO_0000544', 'ENSG00000188379', 'literature', 0.7732159986824866, 256), ('EFO_0000589', 'ENSG00000186951', 'literature', 0.32592042558685136, 256), ('EFO_0000616', 'ENSG00000116824', 'literature', 0.8178757044321686, 256);