nl2sqlproj/spider2-nl2sql huggingface dataset:
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_preliminary_severe_storms.tornado_reports`
(
  timestamp TIMESTAMP OPTIONS(description="Timestamp in UTC"),
  time STRING OPTIONS(description="Hour in UTC"),
  f_scale STRING OPTIONS(description="The F-Scale classifies F0-F5 damage as calibrated by engineers and meteorologists across 28 different types of damage indicators (mainly various kinds of buildings, but also a few other structures as well as trees)."),
  location STRING OPTIONS(description="Location of report"),
  county STRING OPTIONS(description=""),
  state STRING OPTIONS(description=""),
  latitude FLOAT64 OPTIONS(description="Latitude to two decimal places"),
  longitude FLOAT64 OPTIONS(description="Longitude to two decimal places"),
  comments STRING OPTIONS(description=""),
  report_point GEOGRAPHY OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.noaa_preliminary_severe_storms.tornado_reports` (timestamp, time, f_scale, location, county, state, latitude, longitude, comments, report_point) VALUES ('2019-01-04 10:40:00+00:00', '1040', 'UNK', '2 N GRABALL', 'HENRY', 'AL', 31.62, -85.28, 'TREE DAMAGE FROM A BRIEF TORNADO ABOUT 1.5 MI N OF ABBEVILLE / 2 MI N GRABALL. (TAE)', 'POINT(-85.28 31.62)'), ('2019-01-19 20:04:00+00:00', '2004', 'UNK', '3 ENE MULBERRY', 'AUTAUGA', 'AL', 32.49, -86.73, '*** 2 INJ *** CORRECTS PREVIOUS TORNADO REPORT TO INCLUDE 2 INJURIES. A NWS STORM SURVEY TEAM CONFIRMED A TORNADO OF EF-1 INTENSITY... WHICH OCCURRED JUST NORTHWEST OF (BMX)', 'POINT(-86.73 32.49)'), ('2019-01-19 20:52:00+00:00', '2052', 'UNK', '3 SW WETUMPKA', 'ELMORE', 'AL', 32.52, -86.24, '*** 4 INJ *** A NWS STORM SURVEY TEAM CONFIRMED A TORNADO OF HIGH-END EF-2 INTENSITY THAT BEGAN JUST SOUTHWEST OF WETUMPKA AND CONTINUED NORTHEAST... ENDING JUST BEFORE (BMX)', 'POINT(-86.24 32.52)'), ('2019-01-19 20:58:00+00:00', '2058', 'UNK', '2 W COTTAGE GROVE', 'COOSA', 'AL', 32.85, -86.15, 'A NWS STORM SURVEY TEAM CONFIRMED A TORNADO OF EF-1 INTENSITY... AFFECTING AREAS JUST SOUTHEAST OF ROCKFORD IN COOSA COUNTY ALONG COUNTY ROAD 101. (BMX)', 'POINT(-86.15 32.85)'), ('2019-02-23 23:44:00+00:00', '2344', 'UNK', '3 WSW GAINESVILLE LAKE', 'PICKENS', 'AL', 33.06, -88.31, 'CORRECTS PREVIOUS TORNADO REPORT FROM 3 WSW GAINSVILLE LAKE. THE TORNADO TOUCHED DOWN JUST EAST OF NANCY CLARK ROAD... AND FIRST CAUSED DAMAGE ALONG AN EAST-WEST TREELI (BMX)', 'POINT(-88.31 33.06)');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_preliminary_severe_storms.wind_reports`
(
  timestamp TIMESTAMP OPTIONS(description="Timestamp in UTC"),
  time STRING OPTIONS(description="Hour in UTC"),
  speed INT64 OPTIONS(description="Speed in Miles per hour"),
  location STRING OPTIONS(description="Location of report"),
  county STRING OPTIONS(description=""),
  state STRING OPTIONS(description=""),
  latitude FLOAT64 OPTIONS(description="Latitude to two decimal places"),
  longitude FLOAT64 OPTIONS(description="Longitude to two decimal places"),
  comments STRING OPTIONS(description=""),
  report_point GEOGRAPHY OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.noaa_preliminary_severe_storms.wind_reports` (timestamp, time, speed, location, county, state, latitude, longitude, comments, report_point) VALUES ('2019-01-19 22:54:00+00:00', '2254', NULL, '2 N CRAWFORD', 'LEE', 'AL', 32.49, -85.18, 'TREES DOWN NEAR THE INTERSECTION OF LEE RD 440 AND LEE RD 179. ALSO REPORT OF TREES DOWN JUST TO THE EAST NEAR THE INTERSECTION OF LEE RD 240 AND LEE RD 212. TIME ESTIM (BMX)', 'POINT(-85.18 32.49)'), ('2019-02-12 18:11:00+00:00', '1811', NULL, '3 SW MONTEREY HEIGHTS', 'LEE', 'AL', 32.49, -85.13, 'REPORTS OF TREES DOWN IN VARIOUS LOCATIONS IN EASTERN LEE COUNTY FROM BOWING STORM SEGMENT. TIME ESTIMATED. (BMX)', 'POINT(-85.13 32.49)'), ('2019-03-03 20:22:00+00:00', '2022', NULL, 'SMITH''S STATION', 'LEE', 'AL', 32.6, -85.24, 'CORRECTS PREVIOUS TORNADO REPORT FROM SALEM. US HWY 280 BLOCKED BY DOWNED CELL TOWER ACROSS HWY. (BMX)', 'POINT(-85.24 32.6)'), ('2019-03-26 00:13:00+00:00', '0013', NULL, '1 NNW SMITHS STATION', 'LEE', 'AL', 32.55, -85.1, 'A TREE WAS DOWNED ONTO A HOME. (BMX)', 'POINT(-85.1 32.55)'), ('2019-06-07 17:56:00+00:00', '1756', NULL, '1 SSE ROBERT G. PITTS A', 'LEE', 'AL', 32.6, -85.42, 'TREE DOWN ON A HOME. TIME ESTIMATED FROM RADAR. (BMX)', 'POINT(-85.42 32.6)');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_historic_severe_storms.hail_reports`
(
  timestamp TIMESTAMP OPTIONS(description="Timestamp in UTC"),
  time STRING OPTIONS(description="Hour in UTC"),
  size INT64 OPTIONS(description="Size in 1/100 of an Inch (175 = 1.75in)"),
  location STRING OPTIONS(description="Location of report"),
  county STRING OPTIONS(description=""),
  state STRING OPTIONS(description=""),
  latitude FLOAT64 OPTIONS(description="Latitude to two decimal places"),
  longitude FLOAT64 OPTIONS(description="Longitude to two decimal places"),
  comments STRING OPTIONS(description=""),
  report_point GEOGRAPHY OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.noaa_historic_severe_storms.hail_reports` (timestamp, time, size, location, county, state, latitude, longitude, comments, report_point) VALUES ('2021-04-09 15:01:00+00:00', '1501', 150, '4 ESE MARBURY', 'AUTAUGA', 'AL', 32.67, -86.42, 'FORWARDED BY BROADCAST MEDIA VIA SOCIAL MEDIA. (BMX)', 'POINT(-86.42 32.67)'), ('2021-05-03 23:30:00+00:00', '2330', 100, '3 NNE PRATTVILLE', 'AUTAUGA', 'AL', 32.5, -86.44, 'QUARTER SIZE HAIL WAS REPORTED ON OLD RIDGE ROAD NORTH OF PRATTVILLE. (BMX)', 'POINT(-86.44 32.5)'), ('2021-04-10 08:20:00+00:00', '0820', 400, '1 SSW ORANGE BEACH', 'BALDWIN', 'AL', 30.27, -87.59, 'TWO SEPARATE PHOTOS SHOW HAIL NEAR SOFTBALL SIZE IN ORANGE BEACH. SIGNIFICANT HAIL DAMAGE REPORTED TO NUMEROUS VEHICLES AND METALS ROOFS IN THE AREA. (MOB)', 'POINT(-87.59 30.27)'), ('2021-04-10 08:40:00+00:00', '0840', 200, '4 SW LILLIAN', 'BALDWIN', 'AL', 30.38, -87.48, 'REPORT OF 2 INCH SIZE HAIL FURTHER INLAND (SOUTHWEST OF LILLIAN). (MOB)', 'POINT(-87.48 30.38)'), ('2021-04-15 12:56:00+00:00', '1256', 100, '2 WSW FOLEY', 'BALDWIN', 'AL', 30.39, -87.72, 'CORRECTS PREVIOUS HAIL REPORT FROM 2 WSW FOLEY. REPORT OF QUARTER-SIZE HAIL IN SOUTHWEST FOLEY. TIME AND LOCATION GIVEN BY LOCAL POLICE. (MOB)', 'POINT(-87.72 30.39)');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_historic_severe_storms.tornado_reports`
(
  timestamp TIMESTAMP OPTIONS(description="Timestamp in UTC"),
  time STRING OPTIONS(description="Hour in UTC"),
  f_scale STRING OPTIONS(description="The F-Scale classifies F0-F5 damage as calibrated by engineers and meteorologists across 28 different types of damage indicators (mainly various kinds of buildings, but also a few other structures as well as trees)."),
  location STRING OPTIONS(description="Location of report"),
  county STRING OPTIONS(description=""),
  state STRING OPTIONS(description=""),
  latitude FLOAT64 OPTIONS(description="Latitude to two decimal places"),
  longitude FLOAT64 OPTIONS(description="Longitude to two decimal places"),
  comments STRING OPTIONS(description=""),
  report_point GEOGRAPHY OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.noaa_historic_severe_storms.tornado_reports` (timestamp, time, f_scale, location, county, state, latitude, longitude, comments, report_point) VALUES ('2019-01-04 10:40:00+00:00', '1040', 'UNK', '2 N GRABALL', 'HENRY', 'AL', 31.62, -85.28, 'TREE DAMAGE FROM A BRIEF TORNADO ABOUT 1.5 MI N OF ABBEVILLE / 2 MI N GRABALL. (TAE)', 'POINT(-85.28 31.62)'), ('2019-01-19 20:04:00+00:00', '2004', 'UNK', '3 ENE MULBERRY', 'AUTAUGA', 'AL', 32.49, -86.73, '*** 2 INJ *** CORRECTS PREVIOUS TORNADO REPORT TO INCLUDE 2 INJURIES. A NWS STORM SURVEY TEAM CONFIRMED A TORNADO OF EF-1 INTENSITY... WHICH OCCURRED JUST NORTHWEST OF (BMX)', 'POINT(-86.73 32.49)'), ('2019-01-19 20:52:00+00:00', '2052', 'UNK', '3 SW WETUMPKA', 'ELMORE', 'AL', 32.52, -86.24, '*** 4 INJ *** A NWS STORM SURVEY TEAM CONFIRMED A TORNADO OF HIGH-END EF-2 INTENSITY THAT BEGAN JUST SOUTHWEST OF WETUMPKA AND CONTINUED NORTHEAST... ENDING JUST BEFORE (BMX)', 'POINT(-86.24 32.52)'), ('2019-01-19 20:58:00+00:00', '2058', 'UNK', '2 W COTTAGE GROVE', 'COOSA', 'AL', 32.85, -86.15, 'A NWS STORM SURVEY TEAM CONFIRMED A TORNADO OF EF-1 INTENSITY... AFFECTING AREAS JUST SOUTHEAST OF ROCKFORD IN COOSA COUNTY ALONG COUNTY ROAD 101. (BMX)', 'POINT(-86.15 32.85)'), ('2019-02-23 23:44:00+00:00', '2344', 'UNK', '3 WSW GAINESVILLE LAKE', 'PICKENS', 'AL', 33.06, -88.31, 'CORRECTS PREVIOUS TORNADO REPORT FROM 3 WSW GAINSVILLE LAKE. THE TORNADO TOUCHED DOWN JUST EAST OF NANCY CLARK ROAD... AND FIRST CAUSED DAMAGE ALONG AN EAST-WEST TREELI (BMX)', 'POINT(-88.31 33.06)');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_historic_severe_storms.wind_reports`
(
  timestamp TIMESTAMP OPTIONS(description="Timestamp in UTC"),
  time STRING OPTIONS(description="Hour in UTC"),
  speed INT64 OPTIONS(description="Speed in Miles per hour"),
  location STRING OPTIONS(description="Location of report"),
  county STRING OPTIONS(description=""),
  state STRING OPTIONS(description=""),
  latitude FLOAT64 OPTIONS(description="Latitude to two decimal places"),
  longitude FLOAT64 OPTIONS(description="Longitude to two decimal places"),
  comments STRING OPTIONS(description=""),
  report_point GEOGRAPHY OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.noaa_historic_severe_storms.wind_reports` (timestamp, time, speed, location, county, state, latitude, longitude, comments, report_point) VALUES ('2019-01-19 20:17:00+00:00', '2017', NULL, '3 NNW BOOTH', 'AUTAUGA', 'AL', 32.54, -86.6, 'DAMAGE TO A MOBILE HOME REPORTED BY EMA. PROBABLE TORNADO. (BMX)', 'POINT(-86.6 32.54)'), ('2019-02-12 16:36:00+00:00', '1636', NULL, 'PRATTVILLE', 'AUTAUGA', 'AL', 32.46, -86.45, 'CORRECTS PREVIOUS TSTM WND DMG REPORT FROM PRATTVILLE. 5 TREES WERE SNAPPED OFF IN THE CAMELLIA ESTATES NEIGHBORHOOD IN PRATTVILLE. AT LEAST ONE RESIDENCE SUSTAINED ROO (BMX)', 'POINT(-86.45 32.46)'), ('2019-03-03 19:25:00+00:00', '1925', NULL, '4 NNW AUTAUGAVILLE', 'AUTAUGA', 'AL', 32.49, -86.69, 'TREES DOWN ALONG CR 19 NORTH OF AUTAUGAVILLE. (BMX)', 'POINT(-86.69 32.49)'), ('2019-06-26 03:15:00+00:00', '0315', NULL, '1 E PRATTVILLE', 'AUTAUGA', 'AL', 32.46, -86.43, 'TREE DOWN ON SUMMER LN. WINDS ESTIMATED AT 40-50 MPH AS SUGGESTED BY RADAR AND NEARBY SURFACE OB AT K1A9. (BMX)', 'POINT(-86.43 32.46)'), ('2019-04-19 00:33:00+00:00', '0033', NULL, 'SEMINOLE', 'BALDWIN', 'AL', 30.52, -87.47, 'REPORTS OF DOWNED POWER LINES NEAR SEMINOLE. TIME ESTIMATED BY RADAR. (MOB)', 'POINT(-87.47 30.52)');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_passive_acoustic_index.nrs_metadata`
(
  file_name STRING,
  deployment_name STRING,
  start_date DATE,
  start_time TIME,
  source_organization STRING,
  funding_organization STRING,
  project_name STRING,
  sensor_depth INT64,
  sample_rate INT64,
  duration INT64,
  platform_name STRING,
  lon FLOAT64,
  lat FLOAT64,
  point_geom GEOGRAPHY,
  file_link STRING
);

INSERT INTO `bigquery-public-data.noaa_passive_acoustic_index.nrs_metadata` (file_name, deployment_name, start_date, start_time, source_organization, funding_organization, project_name, sensor_depth, sample_rate, duration, platform_name, lon, lat, point_geom, file_link) VALUES ('NRS03_20141110_131736.wav', 'NRS-2014-2015-03', '2014-11-10', '13:17:36', 'PMEL', 'NOAA/NMFS/Ocean Acoustics Program', 'NRS', 488, 5, 60, 'Mooring', -125.5222, 47.7651, 'POINT(-125.5222 47.7651)', 'gs://noaa-passive-bioacoustic/nrs/03/2014-2015/audio/NRS03_20141110_131736.wav'), ('NRS03_20141110_171742.wav', 'NRS-2014-2015-03', '2014-11-10', '17:17:42', 'PMEL', 'NOAA/NMFS/Ocean Acoustics Program', 'NRS', 488, 5, 60, 'Mooring', -125.5222, 47.7651, 'POINT(-125.5222 47.7651)', 'gs://noaa-passive-bioacoustic/nrs/03/2014-2015/audio/NRS03_20141110_171742.wav'), ('NRS03_20141110_011715.wav', 'NRS-2014-2015-03', '2014-11-10', '01:17:15', 'PMEL', 'NOAA/NMFS/Ocean Acoustics Program', 'NRS', 488, 5, 60, 'Mooring', -125.5222, 47.7651, 'POINT(-125.5222 47.7651)', 'gs://noaa-passive-bioacoustic/nrs/03/2014-2015/audio/NRS03_20141110_011715.wav'), ('NRS03_20141110_211749.wav', 'NRS-2014-2015-03', '2014-11-10', '21:17:49', 'PMEL', 'NOAA/NMFS/Ocean Acoustics Program', 'NRS', 488, 5, 60, 'Mooring', -125.5222, 47.7651, 'POINT(-125.5222 47.7651)', 'gs://noaa-passive-bioacoustic/nrs/03/2014-2015/audio/NRS03_20141110_211749.wav'), ('NRS03_20141110_091729.wav', 'NRS-2014-2015-03', '2014-11-10', '09:17:29', 'PMEL', 'NOAA/NMFS/Ocean Acoustics Program', 'NRS', 488, 5, 60, 'Mooring', -125.5222, 47.7651, 'POINT(-125.5222 47.7651)', 'gs://noaa-passive-bioacoustic/nrs/03/2014-2015/audio/NRS03_20141110_091729.wav');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_passive_acoustic_index.sanctsound_metadata`
(
  file_name STRING,
  data_collection_name STRING,
  start_date DATE,
  start_time TIME,
  source_organization STRING,
  funding_organization STRING,
  project_name STRING,
  sensor_depth FLOAT64,
  sample_rate INT64,
  recording_percent INT64,
  platform_name STRING,
  longitude FLOAT64,
  latitude FLOAT64,
  file_link STRING
);

INSERT INTO `bigquery-public-data.noaa_passive_acoustic_index.sanctsound_metadata` (file_name, data_collection_name, start_date, start_time, source_organization, funding_organization, project_name, sensor_depth, sample_rate, recording_percent, platform_name, longitude, latitude, file_link) VALUES ('SanctSound_CI01_02.xml', 'SanctSound_CI01_02', '2019-03-25', '21:00:00', 'NOAA ONMS,US Navy LMR', 'NOAA ONMS,US Navy LMR', 'SanctSound', 17.0, 48000, 100, 'Mooring', -120.08105, 34.0438, NULL), ('SanctSound_CI01_02.json', 'SanctSound_CI01_02', '2019-03-25', '21:00:00', 'NOAA ONMS,US Navy LMR', 'NOAA ONMS,US Navy LMR', 'SanctSound', 17.0, 48000, 100, 'Mooring', -120.08105, 34.0438, NULL), ('CI01_02_RBRsT_101578.mat', 'SanctSound_CI01_02', '2019-03-25', '21:00:00', 'NOAA ONMS,US Navy LMR', 'NOAA ONMS,US Navy LMR', 'SanctSound', 17.0, 48000, 100, 'Mooring', -120.08105, 34.0438, NULL), ('CI01_02_RBRsT_101578.png', 'SanctSound_CI01_02', '2019-03-25', '21:00:00', 'NOAA ONMS,US Navy LMR', 'NOAA ONMS,US Navy LMR', 'SanctSound', 17.0, 48000, 100, 'Mooring', -120.08105, 34.0438, NULL), ('CI01_02_RBRsT_101578.rsk', 'SanctSound_CI01_02', '2019-03-25', '21:00:00', 'NOAA ONMS,US Navy LMR', 'NOAA ONMS,US Navy LMR', 'SanctSound', 17.0, 48000, 100, 'Mooring', -120.08105, 34.0438, NULL);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.noaa_gsod.stations`
(
  usaf STRING OPTIONS(description=""),
  wban STRING OPTIONS(description=""),
  name STRING OPTIONS(description=""),
  country STRING OPTIONS(description=""),
  state STRING OPTIONS(description=""),
  call STRING OPTIONS(description=""),
  lat FLOAT64 OPTIONS(description=""),
  lon FLOAT64 OPTIONS(description=""),
  elev STRING OPTIONS(description=""),
  begin STRING OPTIONS(description=""),
  `end` STRING OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.noaa_gsod.stations` (usaf, wban, name, country, state, call, lat, lon, elev, begin, end) VALUES ('007018', '99999', 'WXPOD 7018                   ', NULL, NULL, NULL, 0.0, 0.0, '+7018.0', '20110309', '20130730'), ('007026', '99999', 'WXPOD 7026                   ', 'AF', NULL, NULL, 0.0, 0.0, '+7026.0', '20120713', '20170822'), ('007070', '99999', 'WXPOD 7070                   ', 'AF', NULL, NULL, 0.0, 0.0, '+7070.0', '20140923', '20150926'), ('008268', '99999', 'WXPOD8278                    ', 'AF', NULL, NULL, 32.95, 65.567, '+1156.7', '20100519', '20120323'), ('008307', '99999', 'WXPOD 8318                   ', 'AF', NULL, NULL, 0.0, 0.0, '+8318.0', '20100421', '20100421');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.categories`
(
  productSKU STRING,
  category STRING
);

INSERT INTO `data-to-insights.ecommerce.categories` (productSKU, category) VALUES ('GGOEGOBC078699', 'Fun'), ('GGOEAOBH078799', 'Fun'), ('GGOEGBJC019999', 'Bags'), ('GGOEGBRJ037399', 'Bags'), ('GGOEGBCR024399', 'Bags');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.product_list`
(
  productSKU STRING,
  v2ProductName STRING
);

INSERT INTO `data-to-insights.ecommerce.product_list` (productSKU, v2ProductName) VALUES ('10 55401', 'Lip Balm'), ('9180842', 'Maze Pen'), ('GGOEGGOA017399', 'Maze Pen'), ('GGOEGAAX0213', 'Yoga Mat'), ('9182788', 'Yoga Mat');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.partition_by_day`
(
  date_formatted DATE,
  fullvisitorId STRING
)
PARTITION BY date_formatted
OPTIONS(
  description="a table partitioned by date"
);

INSERT INTO `data-to-insights.ecommerce.partition_by_day` (date_formatted, fullvisitorId) VALUES ('2017-06-09', '9048843609752982673'), ('2017-06-09', '9644130921840916570'), ('2017-06-09', '5125743408568920135'), ('2017-06-09', '7068061647475096007'), ('2017-06-09', '0868971251098781302');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.all_sessions`
(
  fullVisitorId STRING,
  channelGrouping STRING,
  time INT64,
  country STRING,
  city STRING,
  totalTransactionRevenue INT64,
  transactions INT64,
  timeOnSite INT64,
  pageviews INT64,
  sessionQualityDim INT64,
  date STRING,
  visitId INT64,
  type STRING,
  productRefundAmount INT64,
  productQuantity INT64,
  productPrice INT64,
  productRevenue INT64,
  productSKU STRING,
  v2ProductName STRING,
  v2ProductCategory STRING,
  productVariant STRING,
  currencyCode STRING,
  itemQuantity INT64,
  itemRevenue INT64,
  transactionRevenue INT64,
  transactionId STRING,
  pageTitle STRING,
  searchKeyword STRING,
  pagePathLevel1 STRING,
  eCommerceAction_type STRING,
  eCommerceAction_step INT64,
  eCommerceAction_option STRING
);

INSERT INTO `data-to-insights.ecommerce.all_sessions` (fullVisitorId, channelGrouping, time, country, city, totalTransactionRevenue, transactions, timeOnSite, pageviews, sessionQualityDim, date, visitId, type, productRefundAmount, productQuantity, productPrice, productRevenue, productSKU, v2ProductName, v2ProductCategory, productVariant, currencyCode, itemQuantity, itemRevenue, transactionRevenue, transactionId, pageTitle, searchKeyword, pagePathLevel1, eCommerceAction_type, eCommerceAction_step, eCommerceAction_option) VALUES ('0091280705703616305', 'Direct', 763918, 'South Korea', 'not available in demo dataset', NULL, NULL, 1210, 62, NULL, '20170107', 1483821753, 'PAGE', NULL, NULL, 0, NULL, '9180781', 'Suitcase Organizer Cubes', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('6470524072905607258', 'Paid Search', 27641, 'United States', 'New York', NULL, NULL, 33, 4, NULL, '20170201', 1485987637, 'PAGE', NULL, NULL, 0, NULL, '9180833', 'Rubber Grip Ballpoint Pen 4 Pack', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('6135979830533561674', 'Display', 191668, 'United States', 'San Francisco', NULL, NULL, 210, 7, NULL, '20170201', 1485988552, 'PAGE', NULL, NULL, 0, NULL, '9180833', 'Rubber Grip Ballpoint Pen 4 Pack', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('0755589803493813396', 'Organic Search', 51011, 'Ireland', 'Dublin', NULL, NULL, 446, 17, NULL, '20170203', 1486130699, 'PAGE', NULL, NULL, 0, NULL, '9180833', 'Rubber Grip Ballpoint Pen 4 Pack', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('4584480734761524599', 'Organic Search', 88002, 'Poland', 'not available in demo dataset', NULL, NULL, 190, 9, 1, '20170728', 1501238002, 'PAGE', NULL, NULL, 0, NULL, '9180838', 'Metal Texture Roller Pen', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.sales_report`
(
  productSKU STRING,
  total_ordered INT64,
  name STRING,
  stockLevel INT64,
  restockingLeadTime INT64,
  sentimentScore FLOAT64,
  sentimentMagnitude FLOAT64,
  ratio FLOAT64
);

INSERT INTO `data-to-insights.ecommerce.sales_report` (productSKU, total_ordered, name, stockLevel, restockingLeadTime, sentimentScore, sentimentMagnitude, ratio) VALUES ('GGOEGAAX0325', 6, ' Men''s Short Sleeve Hero Tee Charcoal', 104, 12, 0.0, 0.5, 0.057692307692307696), ('GGOEGOLC014299', 2, ' Metallic Notebook Set', 610, 5, 0.0, 0.1, 0.003278688524590164), ('GGOEGBRA037499', 5, 'Waterproof Backpack', 230, 10, 0.0, 0.1, 0.021739130434782608), ('GGOEWFKA083199', 5, ' Mood Original Window Decal', 66, 8, 0.0, 0.1, 0.07575757575757576), ('GGOEGBRJ037399', 11, ' Rucksack', 228, 5, 0.0, 0.1, 0.04824561403508772);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.days_with_rain`
(
  date DATE,
  station_name STRING,
  prcp FLOAT64
)
PARTITION BY date
OPTIONS(
  partition_expiration_days=60.0,
  description="weather stations with precipitation, partitioned by day"
);

INSERT INTO `data-to-insights.ecommerce.days_with_rain` (date, station_name, prcp) VALUES ;
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.all_sessions_raw`
(
  fullVisitorId STRING,
  channelGrouping STRING,
  time INT64,
  country STRING,
  city STRING,
  totalTransactionRevenue INT64,
  transactions INT64,
  timeOnSite INT64,
  pageviews INT64,
  sessionQualityDim INT64,
  date STRING,
  visitId INT64,
  type STRING,
  productRefundAmount INT64,
  productQuantity INT64,
  productPrice INT64,
  productRevenue INT64,
  productSKU STRING,
  v2ProductName STRING,
  v2ProductCategory STRING,
  productVariant STRING,
  currencyCode STRING,
  itemQuantity INT64,
  itemRevenue INT64,
  transactionRevenue INT64,
  transactionId STRING,
  pageTitle STRING,
  searchKeyword STRING,
  pagePathLevel1 STRING,
  eCommerceAction_type STRING,
  eCommerceAction_step INT64,
  eCommerceAction_option STRING
);

INSERT INTO `data-to-insights.ecommerce.all_sessions_raw` (fullVisitorId, channelGrouping, time, country, city, totalTransactionRevenue, transactions, timeOnSite, pageviews, sessionQualityDim, date, visitId, type, productRefundAmount, productQuantity, productPrice, productRevenue, productSKU, v2ProductName, v2ProductCategory, productVariant, currencyCode, itemQuantity, itemRevenue, transactionRevenue, transactionId, pageTitle, searchKeyword, pagePathLevel1, eCommerceAction_type, eCommerceAction_step, eCommerceAction_option) VALUES ('5504767650716007519', 'Organic Search', 261109, 'United States', 'not available in demo dataset', NULL, NULL, 326, 9, NULL, '20170108', 1483893305, 'PAGE', NULL, NULL, 0, NULL, '9180781', 'Suitcase Organizer Cubes', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('0091280705703616305', 'Direct', 802570, 'South Korea', 'not available in demo dataset', NULL, NULL, 1210, 62, NULL, '20170107', 1483821753, 'EVENT', NULL, NULL, 0, NULL, '9180781', 'Suitcase Organizer Cubes', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('4784312403795214032', 'Direct', 256690, 'United States', 'Austin', NULL, NULL, 257, 6, NULL, '20170628', 1498713485, 'PAGE', NULL, NULL, 0, NULL, '9180793', '26 oz Double Wall Insulated Bottle', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('4530570593036389348', 'Paid Search', 26105, 'United States', 'not available in demo dataset', NULL, NULL, 652, 25, NULL, '20170626', 1498488812, 'PAGE', NULL, NULL, 0, NULL, '9180793', '26 oz Double Wall Insulated Bottle', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL), ('6349715060829365831', 'Organic Search', 304876, 'United States', 'not available in demo dataset', NULL, NULL, 305, 16, NULL, '20170515', 1494858170, 'PAGE', NULL, NULL, 0, NULL, '9180824', 'Foam Can and Bottle Cooler', '(not set)', '(not set)', 'USD', NULL, NULL, NULL, NULL, NULL, NULL, '/storeitem.html', '0', 1, NULL);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.products`
(
  SKU STRING,
  name STRING,
  orderedQuantity INT64,
  stockLevel INT64,
  restockingLeadTime INT64,
  sentimentScore FLOAT64,
  sentimentMagnitude FLOAT64
);

INSERT INTO `data-to-insights.ecommerce.products` (SKU, name, orderedQuantity, stockLevel, restockingLeadTime, sentimentScore, sentimentMagnitude) VALUES ('GGADFBSBKS42347', 'PC gaming speakers', 0, 100, 1, nan, nan), ('GGOEGAAX0581', ' Women''s Colorblock Tee White', 0, 0, 8, 0.8, 2.0), ('GGOEGAAX0596', ' Men''s Quilted Insulated Vest Black', 26, 32, 8, 0.8, 2.0), ('GGOEGAAX0591', ' Men''s Short Sleeve Performance Badge Tee Pewter', 27, 29, 15, 0.6, 1.7), ('GGOEGAAX0605', ' Women''s Quilted Insulated Vest White', 10, 16, 9, 0.6, 1.6);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.partitions`
(
  total_transactions INT64,
  date_formatted DATE
)
PARTITION BY date_formatted
OPTIONS(
  description="a table partitioned by date"
);

INSERT INTO `data-to-insights.ecommerce.partitions` (total_transactions, date_formatted) VALUES (38, '2016-09-04');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.classification_model_2_results`
(
  predicted_will_buy_on_return_visit INT64,
  predicted_will_buy_on_return_visit_probs ARRAY<STRUCT<label INT64, prob FLOAT64>>,
  unique_session_id STRING,
  will_buy_on_return_visit INT64,
  latest_ecommerce_progress INT64,
  bounces INT64,
  time_on_site INT64,
  pageviews INT64,
  source STRING,
  medium STRING,
  channelGrouping STRING,
  deviceCategory STRING,
  country STRING
);

INSERT INTO `data-to-insights.ecommerce.classification_model_2_results` (predicted_will_buy_on_return_visit, predicted_will_buy_on_return_visit_probs, unique_session_id, will_buy_on_return_visit, latest_ecommerce_progress, bounces, time_on_site, pageviews, source, medium, channelGrouping, deviceCategory, country) VALUES (0, '[{''label'': 1, ''prob'': 0.008711616663146755}
 {''label'': 0, ''prob'': 0.9912883833368532}]', '039162912574895154-1500907331', 0, 0, 0, 50, 2, 'aol', 'organic', 'Organic Search', 'desktop', 'United States'), (0, '[{''label'': 1, ''prob'': 0.006927288242416253}
 {''label'': 0, ''prob'': 0.9930727117575837}]', '8515268164140442346-1499821254', 0, 0, 0, 74, 2, 'ask', 'organic', 'Organic Search', 'desktop', 'China'), (0, '[{''label'': 1, ''prob'': 0.011216156414053786}
 {''label'': 0, ''prob'': 0.9887838435859462}]', '9183889190192076181-1500066908', 0, 2, 0, 33, 2, 'ask', 'organic', 'Organic Search', 'desktop', 'Denmark'), (0, '[{''label'': 1, ''prob'': 0.006455195065441124}
 {''label'': 0, ''prob'': 0.9935448049345589}]', '4953612077845637467-1500391508', 0, 0, 0, 78, 2, 'ask', 'organic', 'Organic Search', 'desktop', 'Japan'), (0, '[{''label'': 1, ''prob'': 0.00628555672342287}
 {''label'': 0, ''prob'': 0.9937144432765771}]', '7239412501820855280-1499201744', 0, 0, 0, 30, 2, 'ask', 'organic', 'Organic Search', 'desktop', 'France');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.checkout_nudge`
(
  fullVisitorID STRING,
  number_of_sessions INT64,
  number_of_products_viewed INT64,
  session_time_on_site_minutes_max FLOAT64,
  eCommerceAction_type_max STRING
);

INSERT INTO `data-to-insights.ecommerce.checkout_nudge` (fullVisitorID, number_of_sessions, number_of_products_viewed, session_time_on_site_minutes_max, eCommerceAction_type_max) VALUES ('0697698087141419098', 1, 256, 7.2, '5'), ('1495718436219461866', 1, 1, 127.36666666666666, '5'), ('2728377808603106296', 1, 1, 30.066666666666666, '5'), ('7564646136287671879', 1, 1, 24.35, '5'), ('5385229023191936063', 1, 1, 23.133333333333333, '5');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ecommerce.sales_by_sku`
(
  productSKU STRING,
  total_ordered INT64
);

INSERT INTO `data-to-insights.ecommerce.sales_by_sku` (productSKU, total_ordered) VALUES ('GGOEGOAQ012899', 456), ('GGOEGDHC074099', 334), ('GGOEGOCB017499', 319), ('GGOEGOCC077999', 290), ('GGOEGFYQ016599', 253);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.metric_names`
(
  stat_name STRING,
  label STRING,
  concept_name STRING,
  off_or_def STRING,
  rank_asc BOOL,
  rd_dec INT64,
  off_def_stat_name STRING
);

INSERT INTO `data-to-insights.ncaa.metric_names` (stat_name, label, concept_name, off_or_def, rank_asc, rd_dec, off_def_stat_name) VALUES ('tm_to_pct', 'TO%', 'Turnovers', 'Off', True, 1, 'off_to_pct'), ('opp_to_pct', 'TO%', 'Turnovers', 'Def', False, 1, 'def_to_pct'), ('tm_drb_pct', 'DRB%', 'Rebounding', 'Def', False, 1, 'drb_pct'), ('tm_orb_pct', 'ORB%', 'Rebounding', 'Off', False, 1, 'orb_pct'), ('tm_efg_pct', 'eFG%', 'Shooting', 'Off', False, 1, 'off_efg_pct');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.mbb_historical_teams_seasons`
(
  season INT64 OPTIONS(description="Season the game was played in"),
  market STRING OPTIONS(description="Team school name (using Sportradar names)"),
  name STRING OPTIONS(description="Team name"),
  team_code INT64 OPTIONS(description="School code (see http://stats.ncaa.org/game_upload/team_codes)"),
  team_id STRING OPTIONS(description="Sportradar team ID"),
  alias STRING OPTIONS(description="Team alias"),
  division INT64 OPTIONS(description="The division the team played in at this time of this season"),
  current_division STRING OPTIONS(description="The division the team currently plays in"),
  wins INT64 OPTIONS(description="Number of wins in this season"),
  losses INT64 OPTIONS(description="Number of losses in this season"),
  ties INT64 OPTIONS(description="Number of ties in this season")
)
OPTIONS(
  description="Season record information for Men's Basketball, starting with the 1894-95 season. Each game is included twice, with one entry per team. \n\nData provided by the NCAA."
);

INSERT INTO `data-to-insights.ncaa.mbb_historical_teams_seasons` (season, market, name, team_code, team_id, alias, division, current_division, wins, losses, ties) VALUES (1956, NULL, NULL, 296, NULL, NULL, 1, NULL, 0, 0, 0), (1903, NULL, NULL, 137, NULL, NULL, 1, NULL, 7, 0, 0), (1908, NULL, NULL, 137, NULL, NULL, 1, NULL, 12, 0, 0), (2006, NULL, NULL, 28593, NULL, NULL, 1, NULL, 0, 0, 0), (1908, NULL, NULL, 479, NULL, NULL, 1, NULL, 13, 0, 0);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.2018_tournament_results`
(
  season INT64,
  round INT64,
  days_from_epoch INT64,
  game_date DATE,
  day STRING,
  label STRING,
  seed STRING,
  market STRING,
  name STRING,
  alias STRING,
  school_ncaa STRING,
  points INT64,
  opponent_seed STRING,
  opponent_market STRING,
  opponent_name STRING,
  opponent_alias STRING,
  opponent_school_ncaa STRING,
  opponent_points INT64
);

INSERT INTO `data-to-insights.ncaa.2018_tournament_results` (season, round, days_from_epoch, game_date, day, label, seed, market, name, alias, school_ncaa, points, opponent_seed, opponent_market, opponent_name, opponent_alias, opponent_school_ncaa, opponent_points) VALUES (2018, 68, 17603, '2018-03-13', 'Tuesday', 'win', '16', 'Radford', 'Highlanders', 'RAD', 'Radford', 71, '16', 'LIU Brooklyn', 'Blackbirds', 'LIU', 'LIU Brooklyn', 61), (2018, 68, 17603, '2018-03-13', 'Tuesday', 'win', '11', 'St. Bonaventure', 'Bonnies', 'SBON', 'St. Bonaventure', 65, '11', 'UCLA', 'Bruins', 'UCLA', 'UCLA', 58), (2018, 68, 17603, '2018-03-13', 'Tuesday', 'loss', '16', 'LIU Brooklyn', 'Blackbirds', 'LIU', 'LIU Brooklyn', 61, '16', 'Radford', 'Highlanders', 'RAD', 'Radford', 71), (2018, 68, 17603, '2018-03-13', 'Tuesday', 'loss', '11', 'UCLA', 'Bruins', 'UCLA', 'UCLA', 58, '11', 'St. Bonaventure', 'Bonnies', 'SBON', 'St. Bonaventure', 65), (2018, 68, 17604, '2018-03-14', 'Wednesday', 'win', '16', 'Texas Southern', 'Tigers', 'TXSO', 'Texas Southern', 64, '16', 'North Carolina Central', 'Eagles', 'NCCU', 'N.C. Central', 46);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.mbb_historical_teams_games`
(
  season INT64 OPTIONS(description="[Game data] Season the game was played in"),
  scheduled_date STRING OPTIONS(description="[Game data] Date the game was played"),
  attendance FLOAT64 OPTIONS(description="[Game data] Attendance of the game"),
  market STRING OPTIONS(description="[Team data] Team school name (using Sportradar names)"),
  name STRING OPTIONS(description="[Team data] Team name"),
  team_code STRING OPTIONS(description="[Team data] School code (see http://stats.ncaa.org/game_upload/team_codes)"),
  team_id STRING OPTIONS(description="[Team data] Sportradar team ID"),
  alias STRING OPTIONS(description="[Team data] Team alias"),
  current_division STRING OPTIONS(description="[Team data] The division the team currently plays in"),
  points_game INT64 OPTIONS(description="[Game data] Points scored by team"),
  win BOOL OPTIONS(description="[Game data] Whether the team won the game"),
  opp_market STRING OPTIONS(description="[Opponent data] Opponent school name (using Sportradar names)"),
  opp_name STRING OPTIONS(description="[Opponent data] Opponent name"),
  opp_code INT64 OPTIONS(description="[Opponent data] Opponent school code (see http://stats.ncaa.org/game_upload/team_codes)"),
  opp_id STRING OPTIONS(description="[Opponent data] Opponent school ID (using Sportradar IDs)"),
  opp_alias STRING OPTIONS(description="[Opponent data] Opponent alias"),
  opp_current_division STRING OPTIONS(description="[Opponent data] The division the opponent currently plays in"),
  opp_points_game INT64 OPTIONS(description="[Opponent data] Points scored by opponent")
)
OPTIONS(
  description="Final scores for men's basketball games, starting with the 1996-97 season. Each game is included twice, with one entry per team. \n\nData provided by the NCAA."
);

INSERT INTO `data-to-insights.ncaa.mbb_historical_teams_games` (season, scheduled_date, attendance, market, name, team_code, team_id, alias, current_division, points_game, win, opp_market, opp_name, opp_code, opp_id, opp_alias, opp_current_division, opp_points_game) VALUES (1996, NULL, nan, NULL, NULL, '121', NULL, NULL, NULL, 85, False, NULL, NULL, 506107, NULL, NULL, NULL, 98), (1996, NULL, nan, NULL, NULL, '200', NULL, NULL, NULL, 72, False, NULL, NULL, 770, NULL, NULL, NULL, 78), (1996, NULL, nan, NULL, NULL, '511', NULL, NULL, NULL, 78, False, NULL, NULL, 50, NULL, NULL, NULL, 86), (1996, NULL, nan, NULL, NULL, '570', NULL, NULL, NULL, 64, False, NULL, NULL, 78, NULL, NULL, NULL, 77), (1996, NULL, nan, NULL, NULL, '267', NULL, NULL, NULL, 77, False, NULL, NULL, 717, NULL, NULL, NULL, 80);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.team_colors`
(
  market STRING,
  id STRING,
  code_ncaa INT64,
  color STRING
)
OPTIONS(
  description="Hex color codes for the 351 current men's D1 basketball teams."
);

INSERT INTO `data-to-insights.ncaa.team_colors` (market, id, code_ncaa, color) VALUES ('Milwaukee', '5d77800f-1ae6-4b66-8e97-b0dbb8bbc717', 797, '#000000'), ('Colorado', '9fccbf28-2858-4263-821c-fdefb3c7efa3', 157, '#000000'), ('Northeastern', '93df9b18-e9fc-42a7-bb45-a736c203b4dc', 500, '#000000'), ('Georgia Southern', '6b955b96-b736-475e-bffd-e4acf2054169', 253, '#000066'), ('Richmond', '9b66e1e0-aace-4671-9be2-54c8acf5ecfc', 575, '#000066');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.adjusted_metrics`
(
  season INT64,
  tm_code INT64,
  tm STRING,
  stat_name STRING,
  raw_stat FLOAT64,
  raw_rtg FLOAT64,
  raw_rk FLOAT64,
  adj_stat FLOAT64,
  adj_rtg FLOAT64,
  adj_rk FLOAT64,
  through_games_of STRING
);

INSERT INTO `data-to-insights.ncaa.adjusted_metrics` (season, tm_code, tm, stat_name, raw_stat, raw_rtg, raw_rk, adj_stat, adj_rtg, adj_rk, through_games_of) VALUES (2014, 768, 'West Virginia', 'tm_to_pct', 18.692552895179343, 57.843223517450205, 148.0, 18.868623809468673, 54.179426996736105, 161.0, '2015-04-06'), (2014, 768, 'West Virginia', 'opp_to_pct', 27.976933472255173, 99.99724229627762, 2.0, 28.054161776414027, 99.99889264692368, 1.0, '2015-04-06'), (2014, 768, 'West Virginia', 'tm_drb_pct', 69.0782953419227, 48.83061368956135, 175.0, 72.19560093009977, 83.08218101268344, 58.0, '2015-04-06'), (2014, 768, 'West Virginia', 'tm_orb_pct', 40.1536312849162, 98.8793521071588, 5.0, 41.23624832730413, 99.61413974634979, 3.0, '2015-04-06'), (2014, 768, 'West Virginia', 'opp_efg_pct', 52.736777367773676, 8.177041776950473, 323.0, 51.23757998762123, 27.843632762986438, 249.0, '2015-04-06');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.2019_tournament_seeds`
(
  school_ncaa STRING,
  seed INT64,
  season INT64
);

INSERT INTO `data-to-insights.ncaa.2019_tournament_seeds` (school_ncaa, seed, season) VALUES ('North Carolina', 1, 2019), ('Gonzaga', 1, 2019), ('Duke', 1, 2019), ('Virginia', 1, 2019), ('Kentucky', 2, 2019);
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.mascots`
(
  id STRING OPTIONS(description="University unique ID from Sportradar"),
  market STRING OPTIONS(description="The university to which the mascot belongs"),
  name STRING OPTIONS(description="The name of the university’s team"),
  mascot STRING OPTIONS(description="The name of the university's mascot"),
  mascot_name STRING OPTIONS(description="The proper name of the university's mascot, if available (e.g. a character)"),
  mascot_common_name STRING OPTIONS(description="The type of being or creature that the mascot embodies"),
  tax_subspecies STRING OPTIONS(description="The subspecies to which the mascot belongs"),
  tax_species STRING OPTIONS(description="The species to which the mascot belongs"),
  tax_genus STRING OPTIONS(description="The genus to which the mascot belongs"),
  tax_family STRING OPTIONS(description="The family to which the mascot belongs"),
  tax_order STRING OPTIONS(description="The order to which the mascot belongs"),
  tax_class STRING OPTIONS(description="The class to which the mascot belongs"),
  tax_phylum STRING OPTIONS(description="The phylum to which the mascot belongs"),
  tax_kingdom STRING OPTIONS(description="The kingdom to which the mascot belongs"),
  tax_domain STRING OPTIONS(description="The domain to which the mascot belongs"),
  non_tax_type STRING OPTIONS(description="The non-Linnean type of being or creature to which the mascot belongs, if applicable")
);

INSERT INTO `data-to-insights.ncaa.mascots` (id, market, name, mascot, mascot_name, mascot_common_name, tax_subspecies, tax_species, tax_genus, tax_family, tax_order, tax_class, tax_phylum, tax_kingdom, tax_domain, non_tax_type) VALUES ('2959bd24-7007-41ae-a3a3-abdf26888cfc', 'Tulsa', 'Golden Hurricane', 'Hurricane', 'Captain Cane', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 'Weather'), ('ad4bc983-8d2e-4e6f-a8f9-80840a786c64', 'Arizona State', 'Sun Devils', 'Devil', 'Sparky', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 'Devils'), ('f2d01b77-0f5d-4574-9e49-2a3eaf822e44', 'Drexel', 'Dragons', 'Dragon', 'Mario the Magnificent', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 'Dragons'), ('b47d10b8-a2a5-47df-a2f9-7bd0b9d51beb', 'Bradley', 'Braves', 'Gargoyle', 'Kaboom!', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL), ('0113eea0-c943-4fff-9780-ae0fb099e7ef', 'Canisius', 'Golden Griffins', 'Griffin', 'Petey', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 'Griffins');
-- DBMS: bigquery
CREATE TABLE `data-to-insights.ncaa.feature_engineering`
(
  season INT64,
  team STRING,
  poss_40min FLOAT64,
  pace_rating FLOAT64,
  pace_rank FLOAT64,
  pts_100poss FLOAT64,
  efficiency_rating FLOAT64,
  efficiency_rank FLOAT64
);

INSERT INTO `data-to-insights.ncaa.feature_engineering` (season, team, poss_40min, pace_rating, pace_rank, pts_100poss, efficiency_rating, efficiency_rank) VALUES (2014, 'Ohio St.', 66.233, 68.038, 106.0, 24.826, 97.704, 11.0), (2014, 'San Francisco', 65.847, 62.626, 121.0, 2.648, 58.428, 140.0), (2014, 'IUPUI', 64.071, 36.181, 222.0, -9.72, 21.726, 281.0), (2014, 'UConn', 62.675, 18.814, 294.0, 11.1, 81.393, 65.0), (2014, 'Mississippi Val.', 70.918, 98.781, 6.0, -28.753, 1.039, 349.0);
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.reactome_versioned.pathway_v77`
(
  stable_id STRING OPTIONS(description="Reactome pathway stable identifier"),
  url STRING OPTIONS(description="URL to pathway on the Reactome website"),
  name STRING OPTIONS(description="Reactome pathway name"),
  species STRING OPTIONS(description="Reactome pathway species"),
  lowest_level BOOL OPTIONS(description="Indicates if pathway is at the lowest level in the hierarchy, i.e., not a parent")
)
OPTIONS(
  friendly_name="REACTOME PATHWAYS V77 VERSIONED",
  description="Reactome pathways downloaded from https://reactome.org/download-data/ on 08/2021 and filtered to only include human pathways (i.e., species = 'Homo sapiens'). This data is part of the version 77 release of Reactome. Additional information and the Creative Commons license agreement can be found here: https://reactome.org/license",
  labels=[("access", "open"), ("source", "reactome"), ("category", "reference_database"), ("status", "current"), ("data_type", "pathway_annotations")]
);

INSERT INTO `isb-cgc-bq.reactome_versioned.pathway_v77` (stable_id, url, name, species, lowest_level) VALUES ('R-HSA-8956319', 'https://reactome.org/PathwayBrowser/#/R-HSA-8956319', 'Nucleobase catabolism', 'Homo sapiens', False), ('R-HSA-5654743', 'https://reactome.org/PathwayBrowser/#/R-HSA-5654743', 'Signaling by FGFR4', 'Homo sapiens', False), ('R-HSA-3296482', 'https://reactome.org/PathwayBrowser/#/R-HSA-3296482', 'Defects in vitamin and cofactor metabolism', 'Homo sapiens', False), ('R-HSA-5684996', 'https://reactome.org/PathwayBrowser/#/R-HSA-5684996', 'MAPK1/MAPK3 signaling', 'Homo sapiens', False), ('R-HSA-5654732', 'https://reactome.org/PathwayBrowser/#/R-HSA-5654732', 'Negative regulation of FGFR3 signaling', 'Homo sapiens', False);
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.reactome_versioned.physical_entity_v77`
(
  ensembl_id STRING OPTIONS(description="Ensembl database identifier"),
  uniprot_id STRING OPTIONS(description="UniProt database identifier"),
  stable_id STRING OPTIONS(description="Reactome physical entity stable identifier"),
  name STRING OPTIONS(description="Reactome physical entity name"),
  location STRING OPTIONS(description="Reactome physical entity location")
)
OPTIONS(
  friendly_name="REACTOME PHYSICAL ENTITIES V77 VERSIONED",
  description="External protein, gene, or small molecule identifiers that have been mapped to Reactome physical entities. This data was downloaded from https://reactome.org/download-data on 8/2021 and filtered to include only human physical entities. This data is part of the version 77 release of Reactome. Additional information and the Creative Commons license agreement can be found here: https://reactome.org/license",
  labels=[("access", "open"), ("source", "reactome"), ("category", "reference_database"), ("status", "current"), ("data_type", "pathway_annotations")]
);

INSERT INTO `isb-cgc-bq.reactome_versioned.physical_entity_v77` (ensembl_id, uniprot_id, stable_id, name, location) VALUES ('ENSP00000494175', 'P68871', 'R-HSA-1008196', 'HBB', 'cytosol'), ('ENST00000647020', 'P68871', 'R-HSA-1008196', 'HBB', 'cytosol'), ('ENSP00000333994', 'P68871', 'R-HSA-1008196', 'HBB', 'cytosol'), ('ENSG00000244734', 'P68871', 'R-HSA-1008196', 'HBB', 'cytosol'), ('ENST00000335295', 'P68871', 'R-HSA-1008196', 'HBB', 'cytosol');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.reactome_versioned.pathway_hierarchy_v77`
(
  parent_id STRING OPTIONS(description="Reactome pathway stable identifier associated with 'child' pathways"),
  child_id STRING OPTIONS(description="Reactome pathway stable identifier associated with 'parent' pathways")
)
OPTIONS(
  friendly_name="REACTOME PATHWAYS HIERARCHY V77 VERSIONED",
  description="Reactome pathways parent to child hierarchy downloaded from https://reactome.org/download-data/ on 08/2021 and filtered to only include human pathways (i.e., species = 'Homo sapiens'). This data is part of the version 77 release of Reactome. Additional information and the Creative Commons license agreement can be found here: https://reactome.org/license",
  labels=[("access", "open"), ("source", "reactome"), ("category", "reference_database"), ("status", "current"), ("data_type", "pathway_annotations")]
);

INSERT INTO `isb-cgc-bq.reactome_versioned.pathway_hierarchy_v77` (parent_id, child_id) VALUES ('R-HSA-15869', 'R-HSA-8956319'), ('R-HSA-15869', 'R-HSA-499943'), ('R-HSA-15869', 'R-HSA-8956320'), ('R-HSA-15869', 'R-HSA-8956321'), ('R-HSA-68867', 'R-HSA-68616');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.reactome_versioned.pe_to_pathway_v77`
(
  pe_stable_id STRING OPTIONS(description="Reactome physical entity stable identifier"),
  pathway_stable_id STRING OPTIONS(description="Reactome pathway stable identifier"),
  evidence_code STRING OPTIONS(description="Code that indicates the type of evidence supporting physical entity relation to pathway")
)
OPTIONS(
  friendly_name="REACTOME PHYSICAL ENTITIES TO PATHWAY MAPPING V77 VERSIONED",
  description="External protein, gene, or small molecules mapped to Reactome pathways. This data was downloaded from https://reactome.org/download-data on 8/2021 and filtered to include only human physical entities and pathways. This data is part of the version 77 release of Reactome. Additional information and the Creative Commons license agreement can be found here: https://reactome.org/license",
  labels=[("access", "open"), ("source", "reactome"), ("category", "reference_database"), ("status", "current"), ("data_type", "pathway_annotations")]
);

INSERT INTO `isb-cgc-bq.reactome_versioned.pe_to_pathway_v77` (pe_stable_id, pathway_stable_id, evidence_code) VALUES ('R-HSA-904852', 'R-HSA-15869', 'IEA'), ('R-HSA-6786263', 'R-HSA-15869', 'IEA'), ('R-HSA-2311338', 'R-HSA-68875', 'IEA'), ('R-HSA-165978', 'R-HSA-68875', 'IEA'), ('R-HSA-2168081', 'R-HSA-68875', 'IEA');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.targetome_versioned.target_synonyms_v1`
(
  targetID INT64 OPTIONS(description="ID for Targetome target"),
  synonym STRING OPTIONS(description="Synonym or alias for Targetome target")
)
OPTIONS(
  friendly_name="TARGETOME TARGET SYNONYMS V1 VERSIONED",
  description="Synonyms for targets involved in Targetome interactions. More information can be found here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759325/. Data was downloaded from the Targetome Git repository (https://github.com/ablucher/The-Cancer-Targetome) in July 2021.",
  labels=[("access", "open"), ("data_type", "drug_target_interactions"), ("source", "targetome"), ("category", "reference_database"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.targetome_versioned.target_synonyms_v1` (targetID, synonym) VALUES (256, 'Tyrosine-protein kinase HCK'), (512, 'nuclear receptor coactivator 3 isoform a'), (768, 'Serine/threonine-protein kinase Nek3'), (1, 'HTR3A'), (1, '5-hydroxytryptamine receptor 3A');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.targetome_versioned.sources_v1`
(
  sourceID INT64 OPTIONS(description="ID for source supporting Targetome interaction"),
  PubMedID STRING OPTIONS(description="PubMedID identifying literature"),
  databaseName STRING OPTIONS(description="Name of database from which supporting evidence and literature are obtained"),
  db_version STRING OPTIONS(description="Database version"),
  db_downloadURL STRING OPTIONS(description="URL from which database was downloaded"),
  db_downloadDate STRING OPTIONS(description="Date on which database was downloaded")
)
OPTIONS(
  friendly_name="TARGETOME SOURCES V1 VERSIONED",
  description="Targetome literature evidence table, providing support for Targetome interactions. More information can be found here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759325/. Data was downloaded from the Targetome Git repository (https://github.com/ablucher/The-Cancer-Targetome) in July 2021.",
  labels=[("access", "open"), ("data_type", "drug_target_interactions"), ("source", "targetome"), ("category", "reference_database"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.targetome_versioned.sources_v1` (sourceID, PubMedID, databaseName, db_version, db_downloadURL, db_downloadDate) VALUES (1, '7565620', 'IUPHAR', NULL, NULL, '06.15.2016'), (2, '11489465', 'IUPHAR', NULL, NULL, '06.15.2016'), (3, '8818349', 'IUPHAR', NULL, NULL, '06.15.2016'), (4, '20724042', 'IUPHAR', NULL, NULL, '06.15.2016'), (5, '12543790', 'IUPHAR', NULL, NULL, '06.15.2016');