nl2sqlproj/spider2-nl2sql huggingface dataset:
-- DBMS: snowflake
create or replace TABLE CPC_DEFINITION (
	"applicationReferences" VARIANT,
	"breakdownCode" BOOLEAN,
	"childGroups" VARIANT,
	"children" VARIANT,
	"dateRevised" FLOAT,
	"definition" VARIANT,
	"glossary" VARIANT,
	"informativeReferences" VARIANT,
	"ipcConcordant" VARCHAR(16777216),
	"level" FLOAT,
	"limitingReferences" VARIANT,
	"notAllocatable" BOOLEAN,
	"parents" VARIANT,
	"precedenceLimitingReferences" VARIANT,
	"residualReferences" VARIANT,
	"rules" VARIANT,
	"scopeLimitingReferences" VARIANT,
	"status" VARCHAR(16777216),
	"symbol" VARCHAR(16777216),
	"synonyms" VARIANT,
	"titleFull" VARCHAR(16777216),
	"titlePart" VARIANT
);

INSERT INTO "PATENTS"."PATENTS"."CPC_DEFINITION" (status, precedenceLimitingReferences, rules, childGroups, scopeLimitingReferences, level, titlePart, residualReferences, definition, breakdownCode, limitingReferences, glossary, applicationReferences, notAllocatable, titleFull, dateRevised, informativeReferences, symbol, synonyms, children, parents, ipcConcordant) VALUES ('published', '[]', '[]', '[]', '[]', 9.0, '[
  "Swine"
]', '[]', '[]', True, '[]', '[]', '[]', False, 'Swine', 20130101.0, '[]', 'A01K2227/108', '[]', '[]', '[
  "A01K2227/10",
  "A01K2227/00",
  "A01K",
  "A01",
  "A"
]', 'CPCONLY'), ('published', '[]', '[]', '[]', '[]', 9.0, '[
  "Murine"
]', '[]', '[]', True, '[]', '[]', '[]', False, 'Murine', 20130101.0, '[]', 'A01K2227/105', '[]', '[]', '[
  "A01K2227/10",
  "A01K2227/00",
  "A01K",
  "A01",
  "A"
]', 'CPCONLY'), ('published', '[]', '[]', '[]', '[]', 9.0, '[
  "Rabbit"
]', '[]', '[]', True, '[]', '[]', '[]', False, 'Rabbit', 20130101.0, '[]', 'A01K2227/107', '[]', '[]', '[
  "A01K2227/10",
  "A01K2227/00",
  "A01K",
  "A01",
  "A"
]', 'CPCONLY'), ('published', '[]', '[]', '[]', '[]', 9.0, '[
  "Animal producing cells or organs for transplantation"
]', '[]', '[]', True, '[]', '[]', '[]', False, 'Animal producing cells or organs for transplantation', 20130101.0, '[]', 'A01K2267/025', '[]', '[]', '[
  "A01K2267/02",
  "A01K2267/00",
  "A01K",
  "A01",
  "A"
]', 'CPCONLY'), ('published', '[]', '[]', '[]', '[]', 9.0, '[
  "Animal model for genetic diseases"
]', '[]', '[]', True, '[]', '[]', '[]', False, 'Animal model for genetic diseases', 20130101.0, '[]', 'A01K2267/0306', '[]', '[
  "A01K2267/0312",
  "A01K2267/0318",
  "A01K2267/0325"
]', '[
  "A01K2267/03",
  "A01K2267/00",
  "A01K",
  "A01",
  "A"
]', 'CPCONLY');
-- DBMS: snowflake
create or replace TABLE DATASETVOTES (
	"Id" NUMBER(38,0),
	"UserId" NUMBER(38,0),
	"DatasetVersionId" NUMBER(38,0),
	"VoteDate" DATE
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."DATASETVOTES" (VoteDate, Id, UserId, DatasetVersionId) VALUES ('2016-01-28', 400, 484081, 6), ('2016-01-24', 359, 188410, 6), ('2016-01-23', 341, 118065, 6), ('2016-01-17', 247, 400808, 6), ('2016-05-03', 2748, 262803, 6);
-- DBMS: snowflake
create or replace TABLE TEAMMEMBERSHIPS (
	"Id" NUMBER(38,0),
	"TeamId" NUMBER(38,0),
	"UserId" NUMBER(38,0),
	"RequestDate" DATE
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."TEAMMEMBERSHIPS" (Id, TeamId, UserId, RequestDate) VALUES (18940, 4541, 10466, NULL), (19443, 4978, 8263, NULL), (889883, 855573, 860462, NULL), (19205, 4772, 2505, NULL), (1178361, 917458, 659634, NULL);
-- DBMS: snowflake
create or replace TABLE KERNELTAGS (
	"Id" NUMBER(38,0),
	"KernelId" NUMBER(38,0),
	"TagId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELTAGS" (Id, TagId, KernelId) VALUES (5867, 2304, 90782), (14387, 2304, 160689), (1008, 2304, 358835), (4312, 2304, 435514), (18455, 2304, 744580);
-- DBMS: snowflake
create or replace TABLE KERNELVOTES (
	"Id" NUMBER(38,0),
	"UserId" NUMBER(38,0),
	"KernelVersionId" NUMBER(38,0),
	"VoteDate" DATE
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELVOTES" (Id, KernelVersionId, UserId, VoteDate) VALUES (3147639, 83046050, 6437951, '2021-12-23'), (3499202, 83046050, 7611249, '2022-04-06'), (3676963, 83046050, 5890725, '2022-06-03'), (3570039, 83046050, 10007967, '2022-04-28'), (3569330, 83046050, 8560689, '2022-04-28');
-- DBMS: snowflake
create or replace TABLE KERNELS (
	"Id" NUMBER(38,0),
	"AuthorUserId" NUMBER(38,0),
	"CurrentKernelVersionId" NUMBER(38,0),
	"ForkParentKernelVersionId" NUMBER(38,0),
	"ForumTopicId" NUMBER(38,0),
	"FirstKernelVersionId" NUMBER(38,0),
	"CreationDate" NUMBER(38,0),
	"EvaluationDate" DATE,
	"MadePublicDate" DATE,
	"IsProjectLanguageTemplate" BOOLEAN,
	"CurrentUrlSlug" VARCHAR(16777216),
	"Medal" NUMBER(38,0),
	"MedalAwardDate" DATE,
	"TotalViews" NUMBER(38,0),
	"TotalComments" NUMBER(38,0),
	"TotalVotes" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELS" (ForumTopicId, Id, MedalAwardDate, MadePublicDate, FirstKernelVersionId, TotalComments, EvaluationDate, ForkParentKernelVersionId, IsProjectLanguageTemplate, Medal, CreationDate, TotalVotes, TotalViews, CurrentKernelVersionId, CurrentUrlSlug, AuthorUserId) VALUES (nan, 46978346, NULL, '2023-11-28', 152701563, 0, '2023-12-30', nan, False, NULL, 1701170742000000, 1, 50, nan, 'notebook209f8fec22', 17582017), (464880.0, 46979607, NULL, '2023-11-28', 152705157, 1, '2023-11-28', 152550707.0, False, NULL, 1701172382000000, 1, 148, 152712152.0, 'countvectorizer-multinomialnb', 17650091), (nan, 46980103, NULL, '2023-11-28', 152706531, 0, '2023-11-30', nan, False, NULL, 1701172993000000, 1, 121, 152949918.0, 'cam-capture', 17915674), (nan, 46981995, NULL, '2023-11-28', 152711750, 0, '2023-12-05', 152693168.0, False, NULL, 1701175249000000, 1, 316, 153703103.0, 'prisons-in-hungary', 12749163), (nan, 46982846, NULL, '2023-11-28', 152714161, 0, '2023-11-28', nan, False, NULL, 1701176272000000, 1, 75, 152714618.0, 'my-notebook', 13608749);
-- DBMS: snowflake
create or replace TABLE DATASETTASKSUBMISSIONS (
	"Id" NUMBER(38,0),
	"DatasetTaskId" NUMBER(38,0),
	"SubmittedUserId" NUMBER(38,0),
	"CreationDate" NUMBER(38,0),
	"KernelId" NUMBER(38,0),
	"DatasetId" NUMBER(38,0),
	"AcceptedDate" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."DATASETTASKSUBMISSIONS" (DatasetTaskId, DatasetId, SubmittedUserId, Id, AcceptedDate, KernelId, CreationDate) VALUES (2304, NULL, 4348228, 4719, NULL, 12336275, 1602941845000000), (2304, NULL, 5986902, 4743, NULL, 12373911, 1603110187000000), (2304, NULL, 5521499, 4761, NULL, 12304472, 1603290215000000), (2304, NULL, 2050099, 4813, NULL, 12484884, 1603636907000000), (2304, NULL, 3623292, 4827, NULL, 12512601, 1603736617000000);
-- DBMS: snowflake
create or replace TABLE SUBMISSIONS (
	"Id" NUMBER(38,0),
	"SubmittedUserId" NUMBER(38,0),
	"TeamId" NUMBER(38,0),
	"SourceKernelVersionId" VARCHAR(16777216),
	"SubmissionDate" DATE,
	"ScoreDate" DATE,
	"IsAfterDeadline" BOOLEAN,
	"PublicScoreLeaderboardDisplay" FLOAT,
	"PublicScoreFullPrecision" FLOAT,
	"PrivateScoreLeaderboardDisplay" FLOAT,
	"PrivateScoreFullPrecision" FLOAT
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."SUBMISSIONS" (PublicScoreFullPrecision, SourceKernelVersionId, SubmissionDate, PublicScoreLeaderboardDisplay, IsAfterDeadline, PrivateScoreFullPrecision, ScoreDate, TeamId, Id, SubmittedUserId, PrivateScoreLeaderboardDisplay) VALUES (0.4713052641725747, '', '2016-02-16', 0.4713, False, 0.47029765275103375, '2016-02-16', 270557, 2575661, 441360, 0.47029), (0.4761521119797183, '', '2016-02-16', 0.47615, False, 0.4754497853556987, '2016-02-16', 266628, 2574743, 22969, 0.47544), (0.5169891895550529, '', '2016-02-16', 0.51698, False, 0.5158655121170114, '2016-02-16', 277085, 2576136, 137177, 0.51586), (0.5110518882832594, '', '2016-02-16', 0.51105, False, 0.5101954265336581, '2016-02-16', 265697, 2576081, 460599, 0.51019), (0.46151804109644645, '161290', '2016-02-16', 0.46151, False, 0.4602417308754851, '2016-02-16', 272837, 2577187, 191861, 0.46024);
-- DBMS: snowflake
create or replace TABLE KERNELVERSIONDATASETSOURCES (
	"Id" NUMBER(38,0),
	"KernelVersionId" NUMBER(38,0),
	"SourceDatasetVersionId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELVERSIONDATASETSOURCES" (KernelVersionId, SourceDatasetVersionId, Id) VALUES (81536237, 2883584, 108078246), (104735677, 4128768, 145502949), (105348317, 4128768, 146492371), (186690255, 8781824, 266698769), (376521, 256, 252654);
-- DBMS: snowflake
create or replace TABLE DATASETTAGS (
	"Id" NUMBER(38,0),
	"DatasetId" NUMBER(38,0),
	"TagId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."DATASETTAGS" (DatasetId, TagId, Id) VALUES (629, 2304, 445), (655, 2304, 447), (649, 2304, 520), (749, 2304, 699), (290, 2304, 926);
-- DBMS: snowflake
create or replace TABLE FORUMTOPICS (
	"TotalReplies" NUMBER(38,0),
	"LastCommentDate" NUMBER(38,0),
	"FirstForumMessageId" FLOAT,
	"IsSticky" BOOLEAN,
	"ForumId" NUMBER(38,0),
	"Title" VARCHAR(16777216),
	"TotalMessages" NUMBER(38,0),
	"Id" NUMBER(38,0),
	"LastForumMessageId" FLOAT,
	"CreationDate" NUMBER(38,0),
	"TotalViews" NUMBER(38,0),
	"KernelId" FLOAT,
	"Score" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."FORUMTOPICS" (TotalViews, LastForumMessageId, IsSticky, LastCommentDate, TotalReplies, Score, KernelId, Title, TotalMessages, CreationDate, FirstForumMessageId, Id, ForumId) VALUES (0, NULL, False, 1625377492000000, 1, 28, nan, NULL, 0, 1625377492000000, NULL, 250718, 16860), (0, NULL, False, 1625218912000000, 0, 42, 18233971.0, NULL, 0, 1625218912000000, NULL, 250354, 16860), (0, NULL, False, 1617153396000000, 0, 217, 11887338.0, NULL, 0, 1617153396000000, NULL, 229617, 16860), (0, NULL, False, 1621965486000000, 0, 114, 5832124.0, NULL, 0, 1621965486000000, NULL, 241702, 16860), (0, NULL, False, 1616509777000000, 0, 61, 12613420.0, NULL, 0, 1616509777000000, NULL, 228138, 16860);
-- DBMS: snowflake
create or replace TABLE USERS (
	"Id" NUMBER(38,0),
	"UserName" VARCHAR(16777216),
	"DisplayName" VARCHAR(16777216),
	"RegisterDate" VARCHAR(16777216),
	"PerformanceTier" NUMBER(38,0),
	"Country" VARCHAR(16777216)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."USERS" (Id, Country, RegisterDate, PerformanceTier, DisplayName, UserName) VALUES (154581, NULL, '01/01/2014', 0, 'Aashu', 'aashu154581'), (277324, NULL, '01/01/2015', 0, 'Adam Wyeth', 'adamwyeth'), (852854, NULL, '01/01/2017', 0, 'Lolo', 'lolo1995s'), (853107, NULL, '01/01/2017', 0, 'Festus Adeboye', 'doncolio'), (853091, NULL, '01/01/2017', 0, 'pthamie', 'pthamie');
-- DBMS: snowflake
create or replace TABLE USERORGANIZATIONS (
	"Id" NUMBER(38,0),
	"UserId" NUMBER(38,0),
	"OrganizationId" NUMBER(38,0),
	"JoinDate" DATE
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."USERORGANIZATIONS" (Id, JoinDate, OrganizationId, UserId) VALUES (33, '2016-10-04', 5, 724814), (46, '2016-10-17', 3, 346825), (84, '2016-10-20', 41, 755155), (149, '2016-10-20', 66, 56073), (250, '2016-10-24', 114, 331256);
-- DBMS: snowflake
create or replace TABLE KERNELLANGUAGES (
	"Id" NUMBER(38,0),
	"Name" VARCHAR(16777216),
	"DisplayName" VARCHAR(16777216),
	"IsNotebook" BOOLEAN
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELLANGUAGES" (Id, DisplayName, IsNotebook, Name) VALUES (1, 'R', False, 'R'), (12, 'R', False, 'R Notebook HTML'), (13, 'R', True, 'R Notebook'), (16, 'R', True, 'RMarkdown - Interactive'), (8, 'Python', True, 'IPython Notebook');
-- DBMS: snowflake
create or replace TABLE KERNELVERSIONS (
	"LinesUnchangedFromFork" FLOAT,
	"LinesChangedFromFork" FLOAT,
	"LinesDeletedFromFork" FLOAT,
	"LinesUnchangedFromPrevious" FLOAT,
	"TotalLines" FLOAT,
	"IsChange" BOOLEAN,
	"VersionNumber" FLOAT,
	"LinesInsertedFromPrevious" FLOAT,
	"EvaluationDate" DATE,
	"CreationDate" NUMBER(38,0),
	"LinesChangedFromPrevious" FLOAT,
	"ScriptId" NUMBER(38,0),
	"ScriptLanguageId" NUMBER(38,0),
	"ParentScriptVersionId" VARCHAR(16777216),
	"TotalVotes" NUMBER(38,0),
	"AuthorUserId" NUMBER(38,0),
	"Title" VARCHAR(16777216),
	"LinesInsertedFromFork" FLOAT,
	"Id" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELVERSIONS" (VersionNumber, ScriptLanguageId, Title, LinesChangedFromFork, ParentScriptVersionId, LinesChangedFromPrevious, LinesUnchangedFromPrevious, CreationDate, AuthorUserId, TotalVotes, TotalLines, EvaluationDate, LinesInsertedFromFork, LinesUnchangedFromFork, ScriptId, LinesDeletedFromFork, IsChange, LinesInsertedFromPrevious, Id) VALUES (86.0, 9, 'Titanic Problem', nan, NULL, 0.0, 427.0, 1665069639000000, 11500118, 0, 431.0, '2022-10-06', nan, nan, 30636649, nan, True, 4.0, 107355719), (7.0, 9, 'notebookc1fc5ad94b', nan, NULL, 0.0, 426.0, 1706733414000000, 15669490, 0, 431.0, '2024-01-31', nan, nan, 50117187, nan, True, 5.0, 161218273), (10.0, 9, 'Forecasting Diabetes Mellitus', nan, NULL, 14.0, 499.0, 1496235682000000, 378133, 0, 431.0, '2017-05-31', nan, nan, 265878, nan, True, 5.0, 1202703), (16.0, 9, 'Assignment 3', nan, NULL, 0.0, 425.0, 1636958055000000, 8444425, 0, 431.0, '2021-11-15', nan, nan, 21902001, nan, True, 6.0, 79775492), (3.0, 9, 'HW8-anomaly-detection', 0.0, NULL, 0.0, 424.0, 1719567230000000, 6045667, 0, 431.0, '2024-06-28', 207.0, 224.0, 60937253, 76.0, True, 7.0, 185890301);
-- DBMS: snowflake
create or replace TABLE FORUMS (
	"Id" NUMBER(38,0),
	"ParentForumId" NUMBER(38,0),
	"Title" VARCHAR(16777216)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."FORUMS" (Title, Id, ParentForumId) VALUES ('Models', 2578766, NULL), ('Notebooks', 16860, NULL), ('Advanced SQL', 1462513, NULL), ('Data Cleaning', 1462517, NULL), ('Dataset Tasks', 573890, NULL);
-- DBMS: snowflake
create or replace TABLE EPISODEAGENTS (
	"Id" NUMBER(38,0),
	"EpisodeId" NUMBER(38,0),
	"Index" NUMBER(38,0),
	"Reward" FLOAT,
	"State" NUMBER(38,0),
	"SubmissionId" NUMBER(38,0),
	"InitialConfidence" FLOAT,
	"InitialScore" FLOAT,
	"UpdatedConfidence" FLOAT,
	"UpdatedScore" FLOAT
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."EPISODEAGENTS" (Index, EpisodeId, Reward, InitialConfidence, InitialScore, SubmissionId, Id, State, UpdatedConfidence, UpdatedScore) VALUES (1, 33120822, 90009.0, 35.0, 580.0042657891344, 22809035, 81336101, 2, 35.0, 584.479734260055), (1, 33094139, 90009.0, 62.12528253738546, 1272.9005023034138, 24127816, 81282735, 2, 60.78962034206572, 1262.803283593908), (1, 33153184, 90009.0, 35.0, 566.3995879006497, 22599340, 81400825, 2, 35.0, 569.9552747465942), (1, 33182156, 90009.0, 36.79200561544236, 1320.6288982194073, 24115042, 81458769, 2, 36.45203209769453, 1325.9342154604803), (1, 33153219, 90009.0, 35.0, 1173.6191450661524, 23177330, 81400895, 2, 35.0, 1169.175078766726);
-- DBMS: snowflake
create or replace TABLE USERFOLLOWERS (
	"Id" NUMBER(38,0),
	"UserId" NUMBER(38,0),
	"FollowingUserId" NUMBER(38,0),
	"CreationDate" DATE
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."USERFOLLOWERS" (CreationDate, Id, UserId, FollowingUserId) VALUES ('2020-03-08', 412502, 368, 1302389), ('2021-08-18', 851010, 421, 727004), ('2021-08-18', 851009, 421, 1053193), ('2020-04-27', 448467, 440, 473824), ('2017-10-23', 31190, 650, 1221368);
-- DBMS: snowflake
create or replace TABLE EPISODES (
	"Id" NUMBER(38,0),
	"Type" NUMBER(38,0),
	"CompetitionId" NUMBER(38,0),
	"CreateTime" NUMBER(38,0),
	"EndTime" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."EPISODES" (CompetitionId, Id, EndTime, CreateTime, Type) VALUES (60154, 54280896, 1711149568000000, 1711149530000000, 1), (60154, 54215929, 1710568777000000, 1710568729000000, 1), (60154, 54348494, 1711772865000000, 1711772827000000, 1), (60154, 54556515, 1713772515000000, 1713772468000000, 1), (60154, 54667942, 1714797992000000, 1714797902000000, 1);
-- DBMS: snowflake
create or replace TABLE DATASETS (
	"Id" NUMBER(38,0),
	"CreatorUserId" NUMBER(38,0),
	"OwnerUserId" NUMBER(38,0),
	"OwnerOrganizationId" NUMBER(38,0),
	"CurrentDatasetVersionId" NUMBER(38,0),
	"CurrentDatasourceVersionId" NUMBER(38,0),
	"ForumId" NUMBER(38,0),
	"Type" VARCHAR(16777216),
	"CreationDate" NUMBER(38,0),
	"LastActivityDate" DATE,
	"TotalViews" NUMBER(38,0),
	"TotalDownloads" NUMBER(38,0),
	"TotalVotes" NUMBER(38,0),
	"TotalKernels" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."DATASETS" (LastActivityDate, Id, OwnerUserId, Type, TotalDownloads, TotalVotes, CurrentDatasourceVersionId, TotalKernels, TotalViews, ForumId, OwnerOrganizationId, CreatorUserId, CurrentDatasetVersionId, CreationDate) VALUES ('2018-10-02', 58151, 2311653, 'Dataset', 0, 0, 123254, 0, 132, 66990, NULL, 2311653, 112840, 1538462902000000), ('2018-10-02', 58161, 2311653, 'Dataset', 0, 0, 123281, 0, 10, 67000, NULL, 2311653, 112865, 1538464192000000), ('2018-10-02', 58185, 2311653, 'Dataset', 0, 0, 123332, 1, 13, 67025, NULL, 2311653, 112907, 1538468032000000), ('2018-10-02', 58199, 2311653, 'Dataset', 0, 0, 123357, 0, 314, 67040, NULL, 2311653, 112931, 1538469809000000), ('2018-10-02', 58252, 2312500, 'Dataset', 0, 0, 123463, 0, 63, 67095, NULL, 2312500, 113034, 1538480351000000);
-- DBMS: snowflake
create or replace TABLE DATASOURCES (
	"Id" NUMBER(38,0),
	"CreatorUserId" NUMBER(38,0),
	"CreationDate" NUMBER(38,0),
	"Type" VARCHAR(16777216),
	"CurrentDatasourceVersionId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."DATASOURCES" (CreatorUserId, CreationDate, CurrentDatasourceVersionId, Id, Type) VALUES (3867392, 1579359348000000, 925571, 498859, 'Dataset'), (4064256, 1692280786000000, 6399262, 3683191, 'Dataset'), (4064256, 1700233077000000, 7076875, 4068752, 'Dataset'), (4064256, 1710735660000000, 7977563, 4684371, 'Dataset'), (4064256, 1710735708000000, 7977567, 4684374, 'Dataset');
-- DBMS: snowflake
create or replace TABLE USERACHIEVEMENTS (
	"Id" NUMBER(38,0),
	"UserId" NUMBER(38,0),
	"AchievementType" VARCHAR(16777216),
	"Tier" NUMBER(38,0),
	"TierAchievementDate" DATE,
	"Points" NUMBER(38,0),
	"CurrentRanking" NUMBER(38,0),
	"HighestRanking" NUMBER(38,0),
	"TotalGold" NUMBER(38,0),
	"TotalSilver" NUMBER(38,0),
	"TotalBronze" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."USERACHIEVEMENTS" (TotalGold, TierAchievementDate, HighestRanking, CurrentRanking, Id, UserId, TotalSilver, Tier, AchievementType, Points, TotalBronze) VALUES (0, NULL, NULL, NULL, 6426519, 930969, 0, 0, 'Competitions', 0, 0), (0, NULL, NULL, NULL, 6512273, 960263, 0, 0, 'Competitions', 0, 0), (0, NULL, NULL, NULL, 6419651, 928677, 0, 0, 'Competitions', 0, 0), (0, NULL, NULL, NULL, 6510824, 959735, 0, 0, 'Competitions', 0, 0), (0, NULL, NULL, NULL, 7122494, 1159614, 0, 0, 'Competitions', 0, 0);
-- DBMS: snowflake
create or replace TABLE COMPETITIONTAGS (
	"Id" NUMBER(38,0),
	"CompetitionId" NUMBER(38,0),
	"TagId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."COMPETITIONTAGS" (TagId, CompetitionId, Id) VALUES (12038, 13242, 482), (14101, 4032, 315), (14101, 4195, 300), (14101, 4272, 304), (14101, 4280, 298);
-- DBMS: snowflake
create or replace TABLE KERNELVERSIONCOMPETITIONSOURCES (
	"Id" NUMBER(38,0),
	"KernelVersionId" NUMBER(38,0),
	"SourceCompetitionId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELVERSIONCOMPETITIONSOURCES" (Id, SourceCompetitionId, KernelVersionId) VALUES (6280, 3948, 4511), (601723, 3948, 555), (88411, 3948, 841), (974621, 3948, 610), (950711, 3948, 773);
-- DBMS: snowflake
create or replace TABLE TAGS (
	"Id" NUMBER(38,0),
	"ParentTagId" NUMBER(38,0),
	"Name" VARCHAR(16777216),
	"Slug" VARCHAR(16777216),
	"FullPath" VARCHAR(16777216),
	"Description" VARCHAR(16777216),
	"DatasetCount" NUMBER(38,0),
	"CompetitionCount" NUMBER(38,0),
	"KernelCount" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."TAGS" (CompetitionCount, Description, KernelCount, Name, DatasetCount, FullPath, ParentTagId, Id, Slug) VALUES (20, 'Basketball is one of the world''s most popular and widely viewed sports. Analyze Kobe Bryant''s shot selections and peruse our annual March Mania competitions.', 662, 'basketball', 1870, 'subject > health and fitness > exercise > sports > basketball', 4141, 2606, 'basketball'), (14, 'AI in healthcare is a growing interest. One of the major problems is simply converting research into an application. Should be easy, right?', 1654, 'healthcare', 1648, 'subject > health and fitness > health > healthcare', 11111, 4202, 'healthcare'), (10, '', 336, 'earth and nature', 47109, 'subject > earth and nature', 16637, 7000, 'natural-and-physical-sciences'), (8, 'Weather datasets and kernels come in all wind speeds and directions. You have weather data about hurricanes and other inclement phenomena, hourly readings, and general weather for various cities.', 565, 'weather and climate', 1170, 'subject > earth and nature > environment > weather and climate', 7302, 7408, 'weather'), (56, 'Explore datasets, kernels, and competitions related to housing markets in this tag.', 890, 'housing', 721, 'subject > people and society > business > real estate > housing', 11122, 8317, 'housing');
-- DBMS: snowflake
create or replace TABLE FORUMMESSAGEVOTES (
	"Id" NUMBER(38,0),
	"ForumMessageId" NUMBER(38,0),
	"FromUserId" NUMBER(38,0),
	"ToUserId" NUMBER(38,0),
	"VoteDate" DATE
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."FORUMMESSAGEVOTES" (ToUserId, FromUserId, Id, VoteDate, ForumMessageId) VALUES (638, 307512, 183321, '2017-04-06', 6), (368, 6632177, 4402419, '2024-07-16', 28), (2246, 697221, 133472, '2016-08-26', 352), (1828, 514568, 431934, '2018-06-30', 546), (1231, 929000, 177441, '2017-03-14', 563);
-- DBMS: snowflake
create or replace TABLE KERNELVERSIONKERNELSOURCES (
	"Id" NUMBER(38,0),
	"KernelVersionId" NUMBER(38,0),
	"SourceKernelVersionId" NUMBER(38,0)
);

INSERT INTO "META_KAGGLE"."META_KAGGLE"."KERNELVERSIONKERNELSOURCES" (KernelVersionId, SourceKernelVersionId, Id) VALUES (6490319, 6488320, 1069706), (6492453, 6488320, 1071186), (6513221, 6488320, 1077710), (6513555, 6488320, 1078087), (6525168, 6488320, 1082279);
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.OECD_ATTRIBUTES (
    MEASUREMENT_TYPE TEXT,
    MEASURE TEXT,
    FREQUENCY TEXT,
    UNIT TEXT,
    SEASONALLY_ADJUSTED TEXT,
    VARIABLE TEXT,
    VARIABLE_NAME TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."OECD_ATTRIBUTES" (MEASUREMENT_TYPE, MEASURE, FREQUENCY, UNIT, SEASONALLY_ADJUSTED, VARIABLE, VARIABLE_NAME) VALUES (NULL, 'Balance (revenue minus expenditure) from secondary income', 'Annual', 'USD', 'Neither seasonally adjusted nor calendar adjusted', 'BAL_OF_PAY_B_IN2_XDC_USD_A_N', 'Balance of payments to rest of the world: balance (revenue minus expenditure) from secondary income in US dollar, Annual'), (NULL, 'Balance (revenue minus expenditure) from secondary income', 'Quarterly', 'USD', 'Calendar and seasonally adjusted', 'BAL_OF_PAY_B_IN2_XDC_USD_Q_Y', 'Balance of payments to rest of the world: balance (revenue minus expenditure) from secondary income in US dollar, Quarterly (Calendar and seasonally adjusted)'), (NULL, 'Balance (revenue minus expenditure) from secondary income', 'Annual', 'ZAR', 'Neither seasonally adjusted nor calendar adjusted', 'BAL_OF_PAY_B_IN2_XDC_ZAR_A_N', 'Balance of payments to rest of the world: balance (revenue minus expenditure) from secondary income in Rand, Annual'), (NULL, 'Balance (revenue minus expenditure) from capital account', 'Quarterly', 'CHF', 'Neither seasonally adjusted nor calendar adjusted', 'BAL_OF_PAY_B_KA_XDC_CHF_Q_N', 'Balance of payments to rest of the world: balance (revenue minus expenditure) from capital account in Swiss franc, Quarterly'), (NULL, 'Balance (revenue minus expenditure) from capital account', 'Annual', 'INR', 'Neither seasonally adjusted nor calendar adjusted', 'BAL_OF_PAY_B_KA_XDC_INR_A_N', 'Balance of payments to rest of the world: balance (revenue minus expenditure) from capital account in Indian rupee, Annual');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.COMPANY_SECURITY_RELATIONSHIPS (
    SECURITY_ID TEXT,
    SECURITY_NAME TEXT,
    SECURITY_ID_TYPE TEXT,
    COMPANY_ID TEXT,
    COMPANY_NAME TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."COMPANY_SECURITY_RELATIONSHIPS" (SECURITY_ID, SECURITY_NAME, SECURITY_ID_TYPE, COMPANY_ID, COMPANY_NAME) VALUES ('BBG00Q6SF3X5', 'UNITED NATURAL FOODS INC', 'openfigi_figi_id', 'db61b5dc8b1d123383774189e8b57f47', 'UNITED NATURAL FOODS INC'), ('BBG000KX4134', 'POWER REIT', 'openfigi_figi_id', '748f82a466853b495ff37302758e0618', 'POWER REIT'), ('BBG00KN97NR3', 'NORTH AMERICAN CONSTRUCTION', 'openfigi_figi_id', '03e0eb1fe93fafd66765ef15997156d3', 'NORTH AMERICAN CONSTRUCTION GROUP LTD.'), ('BBG00JPVPVD2', 'TESLA INC', 'openfigi_figi_id', '796aed24f8c91888e412d0a6e8dcffed', 'TESLA, INC.'), ('BBG00JR59ZL7', 'FIRST MAJESTIC SILVER CORP', 'openfigi_figi_id', '702df1f0a8462880ff1c0a772b0eff49', 'FIRST MAJESTIC SILVER CORP');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.FDIC_SUMMARY_OF_DEPOSITS_TIMESERIES (
    VALUE NUMBER,
    DATE DATE,
    FDIC_INSTITUTION_ID TEXT,
    UNIT TEXT,
    VARIABLE TEXT,
    FDIC_BRANCH_ID TEXT,
    VARIABLE_NAME TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."FDIC_SUMMARY_OF_DEPOSITS_TIMESERIES" (VALUE, DATE, FDIC_INSTITUTION_ID, UNIT, VARIABLE, FDIC_BRANCH_ID, VARIABLE_NAME) VALUES (119632, '2023-06-30', '2239', 'USD', 'DEPSUMBR', '286466', 'Branch Deposits'), (59230, '2017-06-30', '6499', 'USD', 'DEPSUMBR', '6499', 'Branch Deposits'), (35943, '2014-06-30', '417', 'USD', 'DEPSUMBR', '481396', 'Branch Deposits'), (85928, '2016-06-30', '3123', 'USD', 'DEPSUMBR', '203999', 'Branch Deposits'), (133714, '2007-06-30', '745', 'USD', 'ASSET', '745', 'Institutional Assets');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.US_ECONOMIC_CENSUS_ATTRIBUTES (
    VARIABLE_NAME TEXT,
    CREDIT_CARD_SERVICES_INCOME TEXT,
    MEASURE TEXT,
    VARIABLE TEXT,
    NAICS_CODE TEXT,
    FREQUENCY TEXT,
    PRODUCT_SERVICES_LINE TEXT,
    TAX_STATUS TEXT,
    NAICS_DESCRIPTION TEXT,
    UNIT TEXT,
    OPERATION_TYPE TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."US_ECONOMIC_CENSUS_ATTRIBUTES" (VARIABLE_NAME, CREDIT_CARD_SERVICES_INCOME, MEASURE, VARIABLE, NAICS_CODE, FREQUENCY, PRODUCT_SERVICES_LINE, TAX_STATUS, NAICS_DESCRIPTION, UNIT, OPERATION_TYPE) VALUES ('Production workers for pay period including sept 12 | Iron ore mining (NAICS 2012 code: 212210)', NULL, 'Employment', 'EMPQ3PW_212210_2012', '212210', 'Annual', NULL, NULL, 'Iron ore mining', 'Count', NULL), ('Other employees for pay period including march 12 | Land subdivision (NAICS 2017 code: 237210)', NULL, 'Employment', 'EMPQ1OC_237210_2017', '237210', 'Annual', NULL, NULL, 'Land subdivision', 'Count', NULL), ('Average count of other employees | Fire extinguishers and fire safety equipment merchant wholesalers (NAICS 2017 code: 4239905) | Type of Operation: All establishments | Tax Status: All establishments', NULL, 'Employment', 'EMPSMOD_4239905_2017_00_00', '4239905', 'Annual', NULL, 'All establishments', 'Fire extinguishers and fire safety equipment merchant wholesalers', 'Count', 'All establishments'), ('Range indicating percent of total sales, value of shipments, or revenue imputed | Motor vehicle brake system manufacturing (NAICS 2017 code: 33634) | Tax Status: All establishments', NULL, 'Sales and revenue', 'RCPTOT_IMP_33634_2017__00', '33634', 'Annual', NULL, 'All establishments', 'Motor vehicle brake system manufacturing', 'Count', NULL), ('Count of establishments not reporting inventories | Traveler accommodation (NAICS 2012 code: 7211)', NULL, 'Establishments', 'ESTCNR_7211_2012', '7211', 'Annual', NULL, NULL, 'Traveler accommodation', 'Count', NULL);
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.PERMID_SECURITY_INDEX (
    ASSET_CLASS TEXT,
    EXCHANGE_CODE ARRAY,
    PRIMARY_TICKER TEXT,
    SECURITY_NAME TEXT,
    PRIMARY_EXCHANGE_CODE TEXT,
    SECURITY_STATUS TEXT,
    GLOBAL_TICKERS ARRAY,
    PERMID_SECURITY_ID TEXT,
    PRIMARY_EXCHANGE_NAME TEXT,
    PERMID_QUOTE_ID ARRAY
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."PERMID_SECURITY_INDEX" (ASSET_CLASS, EXCHANGE_CODE, PRIMARY_TICKER, SECURITY_NAME, PRIMARY_EXCHANGE_CODE, SECURITY_STATUS, GLOBAL_TICKERS, PERMID_SECURITY_ID, PRIMARY_EXCHANGE_NAME, PERMID_QUOTE_ID) VALUES ('Other', '[
  "NAS",
  "NYQ"
]', 'EVN', 'EATON VANCE MUNICIPAL INCOME CLOSED FUND', 'NYQ', 'Active', '[
  "EVN",
  "XEVNX"
]', '8589975674', 'NYSE CONSOLIDATED', '[
  "55835369644",
  "55839104515"
]'), ('Ordinary Shares', '[
  "FRA",
  "ISS",
  "MEX"
]', 'LENb', 'LENNAR ORD SHS CLASS B', 'ISS', 'Active', '[
  "LENB*",
  "LENb",
  "LNN0"
]', '8589959375', 'ISE when trading NYSE and AMEX Stocks', '[
  "21627275840",
  "21736829361",
  "55836192793"
]'), ('Other', '[
  "NAS",
  "WCB"
]', 'XFSLX', 'FIRST EAGLE SENIOR LOAN FUND', 'NAS', 'Inactive', '[
  "TSLF",
  "XFSLX"
]', '18040205046', 'NASDAQ CAPITAL MARKET', '[
  "21529763349",
  "21529826402"
]'), ('Ordinary Shares', '[
  "BCO",
  "LSE",
  "MXQ"
]', 'TIF*', 'TIFFANY ORD SHS', 'MXQ', 'Inactive', '[
  "0LFD",
  "0LFDl",
  "TIF*"
]', '8590935543', NULL, '[
  "21633621402",
  "21634297966",
  "21667705791"
]'), ('Ordinary Shares', '[
  "BCO",
  "TDG"
]', 'RWSl', 'RWS HOLDINGS ORD SHS', 'BCO', 'Active', '[
  "RWJ",
  "RWSl"
]', '8590923465', 'BATS CHI-X Trade Reporting', '[
  "21475037440",
  "21538768765"
]');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.FINANCIAL_INSTITUTION_ATTRIBUTES (
    UNIT TEXT,
    DEFINITION TEXT,
    VARIABLE TEXT,
    VARIABLE_NAME TEXT,
    FREQUENCY TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."FINANCIAL_INSTITUTION_ATTRIBUTES" (UNIT, DEFINITION, VARIABLE, VARIABLE_NAME, FREQUENCY) VALUES ('Percent', 'Retained earnings from bank operations, net unrealized holding gains (losses) on available-for-sale securities, and cumulative foreign currency translation adjustments.', 'EQUP', 'Undivided Profits', 'Quarterly'), ('Percent', 'Loan and lease financing receivables, net of unearned income, allowances, and reserves, as a percent of total assets.', 'LNLSNTV', 'Net Loans and Leases to Assets', 'YTD'), ('Percent', 'Net amount of loans secured by junior liens on 1-4 family residential properties (which are held in domestic offices) that have been charged-off and debited to the allowance for loan and lease losses established by the institution. Prior to 2004, this item is not available for TFR Reporters . Calculated as NTRERSF2 / ASSET5', 'NTRERSF2R', 'Secured By Junior Liens', 'YTD'), ('USD', 'That portion of financial standby letters of credit, foreign office guarantees, performance standby letters of credit, and foreign office guarantees (including cash collateral standby letters of credit) conveyed to others.', 'LOCFPSBK', 'Standby Letters of Credit Amount Conveyed To Others', 'YTD'), ('USD', 'Loan Loss Allowance Included in Tier 2 Capital', 'RB2LNRES', 'Loan Loss Allowance Included in Tier 2 Capital', 'YTD');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.FINANCIAL_INSTITUTION_EVENTS (
    NAME_SUCCESSOR TEXT,
    TRANSFORMATION_TYPE TEXT,
    CATEGORY_SUCCESSOR TEXT,
    CATEGORY_PREDECESSOR TEXT,
    NAME_PREDECESSOR TEXT,
    MERGER_ACCOUNTING_METHOD_UTILIZED TEXT,
    ACTIVE_SUCCESSOR BOOLEAN,
    ID_RSSD_PREDECESSOR NUMBER,
    TRANSACTION_DATE DATE,
    ID_RSSD_SUCCESSOR NUMBER,
    ACTIVE_PREDECESSOR BOOLEAN
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."FINANCIAL_INSTITUTION_EVENTS" (NAME_SUCCESSOR, TRANSFORMATION_TYPE, CATEGORY_SUCCESSOR, CATEGORY_PREDECESSOR, NAME_PREDECESSOR, MERGER_ACCOUNTING_METHOD_UTILIZED, ACTIVE_SUCCESSOR, ID_RSSD_PREDECESSOR, TRANSACTION_DATE, ID_RSSD_SUCCESSOR, ACTIVE_PREDECESSOR) VALUES ('California Bank of Commerce, National Association', 'Charter Discontinued', 'Bank', 'Branch', 'Bank of Santa Clarita', 'Purchase/Acquisition', True, 3302312, '2021-10-02', 3076453, True), ('Equity Bank', 'Charter Discontinued', 'Bank', 'Branch', 'KansasLand Bank', 'Purchase/Acquisition', True, 422059, '2024-07-02', 139656, False), ('California Bank of Commerce, National Association', 'Failure', 'Bank', 'Bank', 'Frontier Bank, FSB', NULL, True, 2704740, '2014-11-08', 3076453, False), ('Firstar Bank Council Bluffs', 'Charter Discontinued', 'Branch', 'Branch', 'Firstar Bank Red Oak, National Association', 'Pooling of interests or entities under common control.', False, 467649, '1995-08-28', 213248, False), ('First of America Bank-Illinois, National Association', 'Charter Discontinued', 'Branch', 'Branch', 'First of America Bank - Grayslake, National Association', NULL, False, 794130, '1989-06-04', 363835, False);
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.BANK_FOR_INTERNATIONAL_SETTLEMENTS_ATTRIBUTES (
    COUNTERPARTY_GEO_NAME TEXT,
    VARIABLE_NAME TEXT,
    MEASURE TEXT,
    MEASUREMENT_TYPE TEXT,
    UNIT TEXT,
    VARIABLE TEXT,
    GEO_NAME TEXT,
    FREQUENCY TEXT,
    SOURCE TEXT,
    SERIES_ID TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."BANK_FOR_INTERNATIONAL_SETTLEMENTS_ATTRIBUTES" (COUNTERPARTY_GEO_NAME, VARIABLE_NAME, MEASURE, MEASUREMENT_TYPE, UNIT, VARIABLE, GEO_NAME, FREQUENCY, SOURCE, SERIES_ID) VALUES ('All countries (total)', 'United Kingdom - All Total liabilities of banks with headquarters in All countries (total) vis-a-vis residents of All countries (total), All sectors (FX and break adjusted change (BIS calculated), Debt securities in All currencies (=D+F+U), All currencies, All reporting banks/institutions (domestic, foreign, consortium and unclassified)', 'Total liabilities', NULL, 'USD', 'BIS,WS_LBS_D_PUB,1.0,Q.F.L.D.TO1.A.5J.A.GB.A.5J.A', 'United Kingdom', 'Quarterly', NULL, 'BIS,WS_LBS_D_PUB,1.0'), ('Bermuda', 'Domestic banks from Taiwan - Consolidated Total claims in All currencies with residents of Bermuda (Guarantor basis), All sectors (Amounts outstanding / Stocks, Derivatives, Total (all maturities)', 'Total claims', 'End of period', 'USD', 'BIS,WS_CBS_PUB,1.0,Q.S.TW.4B.U.C.V.A.TO1.A.BM', 'Taiwan', 'Quarterly', NULL, 'BIS,WS_CBS_PUB,1.0'), ('Equatorial Guinea', 'All reporting countries - Cross-border Total liabilities of banks with headquarters in All countries (total) vis-a-vis residents of Equatorial Guinea, Banks, related offices (FX and break adjusted change (BIS calculated), Credit (loans & debt securities) in All currencies (=D+F+U), All currencies, All reporting banks/institutions (domestic, foreign, consortium and unclassified)', 'Total liabilities', NULL, 'USD', 'BIS,WS_LBS_D_PUB,1.0,Q.F.L.B.TO1.A.5J.A.5A.I.GQ.N', 'All reporting countries', 'Quarterly', NULL, 'BIS,WS_LBS_D_PUB,1.0'), ('Chile', 'All reporting countries - Cross-border Total liabilities of banks with headquarters in All countries (total) vis-a-vis residents of Chile, Non-banks, total (Amounts outstanding / Stocks, Loans and deposits in All currencies (=D+F+U), Pound (sterling), All reporting banks/institutions (domestic, foreign, consortium and unclassified)', 'Total liabilities', NULL, 'USD', 'BIS,WS_LBS_D_PUB,1.0,Q.S.L.G.GBP.A.5J.A.5A.N.CL.N', 'All reporting countries', 'Quarterly', NULL, 'BIS,WS_LBS_D_PUB,1.0'), ('All countries (total)', 'Australia - Unallocated Total liabilities of banks with headquarters in All countries (total) vis-a-vis residents of All countries (total), Non-financial corporations (Amounts outstanding / Stocks, All instruments in All currencies (=D+F+U), All currencies, All reporting banks/institutions (domestic, foreign, consortium and unclassified)', 'Total liabilities', NULL, 'USD', 'BIS,WS_LBS_D_PUB,1.0,Q.S.L.A.TO1.A.5J.A.AU.C.5J.U', 'Australia', 'Quarterly', NULL, 'BIS,WS_LBS_D_PUB,1.0');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.BUREAU_OF_LABOR_STATISTICS_EMPLOYMENT_ATTRIBUTES (
    MEASURE TEXT,
    INDUSTRY TEXT,
    SEASONALLY_ADJUSTED BOOLEAN,
    VARIABLE_NAME TEXT,
    REPORT TEXT,
    UNIT TEXT,
    ESTABLISHMENT_SIZE TEXT,
    FREQUENCY TEXT,
    VARIABLE TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."BUREAU_OF_LABOR_STATISTICS_EMPLOYMENT_ATTRIBUTES" (MEASURE, INDUSTRY, SEASONALLY_ADJUSTED, VARIABLE_NAME, REPORT, UNIT, ESTABLISHMENT_SIZE, FREQUENCY, VARIABLE) VALUES ('Quits', 'Total private', False, 'JOLTS: Quits, Total private, 1 to 9 employees, Not seasonally adjusted, Monthly, Level', 'JOLTS', 'Level', '1 to 9 employees', 'Monthly', 'JOLTS:_Quits,_Total_private,_1_to_9_employees,_Not_seasonally_adjusted,_Monthly,_Level'), ('Quits', 'Arts, entertainment, and recreation', False, 'JOLTS: Quits, Arts, entertainment, and recreation, All size classes, Not seasonally adjusted, Annual, Percent', 'JOLTS', 'Percent', 'All size classes', 'Annual', 'JOLTS:_Quits,_Arts,_entertainment,_and_recreation,_All_size_classes,_Not_seasonally_adjusted,_Annual,_Percent'), ('Quits', 'Total private', False, 'JOLTS: Quits, Total private, All size classes, Not seasonally adjusted, Monthly, Percent', 'JOLTS', 'Percent', 'All size classes', 'Monthly', 'JOLTS:_Quits,_Total_private,_All_size_classes,_Not_seasonally_adjusted,_Monthly,_Percent'), ('Job openings', 'Leisure and hospitality', True, 'JOLTS: Job openings, Leisure and hospitality, All size classes, Seasonally adjusted, Monthly, Percent', 'JOLTS', 'Percent', 'All size classes', 'Monthly', 'JOLTS:_Job_openings,_Leisure_and_hospitality,_All_size_classes,_Seasonally_adjusted,_Monthly,_Percent'), ('Quits', 'Education and health services', True, 'JOLTS: Quits, Education and health services, All size classes, Seasonally adjusted, Monthly, Percent', 'JOLTS', 'Percent', 'All size classes', 'Monthly', 'JOLTS:_Quits,_Education_and_health_services,_All_size_classes,_Seasonally_adjusted,_Monthly,_Percent');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.BUREAU_OF_LABOR_STATISTICS_PRICE_ATTRIBUTES (
    SEASONALLY_ADJUSTED BOOLEAN,
    PRODUCT TEXT,
    UNIT TEXT,
    FREQUENCY TEXT,
    BASE_TYPE TEXT,
    VARIABLE_NAME TEXT,
    REPORT TEXT,
    VARIABLE TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."BUREAU_OF_LABOR_STATISTICS_PRICE_ATTRIBUTES" (SEASONALLY_ADJUSTED, PRODUCT, UNIT, FREQUENCY, BASE_TYPE, VARIABLE_NAME, REPORT, VARIABLE) VALUES (False, 'Household furnishings and operations', '2001-12 Index Date', 'Monthly', 'Standard Reference Base', 'CPI: Household furnishings and operations, Not seasonally adjusted, Monthly, 2001-12 Index Date', 'Consumer Price Index', 'CPI:_Household_furnishings_and_operations,_Not_seasonally_adjusted,_Monthly,_2001-12_Index_Date'), (False, 'Men''s underwear, nightwear, swimwear and accessories', '1982-84 Index Date', 'Semi-annual', 'Standard Reference Base', 'CPI: Men''s underwear, nightwear, swimwear and accessories, Not seasonally adjusted, Semi-annual', 'Consumer Price Index', 'CPI:_Men''s_underwear,_nightwear,_swimwear_and_accessories,_Not_seasonally_adjusted,_Semi-annual'), (False, 'Utility (piped) gas service', '2001-12 Index Date', 'Annual', 'Standard Reference Base', 'CPI: Utility (piped) gas service, Not seasonally adjusted, Annual, 2001-12 Index Date', 'Consumer Price Index', 'CPI:_Utility_(piped)_gas_service,_Not_seasonally_adjusted,_Annual,_2001-12_Index_Date'), (False, 'Recorded music and music subscriptions', '1997-12 Index Date', 'Annual', 'Standard Reference Base', 'CPI: Recorded music and music subscriptions, Not seasonally adjusted, Annual, 1997-12 Index Date', 'Consumer Price Index', 'CPI:_Recorded_music_and_music_subscriptions,_Not_seasonally_adjusted,_Annual,_1997-12_Index_Date'), (False, 'Dairy and related products', '1987 Index Date', 'Annual', 'Standard Reference Base', 'CPI: Dairy and related products, Not seasonally adjusted, Annual, 1987 Index Date', 'Consumer Price Index', 'CPI:_Dairy_and_related_products,_Not_seasonally_adjusted,_Annual,_1987_Index_Date');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.FHFA_HOUSE_PRICE_ATTRIBUTES (
    PROPERTY_CLASSIFICATION TEXT,
    SEASONALLY_ADJUSTED BOOLEAN,
    VARIABLE_NAME TEXT,
    INDEX_TYPE TEXT,
    VARIABLE TEXT,
    FREQUENCY TEXT,
    UNIT TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."FHFA_HOUSE_PRICE_ATTRIBUTES" (PROPERTY_CLASSIFICATION, SEASONALLY_ADJUSTED, VARIABLE_NAME, INDEX_TYPE, VARIABLE, FREQUENCY, UNIT) VALUES ('traditional', True, 'FHFA_HPI traditional purchase-only monthly Seasonally Adjusted', 'purchase-only', 'FHFA_HPI_traditional_purchase-only_monthly_SA', 'MONTHLY', 'Index'), ('non-metro', False, 'FHFA_HPI non-metro all-transactions quarterly Not Seasonally Adjusted', 'all-transactions', 'FHFA_HPI_non-metro_all-transactions_quarterly_NSA', 'QUARTERLY', 'Index'), ('traditional', True, 'FHFA_HPI traditional purchase-only quarterly Seasonally Adjusted', 'purchase-only', 'FHFA_HPI_traditional_purchase-only_quarterly_SA', 'QUARTERLY', 'Index'), ('distress-free', True, 'FHFA_HPI distress-free purchase-only quarterly Seasonally Adjusted', 'purchase-only', 'FHFA_HPI_distress-free_purchase-only_quarterly_SA', 'QUARTERLY', 'Index'), ('distress-free', False, 'FHFA_HPI distress-free purchase-only quarterly Not Seasonally Adjusted', 'purchase-only', 'FHFA_HPI_distress-free_purchase-only_quarterly_NSA', 'QUARTERLY', 'Index');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.FHFA_UNIFORM_APPRAISAL_ATTRIBUTES (
    VARIABLE_GROUP TEXT,
    VARIABLE_NAME TEXT,
    CATEGORY TEXT,
    CHARACTERISTIC TEXT,
    UNIT TEXT,
    APPRAISAL_PURPOSE TEXT,
    FREQUENCY TEXT,
    VARIABLE TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."FHFA_UNIFORM_APPRAISAL_ATTRIBUTES" (VARIABLE_GROUP, VARIABLE_NAME, CATEGORY, CHARACTERISTIC, UNIT, APPRAISAL_PURPOSE, FREQUENCY, VARIABLE) VALUES ('25% Quartile of Appraised Value', 'Quarterly 25% Quartile of Appraised Value Property Condition (4 categories) Purchase & Refinance C1 and C2', 'C1 and C2', 'Property Condition (4 categories)', 'USD', 'Purchase & Refinance', 'Quarterly', 'Quarterly_25%_Quartile_of_Appraised_Value_Property_Condition_(4_categories)_Purchase_&_Refinance_C1_and_C2'), ('25% Quartile of Appraised Value', 'Quarterly 25% Quartile of Appraised Value Public Water Refinance Public', 'Public', 'Public Water', 'USD', 'Refinance', 'Quarterly', 'Quarterly_25%_Quartile_of_Appraised_Value_Public_Water_Refinance_Public'), ('25% Quartile of Appraised Value', 'Quarterly 25% Quartile of Appraised Value Tract Largest Race/Ethnicity Group Purchase & Refinance Black (50% or more)', 'Black (50% or more)', 'Tract Largest Race/Ethnicity Group', 'USD', 'Purchase & Refinance', 'Quarterly', 'Quarterly_25%_Quartile_of_Appraised_Value_Tract_Largest_Race/Ethnicity_Group_Purchase_&_Refinance_Black_(50%_or_more)'), ('Median Appraised Value', 'Quarterly Median Appraised Value Property Condition (4 categories) Purchase & Refinance C5 and C6', 'C5 and C6', 'Property Condition (4 categories)', 'USD', 'Purchase & Refinance', 'Quarterly', 'Quarterly_Median_Appraised_Value_Property_Condition_(4_categories)_Purchase_&_Refinance_C5_and_C6'), ('Median Appraised Value', 'Quarterly Median Appraised Value Property Condition (4 categories) Refinance C5 and C6', 'C5 and C6', 'Property Condition (4 categories)', 'USD', 'Refinance', 'Quarterly', 'Quarterly_Median_Appraised_Value_Property_Condition_(4_categories)_Refinance_C5_and_C6');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.STOCK_PRICE_TIMESERIES (
    PRIMARY_EXCHANGE_NAME TEXT,
    ASSET_CLASS TEXT,
    VALUE FLOAT,
    PRIMARY_EXCHANGE_CODE TEXT,
    VARIABLE TEXT,
    DATE DATE,
    VARIABLE_NAME TEXT,
    TICKER TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."STOCK_PRICE_TIMESERIES" (PRIMARY_EXCHANGE_NAME, ASSET_CLASS, VALUE, PRIMARY_EXCHANGE_CODE, VARIABLE, DATE, VARIABLE_NAME, TICKER) VALUES ('NASDAQ CAPITAL MARKET', 'Common Shares', 1.19, 'NAS', 'all-day_high', '2022-08-08', 'All-Day High', 'FAMI'), ('NASDAQ CAPITAL MARKET', 'Equity', 17249.0, 'NAS', 'nasdaq_volume', '2023-02-16', 'Nasdaq Volume', 'TIPT'), ('NEW YORK STOCK EXCHANGE', 'Equity', 817.51, 'NYS', 'post-market_close', '2021-04-26', 'Post-Market Close', 'BLK'), ('NYSE MKT LLC', 'Equity', 2028.0, 'ASE', 'nasdaq_volume', '2018-09-18', 'Nasdaq Volume', 'BRN'), ('NYSE ARCA', 'ETF-Index Fund Shares', 2373734.0, 'PSE', 'nasdaq_volume', '2023-11-16', 'Nasdaq Volume', 'XLP');
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.EUROPEAN_CENTRAL_BANK_TIMESERIES (
    VARIABLE_NAME TEXT,
    UNIT TEXT,
    DATE DATE,
    VALUE_COMMENT TEXT,
    GEO_ID TEXT,
    VARIABLE TEXT,
    VALUE FLOAT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."EUROPEAN_CENTRAL_BANK_TIMESERIES" (VARIABLE_NAME, UNIT, DATE, VALUE_COMMENT, GEO_ID, VARIABLE, VALUE) VALUES ('Harmonized Index Of Consumer Prices - Seasonal Food, Annual Rate Of Change, Eurostat, Neither Seasonally Nor Working Day Adjusted, Percent', 'Percent', '1997-03-31', '', 'country/LTU', 'harmonized_index_of_consumer_prices_seasonal_food_annual_rate_of_change_eurostat_neither_seasonally_nor_working_day_adjusted_percent', 0.024), ('Harmonized Index Of Consumer Prices - Canteens, Monthly Index, Eurostat, Neither Seasonally Nor Working Day Adjusted, Index, 2015=100', 'Index, 2015=100', '2012-03-31', '', 'country/BGR', 'harmonized_index_of_consumer_prices_canteens_monthly_index_eurostat_neither_seasonally_nor_working_day_adjusted_index_2015=100', 89.94), ('Harmonized Index Of Consumer Prices - Mobile Telephone Equipment, Annual Rate Of Change, Eurostat, Neither Seasonally Nor Working Day Adjusted, Percent', 'Percent', '2020-04-30', '', 'country/DEU', 'harmonized_index_of_consumer_prices_mobile_telephone_equipment_annual_rate_of_change_eurostat_neither_seasonally_nor_working_day_adjusted_percent', -0.072), ('Harmonized Index Of Consumer Prices - Margarine And Other Vegetable Fats, Annual Rate Of Change, Eurostat, Neither Seasonally Nor Working Day Adjusted, Percent', 'Percent', '2016-08-31', '', 'country/PRT', 'harmonized_index_of_consumer_prices_margarine_and_other_vegetable_fats_annual_rate_of_change_eurostat_neither_seasonally_nor_working_day_adjusted_percent', 0.002), ('Harmonized Index Of Consumer Prices - Passenger Transport By Railway, Monthly Index, Eurostat, Neither Seasonally Nor Working Day Adjusted, Index, 2015=100', 'Index, 2015=100', '2000-05-31', '', 'country/DEU', 'harmonized_index_of_consumer_prices_passenger_transport_by_railway_monthly_index_eurostat_neither_seasonally_nor_working_day_adjusted_index_2015=100', 66.2);
-- DBMS: snowflake
CREATE TABLE FINANCE__ECONOMICS.CYBERSYN.FX_RATES_TIMESERIES (
    BASE_CURRENCY_NAME TEXT,
    VARIABLE TEXT,
    QUOTE_CURRENCY_NAME TEXT,
    VALUE FLOAT,
    VARIABLE_NAME TEXT,
    BASE_CURRENCY_ID TEXT,
    DATE DATE,
    QUOTE_CURRENCY_ID TEXT
);

INSERT INTO "FINANCE__ECONOMICS"."CYBERSYN"."FX_RATES_TIMESERIES" (BASE_CURRENCY_NAME, VARIABLE, QUOTE_CURRENCY_NAME, VALUE, VARIABLE_NAME, BASE_CURRENCY_ID, DATE, QUOTE_CURRENCY_ID) VALUES ('Swiss Franc', 'chf_sek', 'Swedish Krona', 6.8232, 'CHF/SEK Exchange Rate', 'CHF', '2011-03-10', 'SEK'), ('United States Dollar', 'usd_try', 'Turkish Lira', 1.8111, 'USD/TRY Exchange Rate', 'USD', '2013-03-13', 'TRY'), ('United States Dollar', 'usd_mkd', 'Macedonian Denar', 57.61, 'USD/MKD Exchange Rate', 'USD', '2024-04-25', 'MKD'), ('Canadian Dollar', 'cad_sgd', 'Singapore Dollar', 1.229, 'CAD/SGD Exchange Rate', 'CAD', '2012-12-24', 'SGD'), ('United States Dollar', 'usd_inr', 'Indian Rupee', 8.98, 'USD/INR Exchange Rate', 'USD', '1981-07-28', 'INR');