nl2sqlproj/spider2-nl2sql huggingface dataset:
-- DBMS: snowflake
CREATE TABLE WEATHER__ENVIRONMENT.CYBERSYN.GEOGRAPHY_INDEX (
    LEVEL TEXT,
    ISO_ALPHA2 TEXT,
    GEO_ID TEXT,
    ISO_3166_2_CODE TEXT,
    ISO_NUMERIC_CODE TEXT,
    ISO_ALPHA3 TEXT,
    GEO_NAME TEXT,
    ISO_NAME TEXT
);

INSERT INTO "WEATHER__ENVIRONMENT"."CYBERSYN"."GEOGRAPHY_INDEX" (LEVEL, ISO_ALPHA2, GEO_ID, ISO_3166_2_CODE, ISO_NUMERIC_CODE, ISO_ALPHA3, GEO_NAME, ISO_NAME) VALUES ('CensusBlockGroup', NULL, 'censusBlockGroup/480610125072', NULL, NULL, NULL, 'Block Group 2, Census Tract 125.07, Cameron County, Texas', NULL), ('CensusTract', NULL, 'geoId/26049012906', NULL, NULL, NULL, 'Census Tract 129.06, Genesee County, Michigan', NULL), ('CensusZipCodeTabulationArea', NULL, 'zip/58327', NULL, NULL, NULL, '58327', NULL), ('CensusTract', NULL, 'geoId/55089610101', NULL, NULL, NULL, 'Census Tract 6101.01, Ozaukee County, Wisconsin', NULL), ('CensusZipCodeTabulationArea', NULL, 'zip/78340', NULL, NULL, NULL, '78340', NULL);
-- DBMS: snowflake
CREATE TABLE WEATHER__ENVIRONMENT.CYBERSYN.OUR_WORLD_IN_DATA_ATTRIBUTES (
    UNIT TEXT,
    VARIABLE TEXT,
    MEASURE TEXT,
    VARIABLE_NAME TEXT,
    FREQUENCY TEXT,
    OUR_WORLD_IN_DATA_CHARTS ARRAY
);

INSERT INTO "WEATHER__ENVIRONMENT"."CYBERSYN"."OUR_WORLD_IN_DATA_ATTRIBUTES" (UNIT, VARIABLE, MEASURE, VARIABLE_NAME, FREQUENCY, OUR_WORLD_IN_DATA_CHARTS) VALUES ('Tonnes of CO₂ equivalents', 'annual_methane_emissions_in_co2_equivalents', 'Methane Emissions', 'Annual methane emissions in CO2 equivalents', 'Annual', '[
  "methane-emissions"
]'), ('Percent', 'share_of_global_cumulative_co2_emissions_including_land-use_change', 'Carbon Dioxide Emissions', 'Share of global cumulative CO2 emissions including land-use change', 'Annual', '[
  "share-global-cumulative-co2-including-land"
]'), ('Percent', 'share_of_global_cumulative_co2_emissions_from_oil', 'Carbon Dioxide Emissions', 'Share of global cumulative CO2 emissions from oil', 'Annual', '[
  "share-cumulative-co2-oil"
]'), ('Tonnes', 'nitrous_oxide_emissions_from_waste', 'Nitrous Oxide Emissions', 'Nitrous oxide emissions from waste', 'Annual', '[
  "nitrous-oxide-emissions-by-sector"
]'), ('Tonnes', 'deforestation_co2_trade_by_product_sugar', 'Deforestation CO2 Trade by Product: Sugar', 'Deforestation CO2 Trade by Product: Sugar', 'Annual', '[
  "deforestation-co2-trade-by-product"
]');
-- DBMS: snowflake
CREATE TABLE WEATHER__ENVIRONMENT.CYBERSYN.EIA_ENERGY_ATTRIBUTES (
    REPORT TEXT,
    SECTOR TEXT,
    MEASURE TEXT,
    FREQUENCY TEXT,
    UNIT TEXT,
    VARIABLE_NAME TEXT,
    ENERGY_TYPE TEXT,
    VARIABLE TEXT
);

INSERT INTO "WEATHER__ENVIRONMENT"."CYBERSYN"."EIA_ENERGY_ATTRIBUTES" (REPORT, SECTOR, MEASURE, FREQUENCY, UNIT, VARIABLE_NAME, ENERGY_TYPE, VARIABLE) VALUES ('EIA petroleum gas survey data', NULL, 'Net Receipts', 'Monthly', 'MBBL per day', 'Net Receipts by Pipeline, Tanker, Barge and Rail of Residual Fuel Oil, 0.31 to 1.00% Sulfur, MBBL per day (Monthly)', 'Petroleum', 'net_receipts_by_pipeline_tanker_barge_and_rail_of_residual_fuel_oil_031_to_100_sulfur_mbbl_per_day_monthly'), ('EIA petroleum gas survey data', NULL, 'Through Company Outlets Price', 'Monthly', 'USD per gallon', 'Premium Gasoline Through Company Outlets Price by Refiners and Gas Plants, USD per gallon (Monthly)', 'Petroleum', 'premium_gasoline_through_company_outlets_price_by_refiners_and_gas_plants_usd_per_gallon_monthly'), ('EIA petroleum gas survey data', NULL, 'Rack Sales Price', 'Monthly', 'USD per gallon', 'Conventional Premium Gasoline Rack Sales Price by Refiners and Gas Plants, USD per gallon (Monthly)', 'Petroleum', 'conventional_premium_gasoline_rack_sales_price_by_refiners_and_gas_plants_usd_per_gallon_monthly'), ('EIA petroleum gas survey data', NULL, 'Wholesale/Resale Volume', 'Monthly', 'MGAL per day', 'Residual Fuel Oil, Greater Than 1% Sulfur Wholesale/Resale Volume by Refiners and Gas Plants, MGAL per day (Monthly)', 'Petroleum', 'residual_fuel_oil_greater_than_1_sulfur_wholesale/resale_volume_by_refiners_and_gas_plants_mgal_per_day_monthly'), ('EIA petroleum gas survey data', NULL, 'Landed Costs', 'Monthly', 'USD per barrel', 'US Landed Costs of UK Brent Crude Oil, USD per barrel (Monthly)', 'Petroleum', 'us_landed_costs_of_uk_brent_crude_oil_usd_per_barrel_monthly');
-- DBMS: snowflake
CREATE TABLE WEATHER__ENVIRONMENT.CYBERSYN.NOAA_WEATHER_METRICS_TIMESERIES (
    VARIABLE TEXT,
    VALUE NUMBER,
    NOAA_WEATHER_STATION_ID TEXT,
    DATE DATE,
    DATETIME TIMESTAMP_NTZ,
    UNIT TEXT,
    VARIABLE_NAME TEXT
);

INSERT INTO "WEATHER__ENVIRONMENT"."CYBERSYN"."NOAA_WEATHER_METRICS_TIMESERIES" (VARIABLE, VALUE, NOAA_WEATHER_STATION_ID, DATE, DATETIME, UNIT, VARIABLE_NAME) VALUES ('precipitation', '0.000000', 'US1ALSH0043', '2012-09-10', '2012-09-10 00:00:00', 'Millimeters', 'Precipitation'), ('precipitation', '0.800000', 'USW00094994', '2023-04-03', '2023-04-03 00:00:00', 'Millimeters', 'Precipitation'), ('minimum_temperature', '-5.100000', 'USS0011C01S', '2008-11-28', '2008-11-28 00:00:00', 'Degrees Celsius', 'Minimum Temperature'), ('snow_depth', '351.000000', 'RSM00028275', '2004-03-25', '2004-03-25 00:00:00', 'Millimeters', 'Snow Depth'), ('direction_of_fastest_2_minute_wind', '210.000000', 'USW00093720', '2011-04-20', '2011-04-20 00:00:00', 'Degrees', 'Direction of Fastest 2-Minute Wind');
-- DBMS: snowflake
CREATE TABLE WEATHER__ENVIRONMENT.CYBERSYN.CLIMATE_WATCH_ATTRIBUTES (
    VARIABLE_NAME TEXT,
    EMISSION_TYPE TEXT,
    SCENARIO TEXT,
    SECTOR TEXT,
    FREQUENCY TEXT,
    UNIT TEXT,
    SOURCE TEXT,
    VARIABLE TEXT,
    MEASURE TEXT
);

INSERT INTO "WEATHER__ENVIRONMENT"."CYBERSYN"."CLIMATE_WATCH_ATTRIBUTES" (VARIABLE_NAME, EMISSION_TYPE, SCENARIO, SECTOR, FREQUENCY, UNIT, SOURCE, VARIABLE, MEASURE) VALUES ('Industry | Energy Use by Fuel | Biomass | Scenario: Energy Innovation Recommended_x | Model: Energy Policy Simulator, United States', 'Biomass', 'Energy Innovation Recommended_x', 'Industry', 'Annual', 'Exajoule', 'Energy Policy Simulator, United States', 'industry_energy_use_by_fuel_biomassenergy_innovation_recommended_xenergy_policy_simulator_united_states', 'Energy Use by Fuel'), ('Industry | Energy Use by Fuel | Electricity | Scenario: Consumer Activism | Model: Global Calculator', 'Electricity', 'Consumer Activism', 'Industry', 'Annual', 'Exajoule', 'Global Calculator', 'industry_energy_use_by_fuel_electricityconsumer_activismglobal_calculator', 'Energy Use by Fuel'), ('Industry | Energy Use by Fuel | Electricity | Scenario: Doesn''t tackle climate change | Model: 2050 Pathways Calculator', 'Electricity', 'Doesn''t tackle climate change', 'Industry', 'Annual', 'Exajoule', '2050 Pathways Calculator', 'industry_energy_use_by_fuel_electricitydoesn''t_tackle_climate_change2050_pathways_calculator', 'Energy Use by Fuel'), ('Industry | Mining industry Pollutants | PM2.5 | Scenario: Conditional NDC | Model: Energy Policy Simulator, Mexico', 'PM2.5', 'Conditional NDC', 'Industry', 'Annual', 'Tonnes', 'Energy Policy Simulator, Mexico', 'industry_mining_industry_pollutants_pm2.5conditional_ndcenergy_policy_simulator_mexico', 'Mining industry Pollutants'), ('Industry | Mining industry Pollutants | Sulfur oxides (SOx) | Scenario: Energy Innovation Recommended_x | Model: Energy Policy Simulator, United States', 'Sulfur oxides (SOx)', 'Energy Innovation Recommended_x', 'Industry', 'Annual', 'Tonnes', 'Energy Policy Simulator, United States', 'industry_mining_industry_pollutants_soxenergy_innovation_recommended_xenergy_policy_simulator_united_states', 'Mining industry Pollutants');
-- DBMS: snowflake
CREATE TABLE WEATHER__ENVIRONMENT.CYBERSYN.NOAA_WEATHER_STATION_INDEX (
    NOAA_WEATHER_STATION_NAME TEXT,
    LATITUDE FLOAT,
    ZIP_NAME TEXT,
    COUNTRY_GEO_ID TEXT,
    WORLD_METEOROLOGICAL_ORGANIZATION_ID TEXT,
    ZIP_GEO_ID TEXT,
    SOURCE_DATA ARRAY,
    STATE_GEO_ID TEXT,
    ELEVATION FLOAT,
    NOAA_WEATHER_STATION_ID TEXT,
    WEATHER_STATION_NETWORK TEXT,
    COUNTRY_NAME TEXT,
    ASSOCIATED_NETWORKS ARRAY,
    LONGITUDE FLOAT,
    STATE_NAME TEXT
);

INSERT INTO "WEATHER__ENVIRONMENT"."CYBERSYN"."NOAA_WEATHER_STATION_INDEX" (NOAA_WEATHER_STATION_NAME, LATITUDE, ZIP_NAME, COUNTRY_GEO_ID, WORLD_METEOROLOGICAL_ORGANIZATION_ID, ZIP_GEO_ID, SOURCE_DATA, STATE_GEO_ID, ELEVATION, NOAA_WEATHER_STATION_ID, WEATHER_STATION_NETWORK, COUNTRY_NAME, ASSOCIATED_NETWORKS, LONGITUDE, STATE_NAME) VALUES ('HAYWARD 9.6 E', 46.0296, '54843', 'country/USA', NULL, 'zip/54843', '[
  "Community Collaborative Rain, Hail, and Snow (CoCoRaHS)"
]', 'geoId/55', 424.0, 'US1WISR0011', 'Community Collaborative Rain, Hail, and Snow (CoCoRaHS)-Based ID', 'United States', NULL, -91.2818, 'Wisconsin'), ('SELMA 13 WNW', 32.4567, '36759', 'country/USA', NULL, 'zip/36759', '[
  "NCEI Reference Network Database (Climate Reference Network and Regional Climate Reference Network)"
]', 'geoId/01', 58.8, 'USW00063858', 'Weather Bureau Army Navy ID', 'United States', '[
  "CRN"
]', -87.2422, 'Alabama'), ('MANY', 31.5769, '71449', 'country/USA', NULL, 'zip/71449', '[
  "U.S. Cooperative Summary of the Day (NCDC DSI-3200)",
  "U.S. Cooperative Summary of the Day -- Transmitted via WxCoder3 (NCDC DSI-3207)"
]', 'geoId/22', 77.7, 'USC00165892', 'U.S. Cooperative Network ID', 'United States', NULL, -93.4817, 'Louisiana'), ('PILOT KNOB 2', 37.6206, '63650', 'country/USA', NULL, 'zip/63650', '[
  "U.S. Cooperative Summary of the Day -- Transmitted via WxCoder3 (NCDC DSI-3207)"
]', 'geoId/29', 289.6, 'USC00236688', 'U.S. Cooperative Network ID', 'United States', NULL, -90.6389, 'Missouri'), ('CAPE CHARLES 5 ENE', 37.2908, '23310', 'country/USA', NULL, 'zip/23310', '[
  "NCEI Reference Network Database (Climate Reference Network and Regional Climate Reference Network)"
]', 'geoId/51', 8.8, 'USW00003739', 'Weather Bureau Army Navy ID', 'United States', '[
  "CRN"
]', -75.9269, 'Virginia');
-- DBMS: snowflake
create or replace TABLE INTERNATIONAL_TOP_TERMS (
	"term" VARCHAR(16777216),
	"refresh_date" DATE,
	"region_code" VARCHAR(16777216),
	"country_code" VARCHAR(16777216),
	"region_name" VARCHAR(16777216),
	"week" DATE,
	"score" NUMBER(38,0),
	"rank" NUMBER(38,0),
	"country_name" VARCHAR(16777216)
);

INSERT INTO "GOOGLE_TRENDS"."GOOGLE_TRENDS"."INTERNATIONAL_TOP_TERMS" (week, term, rank, score, refresh_date, region_code, region_name, country_code, country_name) VALUES ('2022-03-13', 'Galatasaray  PAOK', 14, NULL, '2024-09-28', 'TR-39', 'Kırklareli', 'TR', 'Turkey'), ('2022-11-13', 'Galatasaray  PAOK', 14, NULL, '2024-09-28', 'TR-39', 'Kırklareli', 'TR', 'Turkey'), ('2023-01-01', 'Galatasaray  PAOK', 14, NULL, '2024-09-28', 'TR-39', 'Kırklareli', 'TR', 'Turkey'), ('2023-01-15', 'Galatasaray  PAOK', 14, NULL, '2024-09-28', 'TR-39', 'Kırklareli', 'TR', 'Turkey'), ('2023-04-02', 'Galatasaray  PAOK', 14, NULL, '2024-09-28', 'TR-39', 'Kırklareli', 'TR', 'Turkey');
-- DBMS: snowflake
create or replace TABLE INTERNATIONAL_TOP_RISING_TERMS (
	"percent_gain" NUMBER(38,0),
	"region_name" VARCHAR(16777216),
	"term" VARCHAR(16777216),
	"week" DATE,
	"score" NUMBER(38,0),
	"refresh_date" DATE,
	"country_name" VARCHAR(16777216),
	"country_code" VARCHAR(16777216),
	"region_code" VARCHAR(16777216),
	"rank" NUMBER(38,0)
);

INSERT INTO "GOOGLE_TRENDS"."GOOGLE_TRENDS"."INTERNATIONAL_TOP_RISING_TERMS" (rank, region_name, refresh_date, region_code, term, week, country_name, percent_gain, country_code, score) VALUES (10, 'Sibiu', '2024-09-17', 'RO-SB', 'gigi multescu', '2021-03-07', 'Romania', 3500, 'RO', NULL), (10, 'Sibiu', '2024-09-17', 'RO-SB', 'gigi multescu', '2021-04-04', 'Romania', 3500, 'RO', NULL), (10, 'Sibiu', '2024-09-17', 'RO-SB', 'gigi multescu', '2021-05-16', 'Romania', 3500, 'RO', NULL), (10, 'Sibiu', '2024-09-17', 'RO-SB', 'gigi multescu', '2021-05-23', 'Romania', 3500, 'RO', NULL), (10, 'Sibiu', '2024-09-17', 'RO-SB', 'gigi multescu', '2021-09-19', 'Romania', 3500, 'RO', NULL);
-- DBMS: snowflake
create or replace TABLE TOP_TERMS (
	"dma_name" VARCHAR(16777216),
	"dma_id" NUMBER(38,0),
	"term" VARCHAR(16777216),
	"week" DATE,
	"score" NUMBER(38,0),
	"rank" NUMBER(38,0),
	"refresh_date" DATE
);

INSERT INTO "GOOGLE_TRENDS"."GOOGLE_TRENDS"."TOP_TERMS" (week, term, rank, score, refresh_date, dma_id, dma_name) VALUES ('2019-11-17', 'AC Milan', 23, NULL, '2024-09-28', 500, 'Portland-Auburn ME'), ('2019-12-15', 'AC Milan', 23, NULL, '2024-09-28', 500, 'Portland-Auburn ME'), ('2020-02-02', 'AC Milan', 23, NULL, '2024-09-28', 500, 'Portland-Auburn ME'), ('2020-02-09', 'AC Milan', 23, NULL, '2024-09-28', 500, 'Portland-Auburn ME'), ('2020-03-22', 'AC Milan', 23, NULL, '2024-09-28', 500, 'Portland-Auburn ME');
-- DBMS: snowflake
create or replace TABLE TOP_RISING_TERMS (
	"dma_id" NUMBER(38,0),
	"term" VARCHAR(16777216),
	"week" DATE,
	"score" NUMBER(38,0),
	"rank" NUMBER(38,0),
	"percent_gain" NUMBER(38,0),
	"refresh_date" DATE,
	"dma_name" VARCHAR(16777216)
);

INSERT INTO "GOOGLE_TRENDS"."GOOGLE_TRENDS"."TOP_RISING_TERMS" (refresh_date, rank, dma_name, score, week, percent_gain, term, dma_id) VALUES ('2024-09-17', 13, 'Portland-Auburn ME', NULL, '2019-09-15', 1650, '49ers vs vikings', 500), ('2024-09-17', 13, 'Portland-Auburn ME', NULL, '2019-11-17', 1650, '49ers vs vikings', 500), ('2024-09-17', 13, 'Portland-Auburn ME', NULL, '2019-11-24', 1650, '49ers vs vikings', 500), ('2024-09-17', 13, 'Portland-Auburn ME', NULL, '2019-12-29', 1650, '49ers vs vikings', 500), ('2024-09-17', 13, 'Portland-Auburn ME', NULL, '2020-01-19', 1650, '49ers vs vikings', 500);
-- DBMS: snowflake
create or replace TABLE LANGUAGES (
	"repo_name" VARCHAR(16777216),
	"language" VARIANT
);

INSERT INTO "GITHUB_REPOS"."GITHUB_REPOS"."LANGUAGES" (repo_name, language) VALUES ('debjyoti385/awesome-data-mining-datasets', '[]'), ('graidl/test', '[]'), ('iBeacons/grape', '[]'), ('swapnil-pimpale/geep-kernel-training', '[]'), ('TheEvilDev/atom-yeoman', '[]');
-- DBMS: snowflake
create or replace TABLE SAMPLE_REPOS (
	"repo_name" VARCHAR(16777216),
	"watch_count" NUMBER(38,0)
);

INSERT INTO "GITHUB_REPOS"."GITHUB_REPOS"."SAMPLE_REPOS" (watch_count, repo_name) VALUES (256, 'kbandla/APTnotes'), (256, 'bigcompany/hook.io'), (256, 'krisk/Fuse'), (256, 'brigade/react-waypoint'), (256, 'Quartz/mapquery');
-- DBMS: snowflake
create or replace TABLE SAMPLE_FILES (
	"repo_name" VARCHAR(16777216),
	"ref" VARCHAR(16777216),
	"path" VARCHAR(16777216),
	"mode" NUMBER(38,0),
	"id" VARCHAR(16777216),
	"symlink_target" VARCHAR(16777216)
);

INSERT INTO "GITHUB_REPOS"."GITHUB_REPOS"."SAMPLE_FILES" (symlink_target, id, mode, path, repo_name, ref) VALUES (NULL, '64ba26a4afe649818a23565fc4ae6631eaf9d9b1', 33188, 'drivers/isdn/hisax/elsa.c', 'dorimanx/DORIMANX_LG_STOCK_LP_KERNEL', 'refs/heads/master'), (NULL, 'b802f285fe00e6dd3b39af77e3b351d3a4343316', 33188, 'arch/arm/mach-pxa/include/mach/smemc.h', 'dorimanx/DORIMANX_LG_STOCK_LP_KERNEL', 'refs/heads/master'), (NULL, 'c811289b61e21628f28d79b71f27651c39e3e024', 33188, 'drivers/i2c/busses/i2c-eg20t.c', 'dorimanx/DORIMANX_LG_STOCK_LP_KERNEL', 'refs/heads/master'), (NULL, 'b06224a692b9bc255c860f959b7fe5913e957852', 33188, 'arch/arm/mm/proc-arm920.S', 'dorimanx/DORIMANX_LG_STOCK_LP_KERNEL', 'refs/heads/master'), (NULL, 'b699610f51077fda4568a25d8506c69d7a345658', 33188, 'drivers/video/msm/lcdc_external.c', 'dorimanx/DORIMANX_LG_STOCK_LP_KERNEL', 'refs/heads/master');
-- DBMS: snowflake
create or replace TABLE LICENSES (
	"repo_name" VARCHAR(16777216),
	"license" VARCHAR(16777216)
);

INSERT INTO "GITHUB_REPOS"."GITHUB_REPOS"."LICENSES" (repo_name, license) VALUES ('npm/npmconf', 'isc'), ('live627/shiny-bear', 'isc'), ('k7hoven/spexcript', 'isc'), ('photofroggy/Reflex', 'isc'), ('sr-cafe/topisto', 'isc');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.POINT_OF_INTEREST_ADDRESSES_RELATIONSHIPS (
    RELATIONSHIP_TYPE TEXT,
    POI_ID TEXT,
    RELATIONSHIP_START_DATE DATE,
    RELATIONSHIP_END_DATE DATE,
    ADDRESS_ID TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."POINT_OF_INTEREST_ADDRESSES_RELATIONSHIPS" (RELATIONSHIP_TYPE, POI_ID, RELATIONSHIP_START_DATE, RELATIONSHIP_END_DATE, ADDRESS_ID) VALUES ('Overlaps', '08f2a100d2c8339a03800511a0e262db', NULL, NULL, 'addressId/f5b7341c99d6fb3b021b81e2b1440534'), ('Overlaps', '08f44f69346b2d180329f2842dadd97f', NULL, NULL, 'addressId/f292c542fb15aea917efc820024f7f59'), ('Overlaps', '08f444658991457103a40df7d19158a8', NULL, NULL, 'addressId/be401329734185e3737194a6270c0ca3'), ('Overlaps', '08f2a93158a44176039c10b29a8591ca', NULL, NULL, 'addressId/8e9f346e8be0edbb3d3c70118c92d41f'), ('Overlaps', '08f2758d6a55c146031a544fd081a425', NULL, NULL, 'addressId/aecb4f044fac1440c914b9dea833a24c');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.IRS_INDIVIDUAL_INCOME_TIMESERIES (
    SUPPRESSED BOOLEAN,
    DATE DATE,
    VARIABLE TEXT,
    VARIABLE_NAME TEXT,
    GEO_ID TEXT,
    UNIT TEXT,
    VALUE FLOAT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."IRS_INDIVIDUAL_INCOME_TIMESERIES" (SUPPRESSED, DATE, VARIABLE, VARIABLE_NAME, GEO_ID, UNIT, VALUE) VALUES (False, '2018-12-31', 'Total_income_-_Amount,_AGI_bin:_$100,000_under_$200,000', 'Total income - Amount, AGI bin: $100,000 under $200,000', 'zip/47578', 'USD', 5096000.0), (False, '2011-12-31', 'Total_taxes_paid_-_Number_of_returns,_AGI_bin:_$100,000_under_$200,000', 'Total taxes paid - Number of returns, AGI bin: $100,000 under $200,000', 'zip/88337', 'Returns', 69.0), (False, '2017-12-31', 'Total_premium_tax_credit_-_Amount,_AGI_bin:_$100,000_under_$200,000', 'Total premium tax credit - Amount, AGI bin: $100,000 under $200,000', 'zip/50167', 'USD', 0.0), (True, '2017-12-31', 'Taxable_income_-_Amount,_AGI_bin:_$200,000_or_more', 'Taxable income - Amount, AGI bin: $200,000 or more', 'zip/50543', 'USD', nan), (False, '2017-12-31', 'Child_tax_credit_-_Amount,_AGI_bin:_$75,000_under_$100,000', 'Child tax credit - Amount, AGI bin: $75,000 under $100,000', 'zip/50643', 'USD', 128000.0);
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FREDDIE_MAC_HOUSING_ATTRIBUTES (
    VARIABLE_NAME TEXT,
    VARIABLE TEXT,
    UNIT TEXT,
    FREQUENCY TEXT,
    MEASURE TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FREDDIE_MAC_HOUSING_ATTRIBUTES" (VARIABLE_NAME, VARIABLE, UNIT, FREQUENCY, MEASURE) VALUES ('Freddie Mac House Price Index (Not seasonally adjusted)', 'INDEX_NSA', 'Index', 'Monthly', 'Housing Prices'), ('Freddie Mac House Price Index (Seasonally adjusted)', 'INDEX_SA', 'Index', 'Monthly', 'Housing Prices'), ('30-Year Fixed Rate Mortgage Rate, National Average', 'FRM_30_YR', 'Percent', 'Weekly', 'Mortgage Rates'), ('30-Year Fixed Rate Mortgage Fees & Points, National Average', 'FRM_30_YR_FEES_POINTS', 'Percent', 'Weekly', 'Mortgage Rates'), ('15-Year Fixed Rate Mortgage Rate, National Average', 'FRM_15_YR', 'Percent', 'Weekly', 'Mortgage Rates');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FHFA_HOUSE_PRICE_ATTRIBUTES (
    PROPERTY_CLASSIFICATION TEXT,
    VARIABLE_NAME TEXT,
    SEASONALLY_ADJUSTED BOOLEAN,
    INDEX_TYPE TEXT,
    VARIABLE TEXT,
    FREQUENCY TEXT,
    UNIT TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FHFA_HOUSE_PRICE_ATTRIBUTES" (PROPERTY_CLASSIFICATION, VARIABLE_NAME, SEASONALLY_ADJUSTED, INDEX_TYPE, VARIABLE, FREQUENCY, UNIT) VALUES ('traditional', 'FHFA_HPI traditional purchase-only monthly Not Seasonally Adjusted', False, 'purchase-only', 'FHFA_HPI_traditional_purchase-only_monthly_NSA', 'MONTHLY', 'Index'), ('traditional', 'FHFA_HPI traditional purchase-only quarterly Not Seasonally Adjusted', False, 'purchase-only', 'FHFA_HPI_traditional_purchase-only_quarterly_NSA', 'QUARTERLY', 'Index'), ('traditional', 'FHFA_HPI traditional purchase-only monthly Seasonally Adjusted', True, 'purchase-only', 'FHFA_HPI_traditional_purchase-only_monthly_SA', 'MONTHLY', 'Index'), ('non-metro', 'FHFA_HPI non-metro all-transactions quarterly Not Seasonally Adjusted', False, 'all-transactions', 'FHFA_HPI_non-metro_all-transactions_quarterly_NSA', 'QUARTERLY', 'Index'), ('traditional', 'FHFA_HPI traditional purchase-only quarterly Seasonally Adjusted', True, 'purchase-only', 'FHFA_HPI_traditional_purchase-only_quarterly_SA', 'QUARTERLY', 'Index');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.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 "US_REAL_ESTATE"."CYBERSYN"."FHFA_UNIFORM_APPRAISAL_ATTRIBUTES" (VARIABLE_GROUP, VARIABLE_NAME, CATEGORY, CHARACTERISTIC, UNIT, APPRAISAL_PURPOSE, FREQUENCY, VARIABLE) VALUES ('Mean Ratio Contract Price/Appraised Value', 'Annual Mean Ratio Contract Price/Appraised Value Type of Heating Purchase Other', 'Other', 'Type of Heating', 'Ratio', 'Purchase', 'Annual', 'Annual_Mean_Ratio_Contract_Price/Appraised_Value_Type_of_Heating_Purchase_Other'), ('Mean Ratio Contract Price/Appraised Value', 'Annual Mean Ratio Contract Price/Appraised Value Type of Structure Purchase Missing', 'Missing', 'Type of Structure', 'Ratio', 'Purchase', 'Annual', 'Annual_Mean_Ratio_Contract_Price/Appraised_Value_Type_of_Structure_Purchase_Missing'), ('Mean Ratio Contract Price/Appraised Value', 'Annual Mean Ratio Contract Price/Appraised Value Urbanization Level Purchase Rural', 'Rural', 'Urbanization Level', 'Ratio', 'Purchase', 'Annual', 'Annual_Mean_Ratio_Contract_Price/Appraised_Value_Urbanization_Level_Purchase_Rural'), ('Mean Ratio Contract Price/Appraised Value', 'Annual Mean Ratio Contract Price/Appraised Value Year Built Purchase 2010 to current', '2010 to current', 'Year Built', 'Ratio', 'Purchase', 'Annual', 'Annual_Mean_Ratio_Contract_Price/Appraised_Value_Year_Built_Purchase_2010_to_current'), ('Median Appraised Value', 'Annual Median Appraised Value Accessory Dwelling Unit Present Purchase & Refinance No', 'No', 'Accessory Dwelling Unit Present', 'USD', 'Purchase & Refinance', 'Annual', 'Annual_Median_Appraised_Value_Accessory_Dwelling_Unit_Present_Purchase_&_Refinance_No');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.IRS_MIGRATION_BY_CHARACTERISTIC_TIMESERIES (
    VARIABLE_NAME TEXT,
    VARIABLE TEXT,
    UNIT TEXT,
    DATE DATE,
    VALUE NUMBER,
    GEO_ID TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."IRS_MIGRATION_BY_CHARACTERISTIC_TIMESERIES" (VARIABLE_NAME, VARIABLE, UNIT, DATE, VALUE, GEO_ID) VALUES ('Outflow Returns - number of returns, primary taxpayers ages 35 under 45, All AGI classes', 'Outflow_Returns_-_number_of_returns,_primary_taxpayers_ages_35_under_45,_All_AGI_classes', 'Returns', '2022-12-31', 17022, 'geoId/24'), ('Outflow Returns – adjusted gross income from Year 2, primary taxpayers ages 26 under 35, AGI bin: $50,000 under $75,000', 'Outflow_Returns_–_adjusted_gross_income_from_Year_2,_primary_taxpayers_ages_26_under_35,_AGI_bin:_$50,000_under_$75,000', 'USD', '2014-12-31', 61403000, 'geoId/02'), ('Total Returns - number of returns, primary taxpayers ages 26 under, All AGI classes', 'Total_Returns_-_number_of_returns,_primary_taxpayers_ages_26_under,_All_AGI_classes', 'Returns', '2019-12-31', 141322, 'geoId/35'), ('Same State Returns – number of individuals, primary taxpayers ages 45 under 55, AGI bin: $25,000 under $50,000', 'Same_State_Returns_–_number_of_individuals,_primary_taxpayers_ages_45_under_55,_AGI_bin:_$25,000_under_$50,000', 'Individuals', '2018-12-31', 8097, 'geoId/26'), ('Inflow Returns – adjusted gross income from Year 2, primary taxpayers ages 26 under 35, AGI bin: $50,000 under $75,000', 'Inflow_Returns_–_adjusted_gross_income_from_Year_2,_primary_taxpayers_ages_26_under_35,_AGI_bin:_$50,000_under_$75,000', 'USD', '2019-12-31', 296221000, 'geoId/47');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.US_REAL_ESTATE_TIMESERIES (
    GEO_ID TEXT,
    UNIT TEXT,
    VARIABLE_NAME TEXT,
    DATE DATE,
    VALUE NUMBER,
    VARIABLE TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."US_REAL_ESTATE_TIMESERIES" (GEO_ID, UNIT, VARIABLE_NAME, DATE, VALUE, VARIABLE) VALUES ('geoId/47157', 'Count', 'Three- and Four-Family Buildings units: Estimates With Imputation (Monthly, Year-to-Date)', '2008-02-29', '8.00000000', 'UNITS_3_4_UNITS_M_YTD'), ('geoId/C27100', 'Count', 'Five-or-More Family Buildings: Estimates With Imputation (Monthly, Current Month)', '2012-09-30', '0E-8', 'BLDGS_5_UNITS_M'), ('geoId/17135', 'Count', 'Five-or-More Family Buildings units reported: Reported Only Data (Monthly, Current Month)', '2024-06-30', '0E-8', 'UNITS_5_UNITS_REP_M'), ('geoId/17163', 'Count', 'Five-or-More Family Buildings: Estimates With Imputation (Monthly, Year-to-Date)', '2003-03-31', '0E-8', 'BLDGS_5_UNITS_M_YTD'), ('geoId/17097', 'Count', 'Three- and Four-Family Buildings reported: Reported Only Data (Monthly, Current Month)', '2018-03-31', '0E-8', 'BLDGS_3_4_UNITS_REP_M');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.USPS_ADDRESS_CHANGE_ATTRIBUTES (
    VARIABLE_NAME TEXT,
    UNIT TEXT,
    REQUEST_TYPE TEXT,
    MEASURE TEXT,
    FREQUENCY TEXT,
    VARIABLE TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."USPS_ADDRESS_CHANGE_ATTRIBUTES" (VARIABLE_NAME, UNIT, REQUEST_TYPE, MEASURE, FREQUENCY, VARIABLE) VALUES ('Inbound Address Changes, Permanent', 'Count', 'Permanent', 'Inbound Address Changes', 'Month', 'inbound_address_changes_permanent'), ('Inbound Address Changes, Total', 'Count', 'Total', 'Inbound Address Changes', 'Month', 'inbound_address_changes_total'), ('Inbound Address Changes, Businesses', 'Count', 'Businesses', 'Inbound Address Changes', 'Month', 'inbound_address_changes_businesses'), ('Net Address Changes, Individuals', 'Count', 'Individuals', 'Net Address Changes', 'Month', 'net_address_changes_individuals'), ('Outbound Address Changes, Temporary', 'Count', 'Temporary', 'Outbound Address Changes', 'Month', 'outbound_address_changes_temporary');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FHFA_MORTGAGE_PERFORMANCE_ATTRIBUTES (
    VARIABLE_GROUP TEXT,
    UNIT TEXT,
    FREQUENCY TEXT,
    VARIABLE TEXT,
    MARKET TEXT,
    VARIABLE_NAME TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FHFA_MORTGAGE_PERFORMANCE_ATTRIBUTES" (VARIABLE_GROUP, UNIT, FREQUENCY, VARIABLE, MARKET, VARIABLE_NAME) VALUES ('Percent 90 to 180 Days Past Due Date', 'Percent', 'Quarterly', 'Percent_90_to_180_Days_Past_Due_Date_Other Conventional Market', 'Other Conventional Market', 'Percent 90 to 180 Days Past Due Date - Other Conventional Market'), ('Percent 30 or 60 Days Past Due Date', 'Percent', 'Quarterly', 'Percent_30_or_60_Days_Past_Due_Date_Government / Non-Conventional', 'Government / Non-Conventional', 'Percent 30 or 60 Days Past Due Date - Government / Non-Conventional'), ('Percent in Forbearance', 'Percent', 'Quarterly', 'Percent_in_Forbearance_Government / Non-Conventional', 'Government / Non-Conventional', 'Percent in Forbearance - Government / Non-Conventional'), ('Percent in Forbearance', 'Percent', 'Quarterly', 'Percent_in_Forbearance_Other Conventional Market', 'Other Conventional Market', 'Percent in Forbearance - Other Conventional Market'), ('Percent 90 to 180 Days Past Due Date', 'Percent', 'Quarterly', 'Percent_90_to_180_Days_Past_Due_Date_Enterprise Acquisitions', 'Enterprise Acquisitions', 'Percent 90 to 180 Days Past Due Date - Enterprise Acquisitions');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.GEOGRAPHY_RELATIONSHIPS (
    RELATED_GEO_NAME TEXT,
    RELATED_LEVEL TEXT,
    RELATED_GEO_ID TEXT,
    RELATIONSHIP_TYPE TEXT,
    GEO_ID TEXT,
    GEO_NAME TEXT,
    LEVEL TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."GEOGRAPHY_RELATIONSHIPS" (RELATED_GEO_NAME, RELATED_LEVEL, RELATED_GEO_ID, RELATIONSHIP_TYPE, GEO_ID, GEO_NAME, LEVEL) VALUES ('72414', 'CensusZipCodeTabulationArea', 'zip/72414', 'Overlaps', 'geoId/0506610', 'Black Oak', 'City'), ('Block Group 5; Census Tract 9506; Ouachita County; Arkansas', 'CensusBlockGroup', 'censusBlockGroup/051039506005', 'Contains', 'geoId/05103950600', 'Census Tract 9506, Ouachita County, Arkansas', 'CensusTract'), ('Block Group 2, Census Tract 701, McDonald County, Missouri', 'CensusBlockGroup', 'censusBlockGroup/291190701002', 'Contains', 'geoId/29119070100', 'Census Tract 701, McDonald County, Missouri', 'CensusTract'), ('Millstadt Township', 'City', 'geoId/1749399', 'Contains', 'geoId/17', 'Illinois', 'State'), ('Block Group 4, Census Tract 216.15, Denton County, Texas', 'CensusBlockGroup', 'censusBlockGroup/481210216154', 'Contains', 'geoId/48121', 'Denton County', 'County');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FHFA_UNIFORM_APPRAISAL_TIMESERIES (
    UNIT TEXT,
    VARIABLE_NAME TEXT,
    GEO_ID TEXT,
    VARIABLE TEXT,
    SUPPRESSED BOOLEAN,
    VALUE FLOAT,
    DATE DATE
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FHFA_UNIFORM_APPRAISAL_TIMESERIES" (UNIT, VARIABLE_NAME, GEO_ID, VARIABLE, SUPPRESSED, VALUE, DATE) VALUES ('USD', 'Quarterly 75% Quartile of Appraised Value Number of Stories Purchase & Refinance More than 1 Story', 'geoId/36', 'Quarterly_75%_Quartile_of_Appraised_Value_Number_of_Stories_Purchase_&_Refinance_More_than_1_Story', False, 695000.0, '2020-09-30'), ('USD', 'Quarterly 25% Quartile of Appraised Value Updated in the last 15 years Purchase Yes', 'geoId/C31140', 'Quarterly_25%_Quartile_of_Appraised_Value_Updated_in_the_last_15_years_Purchase_Yes', False, 139000.0, '2016-09-30'), ('Percent', 'Quarterly Mean Comps Adjustment Percent Number of Bathrooms Above Grade Purchase & Refinance 2 Full Bathrooms', 'geoId/C37100', 'Quarterly_Mean_Comps_Adjustment_Percent_Number_of_Bathrooms_Above_Grade_Purchase_&_Refinance_2_Full_Bathrooms', False, -0.007, '2015-06-30'), ('USD', 'Quarterly Mean Appraised Value Duty to Serve Rural Area Purchase Rural', 'geoId/C49180', 'Quarterly_Mean_Appraised_Value_Duty_to_Serve_Rural_Area_Purchase_Rural', False, 190500.0, '2018-06-30'), ('Count', 'Annual Count of Appraisals Purchase & Refinance All Appraisals', 'geoId/06007001602', 'Annual_Count_of_Appraisals_Purchase_&_Refinance_All_Appraisals', False, 86.0, '2015-12-31');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FHFA_HOUSE_PRICE_TIMESERIES (
    VALUE NUMBER,
    UNIT TEXT,
    DATE DATE,
    GEO_ID TEXT,
    VARIABLE TEXT,
    VARIABLE_NAME TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FHFA_HOUSE_PRICE_TIMESERIES" (VALUE, UNIT, DATE, GEO_ID, VARIABLE, VARIABLE_NAME) VALUES ('160.69', 'Index', '2009-06-30', 'geoId/M23104', 'FHFA_HPI_traditional_all-transactions_quarterly_NSA', 'FHFA_HPI traditional all-transactions quarterly Not Seasonally Adjusted'), ('105.31', 'Index', '1996-12-31', 'geoId/C29460', 'FHFA_HPI_traditional_all-transactions_quarterly_NSA', 'FHFA_HPI traditional all-transactions quarterly Not Seasonally Adjusted'), ('74.54', 'Index', '1986-06-30', 'geoId/C34980', 'FHFA_HPI_traditional_all-transactions_quarterly_NSA', 'FHFA_HPI traditional all-transactions quarterly Not Seasonally Adjusted'), ('72.10', 'Index', '1988-09-30', 'geoId/C22140', 'FHFA_HPI_traditional_all-transactions_quarterly_NSA', 'FHFA_HPI traditional all-transactions quarterly Not Seasonally Adjusted'), ('62.06', 'Index', '1986-06-30', 'geoId/C33340', 'FHFA_HPI_traditional_all-transactions_quarterly_NSA', 'FHFA_HPI traditional all-transactions quarterly Not Seasonally Adjusted');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FREDDIE_MAC_HOUSING_TIMESERIES (
    VALUE FLOAT,
    VARIABLE_NAME TEXT,
    DATE DATE,
    GEO_ID TEXT,
    UNIT TEXT,
    VARIABLE TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FREDDIE_MAC_HOUSING_TIMESERIES" (VALUE, VARIABLE_NAME, DATE, GEO_ID, UNIT, VARIABLE) VALUES (0.0635, '30-Year Fixed Rate Mortgage Rate, National Average', '2024-08-29', 'country/USA', 'Percent', 'FRM_30_YR'), (172.7589483, 'Freddie Mac House Price Index (Seasonally adjusted)', '2020-07-31', 'geoId/31', 'Index', 'INDEX_SA'), (31.93893565, 'Freddie Mac House Price Index (Not seasonally adjusted)', '1976-09-30', 'geoId/32', 'Index', 'INDEX_NSA'), (83.36771622, 'Freddie Mac House Price Index (Seasonally adjusted)', '1996-08-31', 'geoId/10', 'Index', 'INDEX_SA'), (225.5959953, 'Freddie Mac House Price Index (Not seasonally adjusted)', '2021-05-31', 'geoId/25', 'Index', 'INDEX_NSA');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.IRS_INDIVIDUAL_INCOME_ATTRIBUTES (
    VARIABLE_NAME TEXT,
    SEASONALLY_ADJUSTED BOOLEAN,
    INCOME_BRACKET TEXT,
    UNIT TEXT,
    FREQUENCY TEXT,
    VARIABLE TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."IRS_INDIVIDUAL_INCOME_ATTRIBUTES" (VARIABLE_NAME, SEASONALLY_ADJUSTED, INCOME_BRACKET, UNIT, FREQUENCY, VARIABLE) VALUES ('Total income - Number of returns, AGI bin: $100,000 under $200,000', False, '$100,000 under $200,000', 'Returns', 'Annual', 'Total_income_-_Number_of_returns,_AGI_bin:_$100,000_under_$200,000'), ('Investment interest paid - Amount, AGI bin: $200,000 or more', False, '$200,000 or more', 'USD', 'Annual', 'Investment_interest_paid_-_Amount,_AGI_bin:_$200,000_or_more'), ('Personal property taxes - Number of returns, AGI bin: $25,000 under $50,000', False, '$25,000 under $50,000', 'Returns', 'Annual', 'Personal_property_taxes_-_Number_of_returns,_AGI_bin:_$25,000_under_$50,000'), ('Economic impact payment second round [15, 17] - Amount, AGI bin: $200,000 or more', False, '$200,000 or more', 'USD', 'Annual', 'Economic_impact_payment_second_round_[15,_17]_-_Amount,_AGI_bin:_$200,000_or_more'), ('Domestic production activities deduction - Number of returns, AGI bin: $75,000 under $100,000', False, '$75,000 under $100,000', 'Returns', 'Annual', 'Domestic_production_activities_deduction_-_Number_of_returns,_AGI_bin:_$75,000_under_$100,000');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.US_ADDRESSES (
    STREET_DIRECTIONAL_SUFFIX TEXT,
    STREET_DIRECTIONAL_PREFIX TEXT,
    LONGITUDE FLOAT,
    ID_COUNTRY TEXT,
    ID_ZIP TEXT,
    ADDRESS_ID TEXT,
    ZIP TEXT,
    ID_STATE TEXT,
    LATITUDE FLOAT,
    STREET_TYPE TEXT,
    NUMBER TEXT,
    UNIT TEXT,
    STREET TEXT,
    CITY TEXT,
    ID_CITY TEXT,
    STATE TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."US_ADDRESSES" (STREET_DIRECTIONAL_SUFFIX, STREET_DIRECTIONAL_PREFIX, LONGITUDE, ID_COUNTRY, ID_ZIP, ADDRESS_ID, ZIP, ID_STATE, LATITUDE, STREET_TYPE, NUMBER, UNIT, STREET, CITY, ID_CITY, STATE) VALUES (NULL, NULL, -98.6174384, 'country/USA', 'zip/78065', 'addressId/e45f42a85b03a3ffb52a76a414ca339e', '78065', 'geoId/48', 29.0946826, 'Drive', '190', NULL, 'Flagstone', NULL, NULL, 'TX'), (NULL, NULL, -78.7038928, 'country/USA', 'zip/29582', 'addressId/47c05a55b39b134d61779fc264317a32', '29582', 'geoId/45', 33.8239424, 'Way', '1313', NULL, 'Beautyberry', 'North Myrtle Beach', 'geoId/4551280', 'SC'), (NULL, NULL, -97.2854841, 'country/USA', 'zip/76244', 'addressId/b03f02a21b113f67b8a273fc92eb6dc4', '76244', 'geoId/48', 32.9558573, NULL, '3416', NULL, 'Beekman', 'Fort Worth', 'geoId/4827000', 'TX'), (NULL, NULL, -93.6842709, 'country/USA', 'zip/55364', 'addressId/dd73abec2efcd068488019e9b89e50c6', '55364', 'geoId/27', 44.9411196, 'Lane', '6332', NULL, 'Rambler', 'Mound', 'geoId/2744476', 'MN'), (NULL, 'SW', -80.2142451, 'country/USA', 'zip/33023', 'addressId/f30ebeddef925ab4b94b651fd55f55f1', '33023', 'geoId/12', 25.9898378, 'Street', '6335', NULL, '23rd', 'Miramar', 'geoId/1245975', 'FL');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.POINT_OF_INTEREST_INDEX (
    CATEGORY_MAIN TEXT,
    POI_NAME TEXT,
    CATEGORY_ALTERNATE ARRAY,
    POI_ID TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."POINT_OF_INTEREST_INDEX" (CATEGORY_MAIN, POI_NAME, CATEGORY_ALTERNATE, POI_ID) VALUES ('Video And Video Game Rentals', 'Redbox', '[
  "Books Mags Music And Video",
  "Rental Kiosks"
]', '08f26c862279d1150352e1060f847671'), ('Retirement Home', 'Hudson Place', '[
  "Health And Medical",
  "Public Service And Government"
]', '08f27490544e86b1036967efcd70720e'), ('Construction Services', 'One Source Construction Corp.', '[
  "Commercial Industrial",
  "Contractor"
]', '08f275d740d8184e03d67542272d1020'), ('Church Cathedral', 'Council Road', '[
  "Baptist Church",
  "Religious Organization"
]', '08f26c18910da49303ca27a9af04b9cf'), ('Employment Agencies', 'Impact Employment Solutions', '[
  "Information Technology Company",
  "Professional Services"
]', '08f2a94d0592d19c0352b1ade5f7bfe8');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.GEOGRAPHY_INDEX (
    LEVEL TEXT,
    ISO_ALPHA2 TEXT,
    GEO_ID TEXT,
    ISO_3166_2_CODE TEXT,
    ISO_NUMERIC_CODE TEXT,
    GEO_NAME TEXT,
    ISO_NAME TEXT,
    ISO_ALPHA3 TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."GEOGRAPHY_INDEX" (LEVEL, ISO_ALPHA2, GEO_ID, ISO_3166_2_CODE, ISO_NUMERIC_CODE, GEO_NAME, ISO_NAME, ISO_ALPHA3) VALUES ('CensusBlockGroup', NULL, 'censusBlockGroup/380959515003', NULL, NULL, 'Block Group 3; Census Tract 9515; Towner County; North Dakota', NULL, NULL), ('CensusBlockGroup', NULL, 'censusBlockGroup/380979701001', NULL, NULL, 'Block Group 1; Census Tract 9701; Traill County; North Dakota', NULL, NULL), ('CensusBlockGroup', NULL, 'censusBlockGroup/471490403091', NULL, NULL, 'Block Group 1; Census Tract 403.09; Rutherford County; Tennessee', NULL, NULL), ('CensusBlockGroup', NULL, 'censusBlockGroup/060730139063', NULL, NULL, 'Block Group 3; Census Tract 139.06; San Diego County; California', NULL, NULL), ('CensusBlockGroup', NULL, 'censusBlockGroup/211110124093', NULL, NULL, 'Block Group 3; Census Tract 124.09; Jefferson County; Kentucky', NULL, NULL);
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.FHFA_MORTGAGE_PERFORMANCE_TIMESERIES (
    DATE DATE,
    UNIT TEXT,
    GEO_ID TEXT,
    VARIABLE_NAME TEXT,
    VARIABLE TEXT,
    VALUE FLOAT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."FHFA_MORTGAGE_PERFORMANCE_TIMESERIES" (DATE, UNIT, GEO_ID, VARIABLE_NAME, VARIABLE, VALUE) VALUES ('2024-03-31', 'Percent', 'geoId/17', 'Percent 30 or 60 Days Past Due Date - Other Conventional Market', 'Percent_30_or_60_Days_Past_Due_Date_Other Conventional Market', 0.016), ('2023-12-31', 'Percent', 'geoId/C12940', 'Percent 90 to 180 Days Past Due Date - Government / Non-Conventional', 'Percent_90_to_180_Days_Past_Due_Date_Government / Non-Conventional', 0.026000000000000002), ('2024-03-31', 'Percent', 'geoId/C40140', 'Percent 90 to 180 Days Past Due Date - Enterprise Acquisitions', 'Percent_90_to_180_Days_Past_Due_Date_Enterprise Acquisitions', 0.003), ('2022-12-31', 'Percent', 'geoId/C13820', 'Percent in Forbearance - Government / Non-Conventional', 'Percent_in_Forbearance_Government / Non-Conventional', 0.013999999999999999), ('2023-12-31', 'Percent', 'geoId/56', 'Percent 90 to 180 Days Past Due Date - Other Conventional Market', 'Percent_90_to_180_Days_Past_Due_Date_Other Conventional Market', 0.003);
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.IRS_ORIGIN_DESTINATION_MIGRATION_TIMESERIES (
    SUPPRESSED NUMBER,
    FROM_GEO_ID TEXT,
    VARIABLE_NAME TEXT,
    TO_GEO_ID TEXT,
    UNIT TEXT,
    DATE DATE,
    VALUE NUMBER
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."IRS_ORIGIN_DESTINATION_MIGRATION_TIMESERIES" (SUPPRESSED, FROM_GEO_ID, VARIABLE_NAME, TO_GEO_ID, UNIT, DATE, VALUE) VALUES (0, 'geoId/37081', 'Number of Individuals', 'geoId/08031', 'Individuals', '2012-12-31', 16), (0, 'geoId/12021', 'Number of Returns', 'geoId/12031', 'Returns', '2020-12-31', 40), (0, 'geoId/40011', 'Adjusted Gross Income', 'geoId/40039', 'USD', '2019-12-31', 1826000), (0, 'geoId/36071', 'Number of Returns', 'geoId/12009', 'Returns', '2018-12-31', 32), (0, 'geoId/48113', 'Number of Returns', 'geoId/06053', 'Returns', '2012-12-31', 12);
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.USPS_ADDRESS_CHANGE_TIMESERIES (
    VARIABLE_NAME TEXT,
    DATE DATE,
    VARIABLE TEXT,
    GEO_NAME TEXT,
    GEO_ID TEXT,
    VALUE NUMBER
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."USPS_ADDRESS_CHANGE_TIMESERIES" (VARIABLE_NAME, DATE, VARIABLE, GEO_NAME, GEO_ID, VALUE) VALUES ('Outbound Address Changes, Temporary', '2020-08-31', 'outbound_address_changes_temporary', '55032', 'zip/55032', 0), ('Inbound Address Changes, Permanent', '2023-06-30', 'inbound_address_changes_permanent', 'Quincy', 'geoId/2555745', 582), ('Net Address Changes, Individuals', '2021-08-31', 'net_address_changes_individuals', 'Plaistow', 'geoId/3362500', 4), ('Inbound Address Changes, Businesses', '2022-12-31', 'inbound_address_changes_businesses', '72132', 'zip/72132', 0), ('Outbound Address Changes, Families', '2023-02-28', 'outbound_address_changes_families', 'Bayboro', 'geoId/3703960', 0);
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.US_REAL_ESTATE_ATTRIBUTES (
    SEASONALLY_ADJUSTED BOOLEAN,
    MEASUREMENT_TYPE TEXT,
    UNIT TEXT,
    BUILDING_USE TEXT,
    MEASUREMENT_PERIOD TEXT,
    MEASURE TEXT,
    VARIABLE TEXT,
    VARIABLE_NAME TEXT,
    FREQUENCY TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."US_REAL_ESTATE_ATTRIBUTES" (SEASONALLY_ADJUSTED, MEASUREMENT_TYPE, UNIT, BUILDING_USE, MEASUREMENT_PERIOD, MEASURE, VARIABLE, VARIABLE_NAME, FREQUENCY) VALUES (True, NULL, 'USD', 'Amusement and recreation', NULL, 'Nonresidential Construction', 'ALL_NONRES_AMUSEMENT_SA', 'Nonresidential Construction: Amusement And Recreation (Seasonally Adjusted)', 'Monthly'), (NULL, NULL, 'Percent', 'Commercial', NULL, 'Nonresidential Construction', 'ALL_NONRES_COMMERCIAL_STD_ERR_MM_PY', 'Nonresidential Construction: Commercial: Standard Error, Month-to-month change from previous year', 'Monthly'), (NULL, NULL, 'USD', 'Health care', NULL, 'Nonresidential Construction', 'ALL_NONRES_HEALTH_A', 'Nonresidential Construction: Health Care (Annual)', 'Annual'), (False, NULL, 'USD', 'Health care', NULL, 'Nonresidential Construction', 'ALL_NONRES_HEALTH_NSA', 'Nonresidential Construction: Health Care (Not Seasonally Adjusted)', 'Monthly'), (False, NULL, 'USD', 'Manufacturing', NULL, 'Nonresidential Construction', 'ALL_NONRES_MANUFACTURING_NSA', 'Nonresidential Construction: Manufacturing (Not Seasonally Adjusted)', 'Monthly');
-- DBMS: snowflake
CREATE TABLE US_REAL_ESTATE.CYBERSYN.IRS_MIGRATION_BY_CHARACTERISTIC_ATTRIBUTES (
    AGE_GROUP TEXT,
    UNIT TEXT,
    RETURN_GROUP TEXT,
    FREQUENCY TEXT,
    VARIABLE TEXT,
    SEASONALLY_ADJUSTED BOOLEAN,
    INCOME_BRACKET TEXT,
    VARIABLE_NAME TEXT
);

INSERT INTO "US_REAL_ESTATE"."CYBERSYN"."IRS_MIGRATION_BY_CHARACTERISTIC_ATTRIBUTES" (AGE_GROUP, UNIT, RETURN_GROUP, FREQUENCY, VARIABLE, SEASONALLY_ADJUSTED, INCOME_BRACKET, VARIABLE_NAME) VALUES ('45 under 55', 'USD', 'Outflow Returns', 'Annual', 'Outflow_Returns_–_adjusted_gross_income_from_Year_1,_primary_taxpayers_ages_45_under_55,_AGI_bin:_$10,000_under_$25,000', False, '$10,000 under $25,000', 'Outflow Returns – adjusted gross income from Year 1, primary taxpayers ages 45 under 55, AGI bin: $10,000 under $25,000'), ('26 under 35', 'Individuals', 'Same State Returns', 'Annual', 'Same_State_Returns_–_number_of_individuals,_primary_taxpayers_ages_26_under_35,_AGI_bin:_$75,000_under_$100,000', False, '$75,000 under $100,000', 'Same State Returns – number of individuals, primary taxpayers ages 26 under 35, AGI bin: $75,000 under $100,000'), ('55 under 65', 'Individuals', 'Total Returns', 'Annual', 'Total_Returns_–_number_of_individuals,_primary_taxpayers_ages_55_under_65,_AGI_bin:_$100,000_under_$200,000', False, '$100,000 under $200,000', 'Total Returns – number of individuals, primary taxpayers ages 55 under 65, AGI bin: $100,000 under $200,000'), ('All Ages', 'USD', 'Inflow Returns', 'Annual', 'Inflow_Returns_–_adjusted_gross_income_from_Year_1,_all_ages,_All_AGI_classes', False, 'All AGI classes', 'Inflow Returns – adjusted gross income from Year 1, all ages, All AGI classes'), ('All Ages', 'Returns', 'Total Returns', 'Annual', 'Total_Returns_-_number_of_returns,_all_ages,_All_AGI_classes', False, 'All AGI classes', 'Total Returns - number of returns, all ages, All AGI classes');
-- DBMS: snowflake
create or replace TABLE PEDIGREE (
	"Family_ID" VARCHAR(16777216),
	"Individual_ID" VARCHAR(16777216),
	"Paternal_ID" VARCHAR(16777216),
	"Maternal_ID" VARCHAR(16777216),
	"Gender" NUMBER(38,0),
	"Phenotype" NUMBER(38,0),
	"Population" VARCHAR(16777216),
	"Relationship" VARCHAR(16777216),
	"Siblings" VARCHAR(16777216),
	"Second_Order" VARCHAR(16777216),
	"Third_Order" VARCHAR(16777216),
	"Other_Comments" VARCHAR(16777216)
);

INSERT INTO "_1000_GENOMES"."_1000_GENOMES"."PEDIGREE" (Second_Order, Individual_ID, Other_Comments, Third_Order, Family_ID, Maternal_ID, Relationship, Phenotype, Gender, Population, Paternal_ID, Siblings) VALUES ('0', 'HG01960', '0', '0', 'BB11', 'HG01989', 'child', 0, 2, 'ACB', 'HG01988', '0'), ('0', 'HG02559', '0', '0', 'BB68', 'HG02558', 'child', 0, 2, 'ACB', 'HG02557', '0'), ('0', 'HG02486', '0', '0', 'BB55', 'HG02485', 'child', 0, 1, 'ACB', 'HG02484', '0'), ('0', 'HG02055', '0', '0', 'BB15', 'HG02054', 'child', 0, 1, 'ACB', 'HG02053', '0'), ('0', 'HG02257', '0', '0', 'BB21', 'HG02256', 'child', 0, 2, 'ACB', 'HG02255', '0');
-- DBMS: snowflake
CREATE TABLE AMAZON_VENDOR_ANALYTICS__SAMPLE_DATASET.PUBLIC.BRAND_MARKET_BASKET_ANALYSIS_VC (
    DATE TIMESTAMP_LTZ,
    ASIN TEXT,
    NO3_PURCHASED_TITLE TEXT,
    NO3_COMBINATION_PERCENTAGE_RAW TEXT,
    _REVISION NUMBER,
    PERIOD TEXT,
    _LAST_UPDATED_ON TIMESTAMP_LTZ,
    NO2_COMBINATION_PERCENTAGE FLOAT,
    PRODUCT_TITLE TEXT,
    NO3_PURCHASED_ASIN TEXT,
    NO2_PURCHASED_TITLE TEXT,
    _PARTNERUUID TEXT,
    NO3_COMBINATION_PERCENTAGE FLOAT,
    NO1_COMBINATION_PERCENTAGE FLOAT,
    NO1_COMBINATION_PERCENTAGE_RAW TEXT,
    _CREATED_ON TIMESTAMP_LTZ,
    ID NUMBER,
    NO2_COMBINATION_PERCENTAGE_RAW TEXT,
    NO2_PURCHASED_ASIN TEXT,
    NO1_PURCHASED_TITLE TEXT,
    NO1_PURCHASED_ASIN TEXT
);

INSERT INTO "AMAZON_VENDOR_ANALYTICS__SAMPLE_DATASET"."PUBLIC"."BRAND_MARKET_BASKET_ANALYSIS_VC" (DATE, ASIN, NO3_PURCHASED_TITLE, NO3_COMBINATION_PERCENTAGE_RAW, _REVISION, PERIOD, _LAST_UPDATED_ON, NO2_COMBINATION_PERCENTAGE, PRODUCT_TITLE, NO3_PURCHASED_ASIN, NO2_PURCHASED_TITLE, _PARTNERUUID, NO3_COMBINATION_PERCENTAGE, NO1_COMBINATION_PERCENTAGE, NO1_COMBINATION_PERCENTAGE_RAW, _CREATED_ON, ID, NO2_COMBINATION_PERCENTAGE_RAW, NO2_PURCHASED_ASIN, NO1_PURCHASED_TITLE, NO1_PURCHASED_ASIN) VALUES ('2021-04-06 00:00:00-07:00', 'ASIN_3677', 'TITLE_4243', NULL, 1, 'WEEKLY', '2021-09-15 15:05:09-07:00', 0.0833, 'TITLE_89', 'ASIN_7687', 'TITLE_69', '0ba25d78-760e-4541-8eca-e4ff8292d0b1', 0.0417, 0.0833, NULL, '2021-11-06 15:05:09-07:00', 408636, NULL, 'ASIN_3666', 'TITLE_5', 'ASIN_33'), ('2021-04-06 00:00:00-07:00', 'ASIN_12', 'TITLE_4255', NULL, 1, 'WEEKLY', '2021-09-15 15:05:09-07:00', 0.1111, 'TITLE_59', 'ASIN_7697', 'TITLE_2325', '0ba25d78-760e-4541-8eca-e4ff8292d0b1', 0.1111, 0.1111, NULL, '2021-11-06 15:05:09-07:00', 408654, NULL, 'ASIN_5840', 'TITLE_533', 'ASIN_4092'), ('2021-04-06 00:00:00-07:00', 'ASIN_28', 'TITLE_4264', NULL, 1, 'WEEKLY', '2021-09-15 15:05:09-07:00', 0.3333, 'TITLE_35', 'ASIN_7706', 'TITLE_722', '0ba25d78-760e-4541-8eca-e4ff8292d0b1', 0.3333, 0.3333, NULL, '2021-11-06 15:05:09-07:00', 408665, NULL, 'ASIN_4281', 'TITLE_591', 'ASIN_4150'), ('2021-03-30 00:00:00-07:00', 'ASIN_3653', 'TITLE_39', NULL, 1, 'WEEKLY', '2021-09-15 15:06:21-07:00', 0.2466, 'TITLE_32', 'ASIN_3655', 'TITLE_33', '0ba25d78-760e-4541-8eca-e4ff8292d0b1', 0.2329, 0.4247, NULL, '2021-11-06 15:06:21-07:00', 408677, NULL, 'ASIN_3654', 'TITLE_30', 'ASIN_3652'), ('2021-03-30 00:00:00-07:00', 'ASIN_3650', 'TITLE_32', NULL, 1, 'WEEKLY', '2021-09-15 15:06:21-07:00', 0.1094, 'TITLE_27', 'ASIN_3653', 'TITLE_30', '0ba25d78-760e-4541-8eca-e4ff8292d0b1', 0.0781, 0.1406, NULL, '2021-11-06 15:06:21-07:00', 408679, NULL, 'ASIN_3652', 'TITLE_33', 'ASIN_3654');