090°Données ouvertes
Jeux de données ouverts, entièrement documentés — interrogeables ici, et lisibles par n’importe quel LLM.
Les titres et les descriptions proviennent des sources de données, en anglais.
2 jeux de données
US Housing Starts & New-Home Sales Intelligence (FRED, keyless)
Monthly US housing-starts intelligence panel, 1959-01 onward: total new privately-owned housing units started (thousands of units, seasonally adjusted annual rate; FRED HOUST, U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Residential Construction release, redistributed keyless via FRED fredgraph.csv). Carries 1-month and 12-month changes (levels and percents), the 3-month annualized percent change, and a contraction_flag marking months with fewer starts than a year earlier. Method caveats: Census revises history with each vintage (kept as published, never back-filled); in-window nulls fail loudly, never imputed. Who joins this: home-improvement merchants join demand on year_month + country_code and use starts_yoy_pct / contraction_flag as housing-demand features; sales teams weight real-estate-adjacent pipeline by the contraction regime.
Monthly US new-home-sales intelligence panel, 1963-01 onward: new one-family houses sold in the United States (thousands of units, seasonally adjusted annual rate; FRED HSN1F, U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Residential Sales release, redistributed keyless via FRED fredgraph.csv). Carries 1-month and 12-month changes (levels and percents), the 3-month annualized percent change, and a contraction_flag marking months with fewer sales than a year earlier. Method caveats: a 'sale' is recorded when a deposit is taken or a sales agreement is signed, which can precede the building permit — monthly sales can exceed starts for this reason; Census revises history with each vintage (kept as published, never back-filled); in-window nulls fail loudly, never imputed. Who joins this: home-improvement and building-supply merchants join demand on year_month + country_code and use sales_yoy_pct / contraction_flag as housing-demand features.
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