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.
1 jeux de données
US State Building-Permits Momentum Intelligence (FRED, keyless)
Monthly US state building-permits momentum intelligence, 1988-01 onward: new privately-owned housing units authorized in permit-issuing places for the 50 states + DC (units, seasonally adjusted; U.S. Census Bureau and HUD New Residential Construction release, redistributed keyless via 51 FRED <ST>BPPRIVSA series). Each state-month row carries the permit level, its share of the US total, month-on-month / year-on-year / 3-month-annualized momentum, a documented 0-100 state momentum score (50% winsorized YoY + 30% 3-month annualized + 20% MoM, min-maxed within each month) with deterministic 1..51 rank and t1-t5 quintile tiers, trailing-12-month record-high and contraction flags, plus month-level context (US total, national YoY, breadth of states growing, top state). The transform is pure pandas with no imputation: warm-up cells are honest nulls, in-window gaps fail loudly. Who joins this: home-improvement and building-supply merchants join demand on (year_month, state_code); sales teams weight territory pipeline on state_score / momentum_tier; subscription businesses read contraction_flag as a move-related churn proxy. Caveat: Census revises history with each vintage; small states show noisy raw percents — use the winsorized score and ranks for cross-state comparison. Upstream gap: FRED publishes no 2006-09 observation for DC — that cell carries no row and the month-level aggregates are null for 2006-09.
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