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
U.S. Bureau of Economic Analysis
US metro price-level intelligence from the BEA Regional Price Parities (RPP, 2008–2024 vintage, keyless FRED redistribution, U.S. public domain): ~384 metropolitan statistical areas (OMB 2023 delineations), annual, US = 100. Method: the closed RPPALL<CBSA> universe is pulled via fredgraph.csv; every series must span 2008 to the latest vintage with zero gaps and plausible values or the ingest fails loudly. Derived signals per metro-year: cost_premium_pct (RPP − 100), a documented 5-band price_tier (very_low <90 … very_high ≥110), within-year national_rank (1 = most expensive), 1-year and 5-year index-point drift (rpp_yoy_pp / rpp_5y_pp), and local_purchasing_power_100 (10000/RPP: the national-dollar value of $100 spent locally). Use as prediction features: join to customers/orders/leads by cbsa_code + year for territory-level demand models, site selection, regional pricing, and real (price-level-adjusted) market sizing — the state panel's coarser sibling for metro granularity. Caveats: RPPs compare price levels across places, not inflation over time; the latest 1–2 vintages are routinely revised.
US state price-level intelligence from the BEA Regional Price Parities (RPP, 2008–2024 vintage, keyless FRED redistribution, U.S. public domain): 50 states plus DC, annual, US = 100. Method: the closed 51-series <ST>RPPALL universe is pulled via fredgraph.csv; every series must span 2008 to the latest vintage with zero gaps and plausible values or the ingest fails loudly. Derived signals per state-year: cost_premium_pct (RPP − 100), a documented 5-band price_tier (very_low <90 … very_high ≥110), within-year national_rank (1 = most expensive), 1-year and 5-year index-point drift (rpp_yoy_pp / rpp_5y_pp — relative price convergence or divergence), and local_purchasing_power_100 (10000/RPP: the national-dollar value of $100 spent locally). Use as prediction features: join to customers/orders/leads by state_code + year to deflate nominal amounts into real terms, set regional price lists and sales quotas, and score market affordability — a $29 subscription feels like $26 in California but $33 in Mississippi. Caveats: RPPs compare price levels across places, not inflation over time; the latest 1–2 vintages are routinely revised.
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