US state housing-vacancy slack panel (Census HVS, annual by state)
Usage commercial OKÀ jour
Interroger dans l’atelierLe jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSVTélécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.
Annual US housing-vacancy slack panel by state, 1986 onward: Census Housing Vacancy Survey rental and homeowner vacancy rates for all 50 states + DC, keyless via FRED fredgraph.csv. Carries YoY percentage-point changes, trailing-10-year z-scores vs each state's own history, a documented 0-100 housing_slack_score (within-year min-max of clipped z-scores; higher = more vacant units, weaker housing demand), a within-year slack_rank, cross-state median benchmarks and spreads, and a trailing-10-year-high flag. The grid is complete 1986 -> latest with zero gaps — any hole fails loudly. Who joins this: retailers read state+year slack as a local demand regime (discount vs pricing power); subscription businesses weight churn-risk by slack_rank; sales teams prioritize tight markets.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 2 040
- Colonnes
- 21
- Cadence de la source
- Annuelle
- Dernière actualisation
- 1 oct. 2026
- Thème
- housing
| Colonne | Type | Description |
|---|---|---|
| date | date | Reference year, January 1 (panel join key). One row per state per year, 1986 onward, no gaps — a missing year fails the ingest loudly. (unit: date) |
| year | integer | Calendar year (HVS annual). (unit: year) |
| state_abbreviation | string | USPS 2-letter state/District code (50 states + DC). Join key for state-level merges. (unit: string) |
| state_name | string | State/District name. (unit: string) |
| country | string | Country name (shared normalization layer). (unit: string) |
| country_code | string | ISO 3166-1 alpha-3 country code (USA). (unit: string) |
| rental_vacancy_rate | float | Rental vacancy rate: percent of the rental inventory vacant and available for rent (HVS). The binding demand-leg measure: null in-grid fails loudly. (unit: percent) |
| homeowner_vacancy_rate | float | Homeowner vacancy rate: percent of the homeowner inventory vacant and for sale (HVS). (unit: percent) |
| rental_vacancy_yoy_pp | float | Year-over-year change in the rental vacancy rate, percentage points. Positive = more slack. (unit: percentage_points) |
| homeowner_vacancy_yoy_pp | float | Year-over-year change in the homeowner vacancy rate, percentage points. (unit: percentage_points) |
| rental_vacancy_z10 | float | Rental vacancy z-score vs the state's own trailing 10-year mean/std. Null until 10 observations exist or when the trailing std is 0. (unit: z-score) |
| homeowner_vacancy_z10 | float | Homeowner vacancy z-score vs the state's own trailing 10-year mean/std. Null until 10 observations exist or when the trailing std is 0. (unit: z-score) |
| housing_slack_score | float | Documented 0-100 slack score: within-year min-max of clip(z_rental, -3, 3) and clip(z_homeowner, -3, 3), averaged x100. Higher = more vacant units relative to history = weaker local housing demand. Null before 1996 (needs 10 years of history). (unit: score_0_100) |
| slack_rank | integer | Within-year rank of housing_slack_score, 1 = slackest state that year. (unit: rank) |
| us_median_rental_vacancy | float | Cross-state median rental vacancy rate for the year — the documented robust national benchmark. (unit: percent) |
| us_median_homeowner_vacancy | float | Cross-state median homeowner vacancy rate for the year. (unit: percent) |
| rental_vacancy_vs_us_median_pp | float | State rental vacancy minus the yearly cross-state median, percentage points. (unit: percentage_points) |
| homeowner_vacancy_vs_us_median_pp | float | State homeowner vacancy minus the yearly cross-state median, percentage points. (unit: percentage_points) |
| rental_vacancy_10y_high_flag | integer | 1 when the year's rental vacancy rate is the state's trailing-10-year maximum (local demand trough); else 0. (unit: flag) |
| provenance_url | string | Exact fredgraph.csv source URLs behind the row (rental leg; homeowner leg). (unit: url) |
| row_hash | string | Deterministic 16-hex SHA-256 of state + year + both vacancy rates (idempotency key). (unit: hash) |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| date | year | state_abbreviation | state_name | country | country_code | rental_vacancy_rate | homeowner_vacancy_rate | rental_vacancy_yoy_pp | homeowner_vacancy_yoy_pp | rental_vacancy_z10 | homeowner_vacancy_z10 | housing_slack_score | slack_rank | us_median_rental_vacancy | us_median_homeowner_vacancy | rental_vacancy_vs_us_median_pp | homeowner_vacancy_vs_us_median_pp | rental_vacancy_10y_high_flag | provenance_url | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1986-01-01 | 1 986 | AK | Alaska | United States | USA | 15,3 | 2,4 | — | — | — | — | — | — | 6,9 | 1,6 | 8,4 | 0,8 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=AKRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=AKHVAC | 6216a29861b4f88c |
| 1986-01-01 | 1 986 | AL | Alabama | United States | USA | 5 | 2,8 | — | — | — | — | — | — | 6,9 | 1,6 | -1,9 | 1,2 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=ALRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=ALHVAC | 836611de8db26b98 |
| 1986-01-01 | 1 986 | AR | Arkansas | United States | USA | 7,4 | 1,8 | — | — | — | — | — | — | 6,9 | 1,6 | 0,5 | 0,2 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=ARRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=ARHVAC | 2b6b71bdc194a39e |
| 1986-01-01 | 1 986 | AZ | Arizona | United States | USA | 13,1 | 2,2 | — | — | — | — | — | — | 6,9 | 1,6 | 6,2 | 0,6 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=AZRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=AZHVAC | 0cb98bc55b7ad066 |
| 1986-01-01 | 1 986 | CA | California | United States | USA | 4,9 | 1,1 | — | — | — | — | — | — | 6,9 | 1,6 | -2 | -0,5 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=CARVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=CAHVAC | c37cfac6a3e2b891 |
| 1986-01-01 | 1 986 | CO | Colorado | United States | USA | 13,6 | 2,6 | — | — | — | — | — | — | 6,9 | 1,6 | 6,7 | 1 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=CORVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=COHVAC | 6434f85672428750 |
| 1986-01-01 | 1 986 | CT | Connecticut | United States | USA | 5 | 0,4 | — | — | — | — | — | — | 6,9 | 1,6 | -1,9 | -1,2 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=CTRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=CTHVAC | 668c43ba5d42028a |
| 1986-01-01 | 1 986 | DC | District of Columbia | United States | USA | 3,5 | 2,5 | — | — | — | — | — | — | 6,9 | 1,6 | -3,4 | 0,9 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=DCRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=DCHVAC | 5a63440ada53eba1 |
| 1986-01-01 | 1 986 | DE | Delaware | United States | USA | 4,9 | 1,2 | — | — | — | — | — | — | 6,9 | 1,6 | -2 | -0,4 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=DERVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=DEHVAC | 159616511ff20d15 |
| 1986-01-01 | 1 986 | FL | Florida | United States | USA | 11 | 2,5 | — | — | — | — | — | — | 6,9 | 1,6 | 4,1 | 0,9 | 0 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=FLRVAC;https://fred.stlouisfed.org/graph/fredgraph.csv?id=FLHVAC | 622595b873a6b85b |
Profilé le 1 oct. 2026 à partir de l’instantané 20261001T020110Z-5331fe4f0d83
Mesuré- Complétude
- 95,5 %
- Lignes
- 2 040
- Colonnes
- 21
- Colonnes incomplètes
- 6
19862025
| Colonne | Manquant | Distinctes | Plage | Distribution |
|---|---|---|---|---|
| datedate | 0 % | 43 | 1 janv. 1986 → 1 janv. 2025 | — |
| yearbigint | 0 % | 39 | 1 986 → 2 025médiane 2 006 | |
| state_abbreviationvarchar | 0 % | 55 | — |
|
| state_namevarchar | 0 % | 59 | — |
|
| countryvarchar | 0 % | 1 | — |
|
| country_codevarchar | 0 % | 1 | — |
|
| rental_vacancy_ratedouble | 0 % | 127 | 2,2 → 25,8médiane 7,7 | 40 hors du 1er–99e centile |
| homeowner_vacancy_ratedouble | 0 % | 46 | 0,2 → 5,6médiane 1,6 | 22 hors du 1er–99e centile |
| rental_vacancy_yoy_ppdouble | 2,5 % | 256 | -15,2 → 5,8médiane 0 | 38 hors du 1er–99e centile |
| homeowner_vacancy_yoy_ppdouble | 2,5 % | 110 | -1,8 → 2,3médiane 0 | 38 hors du 1er–99e centile |
| rental_vacancy_z10double | 22,5 % | 1 875 | -2,52 → 2,7médiane -0,2351 | 32 hors du 1er–99e centile |
| homeowner_vacancy_z10double | 22,5 % | 1 777 | -2,51 → 2,63médiane -0,3183 | 32 hors du 1er–99e centile |
| housing_slack_scoredouble | 22,5 % | 1 383 | 0,0239 → 100médiane 42,69 | 32 hors du 1er–99e centile |
| slack_rankbigint | 22,5 % | 45 | 1 → 51médiane 26 | |
| us_median_rental_vacancydouble | 0 % | 21 | 5,9 → 10,3médiane 7,55 | |
| us_median_homeowner_vacancydouble | 0 % | 13 | 0,7 → 2,4médiane 1,7 | |
| rental_vacancy_vs_us_median_ppdouble | 0 % | 362 | -5,9 → 18,8médiane 0 | 39 hors du 1er–99e centile |
| homeowner_vacancy_vs_us_median_ppdouble | 0 % | 117 | -1,4 → 4médiane 0 | 36 hors du 1er–99e centile |
| rental_vacancy_10y_high_flagbigint | 0 % | 2 | 0 → 1médiane 0 | |
| provenance_urlvarchar | 0 % | 46 | — |
|
| row_hashvarchar | 0 % | 1 871 | — |
|
- Actuelle
20261001T020110Z-5331fe4f0d83 · sha256 5331fe4f0d83…
2 040 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/census_hvs_vacancy_slack_intel/us_state_housing_vacancy_annual" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/census_hvs_vacancy_slack_intel/us_state_housing_vacancy_annual").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API : https://datazimuts.com/v1/datasets/census_hvs_vacancy_slack_intel/us_state_housing_vacancy_annual
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20261001T020110Z-5331fe4f0d83 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
APA
US State Housing-Vacancy Slack Intelligence (Census HVS, keyless). (2026). US state housing-vacancy slack panel (Census HVS, annual by state) [Data set, snapshot 20261001T020110Z-5331fe4f0d83, sha256 5331fe4f0d83]. Datazimuts. Retrieved 2026-10-01, from https://datazimuts.com/fr/datasets/census_hvs_vacancy_slack_intel/us_state_housing_vacancy_annual?snapshot=20261001T020110Z-5331fe4f0d83
BibTeX
@misc{dz_census_hvs_vacancy_slack_intel_us_state__5331fe4f,
title = {{US state housing-vacancy slack panel (Census HVS, annual by state)}},
author = {{US State Housing-Vacancy Slack Intelligence (Census HVS, keyless)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/census_hvs_vacancy_slack_intel/us_state_housing_vacancy_annual?snapshot=20261001T020110Z-5331fe4f0d83}},
note = {Snapshot 20261001T020110Z-5331fe4f0d83, sha256 5331fe4f0d83207731cfca20a424a784ab0a4aea359819295e320e76ea195659; accessed 2026-10-01}
}Intégrer un tableau ou un graphique
Collez ce code dans n’importe quelle page. L’intégration est épinglée au même instantané, suit le thème clair ou sombre du lecteur et affiche toujours la source, la licence et un lien de retour.
HTML
<iframe src="https://datazimuts.com/embed/chart?dataset=census_hvs_vacancy_slack_intel%2Fus_state_housing_vacancy_annual&lang=fr&theme=auto&snapshot=20261001T020110Z-5331fe4f0d83&x=date&y=year&agg=avg" title="US state housing-vacancy slack panel (Census HVS, annual by state)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
Posez une question sur ce jeu de données. Les réponses viennent uniquement de sa fiche, de son profil mesuré et de son historique, et citent les faits utilisés.