US CPI component inflation intelligence (monthly)
Monthly US CPI component inflation intelligence from the BLS Consumer Price Index for All Urban Consumers (keyless BLS Public Data API v2): headline, core and ten expenditure components for the U.S. city average (seasonally adjusted) plus the all-items index for the four Census regions. Every series carries YoY inflation, the 12-month YoY trend, the deviation from trend, heating / cooling / steady flags, above-2% and above-3% gauges, a documented 0-100 inflation-pressure score with per-month component ranks, and month-level context: the core-vs-headline gap, the share of major expenditure groups running above 2% / 3%, and the regional inflation spread. Methodology window 2017-01 onward. Caveats: October 2025 is missing for all series (2025 federal lapse in appropriations); regional series are not seasonally adjusted (YoY only); the latest month is preliminary and routinely revised. BLS material is public domain (commercial reuse allowed); source: U.S. Bureau of Labor Statistics.
- Rows
- 1,856
- Columns
- 24
- Source cadence
- Monthly
- Last refreshed
- Sep 26, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| month | string | Reference month: first day of the month, ISO date. The panel covers the consistent methodology window 2017-01 onward. (unit: ISO date) |
| country_code | string | ISO alpha-3 country code (USA for every row). (unit: ISO 3166-1 alpha-3) |
| region_code | string | Census geography: us (U.S. city average) or one of northeast, midwest, south, west. (unit: code) |
| region_name | string | Human-readable geography: United States, Northeast, Midwest, South, West. |
| component_code | string | CPI component: all_items, core, food, energy, housing, shelter, rent, apparel, transportation, medical_care, recreation, education_communication. Primary join key with month. (unit: code) |
| component_name | string | Human-readable component: e.g. All items, Shelter, Rent of primary residence. |
| seasonally_adjusted | boolean | True for the 12 U.S. city-average series; False for the 4 regional series, which BLS publishes only unadjusted. (unit: boolean) |
| index_value | float | Published CPI-U index level, kept verbatim as published. Base 1982-84=100 except recreation and education & communication (December 1997=100): levels are not comparable across components, percent changes are. (unit: index points) |
| yoy_pct | float | Year-over-year percent change of the index — the headline inflation gauge per component. (unit: percent) |
| yoy_trend_12m | float | Trailing 12-month mean of yoy_pct (minimum 6 observations): the slow-moving inflation trend for the component. The 2025-10 gap month is skipped, never interpolated. (unit: percent) |
| yoy_vs_trend_pp | float | yoy_pct minus its 12-month trend, in percentage points. Positive = running hotter than trend. (unit: pp) |
| mom_pct | float | Month-over-month percent change (seasonally adjusted series only; null for regional NSA series). (unit: percent) |
| ann3m_pct | float | 3-month annualized change: ((lvl_t / lvl_{t-3}) ** 4 - 1) * 100 (seasonally adjusted series only). (unit: percent) |
| heating_flag | string | 'heating' when YoY runs more than 0.5pp above its 12-month trend, 'cooling' when more than 0.5pp below, 'steady' otherwise; null when YoY or trend is null. (unit: category) |
| above3_flag | integer | 1 when yoy_pct exceeds 3% (above-tolerance gauge). (unit: binary) |
| above2_flag | integer | 1 when yoy_pct exceeds 2% (above-target gauge). (unit: binary) |
| pressure_score | float | Documented 0-100 composite: yoy_pct min-maxed within each month across the 12 U.S. seasonally adjusted series. Higher = hottest price pressure among CPI components that month. Null for regional rows. (unit: 0-100 score) |
| inflation_rank | integer | Per-month rank of pressure_score across the 12 U.S. SA series (1 = hottest); min-ranking ties. (unit: rank) |
| core_headline_gap_pp | float | Month-level context: core (all items less food and energy) YoY minus headline YoY, in percentage points. Positive = underlying pressure above headline. (unit: pp) |
| breadth_above3_pct | float | Month-level context: share of the 8 major expenditure groups (food, energy, housing, apparel, transportation, medical care, recreation, education & communication) with YoY above 3%. (unit: share 0-1) |
| breadth_above2_pct | float | Month-level context: share of the 8 major expenditure groups with YoY above 2%. (unit: share 0-1) |
| regional_spread_pp | float | Month-level context: max minus min YoY across the four Census regions — the regional divergence gauge. (unit: pp) |
| bls_series_id | string | BLS series id behind the row (e.g. CUSR0000SAH1). |
| row_hash | string | Deterministic 16-hex row hash of series_id + month (idempotency). |
First 10 sample rows — a preview, not the complete dataset.
| month | country_code | region_code | region_name | component_code | component_name | seasonally_adjusted | index_value | yoy_pct | yoy_trend_12m | yoy_vs_trend_pp | mom_pct | ann3m_pct | heating_flag | above3_flag | above2_flag | pressure_score | inflation_rank | core_headline_gap_pp | breadth_above3_pct | breadth_above2_pct | regional_spread_pp | bls_series_id | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-01-01 | USA | us | United States | all_items | All items | true | 243.618 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SA0 | 1b68561138d77c5f |
| 2017-01-01 | USA | us | United States | core | All items less food and energy | true | 250.467 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SA0L1E | 691bcb63be15d2be |
| 2017-01-01 | USA | us | United States | food | Food | true | 248.065 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SAF1 | 8327dda492d49fd6 |
| 2017-01-01 | USA | us | United States | energy | Energy | true | 205.369 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SA0E | d23554574c9eac44 |
| 2017-01-01 | USA | us | United States | housing | Housing | true | 248.164 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SAH | 6c3fd0f2d446c62f |
| 2017-01-01 | USA | us | United States | shelter | Shelter | true | 293.769 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SAH1 | e111619ad748d97c |
| 2017-01-01 | USA | us | United States | rent | Rent of primary residence | true | 303.156 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SEHA | beee117749cda9d0 |
| 2017-01-01 | USA | us | United States | apparel | Apparel | true | 126.044 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SAA | b3d082d7e205649a |
| 2017-01-01 | USA | us | United States | transportation | Transportation | true | 202.082 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SAT | 57f41354f18888aa |
| 2017-01-01 | USA | us | United States | medical_care | Medical care | true | 471.484 | — | — | — | — | — | — | 0 | 0 | — | — | — | 0 | 0 | — | CUSR0000SAM | ed04b5198376cc13 |
- Current
20260926T223309Z-9bfc4e5dd9a3 · sha256 9bfc4e5dd9a3…
1,856 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/bls_cpi_component_intel/us_cpi_component_inflation_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bls_cpi_component_intel/us_cpi_component_inflation_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/bls_cpi_component_intel/us_cpi_component_inflation_monthly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260926T223309Z-9bfc4e5dd9a3 and its content hash, so readers get exactly the data you used.
U.S. Bureau of Labor Statistics. (2026). US CPI component inflation intelligence (monthly) [Data set, snapshot 20260926T223309Z-9bfc4e5dd9a3, sha256 9bfc4e5dd9a3]. Datazimuts. Retrieved 2026-09-26, from https://datazimuts.com/en/datasets/bls_cpi_component_intel/us_cpi_component_inflation_monthly?snapshot=20260926T223309Z-9bfc4e5dd9a3
@misc{dz_bls_cpi_component_intel_us_cpi_component_9bfc4e5d,
title = {{US CPI component inflation intelligence (monthly)}},
author = {{U.S. Bureau of Labor Statistics}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/bls_cpi_component_intel/us_cpi_component_inflation_monthly?snapshot=20260926T223309Z-9bfc4e5dd9a3}},
note = {Snapshot 20260926T223309Z-9bfc4e5dd9a3, sha256 9bfc4e5dd9a30b5902159974e9516e62d71735c76f7eb6eb1ecfd9ffe394883e; accessed 2026-09-26}
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