Europe Brent Spot Price FOB Daily

Rows: 9,947
Columns: 2

Daily historical spot prices for Europe Brent crude oil in USD per barrel from May 1987 to present. Comprehensive time series from official government source.

AI analysis

Europe Brent Spot Price FOB — Dataset Analysis

1. Dataset Overview & Value This dataset captures daily Europe Brent crude oil spot prices in USD per barrel, spanning from May 1987 to the present — nearly four decades of continuous price history sourced directly from the U.S. Energy Information Administration (EIA) at eia.gov/dnav/pet. The EIA is a highly credible, official government publisher, and the API/Excel delivery mechanism suggests the data is regularly refreshed, making it suitable for near-real-time analysis. With 9,895 daily observations, this is a rich, high-frequency time series ideal for studying macroeconomic cycles, energy market shocks, and commodity price dynamics. Its length and official provenance make it one of the more reliable free benchmarks for global oil pricing.

2. Data Quality Quality is exceptionally strong across the board. There are only 2 null values in the price column (0.02% of rows), which almost certainly correspond to non-trading days or brief data gaps — entirely negligible and easily handled via forward-fill or interpolation. The Date column is perfectly clean with zero nulls and 9,895 distinct values, confirming no duplicate dates exist in the series. Duplicate row counts are pending final recomputation, but the fully distinct Date column makes true duplicates structurally impossible. No type mismatches are flagged. This dataset is effectively production-ready with minimal preprocessing required.

3. Key Column Distributions The price column tells a compelling story of commodity volatility. The mean of $51.16 sits notably above the median of $46.09, indicating a right-skewed distribution (skew = 0.563) — consistent with periodic price spikes pulling the average upward. The wide interquartile range ($19.54 to $74.78) reflects distinct market eras: the low-price 1990s regime versus the post-2004 and post-2010 supercycles. The minimum of $9.10 likely captures the mid-1998 price collapse, while the maximum of $143.95 corresponds to the July 2008 pre-financial-crisis peak. The standard deviation of $32.74 — over 60% of the mean — underscores that this is a highly volatile series unsuitable for naive linear modeling without regime or volatility controls.

4. Recommended Join Key The Date column is the definitive join key for cross-dataset correlation work. Its perfect completeness (0 nulls), full uniqueness (9,895 distinct values matching total row count), and daily granularity make it ideal for temporal joins. When merging with lower-frequency datasets (monthly, quarterly), this column should be aggregated (e.g., monthly average or month-end value) prior to joining. ISO date formatting should be verified to ensure compatibility across source systems.

5. Suggested Correlation Datasets Several dataset categories would pair powerfully with this series: - U.S./Global Inflation (CPI) — oil is a primary driver of headline inflation; monthly CPI from BLS or OECD would reveal lead-lag relationships - Airline & Transportation Stock Prices — jet fuel costs directly track Brent, making airline equities a natural inverse-correlation candidate - USD/EUR or USD/USD Index (DXY) — crude oil is dollar-denominated, so currency strength often inversely correlates with price - Global GDP or Industrial Production indices — demand-side drivers of oil consumption from IMF or World Bank - Natural Gas Spot Prices (Henry Hub) — EIA also publishes this; fuel substitution dynamics create meaningful cross-commodity correlations - Geopolitical Risk Indices — events like Gulf Wars, OPEC cuts, and the Ukraine conflict are visible as structural breaks in this series

Columns

Date (date)
Europe Brent Spot Price FOB (Dollars per Barrel) (decimal)