Brent Daily Spot Prices
- Rows
- 9,947
- Columns
- 2
Daily Europe Brent crude oil spot prices in USD per barrel from 1987-05-20 to present. Clean CSV time series derived from EIA data.
AI analysis
Data Analyst Review: Brent Daily Spot Prices
1. Dataset Overview and Value
This dataset provides a long-running daily time series of Europe Brent crude oil spot prices (USD/barrel) spanning nearly 39 years, from May 20, 1987 through May 18, 2026. Sourced via datahub.io's curated "core/oil-prices" package (itself derived from the U.S. Energy Information Administration, a highly authoritative primary source), this is a clean, well-maintained CSV that appears to be actively refreshed — the coverage extending to a near-current date suggests a live or frequently-updated feed rather than a static historical snapshot. Given oil's role as a macroeconomic bellwether, this dataset has strong potential value as an independent variable in correlation studies involving inflation, energy stocks, currency movements (especially petrocurrencies like CAD, NOK, RUB), transportation costs, and geopolitical event studies.
2. Data Quality Observations
Quality signals here are excellent on the surface: zero null cells across both columns, and the Date column shows 9,893 distinct values matching the 9,893 row count — implying no duplicate dates within this reported distinct count, though the formal duplicate-row recomputation (Phase D) is still pending and should be confirmed before finalizing joins. No disproportionate nulls exist in either column. One caveat worth flagging: daily financial time series like this typically have gaps for weekends/holidays (markets closed), so the "9,893 rows" likely reflects trading days only, not calendar days — this is a structural characteristic to account for when aligning with datasets that use full calendar-day indexing.
3. Key Column Distributions
The Price column is the analytical heart of this dataset, ranging from a low of $9.10 to a high of $143.95, with a mean of $51.16 and median of $46.09 — the mean exceeding the median, combined with a positive skew of 0.563, indicates a right-tailed distribution where high-price spikes (e.g., 2008 and 2022 crisis peaks) pull the average upward relative to typical trading levels. The interquartile range ($19.54 to $74.78) spans a wide $55.24, reflecting the dramatic regime shifts oil prices have undergone across multiple boom-bust cycles (1990s lows, 2008 spike/crash, 2014-16 collapse, 2020 COVID crash, 2022 spike). With 5,493 distinct price values against 9,893 rows, there's meaningful repetition, likely from price plateaus during low-volatility periods or rounding conventions. This distribution shape suggests analysts should consider log-transforming price or using returns/percent-change rather than raw levels when running correlation or regression analyses, to reduce heteroscedasticity and skew effects.
4. Recommended Join Keys
The Date column is the clear and only viable join key — it's complete (zero nulls), fully distinct (9,893 unique values, one per row), and spans a well-defined, labeled range. For cross-dataset joins, analysts should standardize on ISO date format and explicitly decide how to handle non-trading days (weekends/holidays) when merging with calendar-complete datasets — options include forward-filling the last known price, resampling both datasets to a common frequency (weekly/monthly), or restricting joins to business-day-only external series.
5. Suggested Pairings for Correlation Discovery
Strong candidates for correlation analysis include: (a) macroeconomic indicators like CPI/inflation indices, U.S. dollar index (DXY), and interest rate series to explore energy-driven inflation dynamics; (b) equity market indices, particularly energy-sector ETFs (XLE), airline/transportation stocks, and broad indices like the S&P 500 for risk-sentiment linkages; (c) currency exchange rates for oil-exporting nations (RUB, NOK, CAD, SAR); (d) other energy commodities (WTI crude, natural gas, coal) to examine spread dynamics and substitution effects; and (e) geopolitical event datasets or OPEC production/quota announcements to contextualize price shocks. Given the dataset's near-40-year depth, it's also well-suited for structural break analysis and volatility regime studies alongside VIX or other market-stress indices.
Columns
- Date (date)
- Price (decimal)
