fredgraph.csv?id=DCOILBRENTEU — Direct CSV Download (Brent Oil)
Brent crude oil is the international benchmark for petroleum pricing, used to price approximately two-thirds of the world’s traded crude. The WTI-Brent spread reflects US-specific supply dynamics versus global market conditions. Daily observations from FRED series DCOILBRENTEU.
Dataset: Brent Crude Oil Price (1987–2026) · Updated —
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Source: FRED series DCOILBRENTEU · Federal Reserve Bank of St. Louis
Macro Takeaway
This indicator is a key component of the macro-financial monitoring framework. Its current level relative to its historical distribution — captured in the percentile and z-score above — provides immediate context for whether conditions are historically normal, stretched, or compressed.
Cross-referencing with the 10-year Treasury yield and the yield curve spread helps situate this indicator within the broader macro regime.
Dataset Overview
| Indicator | Brent Crude Oil Price (1987–2026) |
|---|---|
| Geography | United States |
| Frequency | Daily (business days) |
| Period | 1987–2026 |
| Variables | date, brent_price_usd |
| Format | CSV, Excel (XLSX) |
| Sources | Federal Reserve Bank of St. Louis — FRED |
| Last updated | — |
Dataset Variables
The CSV and Excel files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation date |
brent_price_usd | Float | brent_price_usd value |
Column names match the CSV headers exactly.
Download the Complete Dataset
The full dataset is available in CSV and Excel formats.
FRED Direct CSV Access
The underlying data is available from FRED under series code DCOILBRENTEU:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=DCOILBRENTEU
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/brent-crude-oil.csv
This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.
Using the Dataset in Python
import pandas as pd url = "https://eco3min.fr/dataset/brent-crude-oil.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["dcoilbrenteu"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/brent-crude-oil.csv" df <- read_csv(url) head(df) summary(df$dcoilbrenteu)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
The primary data source is the Federal Reserve’s FRED database, series DCOILBRENTEU. The data is published by the relevant US government agency and made available through FRED with consistent formatting and metadata.
This dataset is updated weekly (Saturday 08:00 UTC) via automated pull from the FRED API.
Historical Regimes
Historical regime analysis for this dataset will be added in a future update. The key stats block above provides immediate context for the current reading relative to the full historical distribution.
Related Macroeconomic Datasets
Brent is the global energy benchmark — used to price approximately two-thirds of the world’s traded crude. The WTI-Brent spread reveals whether oil dynamics are US-specific (shale production, inventory draws) or global (OPEC decisions, geopolitical disruptions). Pairing with inflation measures captures the transmission to the real economy.
- WTI Crude Oil Price — The US benchmark; the WTI-Brent spread reveals geographic dynamics
- US CPI Inflation History — Energy’s direct contribution to headline inflation
- Core CPI Inflation — Second-round energy effects with 12–18 month lag
- US Dollar Index (DTWEXBGS) — Dollar strength inversely correlates with oil prices
- US 10-Year Treasury Yield — Rate response to energy-driven inflation
Related Research
Energy prices interact with the macro-financial system through inflation, monetary policy reactions, and dollar dynamics. The research below documents the frameworks connecting commodity shocks, real interest rates, and global crises.
Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
Explore the Eco3min Dataset Hub
Sources
- Federal Reserve Bank of St. Louis — FRED database