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| license: other | |
| license_name: public-domain-source-us-government | |
| pretty_name: "US Macro Data: Commodities" | |
| language: | |
| - en | |
| tags: | |
| - finance | |
| - economics | |
| - macroeconomics | |
| - time-series | |
| - fred | |
| - commodities | |
| - quant | |
| - backtesting | |
| size_categories: | |
| - 1K<n<10K | |
| configs: | |
| - config_name: long | |
| data_files: data/long.parquet | |
| default: true | |
| - config_name: wide_daily | |
| data_files: data/wide_daily.parquet | |
| - config_name: wide_weekly | |
| data_files: data/wide_weekly.parquet | |
| - config_name: wide_monthly | |
| data_files: data/wide_monthly.parquet | |
| - config_name: wide_quarterly | |
| data_files: data/wide_quarterly.parquet | |
| # US macro data: Commodities (59 series) | |
| 59 commodities series from US government sources, cleaned into one consistent format and ready for pandas. | |
| This free package holds the **last 12 months** (2025-11-03 on) of each series' latest values. It is refreshed weekly. | |
| ```python | |
| import pandas as pd | |
| df = pd.read_parquet("hf://datasets/FinzData/macro-commodities/data/long.parquet") # series_id, date, value | |
| wide = pd.read_parquet("hf://datasets/FinzData/macro-commodities/data/wide_daily.parquet") # one column per series | |
| ``` | |
| or `datasets.load_dataset("FinzData/macro-commodities")`. Wide tables by frequency: `wide_daily` (7 series), `wide_weekly` (4 series), `wide_monthly` (37 series), `wide_quarterly` (11 series). `series.csv` lists every series | |
| with its title, units, frequency and how far back the full history goes. | |
| ## The full history, point in time, through one API | |
| The FinzData API serves every series back to its first observation, **every revision** (what was known on any past | |
| date, so backtests do not peek at later revisions), and **daily updates**, in the same format: | |
| ```python | |
| import finzdata as fz # pip install finzdata | |
| c = fz.Client() # free API key: https://api.finzdata.com/ | |
| c.macro("MSPUS") # full history, latest values | |
| c.macro("MSPUS", vintage="first") # as first released | |
| c.macro("MSPUS", as_of="2020-03-01") # exactly what was known on that date | |
| c.macro_series(category="commodities") # the catalogue for this category | |
| ``` | |
| ## Most-watched series in this package | |
| | ID | Title | Units | Frequency | Full history from | | |
| |---|---|---|---|---| | |
| | `MSPUS` | Median Sales Price of New Houses Sold for the United States | Dollars | Quarterly | 1963 | | |
| | `DCOILWTICO` | Crude Oil Prices: West Texas Intermediate (WTI) - Cushing, Oklahoma | Dollars per Barrel | Daily | 1986 | | |
| | `ASPUS` | Average Sales Price of Houses Sold for the United States | Dollars | Quarterly | 1963 | | |
| | `APU000074714` | Average Price: Gasoline, Unleaded Regular (Cost per Gallon/3.785 Liters) in U.S. City Average | U.S. Dollars | Monthly | 1976 | | |
| | `DHHNGSP` | Henry Hub Natural Gas Spot Price | Dollars per Million BTU | Daily | 1997 | | |
| | `WTISPLC` | Spot Crude Oil Price: West Texas Intermediate (WTI) | Dollars per Barrel | Monthly | 1946 | | |
| | `MCOILWTICO` | Crude Oil Prices: West Texas Intermediate (WTI) - Cushing, Oklahoma | Dollars per Barrel | Monthly | 1986 | | |
| | `APU00007471A` | Average Price: Gasoline, All Types (Cost per Gallon/3.785 Liters) in U.S. City Average | U.S. Dollars | Monthly | 1978 | | |
| | `MHHNGSP` | Henry Hub Natural Gas Spot Price | Dollars per Million BTU | Monthly | 1997 | | |
| | `DHOILNYH` | No. 2 Heating Oil Prices: New York Harbor | Dollars per Gallon | Daily | 1986 | | |
| | `WCOILWTICO` | Crude Oil Prices: West Texas Intermediate (WTI) - Cushing, Oklahoma | Dollars per Barrel | Weekly, Ending Friday | 1986 | | |
| | `APU000072511` | Average Price: Fuel Oil #2 per Gallon (3.785 Liters) in U.S. City Average | U.S. Dollars | Monthly | 1978 | | |
| | `IEAXGG` | Exports of Goods: Nonmonetary gold | Millions of Dollars | Quarterly | 1999 | | |
| | `DGASUSGULF` | Conventional Gasoline Prices: U.S. Gulf Coast, Regular | Dollars per Gallon | Daily | 1986 | | |
| | `FRDGBSAM` | Federal Reserve Bank Held Gold Bullion: On Display | Fine Troy Ounces | Monthly | 2012 | | |
| | `G20XTIMVA01CXMLQ` | International Merchandise Trade Statistics: Imports: Commodities for G20 | US dollars, exchange rate converted | Quarterly | 2005 | | |
| | `WHHNGSP` | Henry Hub Natural Gas Spot Price | Dollars per Million BTU | Weekly | 1997 | | |
| | `APUS12A74714` | Average Price: Gasoline, Unleaded Regular (Cost per Gallon/3.785 Liters) in New York-Newark-Jersey City, NY-NJ-PA (CBSA) | U.S. Dollars | Monthly | 1978 | | |
| | `APUS48A74714` | Average Price: Gasoline, Unleaded Regular (Cost per Gallon/3.785 Liters) in Phoenix-Mesa-Scottsdale, AZ (CBSA) | U.S. Dollars | Monthly | 2018 | | |
| | `DGASNYH` | Conventional Gasoline Prices: New York Harbor, Regular | Dollars per Gallon | Daily | 1986 | | |
| | `APU0000702212` | Average Price: Bread, Whole Wheat, Pan (Cost per Pound/453.6 Grams) in U.S. City Average | U.S. Dollars | Monthly | 1980 | | |
| | `MNGLCP` | U.S. Natural Gas Liquid Composite Price | Dollars per Million BTU | Monthly | 2009 | | |
| | `APUS23B74716` | Average Price: Gasoline, Unleaded Premium (Cost per Gallon/3.785 Liters) in Detroit-Warren-Dearborn, MI (CBSA) | U.S. Dollars | Monthly | 1981 | | |
| | `G20XTIMVA01CXMLSAQ` | International Merchandise Trade Statistics: Imports: Commodities for G20 | US dollars, exchange rate converted | Quarterly | 1999 | | |
| | `IPG211S` | Industrial Production: Mining: Oil and Gas Extraction (NAICS = 211) | Index 2017=100 | Monthly | 1972 | | |
| All 59 series: `series.csv`. Browse them at https://finzdata.com/macro/category/commodities. | |
| ## More from FinzData | |
| - Every macro category: https://huggingface.co/FinzData · index on GitHub: https://github.com/FinzData/macro-data | |
| - Survivorship-free US stock prices since 2000, COT positioning, 13F holdings, insider trades, short interest | |
| - Pricing (history bundles from $195 once): https://finzdata.com/pricing | |
| - Python client (open source): https://github.com/FinzData/finzdata-python | |
| Source: U.S. government agencies via FRED/ALFRED (Federal Reserve Bank of St. Louis). Compiled by FinzData. | |
| Data for research, not investment advice. | |