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FinzData
/
macro-energy

Modalities:
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Formats:
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Languages:
English
Size:
100K - 1M
Tags:
finance
economics
macroeconomics
time-series
fred
energy
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pandas
Polars
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Dataset card Data Studio Files
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FinzData commited on
Commit
1c1bcac
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verified ·
1 Parent(s): 9550839

Weekly refresh 2026-10-31

Browse files
Files changed (6) hide show
  1. README.md +36 -34
  2. data/long.csv +0 -0
  3. data/long.parquet +2 -2
  4. data/wide_daily.parquet +3 -0
  5. data/wide_weekly.parquet +2 -2
  6. series.csv +0 -0
README.md CHANGED
@@ -14,29 +14,31 @@ tags:
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  - quant
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  - backtesting
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  size_categories:
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- - 10K<n<100K
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  configs:
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  - config_name: long
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  data_files: data/long.parquet
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  default: true
 
 
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  - config_name: wide_weekly
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  data_files: data/wide_weekly.parquet
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  - config_name: wide_monthly
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  data_files: data/wide_monthly.parquet
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  ---
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- # US macro data: Energy (1,345 series)
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- 1,345 energy series from US government sources, cleaned into one consistent format and ready for pandas.
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  This free package holds the **last 12 months** (2025-10-31 on) of each series' latest values. It is refreshed weekly.
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33
  ```python
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  import pandas as pd
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  df = pd.read_parquet("hf://datasets/FinzData/macro-energy/data/long.parquet") # series_id, date, value
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- wide = pd.read_parquet("hf://datasets/FinzData/macro-energy/data/wide_weekly.parquet") # one column per series
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  ```
38
 
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- or `datasets.load_dataset("FinzData/macro-energy")`. Wide tables by frequency: `wide_weekly` (7 series), `wide_monthly` (1338 series). `series.csv` lists every series
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  with its title, units, frequency and how far back the full history goes.
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  ## The full history, point in time, through one API
@@ -46,9 +48,9 @@ date, so backtests do not peek at later revisions), and **daily updates**, in th
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  ```python
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  import finzdata as fz # pip install finzdata
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  c = fz.Client() # free API key: https://api.finzdata.com/
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- c.macro("FZELEC_ARG_DEMAND") # full history, latest values
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- c.macro("FZELEC_ARG_DEMAND", vintage="first") # as first released
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- c.macro("FZELEC_ARG_DEMAND", as_of="2020-03-01") # exactly what was known on that date
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  c.macro_series(category="energy") # the catalogue for this category
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  ```
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@@ -56,33 +58,33 @@ c.macro_series(category="energy") # the catalogue for this category
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  | ID | Title | Units | Frequency | Full history from |
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  |---|---|---|---|---|
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- | `FZELEC_ARG_DEMAND` | Electricity demand: Argentina | Terawatt-hours | Monthly | 2018 |
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- | `FZELEC_ARM_DEMAND` | Electricity demand: Armenia | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_ASEAN_DEMAND` | Electricity demand: ASEAN | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_ASIA_DEMAND` | Electricity demand: Asia | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_AUS_DEMAND` | Electricity demand: Australia | Terawatt-hours | Monthly | 1999 |
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- | `FZELEC_AUT_DEMAND` | Electricity demand: Austria | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_AZE_DEMAND` | Electricity demand: Azerbaijan | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_BEL_DEMAND` | Electricity demand: Belgium | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_BGD_DEMAND` | Electricity demand: Bangladesh | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_BGR_DEMAND` | Electricity demand: Bulgaria | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_BIH_DEMAND` | Electricity demand: Bosnia Herzegovina | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_BLR_DEMAND` | Electricity demand: Belarus | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_BOL_DEMAND` | Electricity demand: Bolivia | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_BRA_DEMAND` | Electricity demand: Brazil | Terawatt-hours | Monthly | 2018 |
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- | `FZELEC_CAN_DEMAND` | Electricity demand: Canada | Terawatt-hours | Monthly | 2010 |
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- | `FZELEC_CHE_DEMAND` | Electricity demand: Switzerland | Terawatt-hours | Monthly | 2017 |
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- | `FZELEC_CHL_DEMAND` | Electricity demand: Chile | Terawatt-hours | Monthly | 2016 |
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- | `FZELEC_CHN_DEMAND` | Electricity demand: China | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_COL_DEMAND` | Electricity demand: Colombia | Terawatt-hours | Monthly | 2016 |
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- | `FZELEC_CRI_DEMAND` | Electricity demand: Costa Rica | Terawatt-hours | Monthly | 2019 |
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- | `FZELEC_CYP_DEMAND` | Electricity demand: Cyprus | Terawatt-hours | Monthly | 2017 |
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- | `FZELEC_CZE_DEMAND` | Electricity demand: Czechia | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_DEU_DEMAND` | Electricity demand: Germany | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_DNK_DEMAND` | Electricity demand: Denmark | Terawatt-hours | Monthly | 2015 |
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- | `FZELEC_DOM_DEMAND` | Electricity demand: Dominican Republic | Terawatt-hours | Monthly | 2022 |
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- All 1,345 series: `series.csv`. Browse them at https://finzdata.com/macro/category/energy.
86
 
87
  ## More from FinzData
88
  - Every macro category: https://huggingface.co/FinzData · index on GitHub: https://github.com/FinzData/macro-data
 
14
  - quant
15
  - backtesting
16
  size_categories:
17
+ - 100K<n<1M
18
  configs:
19
  - config_name: long
20
  data_files: data/long.parquet
21
  default: true
22
+ - config_name: wide_daily
23
+ data_files: data/wide_daily.parquet
24
  - config_name: wide_weekly
25
  data_files: data/wide_weekly.parquet
26
  - config_name: wide_monthly
27
  data_files: data/wide_monthly.parquet
28
  ---
29
 
30
+ # US macro data: Energy (2,021 series)
31
 
32
+ 2,021 energy series from US government sources, cleaned into one consistent format and ready for pandas.
33
  This free package holds the **last 12 months** (2025-10-31 on) of each series' latest values. It is refreshed weekly.
34
 
35
  ```python
36
  import pandas as pd
37
  df = pd.read_parquet("hf://datasets/FinzData/macro-energy/data/long.parquet") # series_id, date, value
38
+ wide = pd.read_parquet("hf://datasets/FinzData/macro-energy/data/wide_daily.parquet") # one column per series
39
  ```
40
 
41
+ or `datasets.load_dataset("FinzData/macro-energy")`. Wide tables by frequency: `wide_daily` (487 series), `wide_weekly` (196 series), `wide_monthly` (1338 series). `series.csv` lists every series
42
  with its title, units, frequency and how far back the full history goes.
43
 
44
  ## The full history, point in time, through one API
 
48
  ```python
49
  import finzdata as fz # pip install finzdata
50
  c = fz.Client() # free API key: https://api.finzdata.com/
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+ c.macro("FZCURVE_BRENT_WTI") # full history, latest values
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+ c.macro("FZCURVE_BRENT_WTI", vintage="first") # as first released
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+ c.macro("FZCURVE_BRENT_WTI", as_of="2020-03-01") # exactly what was known on that date
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  c.macro_series(category="energy") # the catalogue for this category
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  ```
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  | ID | Title | Units | Frequency | Full history from |
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  |---|---|---|---|---|
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+ | `FZCURVE_BRENT_WTI` | Brent minus WTI (front-month futures) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_CARRY` | Brent crude oil roll yield (M1 vs M2, annualised) | Percent | Daily | 2008 |
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+ | `FZCURVE_BZ_M1` | Brent crude oil futures curve: month 1 (M1) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M10` | Brent crude oil futures curve: month 10 (M10) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M11` | Brent crude oil futures curve: month 11 (M11) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M12` | Brent crude oil futures curve: month 12 (M12) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M1M12` | Brent crude oil calendar spread, M1 minus M12 | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M1M2` | Brent crude oil calendar spread, M1 minus M2 | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M1M3` | Brent crude oil calendar spread, M1 minus M3 | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M1M6` | Brent crude oil calendar spread, M1 minus M6 | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M2` | Brent crude oil futures curve: month 2 (M2) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M3` | Brent crude oil futures curve: month 3 (M3) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M4` | Brent crude oil futures curve: month 4 (M4) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M5` | Brent crude oil futures curve: month 5 (M5) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M6` | Brent crude oil futures curve: month 6 (M6) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M7` | Brent crude oil futures curve: month 7 (M7) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M8` | Brent crude oil futures curve: month 8 (M8) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_BZ_M9` | Brent crude oil futures curve: month 9 (M9) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_CL_CARRY` | WTI crude oil roll yield (M1 vs M2, annualised) | Percent | Daily | 2008 |
80
+ | `FZCURVE_CL_M1` | WTI crude oil futures curve: month 1 (M1) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_CL_M10` | WTI crude oil futures curve: month 10 (M10) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_CL_M11` | WTI crude oil futures curve: month 11 (M11) | Dollars per Barrel | Daily | 2008 |
83
+ | `FZCURVE_CL_M12` | WTI crude oil futures curve: month 12 (M12) | Dollars per Barrel | Daily | 2008 |
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+ | `FZCURVE_CL_M1M12` | WTI crude oil calendar spread, M1 minus M12 | Dollars per Barrel | Daily | 2008 |
85
+ | `FZCURVE_CL_M1M2` | WTI crude oil calendar spread, M1 minus M2 | Dollars per Barrel | Daily | 2008 |
86
 
87
+ All 2,021 series: `series.csv`. Browse them at https://finzdata.com/macro/category/energy.
88
 
89
  ## More from FinzData
90
  - Every macro category: https://huggingface.co/FinzData · index on GitHub: https://github.com/FinzData/macro-data
data/long.csv CHANGED
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data/long.parquet CHANGED
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series.csv CHANGED
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