OpenBB/website/content/sdk/data-available/economy.md

title, description, keywords

title	description	keywords
Economy	This page offers detailed instructions and examples on how to use the Economy module of the OpenBB terminal. This module provides user-friendly control over various financial and economic functionalities and metrics, enabling users to streamline their workflows in areas such as the management of API keys, data analysis with the many available functions, and querying data from prominent economic and financial databases including FRED and AlphaVantage.	Economy jupyter notebook API FRED AlphaVantage Financial analysis Data Visualization Quandl Nasdaq

import HeadTitle from '@site/src/components/General/HeadTitle.tsx';

The Economy module wraps the functions from the Economy menu of the OpenBB Terminal, and provides the user with more control over their workflow. In a Jupyter Notebook environment, it is quick and easy to get going. To get the most out of these functions, it is highly recommended to acquire API keys for:

• FRED
• Quandl/Nasdaq Data Link
• AlphaVantage

Define the keys for the OpenBB installation with:

openbb.keys.fred(key = 'REPLACE_ME', persist = True)
openbb.keys.quandl(key = 'REPLACE_ME', persist = True)
openbb.keys.av(key = 'REPLACE_ME', persist = True)

How to Use

Below is brief description of each function within the Economy module:

Path	Type	Description
openbb.economy.available_indices	Dictionary	Curated List of Global Indices
openbb.economy.balance	Function	Global Government Deficit/Surplus
openbb.economy.balance_chart	Function	Chart for balance
openbb.economy.bigmac	Function	The Big Mac Index
openbb.economy.bigmac_chart	Function	Chart for bigmac
openbb.economy.ccpi	Function	CPI Components Data by Country
openbb.economy.ccpi_chart	Function	Chart for ccpi
openbb.economy.country_codes	Function	List of Three-Letter ISO Country Codes
openbb.economy.cpi	Function	Harmonized CPI Data by Country
openbb.economy.cpi_chart	Function	Chart for cpi
openbb.economy.currencies	Function	Currencies from WSJ
openbb.economy.debt	Function	Government Debt-to-GDP Ratio
openbb.economy.debt_chart	Function	Chart for debt
openbb.economy.events	Function	Economic Calendar
openbb.economy.fgdp	Function	Real GDP Forecast by Country
openbb.economy.fgdp_chart	Function	Chart for fgdp
openbb.economy.fred	Function	Get FRED series data
openbb.economy.fred_ids	Function	Search for a FRED series ID by keyword
openbb.economy.fred_notes	Function	Search by Keyword for Series Information
openbb.economy.future	Function	Current Prices of Commodities and Futures from FinViz
openbb.economy.futures	Function	Current Prices of Commodities and Futures from WSJ
openbb.economy.gdp	Function	US GDP per Capita from AlphaVantage
openbb.economy.gdp_chart	Function	Chart for gdp
openbb.economy.get_groups	List	List of Groups for Performance and Valuation Functions
openbb.economy.glbonds	Function	Table of Select 10 Year Sovereign Bonds from WSJ
openbb.economy.index	Function	Historical Daily Data for Indices from YahooFinance
openbb.economy.index_chart	Function	Chart for index
openbb.economy.indices	Function	Top US Indices from WSJ
openbb.economy.macro	Function	Gets Series Data from EconDB
openbb.economy.macro_chart	Function	Chart for macro
openbb.economy.macro_countries	List	List of Countries Accepted by Macro Function
openbb.economy.macro_parameters	Dictionary	Dictionary of Parameters & Descriptions for Macro Function
openbb.economy.overview	Function	General Market Overview from WSJ
openbb.economy.perfmap	Function	Opens a Browser to Performance Map from Finviz
openbb.economy.performance	Function	Performance Data (get_groups)
openbb.economy.revenue	Function	Government Revenues by Country
openbb.economy.revenue_chart	Function	Chart for revenue
openbb.economy.rgdp	Function	Real GDP by Country
openbb.economy.rgdp_chart	Function	Chart for rgdp
openbb.economy.search_index	Function	Search for a Global Index by Name
openbb.economy.spending	Function	General Government Spending by Year and Country
openbb.economy.spending_chart	Function	Chart for spending
openbb.economy.treasury	Function	US Treasuries Data
openbb.economy.treasury_chart	Function	Chart for treasury
openbb.economy.treasury_maturities	Function	Table of Accepted Values for Maturities Argument in treasury
openbb.economy.trust	Function	Trust in Government (OECD) as a % by Country
openbb.economy.trust_chart	Function	Chart for trust
openbb.economy.usbonds	Function	Table of Current Rate, Yield, and Yield Change
openbb.economy.usdli	Function	The USD Liquidity Index
openbb.economy.usdli_chart	Function	Chart for usdli
openbb.economy.valuation	Function	Valuation for Group from (get_gropus)

Alternatively, the contents of the economy, or function docstrings, is printed with:

help(openbb.economy)

Examples

Import Statements

The examples will assume that this code block is included with the import statements:

from openbb_terminal.sdk import openbb
import pandas as pd

Index

The index function can request data using a couple of methods. There is a curated list of global indexes which can be entered by symbol or values from the left column of the table below.

indexes = pd.DataFrame.from_dict(openbb.economy.available_indices()).transpose()

indexes

	name	ticker
sp500	S&P 500 Index	^GSPC
sp400	S&P 400 Mid Cap Index	^SP400
sp600	S&P 600 Small Cap Index	^SP600
sp500tr	S&P 500 TR Index	^SP500TR
sp_xsp	S&P 500 Mini SPX Options Index	^XSP
cboe_tyx	CBOE 30 year Treasury Yields	^TYX
cboe_irx	CBOE 13 Week Treasury Bill	^IRX
move	ICE BofAML Move Index	^MOVE
dxy	US Dollar Index	DX-Y.NYB
crypto200	CMC Crypto 200 Index by Solacti	^CMC200

This list can be filtered:

filtered = indexes.name.str.contains('s&p', case = False)
indexes[filtered].head(10)

	name	ticker
sp500	S&P 500 Index	^GSPC
sp400	S&P 400 Mid Cap Index	^SP400
sp600	S&P 600 Small Cap Index	^SP600
sp500tr	S&P 500 TR Index	^SP500TR
sp_xsp	S&P 500 Mini SPX Options Index	^XSP
ca_banks	S&P/TSX Composite Banks Index (CAD)	TXBA.TS
ar_mervel	S&P MERVAL TR Index (USD)	M.BA
eu_speup	S&P Europe 350 Index (EUR)	^SPEUP
uk_spuk	S&P United Kingdom Index (PDS)	^SPUK
in_bse	S&P Bombay SENSEX (INR)	^BSESN

One index, or multiple, can be requested as a single DataFrame:

df = openbb.economy.index(indices = ['sp_energy_oil', 'sp_energy_equipment', 'sp_energy_ig'])

df.tail(3)

Date	sp_energy_oil	sp_energy_equipment	sp_energy_ig
2022-11-14 00:00:00	800.76	330.53	712.28
2022-11-15 00:00:00	809.27	335.84	720.16
2022-11-16 00:00:00	792.32	326.49	704.68

This can also be displayed as a chart:

openbb.economy.index_chart(indices = ['sp_energy_oil', 'sp_energy_equipment', 'sp_energy_ig'])

Performance

Performance metrics for sectors, industries, and regions (US listed) are printed with:

openbb.economy.performance(group = 'energy')

	Name	Week	Month	3Month	6Month	1Year	YTD	Recom	AvgVolume [1M]	RelVolume	Change	Volume [1M]
0	Oil & Gas Drilling	0.0106	0.2154	0.2501	0.1534	0.711	0.8991	1.92	33.58	0.71	-0.013	16.93
1	Oil & Gas E&P	0.0019	0.0618	0.1188	0.15	0.6602	0.6922	2.18	287.09	0.66	-0.0059	136.36
2	Oil & Gas Equipment & Services	-0.0063	0.1613	0.305	0.1219	0.493	0.5702	2.1	74.1	0.52	-0.0125	27.79
3	Oil & Gas Integrated	0.0166	0.0557	0.0885	0.0462	0.4014	0.4114	2.23	122.44	0.71	-0.0079	62.12
4	Oil & Gas Midstream	-0.0113	0.038	-0.019	0.0045	0.1551	0.2027	2.3	105.55	0.65	-0.0115	48.8
5	Oil & Gas Refining & Marketing	0.0147	0.0929	0.1562	0.1585	0.6038	0.6084	2.13	30.59	0.61	-0.0006	13.32
6	Thermal Coal	-0.0096	0.0291	-0.0494	0.1289	1.2305	1.0504	1.97	8.74	0.69	-0.0207	4.28
7	Uranium	-0.0176	0.0416	0.0856	0.0426	-0.1746	0.0267	1.61	32.44	0.54	-0.0125	12.58

Performance by sector:

openbb.economy.performance(group = 'sector')

	Name	Week	Month	3Month	6Month	1Year	YTD	Recom	AvgVolume [1M]	RelVolume	Change	Volume [1M]
0	Basic Materials	-0.0032	0.129	0.0195	-0.0572	-0.0684	-0.0928	2.22	469.94	0.66	-0.0116	222.2
1	Communication Services	0.0343	0.0128	-0.1444	-0.1297	-0.3837	-0.3529	1.97	731.34	0.72	0.0004	377.12
2	Consumer Cyclical	0.0111	0.0266	-0.1386	-0.0182	-0.3665	-0.3221	2.14	1430	1.01	-0.0034	1040
3	Consumer Defensive	0.003	0.0757	-0.0302	0.0573	-0.019	-0.0574	2.31	298.74	0.85	-0.0019	181.95
4	Energy	0.0067	0.0629	0.0913	0.0736	0.4208	0.4497	2.21	694.52	0.65	-0.008	322.19
5	Financial	-0.0095	0.0934	-0.0098	0.0339	-0.1259	-0.1137	2.24	861.74	0.79	-0.005	489.78
6	Healthcare	-0.0121	0.0703	-0.0125	0.0177	-0.1074	-0.1161	2.11	1180	0.87	0.0002	736.58
7	Industrials	-0.0118	0.0969	-0.0223	0.0723	-0.1138	-0.101	2.32	573.08	0.7	-0.005	285.24
8	Real Estate	-0.0259	0.0884	-0.1441	-0.0961	-0.2413	-0.2738	2.18	341.84	0.55	-0.0055	134.66
9	Technology	0.0149	0.0938	-0.1095	-0.0044	-0.3024	-0.2957	2.03	1460	0.86	0.0039	904.44
10	Utilities	-0.0235	0.0485	-0.1212	-0.0582	-0.0054	-0.0569	2.29	166.21	0.67	-0.0142	79.25

Events

A global economic calendar is accessible through the events function:

help(openbb.economy.events)

Help on Operation in module openbb_terminal.core.library.operation:

<openbb_terminal.core.library.operation.Operation object>
    Get economic calendar for countries between specified dates

    Parameters
    ----------
    countries : [List[str],str]
        List of countries to include in calendar.  Empty returns all
    start_date : str
        Start date for calendar
    end_date : str
        End date for calendar

    Returns
    -------
    pd.DataFrame
        Economic calendar

With no arguments, events will return the calendar from today:

openbb.economy.events().head(10)

	Time (ET)	Country	Event	Actual	Consensus	Previous	Date
0	01:45	Germany	German Buba President Nagel Speaks	-	-	-	2023-04-13
1	01:45	Germany	German Buba Vice President Buch Speaks	-	-	-	2023-04-13
2	02:00	United Kingdom	Construction Output	2.4%	0.9%	-1.7%	2023-04-13
3	02:00	United Kingdom	U.K. Construction Output	5.7%	1.6%	3.3%	2023-04-13
4	02:00	United Kingdom	GDP	0.0%	0.1%	0.4%	2023-04-13
5	02:00	United Kingdom	Index of Services	0.1%	-0.2%	0.1%	2023-04-13
6	02:00	United Kingdom	Industrial Production	-0.2%	0.2%	-0.5%	2023-04-13
7	02:00	United Kingdom	Industrial Production	-3.1%	-3.7%	-3.2%	2023-04-13
8	02:00	United Kingdom	Manufacturing Production	-2.4%	-4.7%	-2.8%	2023-04-13
9	02:00	United Kingdom	Manufacturing Production	0.0%	0.2%	-0.1%	2023-04-13

Calendar events can be requested for a specific countries and date ranges:

openbb.economy.events(countries = ['United States'], start_date = '2022-11-18', end_date = '2022-11-18').head(5)

	Time (ET)	Country	Event	Actual	Consensus	Previous	Date
0	09:40	United States	Fed Collins Speaks	-	-	-	2022-11-18
1	11:00	United States	Existing Home Sales	-5.9%	-	-1.5%	2022-11-18
2	11:00	United States	Existing Home Sales	4.43M	4.38M	4.71M	2022-11-18
3	11:00	United States	US Leading Index	-0.8%	-0.4%	-0.5%	2022-11-18
4	14:00	United States	U.S. Baker Hughes Oil Rig Count	623	-	622	2022-11-18

FRED

Search the FRED database for a series titles containing keywords:

series_ids = openbb.economy.fred_ids(search_query = 'Oil and Gas')

series_ids.head(5)

id	title
PCU333132333132	Producer Price Index by Industry: Oil and Gas Field Machinery and Equipment Manufacturing
CES1021100001	All Employees, Oil and Gas Extraction
IPG211111CS	Industrial Production: Mining, Quarrying, and Oil and Gas Extraction: Crude Oil (NAICS = 211111pt.)
A33DNO	Manufacturers' New Orders: Mining, Oil, and Gas Field Machinery Manufacturing
PCU21112111	Producer Price Index by Industry: Oil and Gas Extraction

Macro

The macro function will return a Tuple. See refer to the docstring below to see the input arguments:

help(openbb.economy.macro)

Help on Operation in module openbb_terminal.core.library.operation:

<openbb_terminal.core.library.operation.Operation object>
    Use 'economy.macro_chart' to access the view.
    This functions groups the data queried from the EconDB database [Source: EconDB]

        Parameters
        ----------
        parameters: list
            The type of data you wish to download. Available parameters can be accessed through economy.macro_parameters().
        countries : list
            The selected country or countries. Available countries can be accessed through economy.macro_countries().
        transform : str
            The selected transform. Available transforms can be accessed through get_macro_transform().
        start_date : str
            The starting date, format "YEAR-MONTH-DAY", i.e. 2010-12-31.
        end_date : str
            The end date, format "YEAR-MONTH-DAY", i.e. 2020-06-05.
        symbol : str
            In what currency you wish to convert all values.

        Returns
        -------
        Tuple[pd.DataFrame, Dict[Any, Dict[Any, Any]], str]
            A DataFrame with the requested macro data of all chosen countries,
            A dictionary containing the units of each country's parameter (e.g. EUR),
            A string denomination which can be Trillions, Billions, Millions, Thousands

        Examples
        --------
        >>> from openbb_terminal.sdk import openbb
        >>> macro_df = openbb.economy.macro()

openbb.economy.macro_parameters() will return a list of dictionaries. Read it as a DataFrame with:

parameters = pd.DataFrame.from_dict(openbb.economy.macro_parameters()).transpose()

parameters.tail(5)

	name	period	description
Y10YD	Long term yield (10-year)	Monthly	The 10-year yield is used as a proxy for mortgage rates. It's also seen as a sign of investor sentiment about the country's economy.
M3YD	3 month yield	Monthly	The yield received for investing in a government issued treasury security that has a maturity of 3 months
HOU	House price index	Monthly	House price index defined with base 2015 for Europe with varying bases for others. See: https://www.econdb.com/main-indicators
OILPROD	Oil production	Monthly	The amount of oil barrels produced per day in a month within a country.
POP	Population	Monthly	The population of a country. This can be in thousands or, when relatively small, in actual units.

The data from the macro function is unpacked like:

data,units,denomination = openbb.economy.macro(parameters = ['Y10YD'], countries = ['United States', 'Poland', 'France', 'Italy', 'Spain', 'Germany'])

data.tail(10)

date	France	Germany	Italy	Poland	Spain	United States
2022-05-01	1.52	0.95	2.99	6.64	2.04	2.9
2022-06-01	2.06	1.45	3.64	7.14	2.63	3.14
2022-07-01	1.71	1.08	3.36	6.37	2.31	2.9
2022-08-01	1.69	1.03	3.3	5.8	2.15	2.9
2022-09-01	2.41	1.8	4.14	6.28	2.92	3.52
2022-10-01	2.77	2.19	4.53	7.82	3.29	3.98
2022-11-01	2.58	2.07	4.24	7.24	3.07	3.89
2022-12-01	2.62	2.09	4.26	6.61	3.09	3.62
2023-01-01	2.69	2.19	4.24	6.02	3.2	3.53
2023-02-01	2.87	2.37	4.27	6.18	3.39	3.75