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374 lines
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Markdown
Vendored
---
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title: Economy
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description: This page offers detailed instructions and examples on how to use the
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Economy module of the OpenBB terminal. This module provides user-friendly control
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over various financial and economic functionalities and metrics, enabling users
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to streamline their workflows in areas such as the management of API keys, data
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analysis with the many available functions, and querying data from prominent economic
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and financial databases including FRED and AlphaVantage.
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keywords:
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- Economy
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- jupyter notebook
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- API
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- FRED
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- AlphaVantage
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- Financial analysis
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- Data Visualization
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- Quandl
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- Nasdaq
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---
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import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
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<HeadTitle title="Economy - Intros - Usage | OpenBB SDK Docs" />
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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:
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- [FRED](https://fred.stlouisfed.org)
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- [Quandl/Nasdaq Data Link](https://data.nasdaq.com)
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- [AlphaVantage](https://www.alphavantage.co/)
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Define the keys for the OpenBB installation with:
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```python
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openbb.keys.fred(key = 'REPLACE_ME', persist = True)
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openbb.keys.quandl(key = 'REPLACE_ME', persist = True)
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openbb.keys.av(key = 'REPLACE_ME', persist = True)
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```
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## How to Use
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Below is brief description of each function within the Economy module:
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| Path | Type | Description |
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| :---------------------------------- | :--------: | -------------------------------------------------------------: |
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| openbb.economy.available_indices | Dictionary | Curated List of Global Indices |
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| openbb.economy.balance | Function | Global Government Deficit/Surplus |
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| openbb.economy.balance_chart | Function | Chart for `balance` |
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| openbb.economy.bigmac | Function | The Big Mac Index |
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| openbb.economy.bigmac_chart | Function | Chart for `bigmac` |
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| openbb.economy.ccpi | Function | CPI Components Data by Country |
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| openbb.economy.ccpi_chart | Function | Chart for `ccpi` |
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| openbb.economy.country_codes | Function | List of Three-Letter ISO Country Codes |
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| openbb.economy.cpi | Function | Harmonized CPI Data by Country |
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| openbb.economy.cpi_chart | Function | Chart for `cpi` |
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| openbb.economy.currencies | Function | Currencies from WSJ |
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| openbb.economy.debt | Function | Government Debt-to-GDP Ratio |
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| openbb.economy.debt_chart | Function | Chart for `debt` |
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| openbb.economy.events | Function | Economic Calendar |
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| openbb.economy.fgdp | Function | Real GDP Forecast by Country |
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| openbb.economy.fgdp_chart | Function | Chart for `fgdp` |
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| openbb.economy.fred | Function | Get FRED series data |
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| openbb.economy.fred_ids | Function | Search for a FRED series ID by keyword |
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| openbb.economy.fred_notes | Function | Search by Keyword for Series Information |
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| openbb.economy.future | Function | Current Prices of Commodities and Futures from FinViz |
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| openbb.economy.futures | Function | Current Prices of Commodities and Futures from WSJ |
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| openbb.economy.gdp | Function | US GDP per Capita from AlphaVantage |
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| openbb.economy.gdp_chart | Function | Chart for `gdp` |
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| openbb.economy.get_groups | List | List of Groups for Performance and Valuation Functions |
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| openbb.economy.glbonds | Function | Table of Select 10 Year Sovereign Bonds from WSJ |
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| openbb.economy.index | Function | Historical Daily Data for Indices from YahooFinance |
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| openbb.economy.index_chart | Function | Chart for `index` |
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| openbb.economy.indices | Function | Top US Indices from WSJ |
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| openbb.economy.macro | Function | Gets Series Data from EconDB |
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| openbb.economy.macro_chart | Function | Chart for `macro` |
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| openbb.economy.macro_countries | List | List of Countries Accepted by Macro Function |
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| openbb.economy.macro_parameters | Dictionary | Dictionary of Parameters & Descriptions for Macro Function |
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| openbb.economy.overview | Function | General Market Overview from WSJ |
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| openbb.economy.perfmap | Function | Opens a Browser to Performance Map from Finviz |
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| openbb.economy.performance | Function | Performance Data (get_groups) |
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| openbb.economy.revenue | Function | Government Revenues by Country |
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| openbb.economy.revenue_chart | Function | Chart for `revenue` |
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| openbb.economy.rgdp | Function | Real GDP by Country |
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| openbb.economy.rgdp_chart | Function | Chart for `rgdp` |
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| openbb.economy.search_index | Function | Search for a Global Index by Name |
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| openbb.economy.spending | Function | General Government Spending by Year and Country |
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| openbb.economy.spending_chart | Function | Chart for `spending` |
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| openbb.economy.treasury | Function | US Treasuries Data |
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| openbb.economy.treasury_chart | Function | Chart for `treasury` |
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| openbb.economy.treasury_maturities | Function | Table of Accepted Values for Maturities Argument in `treasury` |
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| openbb.economy.trust | Function | Trust in Government (OECD) as a % by Country |
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| openbb.economy.trust_chart | Function | Chart for `trust` |
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| openbb.economy.usbonds | Function | Table of Current Rate, Yield, and Yield Change |
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| openbb.economy.usdli | Function | The USD Liquidity Index |
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| openbb.economy.usdli_chart | Function | Chart for `usdli` |
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| openbb.economy.valuation | Function | Valuation for Group from (get_gropus) |
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Alternatively, the contents of the economy, or function docstrings, is printed with:
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```python
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help(openbb.economy)
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```
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## Examples
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### Import Statements
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The examples will assume that this code block is included with the import statements:
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```python
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from openbb_terminal.sdk import openbb
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import pandas as pd
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```
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### Index
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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.
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```python
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indexes = pd.DataFrame.from_dict(openbb.economy.available_indices()).transpose()
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indexes
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```
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| | name | ticker |
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| :-------- | :------------------------------ | :------- |
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| sp500 | S&P 500 Index | ^GSPC |
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| sp400 | S&P 400 Mid Cap Index | ^SP400 |
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| sp600 | S&P 600 Small Cap Index | ^SP600 |
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| sp500tr | S&P 500 TR Index | ^SP500TR |
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| sp_xsp | S&P 500 Mini SPX Options Index | ^XSP |
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| cboe_tyx | CBOE 30 year Treasury Yields | ^TYX |
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| cboe_irx | CBOE 13 Week Treasury Bill | ^IRX |
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| move | ICE BofAML Move Index | ^MOVE |
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| dxy | US Dollar Index | DX-Y.NYB |
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| crypto200 | CMC Crypto 200 Index by Solacti | ^CMC200 |
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This list can be filtered:
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```python
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filtered = indexes.name.str.contains('s&p', case = False)
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indexes[filtered].head(10)
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```
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| | name | ticker |
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|:----------|:------------------------------------|:---------|
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| sp500 | S&P 500 Index | ^GSPC |
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| sp400 | S&P 400 Mid Cap Index | ^SP400 |
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| sp600 | S&P 600 Small Cap Index | ^SP600 |
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| sp500tr | S&P 500 TR Index | ^SP500TR |
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| sp_xsp | S&P 500 Mini SPX Options Index | ^XSP |
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| ca_banks | S&P/TSX Composite Banks Index (CAD) | TXBA.TS |
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| ar_mervel | S&P MERVAL TR Index (USD) | M.BA |
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| eu_speup | S&P Europe 350 Index (EUR) | ^SPEUP |
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| uk_spuk | S&P United Kingdom Index (PDS) | ^SPUK |
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| in_bse | S&P Bombay SENSEX (INR) | ^BSESN |
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One index, or multiple, can be requested as a single DataFrame:
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```python
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df = openbb.economy.index(indices = ['sp_energy_oil', 'sp_energy_equipment', 'sp_energy_ig'])
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df.tail(3)
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```
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| Date | sp_energy_oil | sp_energy_equipment | sp_energy_ig |
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| :------------------ | ------------: | ------------------: | -----------: |
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| 2022-11-14 00:00:00 | 800.76 | 330.53 | 712.28 |
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| 2022-11-15 00:00:00 | 809.27 | 335.84 | 720.16 |
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| 2022-11-16 00:00:00 | 792.32 | 326.49 | 704.68 |
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This can also be displayed as a chart:
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```python
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openbb.economy.index_chart(indices = ['sp_energy_oil', 'sp_energy_equipment', 'sp_energy_ig'])
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```
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### Performance
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Performance metrics for sectors, industries, and regions (US listed) are printed with:
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```python
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openbb.economy.performance(group = 'energy')
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```
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| | Name | Week | Month | 3Month | 6Month | 1Year | YTD | Recom | AvgVolume [1M] | RelVolume | Change | Volume [1M] |
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| --: | :----------------------------- | ------: | -----: | ------: | -----: | ------: | -----: | ----: | -------------: | --------: | ------: | ----------: |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 7 | Uranium | -0.0176 | 0.0416 | 0.0856 | 0.0426 | -0.1746 | 0.0267 | 1.61 | 32.44 | 0.54 | -0.0125 | 12.58 |
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Performance by sector:
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```python
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openbb.economy.performance(group = 'sector')
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```
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| | Name | Week | Month | 3Month | 6Month | 1Year | YTD | Recom | AvgVolume [1M] | RelVolume | Change | Volume [1M] |
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| --: | :--------------------- | ------: | -----: | ------: | ------: | ------: | ------: | ----: | -------------: | --------: | ------: | ----------: |
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| 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 |
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| 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 |
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| 2 | Consumer Cyclical | 0.0111 | 0.0266 | -0.1386 | -0.0182 | -0.3665 | -0.3221 | 2.14 | 1430 | 1.01 | -0.0034 | 1040 |
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| 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 |
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| 4 | Energy | 0.0067 | 0.0629 | 0.0913 | 0.0736 | 0.4208 | 0.4497 | 2.21 | 694.52 | 0.65 | -0.008 | 322.19 |
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| 5 | Financial | -0.0095 | 0.0934 | -0.0098 | 0.0339 | -0.1259 | -0.1137 | 2.24 | 861.74 | 0.79 | -0.005 | 489.78 |
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| 6 | Healthcare | -0.0121 | 0.0703 | -0.0125 | 0.0177 | -0.1074 | -0.1161 | 2.11 | 1180 | 0.87 | 0.0002 | 736.58 |
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| 7 | Industrials | -0.0118 | 0.0969 | -0.0223 | 0.0723 | -0.1138 | -0.101 | 2.32 | 573.08 | 0.7 | -0.005 | 285.24 |
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| 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 |
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| 9 | Technology | 0.0149 | 0.0938 | -0.1095 | -0.0044 | -0.3024 | -0.2957 | 2.03 | 1460 | 0.86 | 0.0039 | 904.44 |
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| 10 | Utilities | -0.0235 | 0.0485 | -0.1212 | -0.0582 | -0.0054 | -0.0569 | 2.29 | 166.21 | 0.67 | -0.0142 | 79.25 |
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### Events
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A global economic calendar is accessible through the `events` function:
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```python
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help(openbb.economy.events)
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Help on Operation in module openbb_terminal.core.library.operation:
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<openbb_terminal.core.library.operation.Operation object>
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Get economic calendar for countries between specified dates
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Parameters
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----------
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countries : [List[str],str]
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List of countries to include in calendar. Empty returns all
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start_date : str
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Start date for calendar
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end_date : str
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End date for calendar
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Returns
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-------
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pd.DataFrame
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Economic calendar
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```
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With no arguments, `events` will return the calendar from today:
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```python
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openbb.economy.events().head(10)
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```
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| | Time (ET) | Country | Event | Actual | Consensus | Previous | Date |
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|---:|:------------|:---------------|:---------------------------------------|:---------|:------------|:-----------|:-----------|
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| 0 | 01:45 | Germany | German Buba President Nagel Speaks | - | - | - | 2023-04-13 |
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| 1 | 01:45 | Germany | German Buba Vice President Buch Speaks | - | - | - | 2023-04-13 |
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| 2 | 02:00 | United Kingdom | Construction Output | 2.4% | 0.9% | -1.7% | 2023-04-13 |
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| 3 | 02:00 | United Kingdom | U.K. Construction Output | 5.7% | 1.6% | 3.3% | 2023-04-13 |
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| 4 | 02:00 | United Kingdom | GDP | 0.0% | 0.1% | 0.4% | 2023-04-13 |
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| 5 | 02:00 | United Kingdom | Index of Services | 0.1% | -0.2% | 0.1% | 2023-04-13 |
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| 6 | 02:00 | United Kingdom | Industrial Production | -0.2% | 0.2% | -0.5% | 2023-04-13 |
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| 7 | 02:00 | United Kingdom | Industrial Production | -3.1% | -3.7% | -3.2% | 2023-04-13 |
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| 8 | 02:00 | United Kingdom | Manufacturing Production | -2.4% | -4.7% | -2.8% | 2023-04-13 |
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| 9 | 02:00 | United Kingdom | Manufacturing Production | 0.0% | 0.2% | -0.1% | 2023-04-13 |
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Calendar events can be requested for a specific countries and date ranges:
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```python
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openbb.economy.events(countries = ['United States'], start_date = '2022-11-18', end_date = '2022-11-18').head(5)
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```
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| | Time (ET) | Country | Event | Actual | Consensus | Previous | Date |
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|---:|:------------|:--------------|:--------------------------------|:---------|:------------|:-----------|:-----------|
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| 0 | 09:40 | United States | Fed Collins Speaks | - | - | - | 2022-11-18 |
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| 1 | 11:00 | United States | Existing Home Sales | -5.9% | - | -1.5% | 2022-11-18 |
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| 2 | 11:00 | United States | Existing Home Sales | 4.43M | 4.38M | 4.71M | 2022-11-18 |
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| 3 | 11:00 | United States | US Leading Index | -0.8% | -0.4% | -0.5% | 2022-11-18 |
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| 4 | 14:00 | United States | U.S. Baker Hughes Oil Rig Count | 623 | - | 622 | 2022-11-18 |
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### FRED
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Search the FRED database for a series titles containing keywords:
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```python
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series_ids = openbb.economy.fred_ids(search_query = 'Oil and Gas')
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series_ids.head(5)
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```
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| id | title |
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| :-------------- | :-------------------------------------------------------------------------------------------------- |
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| PCU333132333132 | Producer Price Index by Industry: Oil and Gas Field Machinery and Equipment Manufacturing |
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| CES1021100001 | All Employees, Oil and Gas Extraction |
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| IPG211111CS | Industrial Production: Mining, Quarrying, and Oil and Gas Extraction: Crude Oil (NAICS = 211111pt.) |
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| A33DNO | Manufacturers' New Orders: Mining, Oil, and Gas Field Machinery Manufacturing |
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| PCU21112111 | Producer Price Index by Industry: Oil and Gas Extraction |
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### Macro
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The `macro` function will return a Tuple. See refer to the docstring below to see the input arguments:
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```python
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help(openbb.economy.macro)
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Help on Operation in module openbb_terminal.core.library.operation:
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<openbb_terminal.core.library.operation.Operation object>
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Use 'economy.macro_chart' to access the view.
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This functions groups the data queried from the EconDB database [Source: EconDB]
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Parameters
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----------
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parameters: list
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The type of data you wish to download. Available parameters can be accessed through economy.macro_parameters().
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countries : list
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The selected country or countries. Available countries can be accessed through economy.macro_countries().
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transform : str
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The selected transform. Available transforms can be accessed through get_macro_transform().
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start_date : str
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The starting date, format "YEAR-MONTH-DAY", i.e. 2010-12-31.
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end_date : str
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The end date, format "YEAR-MONTH-DAY", i.e. 2020-06-05.
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symbol : str
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In what currency you wish to convert all values.
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Returns
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-------
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Tuple[pd.DataFrame, Dict[Any, Dict[Any, Any]], str]
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A DataFrame with the requested macro data of all chosen countries,
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A dictionary containing the units of each country's parameter (e.g. EUR),
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A string denomination which can be Trillions, Billions, Millions, Thousands
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Examples
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--------
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>>> from openbb_terminal.sdk import openbb
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>>> macro_df = openbb.economy.macro()
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```
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`openbb.economy.macro_parameters()` will return a list of dictionaries. Read it as a DataFrame with:
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```python
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parameters = pd.DataFrame.from_dict(openbb.economy.macro_parameters()).transpose()
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parameters.tail(5)
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```
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| | name | period | description |
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| :------ | :------------------------ | :------ | :----------------------------------------------------------------------------------------------------------------------------------- |
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| 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. |
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| M3YD | 3 month yield | Monthly | The yield received for investing in a government issued treasury security that has a maturity of 3 months |
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| 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 |
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| OILPROD | Oil production | Monthly | The amount of oil barrels produced per day in a month within a country. |
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| POP | Population | Monthly | The population of a country. This can be in thousands or, when relatively small, in actual units. |
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The data from the `macro` function is unpacked like:
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```python
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data,units,denomination = openbb.economy.macro(parameters = ['Y10YD'], countries = ['United States', 'Poland', 'France', 'Italy', 'Spain', 'Germany'])
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data.tail(10)
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```
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| date | France | Germany | Italy | Poland | Spain | United States |
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|:--------------------|----------------------:|-----------------------:|---------------------:|----------------------:|---------------------:|-----------------------------:|
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| 2022-05-01 | 1.52 | 0.95 | 2.99 | 6.64 | 2.04 | 2.9 |
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| 2022-06-01 | 2.06 | 1.45 | 3.64 | 7.14 | 2.63 | 3.14 |
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| 2022-07-01 | 1.71 | 1.08 | 3.36 | 6.37 | 2.31 | 2.9 |
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| 2022-08-01 | 1.69 | 1.03 | 3.3 | 5.8 | 2.15 | 2.9 |
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| 2022-09-01 | 2.41 | 1.8 | 4.14 | 6.28 | 2.92 | 3.52 |
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| 2022-10-01 | 2.77 | 2.19 | 4.53 | 7.82 | 3.29 | 3.98 |
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| 2022-11-01 | 2.58 | 2.07 | 4.24 | 7.24 | 3.07 | 3.89 |
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| 2022-12-01 | 2.62 | 2.09 | 4.26 | 6.61 | 3.09 | 3.62 |
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| 2023-01-01 | 2.69 | 2.19 | 4.24 | 6.02 | 3.2 | 3.53 |
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| 2023-02-01 | 2.87 | 2.37 | 4.27 | 6.18 | 3.39 | 3.75 |
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