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| \n\n#### \\*\\*\\* IMPORTANT LEGAL DISCLAIMER \\*\\*\\*\n\n---\n\n**Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of\nYahoo, Inc.**\n\nyfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's\nan open-source tool that uses Yahoo's publicly available APIs, and is\nintended for research and educational purposes.\n\n**You should refer to Yahoo!'s terms of use**\n([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),\n[here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and\n[here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) **for\ndetails on your rights to use the actual data downloaded. Remember - the\nYahoo! finance API is intended for personal use only.**\n\n |
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\n\n\n**yfinance** offers a threaded and Pythonic way to download market data from [Yahoo!\u24c7 finance](https://finance.yahoo.com).\n\n\u2192 Check out this [Blog post](https://aroussi.com/#post/python-yahoo-finance) for a detailed tutorial with code examples.\n\n[Changelog \u00bb](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)\n\n---\n\n## Quick Start\n\n### The Ticker module\n\nThe `Ticker` module, which allows you to access ticker data in a more Pythonic way:\n\nNote: yahoo finance datetimes are received as UTC.\n\n```python\nimport yfinance as yf\n\nmsft = yf.Ticker(\"MSFT\")\n\n# get stock info\nmsft.info\n\n# get historical market data\nhist = msft.history(period=\"max\")\n\n# show actions (dividends, splits)\nmsft.actions\n\n# show dividends\nmsft.dividends\n\n# show splits\nmsft.splits\n\n# show financials\nmsft.financials\nmsft.quarterly_financials\n\n# show major holders\nmsft.major_holders\n\n# show institutional holders\nmsft.institutional_holders\n\n# show balance sheet\nmsft.balance_sheet\nmsft.quarterly_balance_sheet\n\n# show cashflow\nmsft.cashflow\nmsft.quarterly_cashflow\n\n# show earnings\nmsft.earnings\nmsft.quarterly_earnings\n\n# show sustainability\nmsft.sustainability\n\n# show analysts recommendations\nmsft.recommendations\n\n# show next event (earnings, etc)\nmsft.calendar\n\n# show ISIN code - *experimental*\n# ISIN = International Securities Identification Number\nmsft.isin\n\n# show options expirations\nmsft.options\n\n# show news\nmsft.news\n\n# get option chain for specific expiration\nopt = msft.option_chain('YYYY-MM-DD')\n# data available via: opt.calls, opt.puts\n```\n\nIf you want to use a proxy server for downloading data, use:\n\n```python\nimport yfinance as yf\n\nmsft = yf.Ticker(\"MSFT\")\n\nmsft.history(..., proxy=\"PROXY_SERVER\")\nmsft.get_actions(proxy=\"PROXY_SERVER\")\nmsft.get_dividends(proxy=\"PROXY_SERVER\")\nmsft.get_splits(proxy=\"PROXY_SERVER\")\nmsft.get_balance_sheet(proxy=\"PROXY_SERVER\")\nmsft.get_cashflow(proxy=\"PROXY_SERVER\")\nmsft.option_chain(..., proxy=\"PROXY_SERVER\")\n...\n```\n\nTo use a custom `requests` session (for example to cache calls to the\nAPI or customize the `User-agent` header), pass a `session=` argument to\nthe Ticker constructor.\n\n```python\nimport requests_cache\nsession = requests_cache.CachedSession('yfinance.cache')\nsession.headers['User-agent'] = 'my-program/1.0'\nticker = yf.Ticker('msft aapl goog', session=session)\n# The scraped response will be stored in the cache\nticker.actions\n```\n\nTo initialize multiple `Ticker` objects, use\n\n```python\nimport yfinance as yf\n\ntickers = yf.Tickers('msft aapl goog')\n# ^ returns a named tuple of Ticker objects\n\n# access each ticker using (example)\ntickers.tickers.MSFT.info\ntickers.tickers.AAPL.history(period=\"1mo\")\ntickers.tickers.GOOG.actions\n```\n\n### Fetching data for multiple tickers\n\n```python\nimport yfinance as yf\ndata = yf.download(\"SPY AAPL\", start=\"2017-01-01\", end=\"2017-04-30\")\n```\n\nI've also added some options to make life easier :)\n\n```python\ndata = yf.download( # or pdr.get_data_yahoo(...\n # tickers list or string as well\n tickers = \"SPY AAPL MSFT\",\n\n # use \"period\" instead of start/end\n # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max\n # (optional, default is '1mo')\n period = \"ytd\",\n\n # fetch data by interval (including intraday if period < 60 days)\n # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo\n # (optional, default is '1d')\n interval = \"1m\",\n\n # group by ticker (to access via data['SPY'])\n # (optional, default is 'column')\n group_by = 'ticker',\n\n # adjust all OHLC automatically\n # (optional, default is False)\n auto_adjust = True,\n\n # download pre/post regular market hours data\n # (optional, default is False)\n prepost = True,\n\n # use threads for mass downloading? (True/False/Integer)\n # (optional, default is True)\n threads = True,\n\n # proxy URL scheme use use when downloading?\n # (optional, default is None)\n proxy = None\n )\n```\n\n### Managing Multi-Level Columns\n\nThe following answer on Stack Overflow is for [How to deal with\nmulti-level column names downloaded with\nyfinance?](https://stackoverflow.com/questions/63107801)\n\n- `yfinance` returns a `pandas.DataFrame` with multi-level column\n names, with a level for the ticker and a level for the stock price\n data\n - The answer discusses:\n - How to correctly read the the multi-level columns after\n saving the dataframe to a csv with `pandas.DataFrame.to_csv`\n - How to download single or multiple tickers into a single\n dataframe with single level column names and a ticker column\n\n---\n\n## `pandas_datareader` override\n\nIf your code uses `pandas_datareader` and you want to download data\nfaster, you can \"hijack\" `pandas_datareader.data.get_data_yahoo()`\nmethod to use **yfinance** while making sure the returned data is in the\nsame format as **pandas\\_datareader**'s `get_data_yahoo()`.\n\n```python\nfrom pandas_datareader import data as pdr\n\nimport yfinance as yf\nyf.pdr_override() # <== that's all it takes :-)\n\n# download dataframe\ndata = pdr.get_data_yahoo(\"SPY\", start=\"2017-01-01\", end=\"2017-04-30\")\n```\n\n---\n\n## Installation\n\nInstall `yfinance` using `pip`:\n\n``` {.sourceCode .bash}\n$ pip install yfinance --upgrade --no-cache-dir\n```\n\nTo install `yfinance` using `conda`, see\n[this](https://anaconda.org/ranaroussi/yfinance).\n\n### Requirements\n\n- [Python](https://www.python.org) \\>= 2.7, 3.4+\n- [Pandas](https://github.com/pydata/pandas) (tested to work with\n \\>=0.23.1)\n- [Numpy](http://www.numpy.org) \\>= 1.11.1\n- [requests](http://docs.python-requests.org/en/master/) \\>= 2.14.2\n- [lxml](https://pypi.org/project/lxml/) \\>= 4.5.1\n\n### Optional (if you want to use `pandas_datareader`)\n\n- [pandas\\_datareader](https://github.com/pydata/pandas-datareader)\n \\>= 0.4.0\n\n---\n\n### Legal Stuff\n\n**yfinance** is distributed under the **Apache Software License**. See\nthe [LICENSE.txt](./LICENSE.txt) file in the release for details.\n\n\nAGAIN - yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's\nan open-source tool that uses Yahoo's publicly available APIs, and is\nintended for research and educational purposes. You should refer to Yahoo!'s terms of use\n([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),\n[here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and\n[here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) for\ndetailes on your rights to use the actual data downloaded.\n\n---\n\n### P.S.\n\nPlease drop me an note with any feedback you have.\n\n**Ran Aroussi**\n\n\n",
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