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Download market data from Yahoo! Finance's API

* IMPORTANT LEGAL DISCLAIMER *

Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of Yahoo, Inc.

yfinance is not affiliated, endorsed, or vetted by Yahoo, Inc. It's an open-source tool that uses Yahoo's publicly available APIs, and is intended for research and educational purposes.

You should refer to Yahoo!'s terms of use (here, here, and here) for details on your rights to use the actual data downloaded. Remember - the Yahoo! finance API is intended for personal use only.

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yfinance offers a threaded and Pythonic way to download market data from Yahoo!Ⓡ finance.

→ Check out this Blog post for a detailed tutorial with code examples.

Changelog »

Quick Start

The Ticker module

The Ticker module, which allows you to access ticker data in a more Pythonic way:

Note: yahoo finance datetimes are received as UTC.

              import              yfinance              as              yf              msft              =              yf.Ticker("MSFT")              # get stock info              msft.info              # get historical market data              hist              =              msft.history(period              =              "max")              # show actions (dividends, splits)              msft.actions              # show dividends              msft.dividends              # show splits              msft.splits              # show financials              msft.financials              msft.quarterly_financials              # show major holders              msft.major_holders              # show institutional holders              msft.institutional_holders              # show balance sheet              msft.balance_sheet              msft.quarterly_balance_sheet              # show cashflow              msft.cashflow              msft.quarterly_cashflow              # show earnings              msft.earnings              msft.quarterly_earnings              # show sustainability              msft.sustainability              # show analysts recommendations              msft.recommendations              # show next event (earnings, etc)              msft.calendar              # show ISIN code - *experimental*              # ISIN = International Securities Identification Number              msft.isin              # show options expirations              msft.options              # show news              msft.news              # get option chain for specific expiration              opt              =              msft.option_chain('YYYY-MM-DD')              # data available via: opt.calls, opt.puts

If you want to use a proxy server for downloading data, use:

              import              yfinance              as              yf              msft              =              yf.Ticker("MSFT")              msft.history(...,              proxy              =              "PROXY_SERVER")              msft.get_actions(proxy              =              "PROXY_SERVER")              msft.get_dividends(proxy              =              "PROXY_SERVER")              msft.get_splits(proxy              =              "PROXY_SERVER")              msft.get_balance_sheet(proxy              =              "PROXY_SERVER")              msft.get_cashflow(proxy              =              "PROXY_SERVER")              msft.option_chain(...,              proxy              =              "PROXY_SERVER") ...

To use a custom requests session (for example to cache calls to the API or customize the User-agent header), pass a session= argument to the Ticker constructor.

              import              requests_cache              session              =              requests_cache.CachedSession('yfinance.cache')              session.headers['User-agent']              =              'my-program/1.0'              ticker              =              yf.Ticker('msft aapl goog',              session              =              session)              # The scraped response will be stored in the cache              ticker.actions

To initialize multiple Ticker objects, use

              import              yfinance              as              yf              tickers              =              yf.Tickers('msft aapl goog')              # ^ returns a named tuple of Ticker objects              # access each ticker using (example)              tickers.tickers.MSFT.info              tickers.tickers.AAPL.history(period              =              "1mo")              tickers.tickers.GOOG.actions

Fetching data for multiple tickers

              import              yfinance              as              yf              data              =              yf.download("SPY AAPL",              start              =              "2017-01-01",              end              =              "2017-04-30")

I've also added some options to make life easier :)

              data              =              yf.download(              # or pdr.get_data_yahoo(...              # tickers list or string as well              tickers              =              "SPY AAPL MSFT",              # use "period" instead of start/end              # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max              # (optional, default is '1mo')              period              =              "ytd",              # fetch data by interval (including intraday if period < 60 days)              # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo              # (optional, default is '1d')              interval              =              "1m",              # group by ticker (to access via data['SPY'])              # (optional, default is 'column')              group_by              =              'ticker',              # adjust all OHLC automatically              # (optional, default is False)              auto_adjust              =              True,              # download pre/post regular market hours data              # (optional, default is False)              prepost              =              True,              # use threads for mass downloading? (True/False/Integer)              # (optional, default is True)              threads              =              True,              # proxy URL scheme use use when downloading?              # (optional, default is None)              proxy              =              None              )

Managing Multi-Level Columns

The following answer on Stack Overflow is for How to deal with multi-level column names downloaded with yfinance?

yfinance returns a pandas.DataFrame with multi-level column names, with a level for the ticker and a level for the stock price data
- The answer discusses:
  - How to correctly read the the multi-level columns after saving the dataframe to a csv with pandas.DataFrame.to_csv
  - How to download single or multiple tickers into a single dataframe with single level column names and a ticker column

`pandas_datareader` override

If your code uses pandas_datareader and you want to download data faster, you can "hijack" pandas_datareader.data.get_data_yahoo() method to use yfinance while making sure the returned data is in the same format as pandas_datareader's get_data_yahoo().

              from              pandas_datareader              import              data              as              pdr              import              yfinance              as              yf              yf.pdr_override()              # <== that's all it takes :-)              # download dataframe              data              =              pdr.get_data_yahoo("SPY",              start              =              "2017-01-01",              end              =              "2017-04-30")

Installation

Install yfinance using pip:

              $ pip install yfinance --upgrade --no-cache-dir

To install yfinance using conda, see this.

Requirements

Python >= 2.7, 3.4+
Pandas (tested to work with >=0.23.1)
Numpy >= 1.11.1
requests >= 2.14.2
lxml >= 4.5.1

Optional (if you want to use `pandas_datareader`)

pandas_datareader >= 0.4.0

Legal Stuff

yfinance is distributed under the Apache Software License. See the LICENSE.txt file in the release for details.

AGAIN - yfinance is not affiliated, endorsed, or vetted by Yahoo, Inc. It's an open-source tool that uses Yahoo's publicly available APIs, and is intended for research and educational purposes. You should refer to Yahoo!'s terms of use (here, here, and here) for detailes on your rights to use the actual data downloaded.