Retrieve nearly all data from Yahoo Finance for one or more ticker symbols
Project description
Yahooquery
Python wrapper around an unofficial Yahoo Finance API.
Install
pip install yahooquery
Ticker
The Ticker
module is the access point to the Yahoo Finance API. Pass a ticker symbol to the Ticker
class.
from yahooquery import Ticker
aapl = Ticker('aapl')
Or pass a list of tickers.
tickers = Ticker(['aapl', 'msft'])
Data
Based on the data you'd like, the result will either be accessed through a dict
or as a pandas.DataFrame
. Accessing data is incredibly easy and pythonic.
Dictionaries
aapl = Ticker('aapl')
# Asset Profile
aapl.asset_profile
{'aapl': {'address1': 'One Apple Park Way', 'city': 'Cupertino', ... }}
# ESG Scores
aapl.esg_scores
{'aapl': {'totalEsg': 72.27, 'environomentScore': 89.81, ... }}
# Financial Data
aapl.financial_data
{'aapl': {'currentPrice': 275.15, 'targetHighPrice': 342.4, ... }}
# Key Statistics
aapl.key_stats
{'aapl': {'priceHint': 2, 'enterpriseValue': 1230054359040, ... }}
# Price Information
aapl.price
{'aapl': {'preMarketChange': {}, 'preMarketPrice': {}, ... }}
# Quote Type
aapl.quote_type
{'aapl': {'exchange': 'NMS', 'quoteType': 'EQUITY', ... }}
# Share Purchase Activity
aapl.share_purchase_activity
{'aapl': {'period': '6m', 'buyInfoCount': 20, ... }}
# Summary Information
aapl.summary_detail
{'aapl': {'priceHint': 2, 'previousClose': 271.46, ... }}
aapl.summary_profile
{'aapl': {'address1': 'One Apple Park Way', 'city': 'Cupertino', ... }}
How about more than one ticker?
# Pass a list of tickers to the Ticker class
tickers = Ticker(['aapl', 'msft'])
tickers.asset_profile
{'aapl': {'address1': 'One Apple Park Way', 'city': 'Cupertino', ... }, 'msft': {'address1': 'One Microsoft Way', 'city': 'Redmond', ... }}
tickers.esg_scores
{'aapl': {'totalEsg': 72.27, 'environomentScore': 89.81, ... }, 'msft': {'totalEsg': 74.8, 'environmentScore': 84.17, ... }}
tickers.financial_data
{'aapl': {'currentPrice': 275.15, 'targetHighPrice': 342.4, ... }, 'msft': {'currentPrice': 154.53, 'targetHighPrice': 174.0, ... }}
tickers.key_stats
{'aapl': {'priceHint': 2, 'enterpriseValue': 1230054359040, ... }, 'msft': {'priceHint': 2, 'enterpriseValue': 1127840350208, ... }}
tickers.price
{'aapl': {'preMarketChange': {}, 'preMarketPrice': {}, ... }, 'msft': {'preMarketChange': {}, 'preMarketPrice': {}, ... }}
tickers.quote_type
{'aapl': {'exchange': 'NMS', 'quoteType': 'EQUITY', ... }, 'msft': {'exchange': 'NMS', 'quoteType': 'EQUITY', ... }}
tickers.share_purchase_activity
{'aapl': {'period': '6m', 'buyInfoCount': 20, ... }, 'msft': {'period': '6m', 'buyInfoCount': 30, ... }}
tickers.summary_detail
{'aapl': {'priceHint': 2, 'previousClose': 271.46, ... }, 'msft': {'priceHint': 2, 'previousClose': 153.24, ... }}
tickers.summary_profile
{'aapl': {'address1': 'One Apple Park Way', 'city': 'Cupertino', ... }, 'msft': {'address1': 'One Microsoft Way', 'city': 'Redmond', ... }}
Dataframes
aapl.company_officers
aapl.earning_history
aapl.grading_history
aapl.insider_holders
aapl.insider_transactions
aapl.institution_ownership
aapl.recommendation_trend
aapl.sec_filings
aapl.fund_ownership
aapl.major_holders
aapl.earnings_trend
# The following methods take a frequency argument. If nothing is provided, annual data will be returned. To return quarterly data, pass "q" as an argument.
aapl.balance_sheet() # Defaults to Annual
aapl.balance_sheet(frequency="q")
aapl.balance_sheet("q")
aapl.cash_flow()
aapl.income_statement()
Fund Specific
Mutual Funds have many of the accessors detailed above as well as the additional ones below:
fund = Ticker('rpbax')
fund.fund_category_holdings # pandas.DataFrame
fund.fund_bond_ratings # pandas.DataFrame
fund.fund_sector_weightings # pandas.DataFrame
fund.fund_performance # dict
fund.fund_bond_holdings # dict
fund.fund_equity_holdings # dict
Options
Retrieve option pricing for every expiration date for given ticker(s)
aapl.option_chain # returns pandas.DataFrame
Historical Pricing
Historical price data can be retrieved for one or more tickers through the history
method.
aapl.history()
If no arguments are provided, as above, default values will be supplied for both period
and interval
, which are ytd
and 1d
, respectively. Additional arguments you can provide to the method are start
and end
. Start and end dates can be either strings with a date format of yyyy-mm-dd
or as a datetime.datetime
object.
aapl.history(period='max')
aapl.history(start='2019-05-01') # Default end date is now
aapl.history(end='2018-12-31') # Default start date is 1900-01-01
# Period options = 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
# Interval options = 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo
If trying to retrieve more than one ticker, one dataframe will be returned and the column ticker
can be used to identify each row appropriately.
tickers = Ticker(['aapl', 'msft'])
tickers.history()
dates | volume | open | low | high | close | ticker |
---|---|---|---|---|---|---|
2019-01-02 07:30:00 | 37039700 | 154.89 | 154.23 | 158.85 | 157.92 | AAPL |
2019-01-03 07:30:00 | 91312200 | 143.98 | 142 | 145.72 | 142.19 | AAPL |
2019-12-12 07:30:00 | 24612100 | 151.65 | 151.02 | 153.44 | 153.24 | MSFT |
2019-12-13 14:00:01 | 23850062 | 153.003 | 152.85 | 154.89 | 154.53 | MSFT |
Multiple Endpoints
Access more than one endpoint in one call using the get_multiple_endoints
method of the Ticker
class. This method ONLY returns dictionaries.
aapl = Ticker('aapl')
endpoints = ['assetProfile', 'esgScores', 'incomeStatementHistory']
aapl.get_multiple_endpoints(endpoints)
{'aapl': {'assetProfile': {...}, 'esgScores', {...}, 'incomeStatementHistory', {...}}}
Type Ticker._ENDPOINTS
to view the list of endpoints supported through this method.
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