stockdex 0.4.0

A package to get stock data from Yahoo Finance

Stockdex

Stockdex is a Python package that provides a simple interface to access financial data from Yahoo Finance. Data is returned as a pandas DataFrame.

Installation

Install the package using pip:

pip install stockdex

Usage

Create Ticker object by passing the ticker symbol. Ticker objects are the main interface to retrieve stock data.

from stockdex import Ticker

# Pick arbitrary ticker
ticker = Ticker('AAPL')

Fundamental data from Yahoo Finance API (fast queries through Yahoo Finance API):

# Price data (use range and dataGranularity to make range and granularity more specific)
price = ticker.price(range='1y', dataGranularity='1d')

# Current trading period of the stock (pre-market, regular, post-market trading periods)
current_trading_period = ticker.current_trading_period

# Fundamental data (use frequency, format, period1 and period2 to fine-tune the returned data)
income_statement = ticker.income_statement(frequency='quarterly')
cash_flow = ticker.cash_flow(format='raw')
balance_sheet = ticker.balance_sheet(period1=datetime(2020, 1, 1))
financials = ticker.financials(period1=datetime(2022, 1, 1), period2=datetime.today())

Fundamental data with criteria from Yahoo Finance website (web scraping):

# Summary including general financial information
summary = ticker.summary

# Financial data as it is seen in the yahoo finance website
income_stmt_web = ticker.income_stmt_web
balance_sheet = ticker.balance_sheet_web
cash_flow = ticker.cashflow_web

# Analysts and estimates
analysis = ticker.analysis

# Data about options
calls = ticker.calls
puts = ticker.puts

# Profile data 
key_executives = ticker.key_executives
description = ticker.description
corporate_governance = ticker.corporate_governance

# Data about shareholders
major_holders = ticker.major_holders
top_institutional_holders = ticker.top_institutional_holders
top_mutual_fund_holders = ticker.top_mutual_fund_holders

# Statistics
valuation_measures = ticker.valuation_measures
financial_highlights = ticker.financial_highlights
trading_information = ticker.trading_information

NASDAQ data from NASDAQ website (web scraping):

Data on NASDAQ website gets updated more frequently than Yahoo Finance data. Below are some of the data that can be retrieved from the NASDAQ website.

# Data about quarterly and yearly earnings, updated on the same day as the earnings release (yahoo finance data is updated after a few days)

quarterly_earnings_surprise = ticker.quarterly_earnings_surprise
yearly_earnings_forecast = ticker.yearly_earnings_forecast
quarterly_earnings_forecast = ticker.quarterly_earnings_forecast

price_to_earnings_ratio = ticker.price_to_earnings_ratio
forecast_price_to_earnings__growth_rates = ticker.forecast_peg_rate

Stocks data from Digrin (web scraping):

Data on Digrin website includes all historical data of the stock in certain categories, unlike Yahoo Finance which only provides the last 5 years of data at most.

# Complete historical data of the stock in certain categories
dividend = ticker.dividend
payout_ratio = ticker.payout_ratio
stock_splits = ticker.stock_splits

EU ETF data from justETF (web scraping):

For EU ETFS, the isin and security_type should be passed to the Ticker object. The isin is the International Securities Identification Number of the ETF and the security_type should be set to etf.

etf = Ticker(isin='IE00B4L5Y983', security_type='etf')

etf_general_info = etf.etf_general_info
etf_wkn = etf.etf_wkn
etf_description = etf.etf_description

# Basic data about the ETF
etf_basics = etf.etf_basics

# Holdings of the ETF by company, country and sector
etf_holdings_companies = etf.etf_holdings_companies
etf_holdings_countries = etf.etf_holdings_countries
etf_holdings_sectors = etf.etf_holdings_sectors

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Check out sphinx documentation here for more information about the package.