yf_docs.py

yf_docs = """
# YFinance UPDATED API DOCUMENTATION
# Always refer the following updated documentation for writing python code to call yf api
## Single Ticker Usage

```python
import yfinance as yf
ticker = yf.Ticker('MSFT')
```

## Multi-Ticker Usage

### Initialization

```python
import yfinance as yf
tickers = yf.Tickers('MSFT AAPL GOOG')
```

### Download Historical Data

Get historical market data for multiple tickers:

```python
# Method 1: Using Tickers object
tickers = yf.Tickers('MSFT AAPL GOOG')
data = tickers.download(period='1mo')

# Method 2: Using download function directly
data = yf.download(['MSFT', 'AAPL', 'GOOG'], period='1mo')
```

Returns:
```python

DataFrame with columns: [('Close', 'AAPL'), ('Close', 'GOOG'), ('Close', 'MSFT'), ('Dividends', 'AAPL'), ('Dividends', 'GOOG'), ('Dividends', 'MSFT'), ('High', 'AAPL'), ('High', 'GOOG'), ('High', 'MSFT'), ('Low', 'AAPL'), ('Low', 'GOOG'), ('Low', 'MSFT'), ('Open', 'AAPL'), ('Open', 'GOOG'), ('Open', 'MSFT'), ('Stock Splits', 'AAPL'), ('Stock Splits', 'GOOG'), ('Stock Splits', 'MSFT'), ('Volume', 'AAPL'), ('Volume', 'GOOG'), ('Volume', 'MSFT')]
Shape: (21, 21)

```

### News

Get news for multiple tickers:

```python
tickers = yf.Tickers('MSFT AAPL GOOG')
news = tickers.news()
```

Returns:
```python

- MSFT: list
- AAPL: list
- GOOG: list
```

### Accessing Individual Tickers

Access individual ticker data from a multi-ticker object:

```python
tickers = yf.Tickers('MSFT AAPL GOOG')
msft_info = tickers.tickers['MSFT'].info
aapl_history = tickers.tickers['AAPL'].history(period='1mo')
```

## Single Ticker Methods

### Info

```python
ticker.info
```

Returns:
```python

- address1: str
- city: str
- state: str
- zip: str
- country: str
- phone: str
- website: str
- industry: str
- industryKey: str
- industryDisp: str
- sector: str
- sectorKey: str
- sectorDisp: str
- longBusinessSummary: str
- fullTimeEmployees: int
- companyOfficers: list
- auditRisk: int
- boardRisk: int
- compensationRisk: int
- shareHolderRightsRisk: int
- overallRisk: int
- governanceEpochDate: int
- compensationAsOfEpochDate: int
- irWebsite: str
- maxAge: int
- priceHint: int
- previousClose: float
- open: float
- dayLow: float
- dayHigh: float
- regularMarketPreviousClose: float
- regularMarketOpen: float
- regularMarketDayLow: float
- regularMarketDayHigh: float
- dividendRate: float
- dividendYield: float
- exDividendDate: int
- payoutRatio: float
- fiveYearAvgDividendYield: float
- beta: float
- trailingPE: float
- forwardPE: float
- volume: int
- regularMarketVolume: int
- averageVolume: int
- averageVolume10days: int
- averageDailyVolume10Day: int
- bid: float
- ask: float
- bidSize: int
- askSize: int
- marketCap: int
- fiftyTwoWeekLow: float
- fiftyTwoWeekHigh: float
- priceToSalesTrailing12Months: float
- fiftyDayAverage: float
- twoHundredDayAverage: float
- currency: str
- enterpriseValue: int
- profitMargins: float
- floatShares: int
- sharesOutstanding: int
- sharesShort: int
- sharesShortPriorMonth: int
- sharesShortPreviousMonthDate: int
- dateShortInterest: int
- sharesPercentSharesOut: float
- heldPercentInsiders: float
- heldPercentInstitutions: float
- shortRatio: float
- shortPercentOfFloat: float
- impliedSharesOutstanding: int
- bookValue: float
- priceToBook: float
- lastFiscalYearEnd: int
- nextFiscalYearEnd: int
- mostRecentQuarter: int
- earningsQuarterlyGrowth: float
- netIncomeToCommon: int
- trailingEps: float
- forwardEps: float
- lastSplitFactor: str
- lastSplitDate: int
- enterpriseToRevenue: float
- enterpriseToEbitda: float
- 52WeekChange: float
- SandP52WeekChange: float
- lastDividendValue: float
- lastDividendDate: int
- exchange: str
- quoteType: str
- symbol: str
- underlyingSymbol: str
- shortName: str
- longName: str
- firstTradeDateEpochUtc: int
- timeZoneFullName: str
- timeZoneShortName: str
- uuid: str
- messageBoardId: str
- gmtOffSetMilliseconds: int
- currentPrice: float
- targetHighPrice: float
- targetLowPrice: float
- targetMeanPrice: float
- targetMedianPrice: float
- recommendationMean: float
- recommendationKey: str
- numberOfAnalystOpinions: int
- totalCash: int
- totalCashPerShare: float
- ebitda: int
- totalDebt: int
- quickRatio: float
- currentRatio: float
- totalRevenue: int
- debtToEquity: float
- revenuePerShare: float
- returnOnAssets: float
- returnOnEquity: float
- grossProfits: int
- freeCashflow: int
- operatingCashflow: int
- earningsGrowth: float
- revenueGrowth: float
- grossMargins: float
- ebitdaMargins: float
- operatingMargins: float
- financialCurrency: str
- trailingPegRatio: float
```

### History

```python
ticker.history(period='1mo')
```

Returns:
```python

DataFrame with columns: ['Open', 'High', 'Low', 'Close', 'Volume', 'Dividends', 'Stock Splits']
Shape: (21, 7)

```

### Financial Statements

#### Income Statement

```python
ticker.income_stmt
```

Returns:
```python

DataFrame with columns: [Timestamp('2024-06-30 00:00:00'), Timestamp('2023-06-30 00:00:00'), Timestamp('2022-06-30 00:00:00'), Timestamp('2021-06-30 00:00:00')]
Shape: (47, 4)

```

## Common Parameters

### Period Options

- `1d`: 1 day
- `5d`: 5 days
- `1mo`: 1 month
- `3mo`: 3 months
- `6mo`: 6 months
- `1y`: 1 year
- `2y`: 2 years
- `5y`: 5 years
- `10y`: 10 years
- `ytd`: Year to date
- `max`: Maximum available data

### Interval Options

- `1m`: 1 minute
- `2m`: 2 minutes
- `5m`: 5 minutes
- `15m`: 15 minutes
- `30m`: 30 minutes
- `60m`: 60 minutes
- `90m`: 90 minutes
- `1h`: 1 hour
- `1d`: 1 day
- `5d`: 5 days
- `1wk`: 1 week
- `1mo`: 1 month
- `3mo`: 3 months
"""