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https://github.com/OpenBB-finance/OpenBB.git
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f3d6dd1db1
* Added basic paragraph * Updated rmr with new format * Added beta text * Simplified get_rolling_beta * Didier changes * Removed advice and lowercased strings * Didn't wait * Fixed wording * Added quantity multiplication * Removed plot_ef, I don't think its operating properly * wording changes, fixed beta * Fixed cash error * Added docstrings Co-authored-by: Colin Delahunty <colindelahunty@Colins-Air.indiana.edu> Co-authored-by: Colin Delahunty <colindelahunty@Colins-MacBook-Air.local>
86 lines
2.0 KiB
Python
86 lines
2.0 KiB
Python
"""Yfinance model"""
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__docformat__ = "numpy"
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from typing import List
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from datetime import datetime, timedelta
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import yfinance as yf
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import pandas as pd
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def get_stocks(tickers: List[str], start: datetime) -> pd.DataFrame:
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"""Gets historic data for list of tickers
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Parameters
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----------
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tickers : List[str]
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Tickers to get data for
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start : datetime
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First date in stock filtered dataframe
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Returns
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----------
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data : pd.DataFrame
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Historic daily prices for stocks
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"""
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df = yf.download(
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tickers=tickers,
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start=start - timedelta(days=365),
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interval="1d",
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progress=False,
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)
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df = df["Adj Close"]
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if len(tickers) > 1:
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df.columns = df.columns.str.lower()
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arrays = [["Close" for _ in df.columns], [x.lower() for x in df.columns]]
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tuples = list(zip(*arrays))
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headers = pd.MultiIndex.from_tuples(tuples, names=["first", "second"])
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df.columns = headers
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if len(tickers) == 1:
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df = df.to_frame(name=("Close", tickers[0]))
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return df
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def get_dividends(tickers: List[str]) -> pd.DataFrame:
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"""Past dividends for list of tickers
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Parameters
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----------
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tickers : List[str]
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Tickers to get data for
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Returns
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----------
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data : pd.DataFrame
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Historic dividends for stocks
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"""
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dfs = []
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for ticker in tickers:
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tick = yf.Ticker(ticker)
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df = tick.dividends.to_frame(name=("Dividend", ticker))
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dfs.append(df)
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return pd.concat(dfs)
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def get_market(start: datetime, ticker: str = "SPY") -> pd.DataFrame:
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"""Get historical data for market asset
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Parameters
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----------
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ticker : str
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Ticker to get data for
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start : datetime
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First date in stock filtered dataframe
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Returns
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----------
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data : pd.DataFrame
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Historic prices for SPY
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"""
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tick = yf.Ticker(ticker)
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df = tick.history(
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start=start - timedelta(days=365),
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interval="1d",
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)["Close"]
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return df.to_frame(name=("Market", "Close"))
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