这几天工作不忙闲着玩ChatGPT，请教怎么下载股票信息。
| Ticker | Start Price | End Price | Price Return | Dividend Return | Gross Return |
|---|---|---|---|---|---|
| AAPL | 192.53 | 181.91 | -5.52% | -5.52% | |
| NVDA | 495.22 | 479.98 | -3.08% | -3.08% | |
| PFE | 28.79 | 29.09 | 1.04% | 1.04% |
"""Python program to download stock price from Yahoo Finance and calculate return"""
import yfinance as yf
import pandas as pd
import datetime
def get_period_return(tickers: list[str], start_date: datetime.date, end_date: datetime.date) -> pd.DataFrame:
hist = yf.download(tickers=tickers, start=f'{start_date:%Y-%m-%d}', end=f'{end_date:%Y-%m-%d}', actions=True)
hist.fillna(method='backfill', inplace=True)
d0 = hist.index[0]
d1 = hist.index[-1]
p0 = hist.loc[d0, 'Close']
p1 = hist.loc[d1, 'Close']
p_rt = p1/p0 - 1
dvd = hist.loc[:, ('Dividends', slice(None))].sum()
dvd.index = dvd.index.get_level_values(level=1)
dvd_rt = dvd/p0
g_rt = p_rt + dvd_rt
p0.name = f'Start Price'
p1.name = f'End Price'
p_rt.name = f'Price Return'
dvd_rt.name = f'Dividend Return'
g_rt.name = f'Gross Return'
res = pd.concat([p0, p1, p_rt, dvd_rt, g_rt], axis=1)
res = res.rename_axis('Ticker').reset_index()
res.loc[res['Dividend Return']==0, 'Dividend Return'] = pd.NA
return res
# Usage
start_date = datetime.date(2023, 12, 29)
end_date = datetime.date(2024, 1, 5)
tickers = ['AAPL', 'PFE', 'NVDA']
period_return = get_period_return(tickers, start_date, end_date)
# do whatever you want with period_return dataframe. e.g.
period_return.to_clipboard()
# and then paste to spreadsheet
