Execute the following steps to download the stock prices and calculate simple/log returns.

1. Import the libraries:

import pandas as pd 
import numpy as np
import yfinance as yf

2. Download the data and keep the adjusted close prices only:

df = yf.download('AAPL', 
                 start='2000-01-01', 
                 end='2010-12-31',
                 progress=False)

df = df.loc[:, ['Adj Close']]
df.rename(columns={'Adj Close':'adj_close'}, inplace=True)

3. Calculate the simple and log returns using the adjusted close prices:

df['simple_rtn'] = df.adj_close.pct_change()
df['log_rtn'] = np.log(df.adj_close/df.adj_close.shift(1))

The resulting DataFrame looks as follows:

The first row will always contain a not a number (NaN) value, as there is no previous price to use for calculating the returns.