I have been using this code to extract (scrape) stock prices from Yahoo Finance for the last year, but now it produces an error. Does anyone know why this is happening and how to fix it?
# Importing necessary packages
from pandas_datareader import data as web
import datetime as dt
import matplotlib.pyplot as plt
import pandas as pd
import os
import numpy as np
# Stock selection from Yahoo Finance
stock = input("Enter stock symbol or ticket symbol (Exp. General Electric is 'GE'): ")
# Visualizing the stock over time and setting up the dataframe
start_date = (dt.datetime.now() - dt.timedelta(days=40000)).strftime("%m-%d-%Y")
df = web.DataReader(stock, data_source='yahoo', start=start_date)
#THE ERROR IS ON THIS LINE^
plt.plot(df['Close'])
plt.title('Stock Prices Over Time',fontsize=14)
plt.xlabel('Date',fontsize=14)
plt.ylabel('Mid Price',fontsize=14)
plt.show()
RemoteDataError: Unable to read URL: https://finance.yahoo.com/quote/MCD/history?period1=-1830801600&period2=1625284799&interval=1d&frequency=1d&filter=history Response Text: b'\n \n \n \n Yahoo\n \n \n \n html {\n height: 100%;\n }\n body {\n background: #fafafc url(https://s.yimg.com/nn/img/sad-panda-201402200631.png) 50% 50%;\n background-size: cover;\n height: 100%;\n text-align: center;\n font: 300 18px "helvetica neue", helvetica, verdana, tahoma, arial, sans-serif;\n }\n table {\n height: 100%;\n width: 100%;\n table-layout: fixed;\n border-collapse: collapse;\n border-spacing: 0;\n border: none;\n }\n h1 {\n font-size: 42px;\n font-weight: 400;\n color: #400090;\n }\n p {\n color: #1A1A1A;\n }\n #message-1 {\n font-weight: bold;\n margin: 0;\n }\n #message-2 {\n display: inline-block;\n *display: inline;\n zoom: 1;\n max-width: 17em;\n _width: 17em;\n }\n \n \n document.write('&test=\'+encodeURIComponent(\'%\')+\'" width="0px" height="0px"/>');var beacon = new Image();beacon.src="//bcn.fp.yahoo.com/p?s=1197757129&t="+ne...
I use this code to extract data from yahoo:
start = pd.to_datetime(['2007-01-01']).astype(int)[0]//10**9 # convert to unix timestamp.
end = pd.to_datetime(['2020-12-31']).astype(int)[0]//10**9 # convert to unix timestamp.
url = 'https://query1.finance.yahoo.com/v7/finance/download/' + stock_ticker + '?period1=' + str(start) + '&period2=' + str(end) + '&interval=1d&events=history'
df = pd.read_csv(url)