AMZN stock data retrieval with YahooDailyReader - python-3.x

Question

Up until 30 minutes ago I was executing the following code without problems:
import pandas_datareader.data as web
import datetime
start = datetime.datetime(2012,1,1)
end = datetime.datetime(2015,12,31)
AAPL = web.get_data_yahoo('AAPL', start, end)
AMZN = web.get_data_yahoo('AMZN', start, end)
Instead now I get:
Traceback (most recent call last):
File "/Users/me/opt/anaconda3/lib/python3.7/site-packages/pandas_datareader/yahoo/daily.py", line 157, in _read_one_data
data = j["context"]["dispatcher"]["stores"]["HistoricalPriceStore"]
KeyError: 'HistoricalPriceStore'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/me/opt/anaconda3/lib/python3.7/site-packages/pandas_datareader/data.py", line 82, in get_data_yahoo
return YahooDailyReader(*args, **kwargs).read()
File "/Users/me/opt/anaconda3/lib/python3.7/site-packages/pandas_datareader/base.py", line 251, in read
df = self._read_one_data(self.url, params=self._get_params(self.symbols))
File "/Users/me/opt/anaconda3/lib/python3.7/site-packages/pandas_datareader/yahoo/daily.py", line 160, in _read_one_data
raise RemoteDataError(msg.format(symbol, self.__class__.__name__))
pandas_datareader._utils.RemoteDataError: No data fetched for symbol AMZN using YahooDailyReader
How can I fix this?
Is there a work around to get the AMZN data as DataFrame from another source (different from Yahoo_Daily_Reader)?
Python version 3.4.7

Answer 1

How about this solution?
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import scipy.optimize as sco
import datetime as dt
import math
from datetime import datetime, timedelta
from pandas_datareader import data as wb
from sklearn.cluster import KMeans
np.random.seed(777)
start = '2019-4-30'
end = '2019-10-31'
# N = 90
# start = datetime.now() - timedelta(days=N)
# end = dt.datetime.today()
tickers = ['MMM',
'ABT',
'AAPL',
'AMAT',
'APTV',
'ADM',
'ARNC',
'AMZN']
thelen = len(tickers)
price_data = []
for ticker in tickers:
prices = wb.DataReader(ticker, start = start, end = end, data_source='yahoo')[['Adj Close']]
price_data.append(prices.assign(ticker=ticker)[['ticker', 'Adj Close']])
df = pd.concat(price_data)
df.dtypes
df.head()
df.shape
pd.set_option('display.max_columns', 500)
df = df.reset_index()
df = df.set_index('Date')
table = df.pivot(columns='ticker')
# By specifying col[1] in below list comprehension
# You can select the stock names under multi-level column
table.columns = [col[1] for col in table.columns]
table.head()
plt.figure(figsize=(14, 7))
for c in table.columns.values:
plt.plot(table.index, table[c], lw=3, alpha=0.8,label=c)
plt.legend(loc='upper left', fontsize=12)
plt.ylabel('price in $')