In [2]:
import pandas_datareader
from datetime import datetime
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
In [3]:
intc = pandas_datareader.DataReader('INTC', 'yahoo',
datetime(2000, 1, 1),
datetime.now())
amd = pandas_datareader.DataReader('AMD', 'yahoo',
datetime(2000, 1, 1),
datetime.now())
nvda = pandas_datareader.DataReader('NVDA', 'yahoo',
datetime(2000, 1, 1),
datetime.now())
In [9]:
qcom = pandas_datareader.DataReader('QCOM', 'yahoo',
datetime(2000, 1, 1),
datetime.now())
avgo = pandas_datareader.DataReader('AVGO', 'yahoo',
datetime(2000, 1, 1),
datetime.now())
In [6]:
snp = pandas_datareader.DataReader('^GSPC', 'yahoo',
datetime(2000, 1, 1),
datetime.now())
In [7]:
# sep07 = datetime(2007, 8, 15)
# # intc.loc['2015-02-12']
# intc.loc[sep07]
In [11]:
t0 = datetime(2005, 6, 1)
t1 = datetime(2008, 6, 1)
plt.plot(intc.loc[t0:t1].index, intc.loc[t0:t1].Close, c='c', label='INTC')
plt.plot(amd.loc[t0:t1].index, amd.loc[t0:t1].Close, c='m', label='AMD')
plt.plot(nvda.loc[t0:t1].index, nvda.loc[t0:t1].Close, c='y', label='NVDA')
plt.plot(qcom.loc[t0:t1].index, qcom.loc[t0:t1].Close, c='b', label='QCOM')
plt.plot(avgo.loc[t0:t1].index, avgo.loc[t0:t1].Close, c='r', label='AVGO')
plt.legend()
plt.xticks(rotation=45)
plt.grid(True)
In [12]:
t0 = datetime(2014, 6, 1)
t1 = datetime(2018, 6, 1)
plt.plot(intc.loc[t0:t1].index, intc.loc[t0:t1].Close, c='c', label='INTC')
plt.plot(amd.loc[t0:t1].index, amd.loc[t0:t1].Close, c='m', label='AMD')
plt.plot(nvda.loc[t0:t1].index, nvda.loc[t0:t1].Close, c='y', label='NVDA')
plt.plot(qcom.loc[t0:t1].index, qcom.loc[t0:t1].Close, c='b', label='QCOM')
plt.plot(avgo.loc[t0:t1].index, avgo.loc[t0:t1].Close, c='r', label='AVGO')
plt.legend()
plt.xticks(rotation=45)
plt.grid(True)
In [93]:
plt.plot(snp.loc[t0:t1].index, snp.loc[t0:t1].Close.apply(lambda x: x/snp.Close.mean()),
c='orange', label='^GSPC')
plt.legend()
plt.xticks(rotation=45)
plt.grid(True)
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