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import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cbook as cbook
# load up some sample financial data
datafile = cbook.get_sample_data('goog.npy')
r = np.load(datafile).view(np.recarray)
# create two subplots with the shared x and y axes
fig, (ax1, ax2) = plt.subplots(1,2, sharex=True, sharey=True)
pricemin = r.close.min()
ax1.plot(r.date, r.close, lw=2)
ax2.fill_between(r.date, pricemin, r.close, facecolor='blue', alpha=0.5)
for ax in ax1, ax2:
    ax.grid(True)
ax1.set_ylabel('price')
for label in ax2.get_yticklabels():
    label.set_visible(False)
fig.suptitle('Google (GOOG) daily closing price')
fig.autofmt_xdate()

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