import numpy as np import matplotlib.cbook as cbook import matplotlib.dates as dates import matplotlib.ticker as ticker import matplotlib.pyplot as plt
# load some financial data; apple's stock price with cbook.get_sample_data('aapl.npz') as fh: r = np.load(fh)['price_data'].view(np.recarray) r = r[-250:] # get the last 250 days # Matplotlib works better with datetime.datetime than np.datetime64, but the # latter is more portable. date = r.date.astype('O')
for tick in ax.xaxis.get_minor_ticks(): tick.tick1line.set_markersize(0) tick.tick2line.set_markersize(0) tick.label1.set_horizontalalignment('center')