The scatter diagram demonstrates

labeled with different color and size.


import numpy as NP import pre> matplotlib.pyplot as PLT import matplotlib.cbook as cbook Load a numpy record array from # Yahoo CSV data with fields date, open, close, volume adj_close from #, the mpl-data/example directory. The record array stores date as an # the np.datetime64 with a day unit ('D') in the date column. with cbook.get_sample_data as datafile: price_data ('goog.npz') = np.load (datafile) ['price_data'].view (np.recarray) price_data = price_data[-250:] get the most recent trading 250 # days = Delta1 Np.diff (price_data.adj_close) / price_data.adj_close[: -1] Marker size in units of points^2 # (volume = 15 * price_data.volume[: -2] / price_data.volume[0]) **2 close = 0.003 * 0.003 *[/ price_data.close[: -2]: -2] = plt.subplots (fig, ax) ax.scatter (delta1[: -1], delta1[1:], c=close, s=volume, alpha=0.5 (r'$Delta_i$') ax.set_xlabel fontsize=15), ax.set_ylabel (r'$Delta_{i+1}$', fontsize=15) ax.set_title ('Volume and percent change') ax.grid (True) fig.tight_layout ( (


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