实现代码:
import numpy as np import 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 the date as an np.datetime64 with a day unit ('D') in the date column. with cbook.get_sample_data('goog.npz') as datafile: price_data = np.load(datafile)['price_data'].view(np.recarray) price_data = price_data[-250:] # get the most recent 250 trading 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 * price_data.close[:-2] / 0.003 * price_data.open[:-2] fig, ax = plt.subplots() ax.scatter(delta1[:-1], delta1[1:], c=close, s=volume, alpha=0.5) ax.set_xlabel(r'$\Delta_i$', fontsize=15) ax.set_ylabel(r'$\Delta_{i+1}$', fontsize=15) ax.set_title('Volume and percent change') ax.grid(True) fig.tight_layout() plt.show()
总结
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