importmatplotlib.pyplotaspltimportnumpyasnpimportmatplotlib.cbookascbook# Load a numpy record array from yahoo csv data with fields date, open, high,# low, close, volume, adj_close from the mpl-data/sample_data directory. The# record array stores the date as an np.datetime64 with a day unit ('D') in# the date column.price_data=cbook.get_sample_data('goog.npz')['price_data']price_data=price_data[-250:]# get the most recent 250 trading daysdelta1=np.diff(price_data["adj_close"])/price_data["adj_close"][:-1]# Marker size in units of points^2volume=(15*price_data["volume"][:-2]/price_data["volume"][0])**2close=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()

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