具有不同标记颜色和大小的散点图演示。
演示结果:
实现代码:
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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()
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