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"""
Demo of scatter plot with varying marker colors and sizes.
"""
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 python datetime.date as an object array in
# the date column
datafile = cbook.get_sample_data('goog.npy')
try:
# Python3 cannot load python2 .npy files with datetime(object) arrays
# unless the encoding is set to bytes. However this option was
# not added until numpy 1.10 so this example will only work with
# python 2 or with numpy 1.10 and later
price_data = np.load(datafile, encoding='bytes').view(np.recarray)
except TypeError:
price_data = np.load(datafile).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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