The quotes data in the previous step is stored in a Python list. Convert this to a NumPy array and extract the close and volume values:

dates = quotes.T[4]
volume = quotes.T[5]

Calculate the close price and volume returns:

ret = np.diff(close)/close[:-1]
volchange = np.diff(volume)/volume[:-1]

Create a matplotlib figure object:

fig = plt.figure()

Add a subplot to the figure:

ax = fig.add_subplot(111)

Create the scatter plot with the color of the data points linked to the close return, and the size linked to the volume change:

ax.scatter(ret, volchange, c=ret * 100, s=volchange * 100, alpha=0.5)

Set the title of the plot and put a grid on it:

ax.set_title('Close and volume returns')
ax.grid(True)

plt.show()

The scatter plot for DISH appears as follows: