Numpy Beginner's Guide (Update)

Time for action – plotting price and volume returns with a scatter plot

We can easily make a scatter plot of the stock price and volume returns. Again, let's download the necessary data from Yahoo Finance.

1. 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]

2. Calculate the close price and volume returns:

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

3. Create a matplotlib figure object:

   fig = plt.figure()

4. Add a subplot to the figure:

   ax = fig.add_subplot(111)

5. 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, ...