Time for action – finding highest and lowest values

The min and max functions are the answer to our requirement. Perform the following steps to find highest and lowest values:

1. First, we will need to read our file again and store the values for the high and low prices into arrays.

   h,l=np.loadtxt('data.csv', delimiter=',', usecols=(4,5), unpack=True)

   The only thing that changed is the usecols parameter, since the high and low prices are situated in different columns.

2. The following code gets the price range:

   print "highest =", np.max(h)
   print "lowest =", np.min(l)

   These are the values returned:

   highest = 364.9
   lowest = 333.53

   Now, it's trivial to get a midpoint, so it is left as an exercise for the reader to attempt.

3. NumPy allows us to compute the spread of an array with a function called ptp. The ptp function returns the difference between the maximum and minimum values of an array. In other words, it is equal to max(array) - min(array). Call the ptp function.

   print "Spread high price", np.ptp(h)
   print...