Time for action – finding highest and lowest values

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

1. First, 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 easy to get a midpoint, so it is left as an exercise for you 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("Spread...