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 ...

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