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:
- 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
usecolsparameter, since the high and low prices are situated in different columns. - 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.
- NumPy allows us to compute the spread of an array with a function called
ptp(). Theptp()function returns the difference between the maximum and minimum values of an array. In other words, it is equal tomax(array)—min(array). Call theptp...
