The min and max functions are the answer to our requirement. Perform the following steps to find highest and lowest values:
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
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 trivial to get a midpoint, so it is left as an exercise for the reader to attempt.
NumPy allows us to compute the spread of an array with a function called
ptp. Theptpfunction returns the difference between the maximum and minimum values of an array. In other words, it is equal to max(array) - min(array). Call theptpfunction.print "Spread high price", np.ptp(h) print...