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
usecols
parameter, 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 ...
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