A Python question !

I have no idea how to use np.array() to store 1 million pi's

Here is part of my code

numpy.float32 (numpy.sin(numpy.pi))

the output is 1.2246469e-16, but if using 32-bit precision, wouldn't the result be XXXX times 10^(-8) ? Why is it still 10^(-16)?

Part C (2 points) We're insulated from these issues with precision by using 64-bit floating point, but NumPy supports other representations that use small amounts of memory. Use the np, array() function to create another array with 1 million copies of , but this time in 32-bit precision (using data type np. float32 .) You should get a much larger accumulated error