I discovered some useful functions the other day while trying to solve one of the Dataquest guided projects. These all relate somehow to lists and use Numpy. I'm listing them here mainly as a note for my future-self.
import numpy as np
# this code returns a list of n number of items starting at 0
np.arange(3)
---- returns [0,1,2]
# this code is a variation on the previous one
np.arange(3,7)
---- returns [3,4,5,6]
# this adds the functionality of steps in between values
np.arange(2,9,2)
---- returns [2,4,6,8]
# these are slightly different; they sort lists
# if you want to make list of numbers randomly sorted:
np.random.permutation(10)
---- returns the numbers 1-9 in a list, randomly sorted
# you can also pass non-numeric lists into the `permutation`
list = [a,b,c]
np.random.permutation(list)
---- returns something like [b,a,c]