Exercise

# Visualize all walks

`all_walks`

is a list of lists: every sub-list represents a single random walk. If you convert this list of lists to a Numpy array, you can start making interesting plots! `matplotlib.pyplot`

is already imported as `plt`

.

The nested `for`

loop is already coded for you - don't worry about it. For now, focus on the code that comes after this `for`

loop.

Instructions

**100 XP**

- Use
`np.array()`

to convert`all_walks`

to a Numpy array,`np_aw`

. - Try to use
`plt.plot()`

on`np_aw`

. Also include`plt.show()`

. Does it work out of the box? - Transpose
`np_aw`

by calling`np.transpose()`

on`np_aw`

. Call the result`np_aw_t`

. Now every row in`np_all_walks`

represents the position after 1 throw for the 10 random walks. - Use
`plt.plot()`

to plot`np_aw_t`

; also include a`plt.show()`

. Does it look better this time?