and pause with the viewer open when you close the vieweryou'll be asked whether you want to generate another walk answer yand you should be able to generate walks that stay near the starting pointthat wander off mostly in one directionthat have thin sections connecting larger groups of pointsand so on when you want to end the programenter if you're using python remember to use raw_input(instead of input(at note styling the walk in this section we'll customize our plots to emphasize the important characteristics of each walk and deemphasize distracting elements to do sowe identify the characteristics we want to emphasizesuch as where the walk beganwhere it endedand the path taken nextwe identify the characteristics to deemphasizelike tick marks and labels the result should be simple visual representation that clearly communicates the path taken in each random walk coloring the points we'll use colormap to show the order of the points in the walk and then remove the black outline from each dot so the color of the dots will be clearer to color the points according to their position in the walkwe pass the argument list containing the position of each point because the points are plotted in orderthe list just contains the numbers from to as shown hererw_visual py --snip-while truemake random walkand plot the points rw randomwalk(rw fill_walk( point_numbers list(range(rw num_points)plt scatter(rw x_valuesrw y_valuesc=point_numberscmap=plt cm bluesedgecolor='none' = plt show(keep_running input("make another walk( / )"--snip-at we use range(to generate list of numbers equal to the number of points in the walk then we store them in the list point_numberswhich we'll use to set the color of each point in the walk we pass point_numbers to the argumentuse the blues colormapand then pass edgecolor=none to get rid of the black outline around each point the result is plot of the walk that varies from light to dark blue along gradientas shown in figure - generating data