let' remove the axes in this plot so they don' distract us from the path of each walk to turn the axes offuse this coderw_visual py --snip-while true--snip-plt scatter(rw x_values[- ]rw y_values[- ] ='red'edgecolors='none' = remove the axes plt axes(get_xaxis(set_visible(falseplt axes(get_yaxis(set_visible(falseplt show(--snip-to modify the axesuse the plt axes(function to set the visibility of each axis to false as you continue to work with visualizationsyou'll frequently see this chaining of methods run rw_visual py nowyou should see series of plots with no axes adding plot points let' increase the number of points to give us more data to work with to do sowe increase the value of num_points when we make randomwalk instance and adjust the size of each dot when drawing the plotas shown hererw_visual py --snip-while truemake random walkand plot the points rw randomwalk( rw fill_walk(plot the pointsand show the plot point_numbers list(range(rw num_points)plt scatter(rw x_valuesrw y_valuesc=point_numberscmap=plt cm bluesedgecolor='none' = --snip-this example creates random walk with , points (to mirror realworld dataand plots each point at size = the resulting walk is wispy and cloud-likeas shown in figure - as you can seewe've created piece of art from simple scatter plotexperiment with this code to see how much you can increase the number of points in walk before your system starts to slow down significantly or the plot loses its visual appeal generating data