at the barest minimumwe can expect the two test datasets to belong to different clusters our expectation is proved right when the print statement prints and thus confirming that our test data does indeed fall under two different clusters data visualization numerical analysis does not sometimes lend itself to easy understanding indeeda single image is worth , words and in this sectionan image would be worth , tables comprised of numbers only images present quick way to analyze data differences in size and lengths are quick markers in an image upon which conclusions can be drawn in this sectionwe will take tour of the different ways to represent data besides the graphs listed herethere is more that can be achieved when chatting data bar chart to chart the values and into bar graphwe will store the values in an array and pass it to the bar function the bars in the graph represent the magnitude along the yaxisimport matplotlib pyplot as plt data [ x_values range(len(data)plt bar(x_valuesdataplt show(x_values stores an array of values generated by range(len(data)alsox_values will determine the points on the -axis where the bars will be drawn the first bar will be drawn on the -axis where is the second bar with data will be drawn on the -axis where is