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3.1.3 Scatter Plot

        A scatter plot comprises individual data points as markers on a two-dimensional graph. It is particularly useful for
        visualizing the discrete data, as shown in Fig 3.9 below.
        Let us consider the following code snippet where we have two lists: expenses and revenue, representing monthly
        expenses and revenue, respectively. The scatter plot is created using plt.scatter() function, where the x-axis
        represents expenses and the y-axis represents revenue. Each data point is plotted as a blue marker.
        Labels are set for the x-axis, y-axis, and title using plt.xlabel(), plt.ylabel(), and plt.title() functions,
        respectively. Finally, plt.show() displays the scatter plot.
         >>> import matplotlib.pyplot as plt
         >>> expenses = [100, 200, 150, 300, 250]  # Monthly expenses
         >>> revenue = [500, 600, 650, 700, 800]  # Monthly revenue
         >>> plt.scatter(revenue, expenses, color='blue')
         >>> plt.xlabel('Revenue (in INR)')
         >>> plt.ylabel('Expenses (in INR)')
         >>> plt.title('Expenses vs. Revenue')
         >>> plt.show()




























                                                Fig 3.9: Expenses vs. Revenue
        The plt.plot() function that we used to plot a single point in the beginning of this chapter may also be used to
        draw a scatter, by specifying the two sequences: one for the x-coordinates and the other for the y-coordinates, as
        shown below (Fig 3.10):

         >>> import matplotlib.pyplot as plt
         >>> expenses = [100, 200, 150, 300, 250]  # Monthly expenses
         >>> revenue = [500, 600, 650, 700, 800]  # Monthly revenue
         >>> plt.plot(revenue, expenses, 'bo')
         >>> plt.xlabel('Revenue (in INR)')
         >>> plt.ylabel('Expenses (in INR)')
         >>> plt.title('Expenses vs. Revenue')
         >>> plt.show()











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