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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def plot_stats(statistics, ylog=False, view=False, filename='avg_fitness.svg'):
 """ Plots the population's average and best fitness. """

    if plt is None:
        warnings.warn("This display is not available due to a missing optional dependency (matplotlib)")
        return

    generation = range(len(statistics.most_fit_genomes))
    best_fitness = [c.fitness for c in statistics.most_fit_genomes]
    avg_fitness = np.array(statistics.get_fitness_mean())
    stdev_fitness = np.array(statistics.get_fitness_stdev())

    plt.plot(generation, avg_fitness, 'b-', label="average")
    plt.plot(generation, avg_fitness - stdev_fitness, 'g-.', label="-1 sd")
    plt.plot(generation, avg_fitness + stdev_fitness, 'g-.', label="+1 sd")
    plt.plot(generation, best_fitness, 'r-', label="best")

    plt.title("Population's average and best fitness")
    plt.xlabel("Generations")
    plt.ylabel("Fitness")
    plt.grid()
    plt.legend(loc="best")
    if ylog:
        plt.gca().set_yscale('symlog')

    plt.savefig(filename)
    if view:
        plt.show()

    plt.close()