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corresponding actual value. x = np.linspace(1960, 2015, 55) # Normalize x x = x / max(x) plt.figure(figsize=(8,5)) y = sigmoid(x, popt[0], popt[1]) # Plotting the original data points plt.plot(xdata, ydata, 'ro', label='data') # Plotting the fitted prediction line plt.plot(x, y, linewidth=3.0,