Plotting a polynomial fit from points takes an array of (x, y) points, finds the equation of the polynomial that best connects them, then plots the line on a display along with the points.
Solution for How to plot a polynomial fit from an array of points using NumPy and Matplotlib in Python : You can use numpy.polyfit() and numpy.poly1d() to plot a polynomial fit from an array of points
- Slice the array of points to get separate x and y vectors.
- Use numpy.polyfit(x, y, deg) and np.poly1d(c_or_r) with the result of numpy.polyfit() as c_or_r to calculate the polynomial.
- Calculate new x and y values using numpy.linspace(start, stop) with x as start and x[-1] as stop, and the calculated polynomial, respectively.
- Plot the polynomial fit using matplotlib.plot(x, y, fmt, x’ y’) and plt.xlim(x, y).