The advantage is that the calculation is globally efficient, but the disadvantage is that the calculation complexity is high and the data points are sensitive to change.

1, global: Lagrange interpolation can use all known data points for interpolation, which can better fit the changing trend of the whole data set.

2. Efficient calculation: Newton interpolation adopts the method of difference quotient, and the coefficients of interpolation polynomial can be obtained by recursive calculation, with high calculation efficiency.

3. High computational complexity: Lagrangian interpolation needs to calculate the Lagrangian basis function corresponding to each data point, which has high computational complexity, especially when there are many data points.

4. Data points are sensitive to changes: Newton interpolation uses the difference quotient to calculate the coefficients of interpolation polynomials. When the distance between data points is uneven or the number of data points is small, the interpolation result is very sensitive to the position of data points.