Analysis functions
LabPlot supports a wide variety of data analysis functions:
Interpolation
Smoothing
Nonlinear curve fitting
Fourier filter
All of them can be applied to any data consisting of x- and y-columns. The analysis functions can be accessed using the Analysis menu or the context menu of a worksheet. The newly created curves can be customized (line style, symbol style, ) like any other x-y-curve.

Interpolation
Interpolation of data can be done with several algorithm:
linear
polynomial (if number of data points < 100)
cubic spline
cubic spline (periodic)
Akima spline
Akima spline (periodic)
Steffen spline (needs GSL ≥ 2.0)
cosine
exponential
piecewise cubic Hermite (finite differences, Catmull-Rom, cardinal, Kochanek-Bartels)
rational functions
The interpolating function is calculated with the given number n of data points and evaluated as:
function
derivative
second derivative
integral (starting from zero)

Smoothing
A number of different smoothing methods are supported:
Moving average (central)
Moving average (lagged)
Percentile filter
Savitzky-Golay
All smoothing methods support several padding modes (constant, periodic, mirror, nearest, etc.) for the beginning and end of the data set. The moving averages support several weight functions (uniform, triangular, binomial, parabolic, tricubic, etc.) which can be selected to weight the selected data points depending on their distance.

Curve fitting
Linear and non-linear curve fitting of data can be done with several predefined fit-models (for instance polynomial, exponential, Gaussian or custom) to data consisting of x- and y-columns with an optional weight column. With a custom model any function with unlimited number of parameters can be used for fitting. The options (number of iterations, tolerance, number of fitted points) can be used to optimize the fitting result which is displayed in the results text.

Fourier filter
This function can be used to apply a Fourier filter to any data consisting of x- and y-columns. Supported filter types are:
Low pass
High pass
Band pass
Band reject (band block)
where any of them can have the form
Ideal
Butterworth (order 1 to 10)
Chebyshev type I or II (order 1 to 10)
Optimal "L"egendre (order 1 to 10)
Bessel-Thomson (any order)
The cutoff value(s) can be specified in the units frequency (Hertz), fraction (0.0 to 1.0) or index of the data points.

Fourier transform
To convert a signal from time to frequency domain or to change between other conjugate variables like position and momentum (k-space) a discrete Fourier transform can be applied. Following options can be used to suite one needs:
window function (Welch, Hann, Hamming, etc.) to avoid leakage effects
output (magnitude, amplitude, phase, dB, etc.)
one or two sided spectrum with or without shifting
x axis scaling to frequency, index or period