Data are plotted with plotting widgets. Here is a list:

A plotter which plots a function on the graph. Functions can be functions of x or y (parametric functions are not done yet!), and are defined in Python expression syntax, which is very close to most other languages. For example 3*x**2 + 2*x - 4. A number of functions are available (e.g. sin, cos, tan, exp, log...). Technically, Veusz imports the numpy package when evaluating, so numpy functions are available. As well as the function setting, also settable is the line type to plot the function, and the number of steps to evaluate the function when plotting. Filling is supported above/below/left/right of the function.

A plotter which plots scatter, line, or stepped plots. This versatile plotter takes an x and y dataset, and plots (optional) points, in a chosen marker and colour, connecting them with (optional) lines, and plotting (optional) error bars. An xy plotter can also plot a stepped line, allowing histograms to be plotted (note that it doesn't yet do the binning of the data). The settings for the xy widget are the various attibutes for the points, line and error bars, the datasets to plot, and the axes to plot on. The xy plotter can plot a label next to each dataset, which is either the same for each point or taken from a text dataset.If you wish to leave gaps in a plot, the input value "nan" can be specified in the numeric dataset.

Fit a function to data. This plotter is a like the function plotter, but allows fitting of the function to data. This is achived by clicking on a "fit" button, or using the "fit" action of the widget. The fitter takes a function to fit containing the unknowns, e.g. a*x**2 + b*x + c, and initial values for the variables (here a, b and c). It then fits the data (note that at the moment, the fit plotter fits all the data, not just the data that can be seen on the graph) by minimising the chi-squared.

In order to fit properly, the y data (or x, if fitting as a function of x) must have a properly defined, preferably symmetric error. If there is none, Veusz assumes the same fractional error everywhere, or symmetrises asymmetric errors.

Note that more work is required in this widget, as if a parameter is not well defined by the data, the matrix inversion in the fit will fail. In addition Veusz does not supply estimates for the errors or the final chi-squared in a machine readable way.

If the fitting parameters vary significantly from 1, then it is worth "normalizing" them by adding in a factor in the fit equation to bring them to of the order of 1.

A bar chart which plots sets of data as horizontal or vertical bars. Multiple datasets are supported. In "grouped" mode the bars are placed side-by-side for each dataset. In "stacked" mode the bars are placed on top of each other (in the appropriate direction according to the sign of the dataset). Bars are placed on coordinates given, or in integer values from 1 upward if none are given. Error bars are plotted for each of the datasets.

Different fill styles can be given for each dataset given. A separate key value can be given for each dataset.

A box which describes the data plotted. If a key is added to a plot, the key looks for "key" settings of the other data plotted within a graph. If there any it builds up a box containing the symbol and line for the plotter, and the text in the "key" setting of the widget. This allows a key to be very easily added to a plot.

The key may be placed in any of the corners of the plot, in the centre, or manually placed. Depending on the ordering of the widgets, the key will be placed behind or on top of the widget. The key can be filled and surrounded by a box, or not filled or surrounded.

A text label places on a graph. The alignment can be adjusted and the font changed. The position of the label can be specified in fractional terms of the current graph, or using axis coordinates.

These draw a rectangle or ellipse, respectively, of size and rotation given. These widgets can be placed directly on the page or on a graph. The centre can be given in axis coordinates or fractional coordinates.

Draw an external graphs file on the graph or page, with size and rotation given. The centre can be given in axis coordinates or fractional coordinates.

Draw a line with optional arrowheads on the graph or page. One end can be given in axis coordinates or fractional coordinates.

Plot contours of a 2D dataset on the graph. Contours are automatically calculated between the minimum and maximum values of the graph or chosen manually. The line style of the contours can be chosen individually and the region between contours can be filled with shading or colour.

2D datasets currently consist of a regular grid of values between minimum and maximum positions in x and y. They can be constructed from three 1D datasets of x, y and z if they form a regular x, y grid.

Plot a 2D dataset as a coloured image. Different colour schemes can be chosen. The scaling between the values and the image can be specified as linear, logarithmic, square-root or square.

Plot x and y points from datasets as a polygon. The polygon can be placed directly on the page or within a graph. Coordinates are either plotted using the axis or as fractions of the width and height of the containing widget.