A Review of Plotting Libraries for Python

An (ongoing) summary of my experience with some of the utilities available for plotting from a python perspective.

Last updated: 2008-03-06

Ploticus

• (+) Fast, powerful, mature, well-documented
• (-) Not python based

C-based rather than python-based but fast and powerful. There is a (fairly crude) set of python bindings available here: http://www.srcc.lsu.edu/~davids/ploticus_module.html. Alternatively one can just call the ploticus command from a python script.

Matplotlib

• (+) Fairly powerful, mature, well-documented, nice pure python API
• (-) A little slow; requires a backend to be installed (so installation on a server is a problem)
• Could support object-orientation better

PyChart

http://home.gna.org/pychart/

• (+) Pure python, quite simple to use, good documentation
• (-) Not quite as nice looking or as powerful as e.g. ploticus

Biggles

http://biggles.sourceforge.net/

• last updated: 2004-03-08
• looks fine but does not seem to be actively developed any longer

Example

See: http://home.gna.org/pychart/examples/index.html. This is the bar/line example from there:

from pychart import *
theme.get_options()

data = [(10, 20, 30), (20, 65, 33),
    (30, 55, 30), (40, 45, 51),
    (50, 25, 27), (60, 75, 30)]

ar = area.T(size = (150,120),
            y_grid_interval=10,
            x_axis=axis.X(label="X label", label_offset=(0,-7)),
            y_axis=axis.Y(label="Y label"),
            legend = legend.T(), y_range = (0, None))

ar.add_plot(bar_plot.T(label="foo", data=data),
            line_plot.T(label="bar", data=data, ycol=2))
ar.draw()