QtiPlot is fully scriptable via Python, watch the video bellow for a short demonstration of how to create and fully customize a plot using a very simple Python script:
The fact that you can run Python scripts from QtiPlot gives you the possibility to use powerfull existing scientific tools,
like SciPy, SymPy
or rpy2, thus bringing unlimited data analysis power.
Here's a screenshot demonstrating how QtiPlot can become a full-featured computer algebra system (CAS), thanks to SymPy:
In order to run this example, you need an internet connection, since the script will try to download all the
nonlinear regression test files
from the Statistical Reference Datasets Project. Unzip the downloaded script and launch QtiPlot from a command interpreter:
qtiplot -x strd_nist_fit.py
If you don't want to display the QtiPlot user interface, run the example with the following option:
qtiplot -X strd_nist_fit.py
For more details about the Python scripting capabilities available in QtiPlot please read the user manual.