Software
We've compiled a list of 51 free and paid alternatives to python(x,y). The primary competitors include MATLAB, GNU Octave. In addition to these, users also draw comparisons between python(x,y) and Mathematica, Sage, GeoGebra. Also you can look at other similar options here: Education and Reference Software.
We've compiled a list of 51 free and paid alternatives to python(x,y). The primary competitors include MATLAB, GNU Octave. In addition to these, users also draw comparisons between python(x,y) and Mathematica, Sage, GeoGebra. Also you can look at other similar options here: Education and Reference Software.
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Octave is a computer program for performing numerical computations which is mostly compatible with...
142
Mathematica is a computational software program used widely in scientific, engineering, and...
134
Sage is a free open-source mathematics software system licensed under the GPL.
107
GeoGebra is free and multi-platform dynamic mathematics software for learning and teaching.
83
Scilab is a scientific software package for numerical computations providing a powerful open...
79
IPython is an interactive shell for the Python programming language that offers enhanced...
76
SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and...
66
Gnuplot is a portable command-line driven interactive data and function plotting utility.
57
wxMaxima is a document based interface for the computer algebra system Maxima.
37
Python(x,y) is a free scientific and engineering development software for numerical computations...
Python(x,y) is a free scientific and engineering development software for numerical computations...
Windows
Python(x,y) is a free scientific and engineering development software for numerical computations, data analysis and data visualization based on Python programming language, Qt graphical user interfaces and 
Spyder interactive scientific development environment.
With Python(x,y), one can do:
interactive calculations including for example 2D and 3D plotting or symbolic maths,
simple functionnal programming (with 
MATLAB -like syntax) as well as powerful object-oriented programming,
scientific projects development from the simplest script to the most sophisticated application thanks to Qt development framework and Spyder development environment,
parallel computing on multicore/processors computers or even clusters (with Parallel Python),
...and a lot more!
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