If you want quickly to get started with data analysis, here is my advise on free software programs that I use every day for data analysis, statistics and data mining.
R-package – a software for statistical computing written in C. Script oriented.
- Pros: widely used, simple, extensive documentation.
- Cons: less options for graphics compared to competitors, no multi-threading, scripting features are limited compared to full-featured programming languages (such as Python, C++ or Java) .
DMelt – a mathematical software written in Java and based on GNU libraries supported by the DMelt team.
- Pros: support for many languages, Java, Python/Jython, Groovy, Ruby, Octave. Multi-threading. Extensive documentation, 2D/3D graphics and hundreds of code examples.
- Cons: Hard to bind with CPython. Many advanced topics of DMelt documentation are proprietary.
Weka – A Java environment for data mining.
- Pros: advanced GUI, good documentation.
- Cons: support for data visualization is less advanced compared to alternative programs. Scripting support is limited.
Orange – visualization and analysis for novice and experts.
- Pros: Advanced GUI and graphics. Good documentation. Support for CPython.
- Cons: Less choice for scripting compared to alternative statistical packages
