Combination of NumPy, SciPy and Matplotlib/Pylab -a good alternative methodology to MATLAB - A Comparative analysis

Python is a simple, dominant and well-organized interpreted language. Python is used to develop the very high performance scientific related application and it is used to develop an application for Numeric computation, it is frequently used. Using python we can develop a high performance applications Python often utilizes external libraries to perform scientific computing. The most important libraries used are NumPy, SciPy and Matplotlib to perform scientific and numeric applications. The Python libraries are open-source tag-on modules, which do additional frequent mathematical and numerical routines in pre-compiled, high-speed tasks. These two modules are providing the functionality that meets, or perhaps exceeds, that related with common commercial software like MATLAB. The python package NumPy (Numeric Python) is used for manipulating large arrays and matrices of numeric data. The Scientific Python (SciPy) extends the functionality of NumPy with a considerable collection of valuable algorithms, like minimization, Fourier transformation, regression, and other applied mathematical techniques.Matrix Laboratory (MATLAB) is a multiple programming paradigm. it is used for numerical computing environment and it is a proprietary programming language. The following various operations are performed by the MATLAB, operations are plotting of functions and data, matrix manipulations, python use an interface for user to interact with an application, some type of algorithms are used for implementation purpose and another type of programming languages are used to create interfacing with programs. The combination of the following three packages NumPy, SciPy and Matplotlib/Pylab are alternatively used as a MATLAB, so this three packages give the alternative to MATLAB, MATLAB environment is best suit for scientific works. Python provide a alternative to MATLAB.