NumPy is the fundamental package for scientific computing with Python
Mo Data stashed this in Big Data Technologies
Just because you have a “hammer”, doesn’t mean that every problem you come across will be a “nail”.
The intelligent key thing is when you use the same hammer to solve what ever problem you came across. Like the same way when we indented to solve a datamining problem we will face so many issues but we can solve them by using python in a intelligent way.
In very next post i am going to wet your hands to solve one interesting datamining problem using python programming language. so in this post i am going to explain you about some powerful python weapons( packages )
Before stepping directly to python packages let me clear you a doubt which is rotating in your mind right now. Why python?
Why Python ?We all know that python is powerful programming language ,But what does that mean, exactly? What makes python a powerful programming language?
Python is EasyUniversally Python has gained a reputation because of it’s easy learning. The syntax of python programming language is designed to be easily readable. python has significant popularity in scientific computing. The people working in this field are scientists first, and programmers second.
Python is EfficientNow a days we working on bulk amount of data popularly know as BIG DATA. The more data you have to process, the more important it becomes to manage the memory you use. Here python will work very efficiently.
Python is FastWe all know Python is an interpreted language, we may think that it may be slow but some amazing work has been done over the past years to improve Python’s performance. My point is that if you want to do high-performance computing, Python is a viable best option today.
Hope I cleared your doubt about “Why Python?”, so let me jump to Python Packages for data mining.
NumPy is the fundamental package for scientific computing with Python. It contains among other things.NumPy is an extension to the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays. The ancestor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications.