{"id":131,"date":"2014-11-01T04:12:15","date_gmt":"2014-11-01T04:12:15","guid":{"rendered":"http:\/\/dataaspirant.wordpress.com\/?p=131"},"modified":"2023-10-17T08:40:01","modified_gmt":"2023-10-17T03:10:01","slug":"python-packages-for-datamining","status":"publish","type":"post","link":"https:\/\/dataaspirant.com\/python-packages-for-datamining\/","title":{"rendered":"Python Packages For Datamining"},"content":{"rendered":"
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Home<\/a>\u00a0| About<\/a>\u00a0| Data scientists Interviews<\/a>\u00a0| For beginners<\/a>\u00a0| Join us<\/a><\/h5>\n

Python Packages For Datamining<\/h1>\n

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Just because you have a \u201chammer\u201d, doesn\u2019t mean that every problem you come across will be a \u201cnail\u201d.<\/em><\/span><\/p>\n

The intelligent key thing is when you use \u00a0the same hammer to solve what ever problem you came across. Like the same way when we intended to solve a datamining problem \u00a0we will face so many issues but we can solve them by using python in a intelligent way.<\/p>\n

In very next post I am going to wet your hands to solve one interesting\u00a0 datamining problem using python programming language. So in this post I am going to explain you about some powerful python weapons( packages )<\/p>\n

Before stepping directly into python packages let me clear you a\u00a0doubt which is rotating in your mind right now. Why python ?<\/p>\n

Why Python ?<\/strong><\/h2>\n

We all know that python is powerful programming language ,But what does that mean, exactly? What makes python \u00a0a powerful\u00a0programming language?<\/p>\n

Python is Easy<\/h3>\n

Universally\u00a0Python has gained reputation because of its easy learning. The syntax of python programming language is designed to be easily readable. Python has significant popularity in \u00a0scientific computing. The people working in this field are scientists first, and programmers second.<\/p>\n

Python is Efficient<\/h3>\n

Now a days we are working on\u00a0bulk amount of data popularly know as BIG DATA.<\/strong>\u00a0\u00a0The more data you have to process, the more important it becomes to manage the memory you use. Here python will work very efficiently.<\/p>\n

Python is Fast<\/h3>\n

We all know\u00a0Python is an interpreted<\/em> language, we may think that it may be\u00a0slow 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 option today.<\/p>\n

Hope I cleared your doubt “why python?” so let me jump to Python Packages for datamining.<\/p>\n

NumPy<\/h2>\n

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About:<\/strong><\/p>\n

\u00a0 \u00a0 \u00a0NumPy 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.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
Original author(s)<\/span><\/th>\nTravis Oliphant<\/span><\/td>\n<\/tr>\n
Developer(s)<\/span><\/th>\nCommunity project<\/span><\/td>\n<\/tr>\n
Initial release<\/span><\/th>\nAs Numeric, 1995; as NumPy, 2006<\/span><\/td>\n<\/tr>\n
Stable release<\/span><\/th>\n1.9.0 \/ 7\u00a0September 2014; 36 days ago<\/span><\/span><\/td>\n<\/tr>\n
Written in<\/span><\/th>\nPython, C<\/span><\/td>\n<\/tr>\n
Operating system<\/span><\/th>\nCross-platform<\/span><\/td>\n<\/tr>\n
Type<\/span><\/th>\nTechnical computing<\/span><\/td>\n<\/tr>\n
License<\/span><\/th>\nBSD-new license<\/span><\/td>\n<\/tr>\n
Website<\/span><\/th>\nwww.numpy.org<\/a><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Installing numpy:<\/strong><\/p>\n

I strongly\u00a0believe that python is already installed in your computer, if python is not installed in your computer please install it first.<\/p>\n

Installing numpy in linux<\/strong><\/p>\n

Open your terminal and copy this commands<\/p>\n

sudo apt-get update\nsudo apt<\/span>-<\/span>get install python<\/span>-<\/span>numpy<\/span><\/code><\/pre>\n
Sample numpy code<\/strong><\/p>\n
Sample numpy code for using reshape function<\/p>\n
[sourcecode language=”python” wraplines=”false”]<\/p>\n
from numpy import *
\na = arange(12)
\na = a.reshape(3,2,2)
\nprint a<\/p>\n
[\/sourcecode]<\/p>\n
Script output<\/strong><\/p>\n
[[[ 0 1]\n [ 2 3]]\n\n [[ 4 5]\n [ 6 7]]\n\n [[ 8 9]\n [10 11]]]<\/pre>\n
SciPy<\/h3>\n
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About:<\/strong><\/p>\n
\u00a0 \u00a0 SciPy (pronounced “Sigh Pie”) is open-source software for mathematics, science, and engineering. The SciPy library\u00a0depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to\u00a0work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for\u00a0numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are\u00a0free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world’s\u00a0leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, Scipy is one of the most need one.<\/p>\n\n\n\n\n\n\n\n\n\n\n
Original author(s)<\/a><\/span><\/th>\nTravis Oliphant, Pearu Peterson, Eric Jones<\/span><\/td>\n<\/tr>\n
Developer(s)<\/a><\/span><\/th>\nCommunity library project<\/span><\/td>\n<\/tr>\n
Stable release<\/a><\/span><\/th>\n0.14.0 \/ 3\u00a0May 2014; 5 months ago<\/span><\/span><\/td>\n<\/tr>\n
Written in<\/span><\/th>\nPython<\/a>, Fortran<\/a>, C<\/a>, C++<\/a>[1]<\/a><\/sup><\/span><\/td>\n<\/tr>\n
Operating system<\/a><\/span><\/th>\nCross-platform<\/a> (list)<\/a><\/span><\/td>\n<\/tr>\n
Type<\/a><\/span><\/th>\nTechnical computing<\/a><\/span><\/td>\n<\/tr>\n
License<\/a><\/span><\/th>\nBSD-new license<\/a><\/span><\/td>\n<\/tr>\n
Website<\/span><\/th>\nwww.scipy.org<\/a><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Installing SciPy\u00a0in linux<\/strong><\/p>\n
Open your terminal and copy this commands<\/p>\n
sudo apt-get update\nsudo apt<\/span>-<\/span>get install python-scipy<\/span><\/code><\/pre>\n
Sample SciPy code<\/strong><\/p>\n
[sourcecode language=”python” wraplines=”false”]<\/p>\n
from scipy import special, optimize
\nf = lambda x: -special.jv(3, x)
\nsol = optimize.minimize(f, 1.0)
\nx = linspace(0, 10, 5000)
\nplot(x, special.jv(3, x), ‘-‘, sol.x, -sol.fun, ‘o’)
\nsavefig(‘plot.png’, dpi=96)
\n[\/sourcecode]<\/p>\n
\u00a0Script output<\/strong><\/p>\n
Pandas<\/h3>\n
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About:<\/strong><\/p>\n
Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with \u201crelational\u201d or \u201clabeled\u201d data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has broader goal of becoming the most powerful and flexible open source data analysis \/ manipulation tool available in any language. It is already well on its way toward this goal.<\/p>\n
Pandas is well suited for many different kinds of data:<\/strong><\/p>\n
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