Book Image

Python Data Mining Quick Start Guide

By : Nathan Greeneltch
Book Image

Python Data Mining Quick Start Guide

By: Nathan Greeneltch

Overview of this book

Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle.
Table of Contents (9 chapters)

Installing the Anaconda distribution and Conda package manager

These tools from Anaconda are available on both Windows and Linux systems. See the following install instructions.

Installing on Linux

To install the distribution, follow these steps given as follows:

  1. First, download the latest installer build from https://www.anaconda.com/download/#linux.
  2. Then, in the Linux Terminal, pass this bash command:
$ bash Anaconda-latest-Linux-x86_64.sh
  1. Follow the prompts in the terminal and it will begin installing. Once done, you will be asked if you want to allow Conda to be auto-initialized with a .bashrc entry. I recommend choosing N and activating it manually when needed, just in case you decide to have multiple versions of Conda on your system. In this case, you can launch the Conda prompt by using the following command:
$ source /{anaconda3_dir}/bin/activate

This is will source the Conda activate shell script and call it to activate the base environment, which is the default Anaconda Python bundle. Adding new environments will be discussed in the following section on how to install specific libraries. At this point, passing the Python command will open an interactive shell where you can execute Python code line-by-line, as shown in the following code snippet:

(base) $ Python
Python 3.7.0 (default, Jun 28 2018, 13:15:42)
[GCC 7.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
>>> numpy.random.random(10)
array([0.48489815, 0.80944492, 0.89740441, 0.93031125, 0.71774534,
0.63817451, 0.93231809, 0.75820457, 0.17550135, 0.62126858])

Alternatively, you can execute the code in a stored Python script by using the following command:

(base) $ Python script.py

Installing on Windows

To install on Windows, follow the steps given as follows:

  1. First, download the executable from https://conda.io/docs/user-guide/install/windows.html
  2. Then, launch the Anaconda prompt that can be found in a program search from the Windows Start menu

Anaconda prompt is a Windows command prompt with all the environment variables set to point to Anaconda. That's it; you are ready to use your base Python environment.

Installing on macOS

To install on macOS, follow the steps given as follows:

  1. First, download the graphical installer from the Anaconda distribution site https://www.anaconda.com/distribution/
  2. Launch the package and follow the on-screen prompts, which should set up everything you need automatically