Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Python Data Mining Quick Start Guide
Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide: A beginner's guide to extracting valuable insights from your data

eBook
€13.98 €19.99
Paperback
€24.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
Table of content icon View table of contents Preview book icon Preview Book

Python Data Mining Quick Start Guide

Basic Terminology and Our End-to-End Example

The philosophy behind a quick-start guide is that the topic at hand is best learned by doing. In this chapter, I will present a quick overview of important vocabulary, concepts, and terminology that you need to get started, and then jump directly into a full end-to-end working example of data mining in Python. Later chapters will flesh out the steps in the working example in more detail.

The following topics will be covered in this chapter:

  • Basic data terminology
  • Basic statistics
  • An end-to-end example of data mining in Python

Basic data terminology

This section is meant to be a quick overview of the terms that you should know before you get started. This list is very streamlined and is not exhaustive. Please refer to the suggested reading in Chapter 1, Data Mining and Getting Started with Python Tools, for wider coverage of domain-specific terminology.

Sample spaces

The sample space is the space that is covered by all the possible outcomes of a measurement. For example, if a feature column in a dataset is populated with the number of days last month that a responder watched television, then the sample space will include all the integers in the {0,1,2...31} set. If a manufacturing tool measures the temperature difference before and after processing...

Basic summary statistics

Practitioners in the field of descriptive analytics use a set of four summary statistics to quickly understand a dataset. With practice, you should be able to strengthen your intuition about each one of these statistical measurements. In fact, it's a great place to start with most problem statements that you will face. The four summary statistics are described as follows:

  • Locations: The location or center of the data; this can be measured by the mean (average), median, or mode. The median is the point of delineation in 50% of the data, and the mode is the most occurring points, or largest part of the distribution.
  • Spread: How the data is spread around the center; this can be measured with standard deviation, which sums the average distance from the mean of each data point, or variance, which is the square of the deviation.
  • Shape: A description...

An end-to-end example of data mining in Python

Let's start with a full end-to-end example demonstrating the topics and strategies covered in the rest of the book. Subsequent chapters will go into further detail on each part of the analytical process. I suggest that you read through this example fully before moving on in the book.

Loading data into memory – viewing and managing with ease using pandas

First, we will need to load data into memory so that Python can interact with it. Pandas will be our data management and manipulation library:

# load data into Pandas
import pandas as pd
df = pd.read_csv("./data/iris.csv")

Let's use some built-in pandas features to do sanity checks on our data load and...

Summary

This chapter covered the basic statistics and data terminology that are required for working in data mining. The final portion of the chapter was dedicated to a full working example, which combined the types of techniques that will be introduced later on in this book. After reading this chapter, you should have a better understanding of the thought processes behind analysis and the common steps taken to address a problem statement that you may encounter in the field. The subsequent chapters will explore each aspect of the example in more depth, with the next chapter focusing on collecting data, loading it into memory, and exploring it with ease.

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Grasp the basics of data loading, cleaning, analysis, and visualization
  • Use the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data mining
  • Your one-stop guide to build efficient data mining pipelines without going into too much theory

Description

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.

Who is this book for?

Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.

What you will learn

  • Explore the methods for summarizing datasets and visualizing/plotting data
  • Collect and format data for analytical work
  • Assign data points into groups and visualize clustering patterns
  • Learn how to predict continuous and categorical outputs for data
  • Clean, filter noise from, and reduce the dimensions of data
  • Serialize a data processing model using scikit-learn's pipeline feature
  • Deploy the data processing model using Python's pickle module

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 25, 2019
Length: 188 pages
Edition : 1st
Language : English
ISBN-13 : 9781789806403
Category :
Languages :
Concepts :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning

Product Details

Publication date : Apr 25, 2019
Length: 188 pages
Edition : 1st
Language : English
ISBN-13 : 9781789806403
Category :
Languages :
Concepts :

Packt Subscriptions

See our plans and pricing
Modal Close icon
€18.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
€189.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts
€264.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total 79.97
Python Machine Learning Cookbook
€29.99
Python Data Mining Quick Start Guide
€24.99
Big Data Analysis with Python
€24.99
Total 79.97 Stars icon

Table of Contents

8 Chapters
Data Mining and Getting Started with Python Tools Chevron down icon Chevron up icon
Basic Terminology and Our End-to-End Example Chevron down icon Chevron up icon
Collecting, Exploring, and Visualizing Data Chevron down icon Chevron up icon
Cleaning and Readying Data for Analysis Chevron down icon Chevron up icon
Grouping and Clustering Data Chevron down icon Chevron up icon
Prediction with Regression and Classification Chevron down icon Chevron up icon
Advanced Topics - Building a Data Processing Pipeline and Deploying It Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Most Recent
Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(10 Ratings)
5 star 100%
4 star 0%
3 star 0%
2 star 0%
1 star 0%
Filter icon Filter
Most Recent

Filter reviews by




Amazon Customer Jun 23, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great explanation and presentation covered with examples on all topics related to data mining and machine learning principles. Recommend to anyone starting in this field as well as seasoned professionals.
Amazon Verified review Amazon
Keegan Schlake Jun 13, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is a wonderful introduction to data mining and was incredibly helpful. The data sets and applications come at no extra charge and the book is both intuitive and well paced. I could not give this book a higher recommendation if you're interested in the field.
Amazon Verified review Amazon
nan jiang Apr 20, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It's an excellent book if you want to learn the basics of data mining for machine learning. I have recommended to the students in my university who are considering a career in data analytics.
Amazon Verified review Amazon
Erik Thorelli Jul 21, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book for learning the basics of data mining for machine learning... or reminding someone of them.
Amazon Verified review Amazon
Colleen Green Jul 19, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Novice going into this, couldn’t imagine a more user-friendly introduction to data mining!! The author incorporates visuals and clarity of writing I found helpful. I know friends who are learning Python and I always recommend this in case data mining is something they see in their future.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.