Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
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

Arrow left icon
Profile Icon Greeneltch
Arrow right icon
Free Trial
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (10 Ratings)
Paperback Apr 2019 188 pages 1st Edition
eBook
NZ$14.99 NZ$38.99
Paperback
NZ$48.99
Subscription
Free Trial
Arrow left icon
Profile Icon Greeneltch
Arrow right icon
Free Trial
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (10 Ratings)
Paperback Apr 2019 188 pages 1st Edition
eBook
NZ$14.99 NZ$38.99
Paperback
NZ$48.99
Subscription
Free Trial
eBook
NZ$14.99 NZ$38.99
Paperback
NZ$48.99
Subscription
Free Trial

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
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 : 9781789800265
Category :
Languages :
Concepts :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Apr 25, 2019
Length: 188 pages
Edition : 1st
Language : English
ISBN-13 : 9781789800265
Category :
Languages :
Concepts :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 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
$199.99 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 NZ$7 each
Feature tick icon Exclusive print discounts
$279.99 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 NZ$7 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total NZ$ 154.97
Python Machine Learning Cookbook
NZ$56.99
Python Data Mining Quick Start Guide
NZ$48.99
Big Data Analysis with Python
NZ$48.99
Total NZ$ 154.97 Stars icon
Banner background image

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

Top Reviews
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
Top Reviews

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
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
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
TJMOTOX5 Jun 10, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very good intro book to get you started. The author is positive and upbeat and tries to keep the material interesting. The coding exercises are easy to follow and the concepts are clearly explained. The chapter on clustering is the best description I’ve ever seen on the topic. It’s a bit short, but the price is right!
Amazon Verified review Amazon
Carlos Vicens Jun 07, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great intro to the field. I started with no background and got some code going in no time. The second half of the book is conceptual. I think it will be very helpful in my new career to have seen that first principles treatment of clustering and prediction algos. I recommend to anyone trying to get started in the field of data mining or machine learning.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.