Python Data Science Essentials: Become an efficient data science practitioner by thoroughly understanding the key concepts of Python

Alberto Boschetti

€32.99

4.2 (6 Ratings)

Paperback Apr 2015 258 pages 1st Edition

Alberto Boschetti

€32.99

4.2 (6 Ratings)

Paperback Apr 2015 258 pages 1st Edition

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

View table of contents

Preview Book

Download Code

Key benefits

Quickly get familiar with data science using Python
Save tons of time through this reference book with all the essential tools illustrated and explained
Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience

Description

The book starts by introducing you to setting up your essential data science toolbox. Then it will guide you across all the data munging and preprocessing phases. This will be done in a manner that explains all the core data science activities related to loading data, transforming and fixing it for analysis, as well as exploring and processing it. Finally, it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results. In this walkthrough, structured as a data science project, you will always be accompanied by clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.

Who is this book for?

If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills.

What you will learn

Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux
Get data ready for your data science project
Manipulate, fix, and explore data in order to solve data science problems
Set up an experimental pipeline to test your data science hypothesis
Choose the most effective and scalable learning algorithm for your data science tasks
Optimize your machine learning models to get the best performance
Explore and cluster graphs, taking advantage of interconnections and links in your data

Estimated delivery fee Deliver to Netherlands

Premium delivery 7 - 10 business days

€17.95

(Includes tracking information)

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

€32.99

€41.99

Total € 74.98

FAQs

What is the delivery time and cost of print book?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

What is custom duty/charge?

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order?

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges?

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.

How can I cancel my order?

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact [email protected] with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at [email protected] using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy?

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on [email protected] with the order number and issue details as explained below:

If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on [email protected] within one hour of placing the order and we will replace/refund you the item cost.
Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on [email protected] who will be able to resolve this issue for you.
You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on [email protected] within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged?

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use?

You can pay with the following card types:

Visa Debit
Visa Credit
MasterCard
PayPal

What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

Filter reviews by

All

Amazon verified reviews

Sh Oct 06, 2015

I have some R experience and wanted to learn Python for data science. This book is great for that. Chapters are nicely layer out, starting from preprocessing, feature selection and then machine learning models. It even has a section on Restricted Boltzmann Machines for image analysis.

Amazon Verified review

Jay. L Dec 30, 2016

compared with other data science book in python, this one is thinner but still comprehensive. Not the best if you want to start learning all the tools and methods, but great for reviewing and refreshing what you've learnt from other places

Bibliophage Jun 06, 2015

I am a senior engineer with years of experience working primarily in C, C#, perl, and T-SQL. I have basic python, and dusty memories of two years of college math. In the last year, my data set has ballooned at the rate of 1Tb every two months and will soon exceed the handling capacity of my old analytics stack. Blessed by my manager with a shiny new hadoop cluster and time to study, I'm learning new tricks. This book is one of the first I found, and for me it was perfect. It reads like a walk-through from a smart coworker: enough to get me going, the most important moving parts, a few gotchas, where to go for help, some simple working examples... It got me moving on my first project in just a few hours. This is the book I'd have written for myself.

Oleg Okun Dec 06, 2015

Although I am an experienced Data Scientist who knows well Python's stack for Data Science (scikit-learn, pandas, statsmodels, numpy, scipy, matplotlib, IPython), this book captured my attention and I have read a half of it during the first two days after getting the book. This book is easy to read for novices and experts alike (it does not contain a lot of math and wherever there are formulas they are not difficult to grasp), though some familiarity with Python packages comprising the Data Science stack will greatly facilitate material understanding. The writing style authors chose is excellent as it teaches readers in a very logical and pedagogically appealing way: the way of data pre-processing and analysis occur in projects that data scientists and engineers often encounter when aiming to solve the real-worlds tasks.The books begins with a description of how to install Python and various packages needed to run the code. The purpose of these packages is also explained. Different Python distributions are briefly discussed together with their characteristics, so that a reader can select a distribution particularly suitable to his/her needs. As all code examples in the book are run in IPython Notebook, special attention is paid to a short but comprehensive introduction into IPython itself. Data sets used in the book are described too.After advising on installation of Python and its packages, the book guides readers towards fast and easy data loading from a file, including the case when the entire data set cannot be loaded during one read in the memory and the solution offered is to load it in chunks by using pandas.Furthermore, answers to the following problems are provided: how to deal with erroneous records, how to treat categorical and text data, what are useful data cleansing and transformation operations implemented in pandas, how to use the optimized data structures - numpy arrays - and what operations on them can be done.Once data is loaded and converted to a suitable representation, the book then spends a chapter on the general Data Science pipeline that can be implemented with scikit-learn. The pipeline includes dimensionality reduction via either feature extraction or feature selection, outlier detection, predictive modeling (classification and regression), optimization of model's hyper-parameters, and model's performance evaluation. This material creates the holistic view what typical data analysis is comprised of.The next chapter introduces several popular machine learning algorithms in detail. Among them are linear and logistic regression, Naive Bayes, support vector machines, bagging and boosting ensembles. Special attention is paid to scikit-learn solutions of the 3Vs of big data: namely, volume, velocity and variety. Scalability with volume is solved with incremental learning when at any given moment of time, only a portion (batch) of the entire data fit to the available memory is used to update a model, hence, a model learns incrementally as new batches arrive. To keep up with velocity, scikit-learn offers a number of classification and regression algorithms optimized for speed. Data variety is deal with the help of hashing and sparse matrices. The chapter ends with short examples of doing basic operations of Natural Language Processing with the NLTK package and data clustering.Final two chapters are devoted to social network analysis with the NetworkX package and data visualization with the matplotlib and pandas packages, respectively.Although I have both paper and electronic versions of this book, I would advise first to buy the paper version as numerous code is much easier to understand in this format because one can see the entire snapshot at once.

Mary Anne Thygesen Dec 18, 2015

The book covers fundamentals of Data Science. Code for the book is available from the publisher. I used Anaconda Launcher which nicely converted the notebooks to jupyter and ran them well. My favorite chapter was chapter five Social Network Analysis. I like the table on graph examples, type, node and edges. It is useful for writing code.

Python Data Science Essentials: Become an efficient data science practitioner by thoroughly understanding the key concepts of Python

What do you get with Print?