Python Data Science Handbook

This book is a customized version in Taiwan, and the content is extracted from Chapters 1 to 15 of the book "Introduction to Python Programming and Data Structures, Global Edition, 3rd edition".-- --For introductory courses in Python Programming.A fundamentals first approach to programming helps students create efficient, elegant code.Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.For a list of

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure.Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.

Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book introduces you to the Wolfram programming langua

Python programmers will improve their computer science skills with these useful one-liners.Python One-Liners will teach you how to read and write one-liners: concise statements of useful functionality

Avoid data blunders and create truly useful visualizations Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders t

The Educational Leader’s Guide to Improvement Science: Data, Design and Cases for Reflection is a collection illustrating applied organizational problem-solving using methods of Improvement Scien

The fast and easy way to learn Python programming and statisticsPython is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of peop

Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax ba

The Cambridge Handbook of International Prevention Science offers a comprehensive global overview on prevention science with the most up-to-date research from around the world. Over 100 scholars from 27 different countries (including Australia, Bhutan, Botswana, India, Israel, Mexico, Singapore, South Korea, Spain and Thailand) contributed to this volume, which covers a wide range of topics important to prevention science. It includes major sections on the foundations of prevention as well as examples of new initiatives in the field, detailing current prevention efforts across the five continents. A unique and innovative volume, The Cambridge Handbook of International Prevention Science is a valuable resource for established scholars, early professionals, students, practitioners and policy-makers.

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully rev

"A great, action-oriented book for novice data analysts. If you have no background in quantitative social science, Fogarty's book gives you a toolbox for starting statistical analysis and develop

A new volume in the Handbook of Sports Medicine and Science series from the International Olympic Committee, this volume Canoeing provides an accessible and comprehensive summary of the topic. Pr

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your ten

Transportation Science explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, c

Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase you

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the pr

Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine

Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional ac

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data

Interpretive political science focuses on the meanings that shape actions and institutions, and the ways in which they do so. This Handbook explores the implications of interpretive theory for the stu

Data science is the most exciting skill you can master. Data has dramatically changed how our world works. From entertainment to politics, from technology to advertising and from science to the busine

A fully updated tutorial on the basics of the Python programming language for science studentsPython is a computer programming language that is rapidly gaining popularity throughout the sciences. This

Introduction to Data Compression, Fifth Edition, builds on the success of what is widely considered the best introduction and reference text on the art and science of data compression. Data compressio

The book provides a carefully researched, compact source of key earth science information and data, logically sorted by subject matter, and then cross-referenced. Appealing to both experts and non-exp

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing results using various modeling options. Common pitfalls, data issues, and interpretation of model results are also addressed. Programs in both R and SAS are made available for all results presented in the text so that readers can emulate and adapt analyses for

The essential pharmacotherapy data needed for clinical practice and board preparation – in one carry-anywhere guidePharmacotherapy Handbook, Tenth Edition delivers the critical information need to mak

Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn an

In recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and bio

This book helps your team embrace a data science mindset. Data tools are getting better and continuing to improve. As the field continues to grow new players are inventing better solutions. Yet you sh

Evidence-Based Climate Science: Data Opposing CO2 Emissions as the Primary Source of Global Warming, Second Edition, includes updated data related to the causes of global climate change from experts i

Information Security Science: Measuring the Vulnerability to Data Compromises provides the scientific background and analytic techniques to understand and measure the risk associated with information

This undergraduate textbook provides an introduction to High Performance Computing (HPC) for Data Science and is divided into two parts. The first covers the fundamentals of HPC and the second part de

The Handbook of Research Design in Mathematics and Science Education is based on results from an NSF-supported project (REC 9450510) aimed at clarifying the nature of principles that govern the effect

The exponential growth of structured and unstructured social data has confronted fields such as political science, sociology, psychology, information systems, public health, public policy, and communi

Perkovic's Introduction to Programming Using Python: An Application Development Focus, 2e is more than just an introduction to programming. It is an inclusive introduction to Computer Science that tak

Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting w

If you are planning to create data analysis and visualization tools in the context of science, engineering, economics, or social science, then this book is for you. With this book, you will become a v