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Data Preparation and Exploration : Applied to Healthcare Data
Data scientists spend more than two-thirds of their time cleaning, preparing, exploring, and visualizing data before it is ready for modeling and mining.This textbook covers the important steps of data preparation and exploration that anyone who deals with data should know. This textbook is an excellent companion text for our other textbook Introduction to Biomedical Data Science. The data preparation and exploration methods we include are spreadsheet and statistics package approaches, as well as the programming languages R and Python.The reader is introduced to the free stat packages Jamovi and BlueSky Statistics.Multiple techniques for data visualization are presented.Medical datasets are used for demonstrations and student exercises.Importantly, chapter content is supplemented with YouTube videos.Chapters are well referenced (100+) and there is a chapter on health data resources so the reader can find data to prepare and explore on their own. Prominent issues such as how to handle missing data and imbalanced datasets are covered along with sections on descriptive statistics, visualization, correlations, handling duplicates and outliers, scaling, standardization, and much more.A downloadable Data Checklist is available on https://www.informaticseducation.org
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The Wolf : Culture, Nature, Heritage
New insights into the changing human attitudes towards wild nature through the depiction of wolves in human culture and heritage. Few animals arouse such strong opinion as the wolf.It occupies a contested, ambiguous, yet central role in human culture and heritage.It appears as both an inspirational emblem of the wild and an embodiment of evil.Offering a mirror to different human attitudes, beliefs, and values, the wolf is, arguably, the species that plays the greatest role in shaping our views on what nature is or should be. North America and, more recently, Europe have witnessed a remarkable return of the grey wolf (Canis lupus, and its close relative the Eurasian wolf, Canis lupus lupus) to eco-systems.The essays collected here explore aspects of this recovery, and consider the history, literature and myth surrounding this iconic species.There are chapters on wolf taxonomy, including the coywolf, the red wolf, and the many faces of the dingo.We also meet the Tasmanian wolf and encounter Nazi Werewolves from Outer Space.The book explores the challenges of separating fact from fiction and superstition, and our willingness to co-exist with large carnivores in the twenty-first century.Biologists, historians, anthropologists, cultural theorists, conservationists and museologists will all find riches in the detail presented in this wolf collection.
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Data Culture : Develop An Effective Data-Driven Organization
Organizations often start their data journey by either procuring the technology or hiring the people.However, without an effective data-driven culture in place, they can struggle to derive value from their investments. Data Culture explores how data leaders can develop and nurture a data-driven culture tailored to their organization's needs.It outlines the types of data leadership and teams needed and the key building blocks for success, such as team recruitment, building and training, leadership, process, behavioural change management, developing, sustaining and measuring a data culture, company values and everyday decision making.It also explores the nuances of how different types of data cultures work with different types of companies, what to avoid and the differences between building a data culture from scratch and changing an existing data culture from within. With this hands-on guide, senior data leader Shorful Islam takes readers through how to successfully establish or change a data culture, sharing his expertise in behavioural change psychology and two decades of experience in fostering data culture in organizations.Supported throughout by real-world examples and cases, this will be an essential read for all data leaders and anyone involved in developing a data-driven organizational culture.
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Data Sketches : A journey of imagination, exploration, and beautiful data visualizations
In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply creative process behind 24 unique data visualization projects, and they combine this with powerful technical insights which reveal the mindset behind coding creatively.Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right.This beautiful book provides an intimate, behind-the-scenes account of all 24 projects and shares the authors’ personal notes and drafts every step of the way. The book features:Detailed information on data gathering, sketching, and coding data visualizations for the web, with screenshots of works-in-progress and reproductions from the authors’ notebooksNever-before-published technical write-ups, with beginner-friendly explanations of core data visualization conceptsPractical lessons based on the data and design challenges overcome during each projectFull-color pages, showcasing all 24 final data visualizationsThis book is perfect for anyone interested or working in data visualization and information design, and especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling.
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Learning Data Science : Data Wrangling, Exploration, Visualization, and Modeling with Python
As an aspiring data scientist, you appreciate why organizations rely on data for important decisions—whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights.We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle.It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide.If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with dataPursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualizationLearn how to use modeling to describe the dataGeneralize findings beyond the data
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Daphne Draws Data : A Storytelling with Data Adventure
With every stroke of her crayon, Daphne transforms numbers into stories, helping new friends solve their problems with the power of data! Daphne is not your ordinary dragon. She doesn't breathe fire—she breathes life into numbers, turning them into pictures that unravel mysteries, forge friendships, and save the day!From the imaginative mind of bestselling author Cole Nussbaumer Knaflic and the vibrant illustrations of John Skewes comes a story that will captivate kids and parents alike.Follow Daphne’s journey to distant lands, where numbers are heroes in disguise and her adventures teach the basics of graphs in a way that’s fun, interactive, and empowering. Young readers will be delighted by the endearing character of Daphne.They’ll be equally enchanted by her colorful companions, amazed by her clever lessons, and inspired to build their own analytical skills (STEM).Daphne’s story isn’t solely about data; it’s also about appreciating that everyone has their own special talents.It's about teamwork, creativity, and the beauty of seeing the world through a different lens. Dive into Daphne Draws Data and let your child draw their own conclusions, both on the page and in the world.This smart tale is perfect for bedtime stories, classroom reads, and fostering the next generation of curious minds and innovative thinkers.
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The Enterprise Data Catalog : Improve Data Discovery, Ensure Data Governance, and Enable Innovation
Combing the web is simple, but how do you search for data at work?It's difficult and time-consuming, and can sometimes seem impossible.This book introduces a practical solution: the data catalog.Data analysts, data scientists, and data engineers will learn how to create true data discovery in their organizations, making the catalog a key enabler for data-driven innovation and data governance. Author Ole Olesen-Bagneux explains the benefits of implementing a data catalog.You'll learn how to organize data for your catalog, search for what you need, and manage data within the catalog.Written from a data management perspective and from a library and information science perspective, this book helps you:Learn what a data catalog is and how it can help your organizationOrganize data and its sources into domains and describe them with metadataSearch data using very simple-to-complex search techniques and learn to browse in domains, data lineage, and graphsManage the data in your company via a data catalogImplement a data catalog in a way that exactly matches the strategic priorities of your organizationUnderstand what the future has in store for data catalogs
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Understanding Data, Culture and Society
- How is data shaping our identities?- What was the 'data revolution', and how did it happen?- How will AI change our societies?We live in the age of datafication: every aspect of our lives has been captured and transformed into data, from our sleeping patterns and step counts to our buying habits and political views. In this exciting new textbook, you will discover the intricate ways in which data and society are interwoven. Explaining key concepts such as 'big data' and putting theory into practice throughout, this book will make you a better expert in data and society, offering an interdisciplinary overview of a rapidly evolving field. This textbook tackles the implications of big data for democracy, identity and the global economy, showing how we cannot view our lives as separate from the technologies we have come to rely on. With learning objectives, case studies, further reading and extra resources provided in each chapter, this book is the ideal companion for students in the digital humanities and social sciences looking to deepen their understanding of data, culture and society.
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