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- Autor: Joel Grus
- Editor: Alta Books
- Data de publicação: 2016-06-27
- ISBN: 857608998X
- Número de páginas: 336 pages
- Tag: science
- Autor: Tom Fawcett
- Editor: Alta Books
- Data de publicação: 2016-03-22
- ISBN: 8576089726
- Número de páginas: 408 pages
- Tag: science, negocios
- Autor: Garrett Wickham
- Editor: O′Reilly
- Data de publicação: 2017-01-20
- ISBN: 1491910399
- Número de páginas: 522 pages
- Tag: science
What exactly is data science? With this book, you’ll gain a clear understanding of this discipline for discovering natural laws in the structure of data. Along the way, you’ll learn how to use the versatile R programming language for data analysis.
Whenever you measure the same thing twice, you get two results—as long as you measure precisely enough. This phenomenon creates uncertainty and opportunity. Author Garrett Grolemund, Master Instructor at RStudio, shows you how data science can help you work with the uncertainty and capture the opportunities. You’ll learn about:
- Data Wrangling—how to manipulate datasets to reveal new information
- Data Visualization—how to create graphs and other visualizations
- Exploratory Data Analysis—how to find evidence of relationships in your measurements
- Modelling—how to derive insights and predictions from your data
- Inference—how to avoid being fooled by data analyses that cannot provide foolproof results
Through the course of the book, you’ll also learn about the statistical worldview, a way of seeing the world that permits understanding in the face of uncertainty, and simplicity in the face of complexity.
- Autor: Kieran Healy
- Editor: Princeton University Press
- Data de publicação: 2019-01-15
- ISBN: 0691181624
- Número de páginas: 296 pages
- Tag: visualization, practical, introduction
An accessible primer on how to create effective graphics from data
This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.
Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.
Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.
- Provides hands-on instruction using R and ggplot2
- Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent
- Includes a library of data sets, code, and functions
- Autor: Cole Nussbaumer Knaflic
- Editor: John Wiley & Sons
- Data de publicação: 2015-11-20
- ISBN: 1119002257
- Número de páginas: 288 pages
- Tag: storytelling, visualization, guide, business, professionals
Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation.
Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:
- Understand the importance of context and audience
- Determine the appropriate type of graph for your situation
- Recognize and eliminate the clutter clouding your information
- Direct your audience's attention to the most important parts of your data
- Think like a designer and utilize concepts of design in data visualization
- Leverage the power of storytelling to help your message resonate with your audience
Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
- Autor: Wes McKinney
- Editor: Novatec
- Data de publicação: 2018-01-09
- ISBN: 8575226479
- Número de páginas: 616 pages
- Tag: python, analise, dados, tratamento, dados, pandas, numpy, ipython
Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R seleção on-line livro
- Autor: Michael Freeman
- Editor: Addison-Wesley Professional
- Data de publicação: 2018-11-29
- ISBN: 0135133106
- Número de páginas: 384 pages
- Tag: programming, skills, science, start, writing, wrangle, analyze, visualize
The Foundational Hands-On Skills You Need to Dive into Data Science
“Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.”
–From the foreword by Jared Lander, series editor
Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience.
Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, you’ll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.
Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything’s focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to
- Install your complete data science environment, including R and RStudio
- Manage projects efficiently, from version tracking to documentation
- Host, manage, and collaborate on data science projects with GitHub
- Master R language fundamentals: syntax, programming concepts, and data structures
- Load, format, explore, and restructure data for successful analysis
- Interact with databases and web APIs
- Master key principles for visualizing data accurately and intuitively
- Produce engaging, interactive visualizations with ggplot and other R packages
- Transform analyses into sharable documents and sites with R Markdown
- Create interactive web data science applications with Shiny
- Collaborate smoothly as part of a data science team
Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
- Autor: Martin Lindstrom
- Editor: HarperCollins Brasil
- Data de publicação: 2016-03-02
- ISBN: 8569809719
- Número de páginas: 240 pages
- Tag: small, poucas, pistas, indicam, grandes, tendencias
- Autor: RJ Andrews
- Editor: John Wiley & Sons
- Data de publicação: 2019-02-06
- ISBN: 1119483891
- Número de páginas: 320 pages
- Tag: trust, inspire, world
How do we create new ways of looking at the world? Join award-winning data storyteller RJ Andrews as he pushes beyond the usual how-to, and takes you on an adventure into the rich art of informing.
Creating Info We Trust is a craft that puts the world into forms that are strong and true. It begins with maps, diagrams, and charts — but must push further than dry defaults to be truly effective. How do we attract attention? How can we offer audiences valuable experiences worth their time? How can we help people access complexity?
Dark and mysterious, but full of potential, data is the raw material from which new understanding can emerge. Become a hero of the information age as you learn how to dip into the chaos of data and emerge with new understanding that can entertain, improve, and inspire. Whether you call the craft data storytelling, data visualization, data journalism, dashboard design, or infographic creation — what matters is that you are courageously confronting the chaos of it all in order to improve how people see the world. Info We Trust is written for everyone who straddles the domains of data and people: data visualization professionals, analysts, and all who are enthusiastic for seeing the world in new ways.
This book draws from the entirety of human experience, quantitative and poetic. It teaches advanced techniques, such as visual metaphor and data transformations, in order to create more human presentations of data. It also shows how we can learn from print advertising, engineering, museum curation, and mythology archetypes. This human-centered approach works with machines to design information for people. Advance your understanding beyond by learning from a broad tradition of putting things “in formation” to create new and wonderful ways of opening our eyes to the world.
Info We Trust takes a thoroughly original point of attack on the art of informing. It builds on decades of best practices and adds the creative enthusiasm of a world-class data storyteller. Info We Trust is lavishly illustrated with hundreds of original compositions designed to illuminate the craft, delight the reader, and inspire a generation of data storytellers.
- Autor: Wes Mckinney
- Editor: O′Reilly
- Data de publicação: 2017-11-03
- ISBN: 1491957662
- Número de páginas: 522 pages
- Tag: python, analysis
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.
- Use the IPython shell and Jupyter notebook for exploratory computing
- Learn basic and advanced features in NumPy (Numerical Python)
- Get started with data analysis tools in the pandas library
- Use flexible tools to load, clean, transform, merge, and reshape data
- Create informative visualizations with matplotlib
- Apply the pandas groupby facility to slice, dice, and summarize datasets
- Analyze and manipulate regular and irregular time series data
- Learn how to solve real-world data analysis problems with thorough, detailed examples