This page contains links to books, videos, tutorials, and more covering different aspects of data visualization. When you see a white ' i " in a black circle, click on it to reveal a description of the resource.
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Storytelling with Data by
Don't simply show your data--tell a story with it! 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!
Stephanie Evergreen's Effective Data Visualization is an excellent starting place and all examples given are created in Excel, making it accessible to learners without coding knowledge.
Effective Data Visualization by
NOW IN FULL COLOR! Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate their data findings. This comprehensive how-to guide functions as a set of blueprints--supported by both research and the author's extensive experience with clients in industries all over the world--for conveying data in an impactful way. Delivered in Evergreen's humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for building the chosen graph in Excel. Now in full color with new examples throughout, the Second Edition includes a revamped chapter on qualitative data, nine new quantitative graph types, new shortcuts in Excel, and an entirely new chapter on Sharing Your Data With the World, which provides advice on using dashboards. New from Stephanie Evergreen! The Data Visualization Sketchbook provides advice on getting started with sketching and offers tips, guidance, and completed sample sketches for a number of reporting formats. Bundle Effective Data Visualization, 2e, and The Data Visualization Sketchbook, using ISBN 978-1-5443-7178-8!
Effective Data Visualization by
NOW IN FULL COLOR! Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate their data findings. This comprehensive how-to guide functions as a set of blueprints--supported by both research and the author's extensive experience with clients in industries all over the world--for conveying data in an impactful way. Delivered in Evergreen's humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for building the chosen graph in Excel. Now in full color with new examples throughout, the Second Edition includes a revamped chapter on qualitative data, nine new quantitative graph types, new shortcuts in Excel, and an entirely new chapter on Sharing Your Data With the World, which provides advice on using dashboards. New from Stephanie Evergreen! The Data Visualization Sketchbook provides advice on getting started with sketching and offers tips, guidance, and completed sample sketches for a number of reporting formats. Bundle Effective Data Visualization, 2e, and The Data Visualization Sketchbook, using ISBN 978-1-5443-7178-8!
Visual Data Storytelling with Tableau by
This is the first end-to-end, full-color guide to telling powerful, actionable data stories using Tableau, the world's #1 visualization software. Renowned expert Lindy Ryan shows you how to communicate the full business implications of your data analyses by combining Tableau's remarkable capabilities with a deep understanding of storytelling and design. Each chapter illuminates key aspects of design practice and data visualization, and guides you step-by-step through applying them in Tableau. Ryan demonstrates how "data stories" resemble and differ from traditional storytelling, and helps you use Tableau to analyze, visualize, and communicate insights that are meaningful to any stakeholder, in any medium. Information Visualization in Tableau presents exercises that give you hands-on practice with the most up-to-date capabilities available through Tableau 10 and the full Tableau software ecosystem. Ryan's classroom-tested exercises won't just help you master the software: they'll show you to craft data stories that inspire action. Coverage includes: The visual data storytelling paradigm: moving beyond static charts to powerful visualizations that combine narrative with interactive graphics How to think like a data scientist, a storyteller, and a designer -- all in the same project Data storytelling case studies: the good, the bad, and the ugly Shaping data stories: blending data science, genre, and visual design Seven best practices for visual data storytelling -- and common pitfalls to avoid Tricks and hacks you can use with any toolset, not just Tableau
Visual Analytics with Tableau by
A four-color journey through a complete Tableau visualization Tableau is a popular data visualization tool that's easy for individual desktop use as well as enterprise. Used by financial analysts, marketers, statisticians, business and sales leadership, and many other job roles to present data visually for easy understanding, it's no surprise that Tableau is an essential tool in our data-driven economy. Visual Analytics with Tableau is a complete journey in Tableau visualization for a non-technical business user. You can start from zero, connect your first data, and get right into creating and publishing awesome visualizations and insightful dashboards. * Learn the different types of charts you can create * Use aggregation, calculated fields, and parameters * Create insightful maps * Share interactive dashboards Geared toward beginners looking to get their feet wet with Tableau, this book makes it easy and approachable to get started right away.
Matplotlib for Python Developers by
Leverage the power of Matplotlib to visualize and understand your data more effectively Key Features Perform effective data visualization with Matplotlib and get actionable insights from your data Design attractive graphs, charts, and 2D plots, and deploy them to the web Get the most out of Matplotlib in this practical guide with updated code and examples Book Description Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you'll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You'll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you'll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you'll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations. What you will learn Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn Create interactive plots with real-time updates Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django Write data visualization code that is readily expandable on the cloud platform Who this book is for This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you're a data scientist or analyst and wish to create attractive visualizations using Python, you'll find this book useful. Some knowledge of Python programming is all you need to get started.
Python Data Science Handbook by
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them allâ??IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, youâ??ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Ggplot2 by
Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures
Data Visualization: A Practical Introduction by
*Also available as a free web book at socviz.co/ *
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
Microsoft Power BI Quick Start Guide by
Bring your data to life with Power BI Key Features Get to grips with the fundamentals of Microsoft Power BI and its Business Intelligence capabilities Build accurate analytical models, reports and dashboards Get faster and more intuitive insights from your data using Microsoft Power BI Book Description Microsoft Power BI is a cloud-based service that helps you easily visualize and share insights using your organization's data.This book will get you started with business intelligence using the Power BI toolset, covering essential concepts such as installation,designing effective data models, as well as building basic dashboards and visualizations to make your data come to life You will learn how to get your data the way you want - connecting to data sources sources and how to clean your data with the Power BI Query Editor. You will next learn how to properly design your data model to make your data easier to work with.. You will next learn how to properly design your data model to navigate table relationships and build DAX formulas to make your data easier to work with. Visualizing your data is another key element of this book, and you will learn how to follow proper data visualization styles and enhanced digital storytelling techniques. By the end of this book, you will understand how to administer your organization's Power BI environment so deployment can be made seamless, data refreshes can run properly, and security can be fully implemented What you will learn Connect to data sources using both import and DirectQuery options Use the Query Editor to apply data transformations and data cleansing processes, including learning how to write M and R scripts Design optimized data models by designing relationships and DAX calculations Leverage built-in and custom visuals to design effective reports Use the Power BI Desktop and Power BI Service to implement Row Level Security on your model Administer a Power BI cloud tenant for your organization Deploy your Power BI Desktop files into the Power BI Report Server Who this book is for This book is for aspiring Business Intelligence professionals who want to get up and running with Microsoft Power BI. If you have a basic understanding of BI concepts and want to learn how to apply them using Microsoft Power BI, this book is for you.