Nan surveys her class to find out what types of pets they have. See how she creates a bar graph to share her results.

Dan, Emma, and Ron want to compare how many apples they picked. Look at the picture graph to tell who picked the most.

Learn everything about graphs, charts, and how to organize information in this fun picture book introduction. Follow two comical creatures as they go graph-crazy! Gonk the frog and his friend Chester have all kinds of questions-- do more of their friends like mud, or not? Who has the biggest feet? What color butterfly is most common? In order to answer these questions, the two friends make all kinds of charts-- and so can you! This funny look at graphs and charts introduces several major ways of organizing information-- bar graphs, pie charts, Venn diagrams, and more. With concrete, easy-to-understand examples and bright, cartoonish illustrations, The Great Graph Contest is a kid-friendly introduction to the basics of data visualization that will have you itching to make your own graphs! An author's note expands on the different kinds of charts pictured in the story, and instructions on making your own graphs and charts are included.

This book constitutes the proceedings of the 16th International Symposium on Graph Drawing, GD 2008, held in Heraklion, Crete, Greece, during September 21-24, 2008. The 31 long papers and 8 short papers presented together with 10 posters and two invited papers were carefully reviewed and selected from 83 submissions. The volume also includes a report on the Graph Drawing Contest which was held during the conference. An important aspect of the conference is bridging the gap between theoretical advances and implemented solutions of geometric representation of graphs and networks. It is motivated by those applications where it is crucial to visualize structural information as graphs.

Mr. Hall surveys his class to find out how many people walk, take the bus, or take a car to get to school. Watch as he makes a circle graph with his data.

Each page includes an attention-grabbing graph, chart, or table with questions to help kids read and interpret the data. Includes bar and line graphs, circle graphs, schedules, pictographs, and lots more. A perfect way to build on kids' interests and prepare them for standardized tests.

This book constitutes the thoroughly refereed post-proceedings of the 12th International Symposium on Graph Drawing, GD 2004, held in New York, NY, USA in September/October 2004. The 39 revised full papers and 12 revised short papers presented together with 4 posters and a report on the graph drawing context were carefully selected during two rounds of reviewing and improvement. All current aspects in graph drawing are addressed ranging from foundational and methodological issues to applications for various classes of graphs in a variety of fields.

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!

The American Mathematics Competition (AMC) series is a group of contests that judge students’ mathematical abilities in the form of a timed test. The AMC 8 is the introductory level competition in this series and is taken by tens of thousands of students every year in grades 8 and below. Students are given 40 minutes to complete the 25 question test. Every right answer receives 1 point and there is no penalty for wrong or missing answers, so the maximum possible score is 25/25. While all AMC 8 problems can be solved without any knowledge of trigonometry, calculus, or more advanced high school mathematics, they can be tantalizingly difficult to attempt without much prior experience and can take many years to master because problems often have complex wording and test the knowledge of mathematical concepts that are not covered in the school curriculum. This book is meant to teach the skills necessary to solve mostly any problem on the AMC 8. However, our goal is to not only teach you how to perfect the AMC 8, but we also want you to learn and understand the topics presented as if you were in a classroom setting. Above all, the first and foremost goal is for you to have a good time learning math! The units that will be covered in this book are the following: - Test Taking Strategies for the AMC 8 - Number Sense in the AMC 8 - Number Theory in the AMC 8 - Algebra in the AMC 8 - Counting and Probability in the AMC 8 - Geometry in the AMC 8 - Advanced Competition Tricks for the AMC 8

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.