Data at Work: Best Practices for Creating Effective Charts and Information Graphics in Microsoft Excel | InformIT
Free e-book download: Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel
Data is everywhere. Whether you work in business, education, science, or any other field, you probably deal with data on a daily basis. But how do you communicate your data effectively to your audience? How do you turn numbers into insights? How do you design charts that are clear, accurate, and engaging?
Free e-book download it Data at Work: Best
If you want to learn how to create effective data visualizations using Microsoft Excel, you should check out this free e-book: Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel by Jorge Camões.
In this book, you will learn:
What are the basic concepts and principles of data visualization
How does the human eye and brain process visual information
How to choose the right chart type for different data types and scenarios
How to format charts for clarity and impact
How to create charts in Microsoft Excel using its built-in features and tools
This book is written for spreadsheet users who want to improve their data visualization skills using Excel. You don't need to have any graphic design or programming experience. You just need to have a basic to advanced level of Excel skills and a desire to learn more.
Ready to dive in? Let's take a closer look at what this book has to offer.
The Building Blocks of Data Visualization
Data visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with data visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives.
Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don't need to be a graphic designer to create functional, elegant charts: this book will show you how.
In the first chapter, you will learn the basic concepts and principles of data visualization, such as:
What is data visualization and why is it important
What are the different types of data and how to classify them
What are the spatial organization of stimuli and how to use it to create visual hierarchy and contrast
What are retinal variables and how to use them to encode data attributes
What are charts and how to use them to display data relationships
What are networks and maps and how to use them to display data structures and locations
What are volume visualizations and how to use them to display data magnitude and density
You will also learn how to evaluate the effectiveness of a chart based on its purpose, audience, and context. You will see examples of good and bad charts and learn how to avoid common mistakes and pitfalls.
Visual Perception
Data visualization is not only about data. It's also about perception. How does the human eye and brain process visual information? What are the implications for data visualization design? How can we use our knowledge of visual perception to enhance comprehension and communication?
In the second chapter, you will learn the basics of visual perception, such as:
How the eye physiology affects what we see and how we see it
How pre-attentive processing and salience help us to quickly identify important features in a visual scene
How working memory limits our ability to store and manipulate information in our mind
You will also learn how to apply these concepts to data visualization design, such as:
How to use color, shape, size, position, orientation, and motion to create visual cues that attract attention and convey meaning
How to use grouping, alignment, proximity, similarity, enclosure, and connection to create visual structure and organization
How to use redundancy, repetition, consistency, and feedback to create visual clarity and familiarity
How to use chunking, summarization, simplification, and filtering to reduce cognitive load and increase understanding
Choosing the Right Chart Type
Data visualization is not only about data and perception. It's also about choice. How do we choose the right chart type for different data types and scenarios? What are the advantages and disadvantages of common chart types such as bar charts, line charts, pie charts, scatter plots, etc.? How do we avoid misleading or confusing our audience with inappropriate or inaccurate chart types?
In the third chapter, you will learn how to select the most appropriate chart type for your data visualization needs, such as:
How to identify the data type (nominal, ordinal, interval, ratio) and the data scenario (comparison, distribution, composition, relationship)
How to match the data type and scenario with the chart type (bar chart, line chart, pie chart, scatter plot, etc.)
How to evaluate the pros and cons of each chart type based on its strengths and weaknesses
How to avoid common pitfalls and errors such as using 3D effects, exploding pie slices, truncated axes, dual axes, etc.
Formatting Charts for Clarity and Impact
```html legends, axes, gridlines, etc.? How do we avoid clutter, chartjunk, and noise that distract from the message? How do we enhance the aesthetics and appeal of our charts without compromising accuracy and integrity?
In the fourth chapter, you will learn how to apply best practices for formatting charts, such as:
How to use color to encode data, highlight key points, create contrast, and establish harmony
How to use fonts to create readability, consistency, and emphasis
How to use labels to provide context, explanation, and evidence
How to use legends to identify data categories and values
How to use axes to define data scales and ranges
How to use gridlines to facilitate data comparison and alignment
You will also learn how to avoid common pitfalls and errors such as using too many colors, fonts, labels, legends, axes, gridlines, etc., or using them inappropriately or inconsistently.
Creating Charts in Microsoft Excel
Data visualization is not only about data, perception, choice, and formatting. It's also about creation. How do we create charts in Microsoft Excel using its built-in features and tools? How do we customize and enhance our charts with additional elements such as annotations, icons, images, etc.? How do we use advanced techniques such as conditional formatting, sparklines, pivot tables, etc.?
In the fifth chapter, you will learn how to use Excel's features and tools to create effective charts and information graphics, such as:
How to use the Chart Wizard to create basic charts quickly and easily
How to use the Chart Tools to modify and format charts
How to use the Design tab to change chart types, layouts, styles, and colors
How to use the Layout tab to add and adjust chart elements such as titles, labels, legends, axes, gridlines, etc.
How to use the Format tab to apply shape effects, fill colors, outline colors, text effects, etc.
How to use the Insert tab to add additional elements such as shapes, icons, pictures, text boxes, etc.
How to use the Data tab to manage data sources and connections
How to use the Formulas tab to create and edit formulas and functions
How to use the Review tab to check spelling and accessibility
How to use the View tab to change zoom level and display options
You will also learn how to use advanced techniques such as:
How to use conditional formatting to apply rules-based formatting based on data values or conditions
How to use sparklines to create mini charts within cells
How to use pivot tables and pivot charts to summarize and analyze large data sets
How to use slicers and timelines to filter and slice data interactively
How to use Power Query and Power Pivot to import and transform data from various sources
How to use Power View and Power Map to create interactive dashboards and maps
Conclusion
Data visualization is a powerful way to communicate data effectively. But it's not easy. It requires a combination of skills and knowledge that span across data analysis, visual design, and spreadsheet software. It also requires a lot of practice and experimentation.
This book has given you a solid foundation for creating effective charts and information graphics in Microsoft Excel. You have learned the basic concepts and principles of data visualization, the basics of visual perception, how to choose the right chart type for different data types and scenarios, how to format charts for clarity and impact, and how to create charts in Microsoft Excel using its built-in features and tools.
But this book is not a manual. It does not provide step-by-step instructions for every chart type or every Excel feature. It does not cover every possible scenario or situation. It does not tell you what chart type or formatting option is always right or wrong.
This book is a guide. It provides you with a framework for thinking about and organizing data in ways that directly relate to your work. It provides you with examples of good and bad charts and explains why they are good or bad. It provides you with tips and tricks for creating charts that are clear, accurate, and engaging.
This book is a starting point. It encourages you to explore and experiment with different chart types, formatting options, and Excel features. It encourages you to use the companion website or the O'Reilly learning platform to download the free e-book and the original Excel files used in the book. It encourages you to use the comments section to send feedback, ask questions, and suggest improvements.
This book is a lighthouse. It guides you through the vast and complex sea of data visualization. But it also encourages you to find your own way and create your own charts.
So what are you waiting for? Download the free e-book now and start creating effective charts and information graphics in Microsoft Excel!
FAQs
What is data visualization?
Data visualization is the process of transforming data into visual forms that can be easily understood and communicated.
Why is data visualization important?
Data visualization is important because it helps us to explore, analyze, and communicate data effectively. It helps us to discover patterns, trends, outliers, and relationships in data. It helps us to convey insights, stories, and messages to our audience. It helps us to make better decisions based on data.
Who is the author of Data at Work?
The author of Data at Work is Jorge Camões, a data visualization consultant and trainer who has been working with data for over 15 years. He runs ExcelCharts.com, a popular blog about data visualization and Excel. He also teaches data visualization at the University of Lisbon and other institutions.
Who is the target audience of Data at Work?