Show Me the Numbers: Designing Tables and Graphs to Enlighten

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Lines that are used to encode values in graphs fall into four categories: standard line, high-low line, trend line and reference line. Standard are particularly good at displaying values that change through time as well as the overall of that change. High-low connect the maximum and minimum quantitative values across multiple data sets at each location along a categorical scale. Trend lines display the overall course of quantitative values that are spread across a series of categorical subdivisions. Reference lines are used to display a set of values against which other can be compared or to mark a point of interest along a categorical scale. Access-restricted-item true Addeddate 2022-06-17 06:08:21 Autocrop_version 0.0.14_books-20220331-0.2 Bookplateleaf 0006 Boxid IA40572219 Camera Sony Alpha-A6300 (Control) Collection_set printdisabled External-identifier

Approximately 70% of the sense receptors in our bodies are dedicated to vision. Graphs and tables are visual means of communication. Sensation is a physical process, involving the receipt of a stimulus. Perception is a cognitive process, involving the interpretation of the physical stimulus in an effort to make sense of it. For a visual stimulus to occur, there must be light. A graph is a method for displaying quantitative information that exhibits the following characteristic: The most common attribute used to identify categorical subdivisions is position. Second is color. Fill pattern are only used when bars are used. Use one-to-one ratio of data height to white space height. Rule and grid can be used to: delineate columns and rows, group subsets of data and highlight subset of data. The problem is that they break up the data. When you use rules, be sure to subdue them visually in relation to the data by keeping the lines as thin and light as possible. When white space alone can’t be used to effectively delineate columns and rows in tables, fill shades and hues work better than grids and rules.Scale lines and aces are intimately related. They divide axes into increments of equal lengths. Quantitative scales are common and logarithmic. The same distance anywhere along a logarithmic scale equals the same percentage.

Font should be as legible as possible and the same font should be used throughout. Fonts that are most legible tend to have a clean and simple design. Fine legible fonts are: serif (Times New Roman, Palatino, Courier) and sans-serif (Arial, Verdana, Tahoma). Access to data is vast. The bigger data gets, the more complicated forms of interactive visualizations are at our disposal. When it comes to communicating data, you want to choose the charts that make the insights from the data the clearest, not the coolest. After you plot the chart, highlight what’s important and overlay annotations to show what your conclusions are from the data.” When you want to convey quantitative information that consist of one or two number do it in written language. There is elegance in simplicity. Quantitative values are numbers. Categories identify what the quantitative values measure. Sometimes numbers simply categorize information and have no quantitative meaning. Tables is a structure for organizing and displaying information. Data are arranged in columns and rows, data are encoded as text (words, numbers).Whatever the reason for breaking the data into groups, keep in mind the following design practices: For time-series you cannot use horizontal bars. You can use: lines, point and lines and vertical bars.

The components that we combine to construct tables and graphs: data and support components. Tables encode data as text. On another hand, the book is directed at a very specific niche and it will be totally useless for those that have no interest in working with numbers and presenting them in a very simplistic way to various audiences. Tables and graphs are part of family of display methods known as charts. Other types of charts are diagrams and maps. Graphs are perceived by our visual systems. Tables interact primarily with our verbal system. Numbers The Guild asked Amy Cesal, Community Director at Data Visualization Society, to share her point of view about creating a meaningful experience in data presentations: It is easy to combine multiple sets of quantitative data in a single graph when they all use the same unit of measures.Edward Tufte: “Above all else show the data.” He introduced the concept data-ink ratio. This is ratio of data ink to total ink. It should be close to 1 as possible, without loss of data information. We can improve a design process either through reducing non-data ink or through enhancing the data ink. Reducing non-data is about subtracting unnecessary non-data ink or de-emphasizing and regulating the remaining non-data ink. We bring out elegance. Latin term eligere means to choose out or to select carefully. Amy suggests subscribing to e-zines that include inspirational data visualization like Flowing Data by Nathan Yau and Fair Warning by Sophie Warnes. When you see what’s possible, then you can apply that inspiration to your own projects. She also suggests joining the Data Visualization Society, which she helped start. This organization is collecting resources and establishing best practices around data visualization to help mature the industry as a whole. I think templates are useful when creating a bunch of graphics and for maintaining consistency. I’ve even created a number of data visualization style guides to help create consistency among charts and graphs. But charts and graphs should look like a family of visuals not identical twins. It’s hard to see the uniqueness of the data and figure out the meaning of the chart if everything is visually identical.

Big Data, Big Dupe is a little book about a big bunch of nonsense. The story of David and Goliath inspires us to hope that something little, when armed with truth, can topple something big that is a lie. This is the author's hope. While others have written about the dangers of Big Data, Stephen Few reveals the deceit that belies its illusory nature. If "data is the new oil," Big Data is the new snake oil. It isn't real. It's a marketing campaign that has distracted us for years from the real and important work of deriving value from data. Data, in and of itself, isn't valuable. It only becomes valuable when we make sense of it. Weaving data into understanding involves several distinct but complementary thinking skills. Foremost among them are critical thinking and scientific thinking. Until information professionals develop these capabilities, we will remain in the dark ages of data. If you're an information professional and have never been trained to think critically and scientifically with data, this book will set your feet on the path that will lead to an Information Age worthy of the name. Through her new book, Nancy shows content professionals how to move from “numbers into narratives.” This will enable them to explain data in a way that drives action in their audience. Different sizes, shapes and hues are only three of the visual attributes that you can use to distinguish different sets of points. When points overlap increase size of graph or decrease size of points. Maybe make them transparent. If you choose points and lines in combination, make sure that the points are not obscured by the lines.

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Time series should be arranged across the columns. Ranking look more natural when arranged from top to bottom. Show Me the Numbers is a master class in the principles and practices of data visualization. It’s an ideal guide for anyone involved in communicating with numbers – whether you’re a business professional, analyst, researcher, or student. And if you’re a fan of Teach Yourself VISUALLY Power BI, you’ll find Show Me the Numbers a complementary read. Gleaning Insights from Data The book starts with the basics, explaining the types of data and which tables or graphs are best for communicating them. But it doesn’t stop there. It builds on these insights by delving into more creative elements of data visualization. The beauty of this book is its broad appeal – it’s as accessible to beginners as it is enlightening to seasoned data professionals. Insights: Wie Windows 11 und Intel vPro die Produktivität und Sicherheit in Unternehmen steigern können