Data at Work will help students to know which type of chart to use and how to format it, regardless of which spreadsheet application they use and whether or not they have any design experience. In this book, they'll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatterplots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant…mehr
Data at Work will help students to know which type of chart to use and how to format it, regardless of which spreadsheet application they use and whether or not they have any design experience. In this book, they'll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatterplots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for students to download, with brief explanations of how they were created.
Jorge Camões has been consulting businesses on how to effectively use information visualizations since 2010 with clients that include the global retail giant, IKEA. Prior to starting his consulting business, Camões worked for 10 years in the business intelligence department of the Portuguese subsidiary of Merck & Co. Camões runs the popular data visualization blog, Excelcharts.com, which has 30K monthly visitors. He works from his home in Lisbon, Portugal.
Inhaltsangabe
Introduction 1. The building blocks 2. Human perception 3. Beyond perception 4. Preparing the data 5. Information visualization 6. Discovery and communication 7. How to choose a chart 8. Comparisons 9. Composition 10. Distribution 11. Evolution 12. Relationships 13. Profiling 14. Aesthetics in visualization 15. Color: how to avoid catastrophe 16. Formatting the chart 17. Conclusions
Introduction 1. The building blocks 2. Human perception 3. Beyond perception 4. Preparing the data 5. Information visualization 6. Discovery and communication 7. How to choose a chart 8. Comparisons 9. Composition 10. Distribution 11. Evolution 12. Relationships 13. Profiling 14. Aesthetics in visualization 15. Color: how to avoid catastrophe 16. Formatting the chart 17. Conclusions
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