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Data and Process Visualisation for Graphic Communication [electronic resource] : A Hands-on Approach with Python / by Francesco Bianconi.

By: Bianconi, Francesco [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: XIX, 242 p. 98 illus., 84 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031570513.Subject(s): Information visualization | Python (Computer program language) | Computer graphics | Data and Information Visualization | Python | Computer GraphicsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 001.4226 Online resources: Click here to access online
Contents:
Part I: Data -- 1. Introducing data -- 2. Magnitudes -- 3. Proportions -- 4. One variable as a function of the other -- 5. Frequency distributions -- 6. Groups -- 7. Relations -- 8. Bivariate data -- 9. Trivariate data -- 10. Geospatial data -- Part II: Representing processes -- 11. Timelines -- 12. Flowcharts -- 13. Gantt charts -- 14. PERT diagrams.
In: Springer Nature eBookSummary: This book guides the reader through the process of graphic communication with a particular focus on representing data and processes. It considers a variety of common graphic communication scenarios among those that arise most frequently in practical applications. The book is organized in two parts: representing data (Part I) and representing processes (Part II). The first part deals with the graphical representation of data. It starts with an introductory chapter on the types of variables, then guides the reader through the most common data visualization scenarios - i.e.: representing magnitudes, proportions, one variable as a function of the other, groups, relations, bivariate, trivariate and geospatial data. The second part covers various tools for the visual representation of processes; these include timelines, flow-charts, Gantt charts and PERT diagrams. In addition, the book also features four appendices which cover cross-chapter topics: mathematics and statistics review, Matplotlib primer, color representation and usage, and representation of geospatial data. Aimed at junior and senior undergraduate students in various technical, scientific, and economic fields, this book is also a valuable aid for researchers and practitioners in data science, marketing, entertainment, media and other fields.
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Part I: Data -- 1. Introducing data -- 2. Magnitudes -- 3. Proportions -- 4. One variable as a function of the other -- 5. Frequency distributions -- 6. Groups -- 7. Relations -- 8. Bivariate data -- 9. Trivariate data -- 10. Geospatial data -- Part II: Representing processes -- 11. Timelines -- 12. Flowcharts -- 13. Gantt charts -- 14. PERT diagrams.

This book guides the reader through the process of graphic communication with a particular focus on representing data and processes. It considers a variety of common graphic communication scenarios among those that arise most frequently in practical applications. The book is organized in two parts: representing data (Part I) and representing processes (Part II). The first part deals with the graphical representation of data. It starts with an introductory chapter on the types of variables, then guides the reader through the most common data visualization scenarios - i.e.: representing magnitudes, proportions, one variable as a function of the other, groups, relations, bivariate, trivariate and geospatial data. The second part covers various tools for the visual representation of processes; these include timelines, flow-charts, Gantt charts and PERT diagrams. In addition, the book also features four appendices which cover cross-chapter topics: mathematics and statistics review, Matplotlib primer, color representation and usage, and representation of geospatial data. Aimed at junior and senior undergraduate students in various technical, scientific, and economic fields, this book is also a valuable aid for researchers and practitioners in data science, marketing, entertainment, media and other fields.

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