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Data and process visualisation for graphic communication = a hands-on approach with python /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data and process visualisation for graphic communication/ by Francesco Bianconi.
其他題名:	a hands-on approach with python /
作者:	Bianconi, Francesco.
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xix, 242 p. :ill. (chiefly col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Graphic methods - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-031-57051-3
ISBN:	9783031570513

Data and process visualisation for graphic communication = a hands-on approach with python /
Bianconi, Francesco.

Data and process visualisation for graphic communicationa hands-on approach with python /[electronic resource] :by Francesco Bianconi. - Cham :Springer Nature Switzerland :2024. - xix, 242 p. :ill. (chiefly col.), digital ;24 cm.

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.

ISBN: 9783031570513

Standard No.: 10.1007/978-3-031-57051-3doiSubjects--Topical Terms:

3448055
Graphic methods
--Data processing.

LC Class. No.: QA90

Dewey Class. No.: 001.4226

Data and process visualisation for graphic communication = a hands-on approach with python /
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520 $a 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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