About the Author
Allen YuAllen Yu, Ph.D. is the co-founder of Codex Genetics Limited, which aims to provide personalized medicine service in Asia with latest genomics technology. Allen has used Python and Matplotlib extensively during his 10-year experience in the field of bioinformatics and Big data analytics. During his research career, Allen published 12 international scientific research articles and presented in 4 international conferences, including on-stage presentations in the Congress On the Future of Engineering Software (COFES) 2011, USA, and Genome Informatics 2014, U.K. Other research highlights include discovering a novel subtype of Spinocerebellar ataxia (SCA40), identifying the cause of pathogenesis for a patient with Spastic paraparesis, leading the Gold medalist team in 2011 International Genetically Engineered Machine (iGEM) competition, and co-developing ViralFusionSeq that can detect viral integration events (e.g. HBV/HCV/HPV) in cancer genomes.
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About This Book
Create and customize live graphs, by adding style, color, font to make appealing graphs.A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits.Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more.
Who This Book Is For
This book is for anyone interested in data visualization, to get insights from big data with Python and Matplotlib 2.x. With this book you will be able to extend your knowledge and learn how to use python code in order to visualize your data with Matplotlib. Basic knowledge of Python is expected.
What You Will Learn
Familiarize with the latest features in Matplotlib 2.xCreate data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more.Make clear and appealing figures for scientific publications.Create interactive charts and animation.Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn.Design intuitive infographics for effective storytelling.
In Detail
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.
Matplotlib 2.x By
發表於2024-12-26
Matplotlib 2.x By Example: Multi-dimensional charts, graphs, and plots in Python 2024 pdf epub mobi 電子書 下載
圖書標籤: DataScience 編程 Visualization
優點:事無巨細,一闆一眼。缺點:代碼往往並不是最優的(最有效率的、最常用的);同一段代碼中,有功能重復的冗餘部分,需要讀者自行優化~
評分優點:事無巨細,一闆一眼。缺點:代碼往往並不是最優的(最有效率的、最常用的);同一段代碼中,有功能重復的冗餘部分,需要讀者自行優化~
評分優點:事無巨細,一闆一眼。缺點:代碼往往並不是最優的(最有效率的、最常用的);同一段代碼中,有功能重復的冗餘部分,需要讀者自行優化~
評分優點:事無巨細,一闆一眼。缺點:代碼往往並不是最優的(最有效率的、最常用的);同一段代碼中,有功能重復的冗餘部分,需要讀者自行優化~
評分優點:事無巨細,一闆一眼。缺點:代碼往往並不是最優的(最有效率的、最常用的);同一段代碼中,有功能重復的冗餘部分,需要讀者自行優化~
Matplotlib 2.x By Example: Multi-dimensional charts, graphs, and plots in Python 2024 pdf epub mobi 電子書 下載