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SKU/Artículo: AMZ-1783987545
Mastering matplotlib
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.65 kg
0.65 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- A practical guide that takes you beyond the basics of matplotlib and gives solutions to plot complex dataAbout This BookCustomize, configure, and handle events, and interact with figures using matplotlibCreate highly intricate and complicated graphs using matplotlibExplore matplotlib's depths through examples and explanations in IPython notebooksWho This Book Is ForIf you are a scientist, programmer, software engineer, or student who has working knowledge of matplotlib and now want to extend your usage of matplotlib to plot complex graphs and charts and handle large datasets, then this book is for you.What You Will LearnAnalyze the matplotlib code base and its internalsRe-render visualized data on the fly based on changes in the user interfaceTake advantage of sophisticated third-party libraries to plot complex data relationshipsCreate custom styles for use in specialize publications, presentations, or online mediaGenerate consolidated master plots comprising many subplots for dashboard-like resultsDeploy matplotlib in Cloud environmentsUtilize matplotlib in big data projectsIn Detailmatplotlib is a Python plotting library that provides a large feature set for a multitude of platforms. Given the depth of the library's legacy and the variety of related open source projects, gaining expert knowledge can be a time-consuming and often confusing process.You'll begin your exciting journey learning about the skills that are necessary in leading technical teams for a visualization project or to become a matplotlib contributor.Supported by highly-detailed IPython Notebooks, this book takes you through the conceptual components underlying the library and then provides a detailed overview of its APIs. From there, you will learn about event handling and how to code for interactive plots.Next you will move on to customization techniques, local configuration of matplotib, and then deployments in Cloud environments. The adventure culminates in an exploration of big data visualization and matplotlib clustering.
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