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in learning effective data visualization techniques with R and a wide-range of its associated libraries.;
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This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization;
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Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization About This Book;
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Packed with practical recipes, this is a step-by-step guide to learning data visualization with D3 with the help of detailed illustrations;
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Statistics and Data Visualization Using R: The Art and Practice of Data Analysis teaches students statistics visually, focusing on;
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popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x;
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the power of R for computational statistics, visualization, and data science, in an integrated development environment. This book is a;
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R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer;
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R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer;
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Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for;
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Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists;
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by the R community * Become familiar with the lattice graphics package for high-level data visualization * Learn about bioinformatics;
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Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis;
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to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality;
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to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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From beginner to Jedi, this cookbook has a recipe for everyone, whether you're just learning how to create data visualizations or have;
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comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it;
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comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it;
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analytics and visualization with the power of R using this step-by-step guide * Wondering how R can be used with Tableau? This book is your one;
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resources to implement a full-fledged LA infrastructure. In closing, the book introduces a set of software tools for data analytics and;
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of graphical networks without having to write any code Learn to optimize the Gephi plugins for efficient data visualization Who This Book Is ForIf;
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geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and;
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The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive;
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