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Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language;
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for basic statistics, graphics, and regression. You'll find recipes on reading data files, creating data frames, computing basic statistics;
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This O'Reilly cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality;
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Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature About This Book;
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discussion of how and why the recipe works. Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have;
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one of its packages and the R code is available at rosuda.org/GDA. Graphical data analysis is useful for data cleaning, exploring data;
Vergelijkbare producten zoals Graphical Data Analysis with R
one of its packages and the R code is available at rosuda.org/GDA. Graphical data analysis is useful for data cleaning, exploring data;
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of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies;
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Shang, Journal of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles;
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analysis for modelling and forecasting temporal data Implement a range of regression techniques for efficient data modelling Get to grips with;
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and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick;
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software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic;
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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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and receive faxes, prepare files for printing, and read and write data across platforms Use spelling and grammar checkers, word counters, and;
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of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis;
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++ programmers. Full of practical techniques for implementing amazing computer graphics and visualizations, using OpenGL. Crammed full of useful recipes;
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manipulation. Heat Maps in R How-to is the book for you if you want to make use of this free and open source software to get the most out of your data;
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will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to;
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and Data with R presents an accessible guide to data manipulations, statistical analysis and graphics using R. Assuming no previous knowledge;
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Transact-SQL. *Importing data. This chapter introduces concepts like normalization and recipes useful for working with imported data tables. *Sets;
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This is an excellent textbook for undergraduate courses in data analysis and regression, for students majoring or minoring in statistics;
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Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques About This Book;
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In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel;
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recipes that provide enhancements to the user interface, and finishing with recipes that cover data and systems integration. You can also refer to;
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, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and;
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, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and;
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