**r in action data analysis and graphics with r robert** - *r in action data analysis and graphics with r robert kabacoff on amazon com free shipping on qualifying offers summary r in action second edition presents both the r language and the examples that make it so useful for business developers focusing on practical solutions*, **sas and r data management statistical analysis and** - *an up to date all in one resource for using sas and r to perform frequent tasks the first edition of this popular guide provided a path between sas and r using an easy to understand dictionary like approach*, **data frame objects in r via r in action r statistics** - *for readers of this blog there is a 38 discount off the r in action book as well as all other ebooks pbooks and meaps at manning publishing house simply by using the code rblogg38 when reaching checkout let us now talk about data frames data frames a data frame is more general than a matrix in that different columns can contain different modes of data numeric character and*, **awesome r find great r packages** - *awesome r a curated list of awesome r packages and tools inspired by awesome machine learning for better navigation see https awesome r com for top 50 cran downloaded packages or repos with 400 integrated development environments integrated development environment*, **post hoc analysis for friedman s test r code r** - *my goal in this post is to give an overview of friedman s test and then offer r code to perform post hoc analysis on friedman s test results*, **learning path on r step by step guide to learn data** - *learning path on r provides a step by step guide to become a data scientist using r the path includes exercises tutorials best practices*, **an introduction to r** - *this is an introduction to r gnu s a language and environment for statistical computing and graphics r is similar to the award winning 1 s system which was developed at bell laboratories by john chambers et al it provides a wide variety of statistical and graphical techniques linear and*, **r data import export** - *1 introduction reading data into a statistical system for analysis and exporting the results to some other system for report writing can be frustrating tasks that can take far more time than the statistical analysis itself even though most readers will find the latter far more appealing*, **tutorials for learning r r bloggers** - *r packages are the fuel that drive the growth and popularity of r r packages are bundles of code data documentation and tests that are easy to share with others before you can use a package you will first have to install it some packages like the base package are automatically installed when you install r other packages like for example the ggplot2 package won t come with the*, **how to reshape data in r tidyr vs reshape2 r bloggers** - *reshape your data from long to wide split a column aggregate a comparison between tidyr and reshape2 r packages to tidy data the post how to reshape data in r tidyr vs reshape2 appeared first on milanor*, **r programming data types wikibooks open books for an** - *data types vectors are the simplest r objects an ordered list of primitive r objects of a given type e g real numbers strings logicals vectors are indexed by integers starting at 1 factors are similar to vectors but where each element is categorical i e one of a fixed number of possibilities or levels a matrix is like a vector but with a specific instruction for the layout such*, **r interview questions and answers dataflair** - *frequently asked r interview questions and answers q 1 explain what is r r is a language and environment for statistical computing and graphics it is an open source programming language r provides a wide variety of statistical and graphical techniques and is highly extensible*, **an introduction to statistical and data sciences via r** - *1 1 introduction for students this book assumes no prerequisites no algebra no calculus and no prior programming coding experience this is intended to be a gentle introduction to the practice of analyzing data and answering questions using data the way data scientists statisticians data journalists and other researchers would*, **r powered web applications with shiny a tutorial and** - *using predefined layout functions as mentioned above you will choose a layout function depending on the type of app you want for this example we will take advantage of a shiny template using the function sidebarlayout which creates a page with a sidebar and a main panel you can review other layout options in the rstudio layout guide in this example we re creating a sidebarpanel and*, **r for data science** - *this book will teach you how to do data science with r you ll learn how to get your data into r get it into the most useful structure transform it visualise it and model it in this book you will find a practicum of skills for data science just as a chemist learns how to clean test tubes and stock a lab you ll learn how to clean data and draw plots and many other things besides*, **mondrian interactive statistical data visualization in java** - *mondrian is a general purpose statistical data visualization system it features outstanding visualization techniques for data of almost any kind and has its particular strength compared to other tools when working with categorical data geographical data and large data*, **statistics com earn a certificate** - 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