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Tidy Modeling with R


This is the website for Tidy Modeling with R. This book is a guide to using a new collection of software in the R programming language for model building, and it has two main goals:

  • First and foremost, this book provides an introduction to how to use our software to create models. We focus on a dialect of R called the tidyverse that is designed to be a better interface for common tasks using R. If you’ve never heard of or used the tidyverse, Chapter 2 provides an introduction. In this book, we demonstrate how the tidyverse can be used to produce high quality models. The tools used to do this are referred to as the tidymodels packages.
  • Second, we use the tidymodels packages to encourage good methodology and statistical practice. Many models, especially complex predictive or machine learning models, can work very well on the data at hand but may fail when exposed to new data. Often, this issue is due to poor choices made during the development and/or selection of the models. Whenever possible, our software, documentation, and other materials attempt to prevent these and other pitfalls.

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Lunes, 21 de septiembre de 2020 Sin comentarios

R for Excel Users: Pivot Tables, VLOOKUPs in R


New business and financial analysts are finding R every day. Most of these new userRs (R users) are coming from a non-programming background. They have ample domain experience in functions like finance, marketing, and business, but their tool of choice is Excel (or more recently Tableau & PowerBI)….

 

 

https://www.business-science.io/finance/2020/02/26/r-for-excel-users.html


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Jueves, 27 de febrero de 2020 Sin comentarios

A simple introduction to programming and statistics with decision trees in R


University students in other disciplines without prior knowledge in statistics and/or programming language are introduced to the statistical method of decision trees in the programming language R during a 45‐minute teaching and practice session. Statistics and programming skills are now frequently required within a wide variety of research fields and private industries. However, students unfamiliar with these subjects may be reluctant to join a full course because of time or student workloads or other commitments or a belief it is not for them. The proposed session is short and can be used as an ice‐breaker to let students have a basic understanding of running statistical models in programming language….

https://onlinelibrary.wiley.com/doi/full/10.1111/test.12210?campaign=wolearlyview

 


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Lunes, 17 de febrero de 2020 Sin comentarios

Animated Plots using ggplot and gganimate


Did you know, that you can transform plain old static ggplot graphs to animated ones? Well you can with the help of the package gganimate by RStudio’s Thomas Lin Pedersen and David Robinson and the results are amazing! My STATWORX colleagues and I are very impressed how effortless all kind of geoms are transformed to suuuper smooth animations. That’s why in this post I will provide a short overview over some of the wonderful functionalities of gganimate, I hope you’ll enjoy them as much as we do!

https://www.statworx.com/de/blog/animated-plots-using-ggplot-and-gganimate/

 


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Domingo, 16 de febrero de 2020 Sin comentarios

Happy collaboration with Rmd to docx


Os dejo un enlace interesante: This article is reposted from graphdoctor.com with the kind permission of Richard Layton.

Enlace


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Jueves, 23 de julio de 2015 Sin comentarios

Paquetes para manipular Datos en R


Computerworld’s list of R packages for data wrangling

Computerworld’s Sharon Machlis published today a very useful list of R packages that every R user should know. The list covers packages for data import, data wrangling, data visualization and package development, but for beginning R users the biggest challenge is usually just dealing with data. To that end, I thought it was worth listing the package for data access and manipulation, which I thoroughly endorse:

  • Data import/accessreadr (text data files), rio (many binary data file formats), readxl (Excel spreadsheets), googlesheets (Google Sheets), RMySQL(MySQL databases), quantmod (economic and financial data sources);
  • Data manipulation: dplyr (general data frame processing); data.table (aggregation and filtering); tidyr (tidying messy data into row/col format); sqldf (SQL queries on data frames), zoo (time series data wrangling)

Check out Sharon’s complete list below for details on these and many other useful R packages.


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Viernes, 15 de mayo de 2015 Sin comentarios

R Markdown Tutorial by RStudio and DataCamp


Interesante Videotutorial para empezar a trabajar con R y Markdown:

In collaboration with Garrett Grolemund, RStudio’s teaching specialist, DataCamp has developed a new interactive course to facilitate reproducible reporting of your R analyses. R Markdown enables you to generate reports straight from your R code, documenting your works as an HTML, pdf or Microsoft document. This course is part of DataCamp’s R training path, but can also be taken as a separate course.

http://blog.datacamp.com/r-markdown-tutorial-reproducible-reporting-in-r/


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Martes, 3 de marzo de 2015 Sin comentarios