CategoriesProgramming Tags Correlation Data Visualisation R Programming In this article, you learn how to make Automated Dashboard with various correlation visualizations in R. First you need to install the `rmarkdown` package into your R library. Assuming that you installed the `rmarkdown`, next you create a new `rmarkdown` script in R. After this you type the following code in order to create a Related Post Automated...
We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but soon I realised, that it will be much easier...
The ggQC package is a quality control extension for ggplot. Use it to create XmR, XbarR, C and many other highly customizable Control Charts. Additional statistical process control functions include Shewart violation checks as well as capability analysis. If your process is running smoothly, visualize the potential impacted of your next process improvement with a Pareto chart. To learn...
In this post, we explore the functionality provided by the plyr package. The ideas behind this package are described in this paper by Hadley Wickham. However, rather than trying to understand the theoretical underpinnings of the package, we look at some of the useful functions provided by this package and how they work. Anyone using R seriously will have come...
This year, the so-called warming stripes, which were created by the scientist Ed Hawkins of the University of Reading, became very famous all over the world. These graphs represent and communicate climate change in a very illustrative and effective way. Visualising global temperature change since records began in 1850. Versions for USA, central England & Toronto available too: https://t.co/H5Hv9YgZ7v pic.twitter.com/YMzdySrr3A—...
Here you find my slides from last nights TWiML & AI EMEA Meetup about Trust in ML models, where I presented the Anchors paper by Carlos Guestrin et al.. I have also just written two articles for the German IT magazin iX about the same topic of...
🎤 Dan Sholler, rOpenSci Postdoctoral Fellow 🕘 Tuesday, December 18, 2018, 10-11AM PST; 7-8PM CET (find your timezone) ☎️ Details for joining the Community Call. Everyone is welcome. No RSVP needed. Researchers use open source software for the capabilities it provides, such as streamlined data access and analysis and interoperability with other pieces of the scientific computing ecosystem. For most complex software,...
Simulate Market Shares for Product Launches with Conjoint Analysis. In this small case study, I will show you how you a can understand your customer by their actual underlying preferences by showing you a concrete example of a conjoint analysis. Read and find how a laptop startup can beat Dell, Acer, Apple & Co. using a conjoint analysis. The post...
As part of the run-up to the release of Data Visualization (out in about ten days! Currently 30% off on Amazon!), I’ve been playing with graphing different kinds of data. One great source of rich time-series data is mortality.org, which hosts a collection of standardized demographic data for a large number of countries. Mortality rates are often interesting to...
Bayesian Nonparametric Models in NIMBLE, Part 1: Density Estimation Bayesian nonparametrics in NIMBLE: Density estimation Overview NIMBLE is a hierarchical modeling package that uses nearly the same language for model specification as the popular MCMC packages WinBUGS, OpenBUGS and JAGS, while making the modeling language extensible — you can add distributions and functions — and
In this article, I hope to inspire you to start exploring satellite imagery datasets. Recently, this technology has gained huge momentum, and we are finding that new possibilities arise when we use satellite image analysis. Satellite data changes the game because it allows us to gather new information that is not readily available to businesses. Artykuł Deep learning in...
Our recent addition to the NLP R universe is called R package ruimtehol which is open sourced at https://github.com/bnosac/ruimtehol This R package is a wrapper around Starspace which provides a neural embedding model for doing the following on text: Text classification Learning word, sentence or document level embeddings Finding sentence or document similarity Ranking web documents Content-based recommendation (e.g. recommend text/music based on the...
We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but soon I realised, that it will be much easier...
1. Introduction In this post we discuss the H2O machine learning platform. We talk about what H2O is, and how to get started with it, using R - we create a Random Forest which we use to classify the Iris Dataset. 2. What is H2O? The definition found on H2O’s Github page is a lot to take in, especially if you’re just...
Solving the puzzles of Advent of Code with R.
Solving the puzzles of Advent of Code with R.
This past year in R has been a good one for me; productive, exciting, different. I decided it was worth taking a moment to reflect and share. Goals were set and met. There were also unexpected changes. CRAN A year ago, at the tail end of 2017, I pu...
We’ve just released a new version of rnoaa with A LOT of changes. Check out the release notes for a complete list of changes. We’ll highlight a few things in this post: New data sources in the package NCDC units added to the output of ncdc() Links: rnoaa source code: https://github.com/ropensci/rnoaa rnoaa on CRAN: https://cran.rstudio.com/web/packages/rnoaa/ Installation Install the lastest from CRAN install.packages("rnoaa") Some binaries are not up yet on CRAN -...
spatsoc is an R package written by Alec Robitaille, Quinn Webber and Eric Vander Wal of the Wildlife Evolutionary Ecology Lab (WEEL) at Memorial University of Newfoundland. It is the lab’s first R package and was recently accepted through the rOpenSci onboarding process with a big thanks to reviewers Priscilla Minotti and Filipe Teixeira, and editor Lincoln Mullen. spatsoc started...
This post will review Kris Boudt’s datacamp course, along with introducing some concepts from it, discuss GARCH, present an application … Continue reading →
Our group has done a lot of work with non-standard calling conventions in R. Our tools work hard to eliminate non-standard calling (as is the purpose of wrapr::let()), or at least make it cleaner and more controllable (as is done in the wrapr dot pipe). And even so, we still get surprised by some of … Continue reading Very...
Introduction The Forgotten Age cycle of Arkham Horror is at a close and Fantasy Flight Games already announced the next cycle, The Circle Undone. Not only that, they’ve announced two mythos packs at a rate that… surprised me. A new cycle announcement and two mythos pack announcements in less than two months? Am I the…Read more Making a Profit...
This is the next article in my series on AzureR, a family of packages for working with Azure in R. I’ll give a short introduction on how to use AzureVM to manage Azure virtual machines, and in particular Data Science Virtual Machines (DSVMs). Creating a VM Creating a VM is as simple as using the create_vm method, which is...
CategoriesProgramming Tags Data Visualisation Linear Regression R Programming Tips & Tricks In this article, you learn how to make a Automated Dashboard with Visualization and Regression for Healthcare Data in R. First you need to install the `rmarkdown` package into your R library. Assuming that you installed the `rmarkdown`, next you create a new `rmarkdown` script in R. I use the healthcare insurance data from...
We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but soon I realised, that it will be much easier...
In all monotonic algorithms that I posted before, I heavily relied on the smbinning::smbinning.custom() function contributed by Herman Jopia as the utility function generating the binning output and therefore feel deeply indebted to his excellent work. However, the availability of smbinning::smbinning.custom() function shouldn’t become my excuse for being lazy. Over the weekend, I drafted a
This post is following exercise 1 in Chapter 12 of Applied Predicative Modeling. Here I use the machine learning package CARET in R to make classification models; in particular, the linear classification models discussed in Chapter 12. The dataset in question is about hepatic injury (liver damage). It includes a dataframe of biological related predictors of liver damage bio, a...
”“Data scientists … spend from 50 percent to 80 percent of their time … collecting and preparing unruly digital data, before it can be explored for useful nuggets.” (— New York Times). The chartbookR package allows the convenient creation of economic and financial data chartbooks. It handles most of the data wrangling and can thus create large chartbooks with few...
Samuel Berchuck is a Postdoctoral Associate in Duke University’s Department of Statistical Science and Forge-Duke’s Center for Actionable Health Data Science. Joshua L. Warren is an Assistant Professor of Biostatistics at Yale University. Introduction Glaucoma is a leading cause of blindness worldwide, with a prevalence of 4% in the population aged 40-80. The disease is characterized by retinal ganglion cell death and...
Contact us if you wish to help support R-bloggers, and place your banner here.
