Tag: packages

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. One hundred seventy-nine new packages made it to CRAN in May. Here are my “Top 40” picks in twelve categories: Computational Methods, Data, Ecology, Epidemiology, Finance, Machine Learning, Networks, Science, Statistics, Time Series, Utilities, and Visualization. Computational Methods graDiEnt v1.0.1: Implements the derivative-free, optim-style Stochastic Quasi-Gradient Differential Evolution optimization algorithm published in ... Read More

Feed: R-bloggers. Author: Econometrics and Free Software. I have this hypothesis that packages that introduce a unique syntax, or a workflow change, get adopted less by users, even if what these packages do is super useful. I’m going to discuss two examples of packages that I think are really, really useful, but sometimes I wonder how many R users use them, or would use them if they were aware these packages existed. I myself, only use one of them! The first package is {typed} which introduces a type system for R. No more silent conversion to and from types without ... Read More

Feed: Recent Announcements. Amazon Elastic Kubernetes Service (EKS) Anywhere now allows you to enable Amazon-curated software packages that extend the core functionalities of Kubernetes on your EKS Anywhere clusters. You can install the Harbor package as a local container registry starting today, with the Emissary-Ingress package and the support for service type load balancing through MetalLB coming in the next few months. More curated packages may be added over time based on customer demand. If you operate EKS Anywhere clusters on-premises, you probably install additional software for capabilities such as ingress, load balancing, and container registry to ensure the security ... Read More

Feed: R-bloggers. Author: %>% dreams. [This article was first published on %>% dreams, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. As I’ve been saying every year for the past seven years or so, I am learning Python. (It’s been a journey.) Python packages like pandas have several ways to work with data. There are several options for indexing, slicing, etc. They have a lot of flexibility but also a lot of conventions ... Read More

Feed: R-bloggers. Author: Dario Radečić. Real-world datasets are messy. Unless the dataset was created for teaching purposes, it’s likely you’ll have to spend hours or even tens of hours cleaning it before you can show it on a dashboard. That’s where two packages for data cleaning in R come into play – janitor and data.validator.  And today you’ll learn how to use them together. If you’re a software engineer, think of data cleaning and validation as writing and testing code. Think of data cleaning as coding an app – it takes a huge amount of time to get it working ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Two hundred and six new packages stuck to CRAN in March. Here are my “Top 40” selections in thirteen categories: Computational Methods, Data, Finance, Game Theory, Genomics, Machine Learning, Medicine, Networks, Science, Statistics, Time Series, Utilities, and Visualization. Computational Methods RCDT v1.1.0: Provides functions to perform 2D Delaunay triangulation, constrained or unconstrained, ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. February was a good month for new R packages on CRAN. Here are my “Top 40” selections from the two hundred packages that arrived in thirteen categories: Computational Methods, “Data”, Genomics, Linguistics, Machine Learning, Mathematics, Medicine, Networks, Science, Sports, Statistics, Utilities, Visualization. Computational Methods fastadi v0.1.0: Implements the adaptive-impute matrix completion algorithm ... Read More

Feed: R-bloggers. Author: Dario Radečić. Data science is vastly different than programming. We use only four languages – R, Python, Julia, and SQL. Now, SQL is non-negotiable, as every data scientist must be proficient in it. Julia is still the new kid on the block. Many argue which is better – Python or R? But today, we ask a different question – how can you use R and Python together? It might seem crazy at first, but hear us out. Both Python and R are stable languages used by many data scientists. Even seasoned package developers, such as Hadley Wickham, ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Two Hundred and two new packages made it to CRAN in January. Several were in applications areas that don’t show up very often, and a few of these made it into my January “Top 40” picks. My selections are listed below in thirteen categories: Agriculture, Computational Methods, Data, Engineering, Finance, Genomics, Machine ... Read More

Feed: R-bloggers. Author: rstats on Bryan Shalloway's Blog. This post is a follow-up to my previous post Identifying R Functions & Packages Used in GitHub Repos that introduced funspotr. funspotr can also be applied to gists: By functions or packages used…?https://t.co/kbSLOpQZLF — Bryan Shalloway (@brshallo) January 22, 2022 A problem I bumped into was that most of Chelsea’s gists don’t actually have .R or .Rmd extensions so my approach skipped most of her snippets. I wanted to parse my own gists but ran into a related problem that most of my github gist code snippets are saved as .md files ... Read More