الدوري الممتاز الهندي 2020

R packages, like any software, require maintenance. Package maintenance includes: Fixing bugs when discovered. Adapting to updates in package dependencies. Providing some level of user and contributor support. When desired, refactoring code or adding... Continue reading: My Experience With Long Term Maintenance Of An R Package http://dlvr.it/TC9DyN

R For SEO Part 7: Loops Welcome back to my R for SEO series. We’re in the home stretch now, with part seven. Today, we’re going to be looking at different ways that we can run functions or commands over a series of elements using the various kinds of ... Continue reading: R For SEO Part 7: Loops http://dlvr.it/TC6cw8

Introduction Hey there, budding C programmer! Ready to embark on your coding journey? Let’s start with the classic “Hello World” program using Visual Studio Code. Don’t worry if you’re new to this – we’ll walk through it step by step! Setting... Continue reading: Your First C Adventure: Hello World in VS Code http://dlvr.it/TC6cjF

Adaptive (online/streaming) learning with uncertainty quantification and explanations using learningmachine in Python and R Continue reading: Conformalized adaptive (online/streaming) learning using learningmachine in Python and R http://dlvr.it/TC6cSD

Ever wondered how to visualize complex data distributions in a way that’s both insightful and aesthetically pleasing? Use the violin plot. It is a powerful tool that combines the best of boxplots and density plots, offering a comprehensive view of your... Continue reading: Violin Plots in R with ggplot2 | Comprehensive Guide http://dlvr.it/TC5xFR

The R programming language has a rich ecosystem of packages that are fantastic for creating beautiful production-grade tables from within R. Today, I’m showing you that one package that makes it really easy (mostly) to create interactive tables. Namely, I’m going to show you {reactable}. 🥳 If you want ... Continue reading: Creating interactive tables with reactable http://dlvr.it/TC5x12

Wingspan is a great game even though I’ve only played it a few times. The mechanics are great, there are […] The post Wingspan Data Analysis appeared first on Dan Oehm | Gradient Descending. Continue reading: Wingspan Data Analysis http://dlvr.it/TC4DJF

Overall, I am quite impressed with the responses! With minimal prompt engineering, document cleaning! It was able to return accurate responses, and even separated different conditions and provided appropriate treatment options. It was also able to return the correct response for tricky questions that our RAG was not able to. ... Continue reading: Gemini 1.5 Flash Better Than RAG? Let’s Check It Out In R! http://dlvr.it/TC3Jzx

Motivation Existing R packages, such as pcaPP, provide efficient implementations of the Kendall correlation coefficient. However, I wanted to create my own package exclusively for this purpose, without additional functions, and that it also allo... Continue reading: Kendallknight: an R package for Kendall’s correlation coefficient http://dlvr.it/TC3JmW

Suppose you are modeling a process that you believe is well approximated as being linear in its inputs, but only within a certain range. Outside that range, the output might saturate or threshold: for example if you are modeling a count or a physical process, you likely can never get […] Continue reading: Post-hoc Adjustment for Zero-Thresholded Linear Models http://dlvr.it/TC1J54

Lessons from Will Hunting and McGayverIn the world of data science, data cleaning is often seen as one of the most time-consuming and least glamorous tasks. Yet, it’s also one of the most critical. Without clean data, even the most sophisticated algorithms and models can produce misleading results. This ... Continue reading: Why Every Data Scientist Needs the janitor Package http://dlvr.it/TC0pcS

Introduction Hello, fellow useRs! Today, we’re going to expand on previous uses of the grepl() function where we looked for a single pattern and move onto to a search for multiple patterns within strings. Whether you’re cleaning data, conductin... Continue reading: Mastering grepl with Multiple Patterns in Base R http://dlvr.it/TC0TGs

Introduction Hello, fellow useRs! Today, we’re going to discuss the art of concatenating matrices in R. Concatenating matrices is all about combining smaller pieces into a larger whole, and in R, the functions rbind() and cbind() are your go-to... Continue reading: Mastering Matrix Concatenation in R: A Guide to rbind() and cbind() http://dlvr.it/TByrYS

Introduction In this post, we’ll cover how to open an Excel workbook using VBA and then call this VBA code from R. This guide will help you automate tasks in Excel directly from R, combining the strengths of both tools. We’ll break down the VBA... Continue reading: Opening an Excel Workbook with VBA and Calling it from R http://dlvr.it/TByrGg

A few months ago I listened to an episode on the Founder’s Journal podcast. The episode reviewed an essay, The Opportunity Cost of Everything, by Jack Raines. If you haven’t read it, then I suggest you invest 10 minutes in doing so. It will be time well spent. Continue reading: Your Life in Weeks http://dlvr.it/TBvpb6

Puzzles no. 514–518PuzzlesAuthor: ExcelBIAll files (xlsx with puzzle and R with solution) for each and every puzzle are available on my Github. Enjoy.Puzzle #514Today we are searching for treasure. Exactly what we need is to find highest 2x2 submatrix ... Continue reading: R Solution for Excel Puzzles http://dlvr.it/TBtQPJ

Introduction Welcome to another exciting R programming tutorial! Today, we will explore how to concatenate vectors of strings using different methods in R: base R, stringr, stringi, and glue. We’ll use a practical example involving a data frame... Continue reading: Mastering String Concatenation of Vectors in R: Base R, stringr, stringi, and glue http://dlvr.it/TBtQG4

John White Alexander, Study in Black and Green I had the opportunity to present an automated Quarto dashboard on Posit’s Monthly End-to-End Workflow with Posit Team, followed by a Q&A. The project involved a script that retrieves Consume... Continue reading: Quarto dashboard creation and automation http://dlvr.it/TBtQ2Y

Real-world problem often happen at the intersection of many areas. For example, maybe you want to build a web app for easier data ingestion. As an R user that’s no problem. You can easily dabble into the world of web development using the fantast... Continue reading: An R User’s Guide to Other Programming Languages http://dlvr.it/TBs6fh

The R Consortium recently interviewed Sanket Sinojia, organizer of the Ahmedabad R User Group (ARUG). With over 14 years of experience in statistical programming and data sciences in the clinical... The post A New R Community in Ahmedabad, India, focused on Clinical Research and Pharmaceutical Industries  appeared first on R Consortium. Continue reading: A New R Community in Ahmedabad, India, focused on Clinical Research and Pharmaceutical Industries  http://dlvr.it/TBrHDd

Introduction String concatenation is a fundamental operation in data manipulation and cleaning. If you are working in R, mastering string concatenation will significantly enhance your data processing capabilities. This blog post will cover diff... Continue reading: Mastering String Concatenation in R: A Comprehensive Guide http://dlvr.it/TBqsDj

Bayesian (nonlinear) adaptive learning Continue reading: Bayesian (nonlinear) adaptive learning http://dlvr.it/TBqrvK

Shiny applications are fantastic for turning data into interactive dashboards and web apps, making data exploration and visualization more engaging. But even the most visually appealing Shiny app can hit performance snags. Lagging visualizations, delayed user interactions, and sluggish data updates can quickly turn a promising Shiny app into a ... Continue reading: Unveiling Bottlenecks: A Guide to Profiling R and R Shiny Code http://dlvr.it/TBqYbR

The post Multiple regression model in R appeared first on Data Science Tutorials Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials. Multiple regression model in R, it is often necessary to fit multiple regression models to a dataset and compare the resulting coefficients ... Continue reading: Multiple regression model in R http://dlvr.it/TBpTdX

Is the Mona Lisa thinking about irrational numbers? by Jerry Tuttle       As a math teacher I sometimes share the following problem-solving strategy: If you are really stuck on a problem, let it sit, come back the ... Continue reading: Is the Mona Lisa thinking about irrational numbers? http://dlvr.it/TBp1Gs

The post Descriptive statistics in R appeared first on Data Science Tutorials Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials. Descriptive statistics in R, it is often necessary to create a table that contains descriptive statistics for variables in a data frame. One ... Continue reading: Descriptive statistics in R http://dlvr.it/TBmzH2

A while ago (2019 seems so long ago now) I started working on something I thought was interesting but which never really got any traction. It has potential once more, so it’s about time I wrote up what it does and why I think it’s a useful idea. I’... Continue reading: Tidy DataFrames but not Tibbles http://dlvr.it/TBmlQy

More than five years ago I started a series of posts on games of chance and for one reason or another never got around to finishing them. Partially redressing that, here is a long-lost and now tidied up post on Snakes and Ladders. Read it before you ne... Continue reading: Snakes and ladders by @ellis2013nz http://dlvr.it/TBlHqK

The following poem, created using Google Gemini AI :robot:, chronicles my journey into the world of ergonomic DIY keyboards. It documents my (evolving) preferences and opinions, as well as a curated list of resources that I have found useful over the last three years. :keyboard: Warning :keyboard: The following verses ... Continue reading: The deep rabbit hole of DIY small ergonomic keyboards http://dlvr.it/TBlHdS

Introduction Counting the occurrences of a specific character within a string is a common task in data processing and text manipulation. Whether you’re working with base R or leveraging the power of packages like stringr or stringi, R provides ... Continue reading: Mastering Character Counting in R: Base R, stringr, and stringi http://dlvr.it/TBlHT0

I developed this dashboard to allow users to explore and compare key social, economic, environmental, and institutional indicators for different countries. Users can select one or more countries and retrieve the most recent data on these indicators fr... Continue reading: Exploring Key Social, Economic, Environmental, and Institutional Indicators http://dlvr.it/TBlHDc

Hey guys, welcome back to my R-tips newsletter. Today I’m introducing GWalkR: An R package for Exploratory Data Analysis in 1 line of code. Just like Tableau. But Costs $0 (100% free). Let’s go! Table of Contents Here’s what you’re learning today: ... Continue reading: Tableau in R for $0 (Introducing GWalkR) http://dlvr.it/TBjcr8

We are pleased to announce the full line-up for this year’s Shiny in Production conference! This year, we’re introducing a new lightning talk session. These short 5 minute talks will allow us to showcase many more uses of Shiny in Production. The conference will still feature 6 full length talks, ... Continue reading: Shiny in Production 2024: Full speaker lineup http://dlvr.it/TBh8pR

Introduction Welcome to another exciting blog post where we walk into the world of R programming. Today, we’re going to explore how to check if a string contains specific characters using three different approaches: base R, stringr, and stringi... Continue reading: How to Check if a String Contains Specific Characters in R: A Comprehensive Guide with Base R, string & stringi http://dlvr.it/TBgHlB

Introduction In the world of data analysis and automation, Excel and R are powerful tools that can work in tandem to streamline workflows. One common task is to check if a specific Excel workbook is open. This can be done using VBA (Visual Basi... Continue reading: Checking If a Workbook is Open Using VBA and Executing from R http://dlvr.it/TBgHXD

#201–206PuzzlesAuthor: ExcelBIAll files (xlsx with puzzle and R with solution) for each and every puzzle are available on my Github. Enjoy.Puzzle #201We need to find out which customer had opportunity to buy specific product (and maybe bought). We rece... Continue reading: PowerQuery Puzzle solved with R http://dlvr.it/TBcvmp

The Bank of Japan has raised the interest rates and Nikkei has crushed the worst since the Black Monday crash of October 1987. The S&P 500 and DAX have declined similarly, but the DAX has performed slightly better. Continue reading: Black Monday Crash http://dlvr.it/TBcvKB

Recently Yanina Bellini Saibene reminded us to update our Slack profile: Friendly reminder: Let’s increase the value of our rOpenSci Slack community. Please add details to your profile, e.g., your photo, your favorite social media handle, what ... Continue reading: Git Tricks for Working with Large Repositories http://dlvr.it/TBctyt

Introduction Greetings, useR! Today, we’re exploring a handy function from base R that will help with string manipulation: toupper(). This little function is the complement to tolower() which I have previously written about. Let’s take a look! ... Continue reading: Converting Text to Uppercase with toupper() in R http://dlvr.it/TBZSTL

In our last article, we explored the S4 OOP system in R. Up until this point, we had only discussed functional OOP systems in R. Today, we are going to learn about two encapsulated OOP systems available for R: Reference Classes –  introduced to R in 2010 in version 2.12.0 (source). Sometimes also ... Continue reading: Object Oriented Programming in R (Part 4): Reference Classes & R6 Classes http://dlvr.it/TBZ3LX

Introduction In this post, we will explore systematic sampling in R using base R functions. Systematic sampling is a technique where you select every (k^{th}) element from a list or dataset. This method is straightforward and useful when you wa... Continue reading: Systematic Sampleing in R with Base R http://dlvr.it/TBWznT

Auto XGBoost, Auto LighGBM, Auto CatBoost, Auto GradientBoosting Continue reading: Auto XGBoost, Auto LighGBM, Auto CatBoost, Auto GradientBoosting http://dlvr.it/TBWbCR

This is just a post to brag about that the CopenhagenR useR group is alive and kicking, again. After COVID-19, the group (like so many other meetups) was on hiatus for a couple of years and without an organizer. In 2023, I thought I would try sta... Continue reading: CopenhagenR, the 2024 spring season http://dlvr.it/TBVsvR

PharmaRUG, China organizer Joe Zhu, spoke with the R Consortium about the growing R community and the increasing use of R in the pharmaceutical industry in China. The group has... The post Pharma RUG: The Rise of R in China’s Pharmaceutical Industry appeared first on R Consortium. Continue reading: Pharma RUG: The Rise of R in China’s Pharmaceutical Industry http://dlvr.it/TBVsbw

Introduction As a blogger who uses R for content creation, I’ve found it incredibly useful to automate some of the repetitive tasks. One such task is creating Quarto Markdown (QMD) files for new blog posts. To simplify this, I’ve added a custom... Continue reading: Automate Your Blog Workflow with a Custom R Function: Creating QMD Files http://dlvr.it/TBVsKp

Richard Layton recently shared a neat article: A subtle flaw in pull(). This is the usual loss of reliable programmable semantics just to avoid a few quote marks (at the cost of many more force eval and paste marks). It is well considered and well writ... Continue reading: Pulling a Loose Thread on Pull() http://dlvr.it/TBSKfC

The post Filter a Vector in R appeared first on Data Science Tutorials Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials. Filter a Vector in R is a fundamental skill that can be applied to a wide range of data analysis tasks. In ... Continue reading: Filter a Vector in R http://dlvr.it/TBSKVn

Motivation Coarse data Simulated example Real data example References Motivation A group of researchers from the Data Science Institute (DSI) at Hasselt University developed a new statistical model to estimate the incubation period of a pathogenic organism based on coarse data. The incubation period of an infectious disease (defined as ... Continue reading: EpiLPS for estimation of incubation times http://dlvr.it/TBSKLj

The R Consortium is pleased to announce that Katherine Jeschke has been appointed Chair of the Grants Committee. She will oversee day-to-day grant processes for both pre- and post-awards, ensuring... The post R Consortium Grants Committee Announces New Chair appeared first on R Consortium. Continue reading: R Consortium Grants Committee Announces New Chair http://dlvr.it/TBS5KK

Summary In the current version of dplyr, if x is not a column name in data frame d, then pull(d, x) attempts to look up the value of x in the environment instead of returning NULL or an error. There are ways to augment pull() to yield the exp... Continue reading: A subtle flaw in pull() http://dlvr.it/TBS58p