الدوري الممتاز الهندي 2020

This is part one of a three part series on Lighthouse for Shiny Apps. Part 1: Using Google Lighthouse for Web Pages (This post) Part 2: Analysing Shiny App start-up Times with Google Lighthouse (Coming soon) Part 3: Analysing Shiny App Component... Continue reading: Using Google Lighthouse for Web Pages http://dlvr.it/SzXw74

Mark Padgham, a Software Research Scientist for rOpenSci, has decades of experience in R, C, and C++, and maintains many packages on CRAN. Mark is leading the development of the... The post deposits R Package Delivers a Common Workflow for R Users appeared first on R Consortium. Continue reading: deposits R Package Delivers a Common Workflow for R Users http://dlvr.it/SzXvzP

R/Shiny allows you to prototype a working web application quickly and easily. However, with increasing amounts of data, your app may become slow and, in extreme cases, crash due to insufficient memory. When the worst-case scenario happens, we need to figure out a way to lower the memory usage ... Continue reading: Maximizing Efficiency: A Guide to Benchmarking Memory Usage in Shiny Apps http://dlvr.it/SzXvsR

The Importance of Error HandlingIn the multifaceted world of R programming, particularly when navigating the intricate paths of data analysis, robust error handling is not merely a precaution; it’s an essential pillar of reliable and trustworthy code development. Picture this: you’re deep into a complex data analysis task, ... Continue reading: Catch Me If You Can: Exception Handling in R http://dlvr.it/SzXh6N

We’ve both coincidentally dipped our toes in the wonderful world of pretty messaging with cli. cli::cli_alert_success("marvellous package adopted!") #__ ✔ marvellous package adopted! In this post, we transform the hurdles we encountered in a... Continue reading: Cliff notes about the cli package http://dlvr.it/SzWd68

Today dqrng version 0.3.2 made it unto CRAN and is now propagating to the mirrors. In addition tikzDevice version 0.12.6 made it unto CRAN as well. Both releases are minor bug fixes triggered by a new WARN on CRAN. Recently the development version of R... Continue reading: Bug fixes for dqrng and tikzDevice http://dlvr.it/SzVNPW

One important aspect of rOpenSci’s mission is to build capacity and promote passionate community members who help the open science and open source software community grow and improve. The rOpenSci Champions Program is a unique opportunity for us... Continue reading: Introducing rOpenSci Mentors – Cohort 2023-2024 http://dlvr.it/SzVNGc

One in a Million – CC-BY-NC by Thomas Hawk Day 29 of 30DayMapChallenge: « Population » (previously). Setup library(tidyverse) library(sf) library(glue) library(sfdep) Data French administrative units (régions, département... Continue reading: Spatial autocorrelation http://dlvr.it/SzShjF

The data.table 2023 user community survey is here, open until December 1st. Continue reading: data.table User Survey http://dlvr.it/SzSh64

All of our public training courses for the first half of 2024 are now open for registration! Head over to the public courses page on our website to book in and start building your programming skills in the new year! Below is a list of all of our ... Continue reading: Training Lineup for 2024: January-June http://dlvr.it/SzSKmc

Introduction If you’re familiar with linear regression in R, you’ve probably encountered the traditional lm() function. While this is a powerful tool, it might not be the best choice when dealing with outliers or influential observations. In suc... Continue reading: Understanding and Implementing Robust Regression in R http://dlvr.it/SzQwpc

Uselessness is such a long useless word! In statistics, R-squared is a statistical measure, that determines the proportion of variance in dependent variable that can be explained by the independent variable. Therefore, it ranges in value from 0 to 1…Read more › Continue reading: Little useless-useful R functions – How to make R-squared useless http://dlvr.it/SzPm3M

Week 47 — Puzzles no. 329–333PuzzlesAuthor: ExcelBIPuzzles:# 329: content file# 330: content file# 331: content file# 332: content file# 333: content fileLets dive into solutions!Puzzle 329In this puzzle we were asked to generate first 50 elements of I... Continue reading: R Solution for Excel Puzzles http://dlvr.it/SzPlmL

Abstract: Join us on November 28th for our last Community meeting of 2023. The R Validation Hub’s Executive Committee will summarize this year’s achievements, our presence at conferences and other... The post R Validation Hub: Wrapping up 2023 and Welcoming 2024! appeared first on R Consortium. Continue reading: R Validation Hub: Wrapping up 2023 and Welcoming 2024! http://dlvr.it/SzPlVP

Machine Learning Classification with quasi-randomized nnetworks in Julia, Python and R Continue reading: Quasi-randomized nnetworks in Julia, Python and R http://dlvr.it/SzPl5P

Mount Fuji sunrise – CC-BY-NC-ND by Gilbert Sopakuwa Day 23 of 30DayMapChallenge: « 3D » (previously). The Tanaka contours (Tanaka 1950) are a method of displaying 3D as a succession of terraces. library(elevatr) library(terr... Continue reading: Tanaka http://dlvr.it/SzLqP2

The introduction of innovative tools like Shiny and Quarto has empowered researchers and data scientists to transform complex data into interactive and insightful reports. This progress is not just an improvement in data visualization but a significant leap towards a new paradigm in clinical research. In this article, we’ll ... Continue reading: Revolutionizing Clinical Research with Interactive Reports: Shiny and Quarto in Action http://dlvr.it/SzLqGs

The Journey to OOP in RIn the world of programming, embarking on the path of Object-Oriented Programming (OOP) is akin to boarding a high-speed train towards more structured, efficient, and maintainable code. As we continue our series, our next stop is... Continue reading: Object-Oriented Express: Refactoring in R http://dlvr.it/SzLq9J

Join our workshop on Using ChatGPT for Exploratory Data Analysis with Python, R and prompting, which is a part of our workshops for Ukraine series!  Here’s some more info:  Title:Using ChatGPT for Exploratory Data Analysis with Python, R and prompting Date: Thursday, November 30th, 18:00 – 20:00 CET (Rome, Berlin, Paris ... Continue reading: Using ChatGPT for Exploratory Data Analysis with Python, R and prompting workshop http://dlvr.it/SzLq34

Abstract / TLDR R-universe now builds WASM binaries of all R packages for use in WebR applications (such as shinylive). For example to test the dev version of dplyr, you can open the WebR demo page and run: install.packages('dplyr', repos = c(' https://tidyverse.r-universe.dev', ' https://repo.r-wasm.org')) /> ... Continue reading: R-universe now builds WASM binaries for all R packages http://dlvr.it/Sz0xCh

Do you often find yourself developing an R/Shiny dashboard and wish you knew how your users were using the dashboard, which views are being used the most and how inputs are being modified? If so, the {shiny.telemetry} R package might be just what you’re looking for. In ... Continue reading: {shiny.telemetry}: Enhanced User Behavior Analytics in R/Shiny Dashboards http://dlvr.it/Syyzkg

New Features: Unlocking More Power My R package {healthyR.ts} has been updated to version 0.3.0; you can install it from either CRAN, r-universe or GitHub. Let’s go over some of the changes and improvements. News 1. util_log_ts() - Logging Ti... Continue reading: {healthyR.ts} New Features: Unlocking More Power http://dlvr.it/SyxqZ0

This blog post contributed by Mouna Belaid, on behalf of the R-Ladies Paris team We were delighted to host a recent hybrid event called Feedback from Experiences in Data Science... The post Highlights from R-Ladies Paris Hybrid Meetup Empowering Community Outreach appeared first on R Consortium. Continue reading: Highlights from R-Ladies Paris Hybrid Meetup Empowering Community Outreach http://dlvr.it/Syx6Vh

My colleague Chung-hong Chan started a new package in our teams GitHub organization. An issue there caught my attention. The performance was very slow of the main function. The issue lay somewhere in the auxiliary functions. This lead me down quite ... Continue reading: Efficient row min calculation: From R to C http://dlvr.it/Syx6Dd

The Need for Speed in RIn the realm of data science, where the landscape is ever-changing and data volumes are incessantly swelling, speed and efficiency in processing aren’t mere conveniences — they’re indispensable. As we unveil the second chapter of our series, we turn the spotlight onto a crucial ... Continue reading: The Fast and the Curious: Optimizing R http://dlvr.it/SywV7B

As the reliance on data intensifies, the need for efficient and effective data analysis methods has never been greater. This article delves into the world of functional programming in R, a paradigm that offers a refreshing and powerful way to handle data analysis tasks. We will compare functional programming techniques ... Continue reading: Unlocking the Power of Functional Programming in R (Part 3): Advanced Techniques & Practical Applications http://dlvr.it/SywTtW

Bleeding Heart – CC-BY by Theo Crazzolara Day 15 of 30DayMapChallenge: « OpenStreetMap » (previously). Using data from OSM we’ll make a web map of defibrillators (AED) in Auvergne-Rhône-Alpes. library(tidyverse) library(sf) library(osmdata) library(glue) library(leaflet) library(htmltools) We send an Overpass API query with {osmdata}: # France regions # See ... Continue reading: Defibrillator from OSM http://dlvr.it/SytfCY

Introduction Multiple linear regression is a powerful statistical method that allows us to examine the relationship between a dependent variable and multiple independent variables. Example Step 1: Load the dataset # Load the mtcars dataset da... Continue reading: How to Perform Multiple Linear Regression in R http://dlvr.it/Sytf35

Discovering 18th century London with new fonts Greetings, humanists, social and data scientists! In this lesson, we delve into the world of data visualization with a focus on the use of different fonts in ggplot2. We are going to learn how to t... Continue reading: How to Change Fonts in ggplot2 with Google Fonts http://dlvr.it/Sytdpp

Join our workshop on  Introduction to mixed frequency data models in R, which is a part of our workshops for Ukraine series!  Here’s some more info:  Title: Introduction to mixed frequency data models in R Date: Thursday, December 14th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) Speaker:Jonas Striaukas, Jonas is ... Continue reading: Introduction to mixed frequency data models in R workshop http://dlvr.it/Sysgjf

Harnessing the coastal winds – CC-BY-NC-ND by Wayne S. Grazio Day 14 of 30DayMapChallenge: « Europe » (previously). Using data from Eurostat we will try to show the spatio-temporal properties of this dataset by placing plots o... Continue reading: Renewable energy in Europe http://dlvr.it/SyrNgr

Introduction Regression models are a powerful tool for predicting future values based on historical data. They are used in a wide range of industries, including finance, healthcare, and marketing. In this blog post, we will learn how to predict ... Continue reading: How to Predict a Single Value Using a Regression Model in R http://dlvr.it/SyqfTj

R Consortium recently talked to Sam Parmar of the Indy UseR group about using R in public health and pharma in Indianapolis. Sam also spoke about his volunteer work with... The post Dive Into R: Collaborate with the Indy UserR Group as a Newsletter Contributor! appeared first on R Consortium. Continue reading: Dive Into R: Collaborate with the Indy UserR Group as a Newsletter Contributor! http://dlvr.it/SynyfX

Introduction Prediction intervals are a powerful tool for understanding the uncertainty of your predictions. They allow you to specify a range of values within which you are confident that the true value will fall. This can be useful for many ta... Continue reading: Unlocking the Power of Prediction Intervals in R: A Practical Guide http://dlvr.it/SynyV6

New arXiv working paper showing how generalized linear mixed effects model (GLMM) trees, along with their R implementation in the glmertree package, can be used to identify subgroups with differently shaped trajectories in linear growth curve... Continue reading: Subgroup detection in linear growth curve models http://dlvr.it/SynyLC

Zhenguo Zhang's Blog /2023/11/11/r-tidy-evaluation-in-ggplot2-part-2/ - knitr::opts_chunk$set(echo=T, fig.align = "center", fig.width = 6, fig.height = 5, dpi=150, warning=FALSE) library(knitr) library(ggplot2) How to use variables to refe... Continue reading: [R] tidy evaluation in ggplot2 (part 2) http://dlvr.it/Sym5zR

I have been lately noticing a glaring trend in some of the non-fiction books that I read: the use and abuse of verbatim quotes. They come in the shape of: “As such and such said: INSERT LONG VERBATIM TEXT HERE” Of course, there are no rules regarding the use of ... Continue reading: Original Text http://dlvr.it/Sym5lT

I had thought most folks likely knew this already, but if you are user of RStudio dailies (this may apply to regular RStudio, but I only use the dailies) and are missing ligatures in the editor (for some fonts), the “fix” is pretty simple (some misguided folks think ligatures are ... Continue reading: Ligatures In RStudio Dailies http://dlvr.it/SykpRC

nnetsauce version 0.15.0, an example of a deep-layered classifier calibrated with Automated Machine Learning (AutoML) Continue reading: A classifier that’s very accurate (and deep) http://dlvr.it/SykpDL

Piedra de Culimacare on the Rio Casiquiare – CC-BY-NC-ND by Carsten ten Brink Day 12 of 30DayMapChallenge: « South America » (previously). Do you know you can circumnavigate the Guiana shield? There is a river, the Rio Casiqui... Continue reading: Casiquiare http://dlvr.it/SykJG9

Roman Road Through Pompeii – CC-BY-NC-ND by cliff hellis Day 11 of 30DayMapChallenge: « Retro » (previously). Using data from Ancient World Mapping Center we map the Roman road network. library(tidyverse) library(sf) library(rnatu... Continue reading: Old map http://dlvr.it/SyjPzQ

When do the two methods agree? When not? Continue reading: Permutation SHAP versus Kernel SHAP http://dlvr.it/Syj9Cb

Users of ggplot2 often run into issues with their saved graphics not having the expected resolution or font sizes. By default, when using RStudio, ggsave() saves graphics at the last dimensions of the plot preview pane and at screen resolution. As a demo, try Then resize the plot preview pane ... Continue reading: Save ggplot Graphics at Intended End-use Dimensions and Resolutions for Best Results http://dlvr.it/SygqSw

Just sharing some teaching materials which might be useful. In the Department of Biology at the University of York in the UK, we teach Data Analysis in R from stage 1 to over 400 students. There are “Becoming a Bioscientist” modules in each of semester of the first two years. These are ... Continue reading: Data Analysis in R for Becoming a Bioscientist http://dlvr.it/Syf40y

Slide, Scan, Sum — Find the largestExcel BI’s Excel Challenge #320 — solved in RDefining the Puzzle:Current puzzle seems not hard, need few minutes to solve. Our host gave us sequence of numbers, both positive and negative and ask to find largest sum i... Continue reading: Slide, Scan, Sum — Find the largest http://dlvr.it/Syf3gn

Excel BI’s Excel Challenge #322— solved in RDefining the Puzzle:Let’s talk about money. We have list of employees, and their salaries. We have to find who’s salaries are closest to average of this list.Find the top 3 employees whose salary is nearest t... Continue reading: Most average payed employees http://dlvr.it/Sycr7X

Let’s be honest – all of your R Shiny app logic is contained in a single app.R file, and it’s probably several hundreds of lines long. No judgment – we’ve all been there. But there’s a better way, and today you’ll learn all about it. R ... Continue reading: R Shiny Modules: How to Create Your First R Shiny Module http://dlvr.it/Syb2wx

Introduction Welcome to the fascinating world of bivariate normal distributions! In this blog post, we’ll embark on a journey to understand, simulate, and visualize these distributions using the powerful R programming language. Whether you’re a ... Continue reading: How to Simulate & Plot a Bivariate Normal Distribution in R: A Hands-on Guide http://dlvr.it/Syb2lg

Setting the Scene with Data QualityIn the multifaceted realm of data science, ‘quality’ isn’t just a desirable attribute, it’s the bedrock upon which all subsequent analysis is built. Think of it as the foundation of a house. Without a solid base, no matter how grand your designs or ... Continue reading: The Function Begins http://dlvr.it/SyYqsJ

I just wrote a post about grouped sequences in dplyr and following that, I’ve been made aware of another couple of solutions to this problem (credit John Mackintosh). The solution involves using the consecutive_id() function, available in dplyr sinc... Continue reading: Grouped Sequences in dplyr Part 2 http://dlvr.it/SyXQWk

Excel BI’s Excel Challenge #316 — solved in RDefining the Puzzle:Probably everyone of us have heard of Fibonacci Numbers. It is a sequence that property is that next number is a sum of two previous. But this time ExcelBI asked us to generate… first 20 ... Continue reading: Even Fibonacci numbers http://dlvr.it/SyXQP6

Excel BI’s Excel Challenge #318 — solved in RDefining the Puzzle:Now we are asked to find sum of small series which value and number depends on input number itself. Sounds weird but it was suprisingly easy and nice.Find the Sum of the Series — 1*2*3 + ... Continue reading: Sum of Series http://dlvr.it/SyWCzb

Excel BI’s Excel Challenge #317 — solved in RDefining the Puzzle:Today we are move single letters from starts to end of words. But with some exceptions.Swap the first and last letter of each words in given names. But if either first or last letter or b... Continue reading: Swap first and last… letter http://dlvr.it/SyWCgj

When odds are helpful Ratio of odds (odds ratio) Communicating odds Appendix Ratios and fractions of events Many variables Other problems We grow up learning proportions, percentages, risks, probabilities. You encounter them when a teacher gives a grade on a test or a doctor describes the risk of an illness. ... Continue reading: Odds Are You’re Using Probabilities to Describe Event Outcomes http://dlvr.it/SyWCNw

My sticky note filled up quickly after I only added setNames() on it, with related functions for dealing with object names, in base R and beyond! (Un)Setting object names: stats::setNames(), unname() and rlang::set_names() I noticed a function ending w... Continue reading: Useful functions for dealing with object names http://dlvr.it/SyTKqw

The R-Universe is used by professionals from different fields, although they all pursue the same objective: to offer their R packages in a simple and accessible way. At rOpenSci we work to provide tools that facilitate access to data and research soft... Continue reading: The rOpenSci Multiverse http://dlvr.it/SyTKcq

For a piece of work I had to calculate the number of matches that a team plays away from home in a row, which we will call days_on_the_road. I was not sure how to do this with dplyr but it’s basically a ‘grouped sequence’. For this ... Continue reading: Grouped Sequences in dplyr http://dlvr.it/SySbMw

I am dealing with nested data, and I remember from an article by Clark (1973) that nested should be analysed using special models. I’ve looked into mixed-effects models, and I’ve reached a structure with random intercepts by subjects and by items. ... Continue reading: FAQs on mixed-effects models http://dlvr.it/SySb2V

Notwithstanding the need for speed in most scientific projects, what should be the minimum acceptable standards in the creation of research materials such as stimuli, custom software for data collection (e.g., experiment in jsPsych, OpenSesame or psychoPy), or scripts for statistical analysis? The answer to this question is contingent ... Continue reading: FAIR standards for the creation of research materials, with examples http://dlvr.it/SySZf2

Statistical/Machine Learning with Python and R, using mlsauce's AdaOpt and LSBoost Continue reading: mlsauce version 0.8.10: Statistical/Machine Learning with Python and R http://dlvr.it/SyQYsc

We learned how to convert the pooled odds ratio from a random-effects model and subsequently calculate the number needed to treat (NNT) or harm (NNH). It’s important to understand that without knowing the event proportions in either the treatment or c... Continue reading: Calculating Number Needed to Treat/Harm (NNT/H) with Odds Ratio http://dlvr.it/SyQYjt

Guadeloupe – CC-BY-SA by SnippyHolloW Day 2 of 30DayMapChallenge: « Lines » (previously). Using data from Openstreetmap we will map the GR G1 trail (fr) crossing Guadeloupe. We could use {osmdata} (see this post), but in this case it’s easier to just grab a GPX file from Waymarked Trail (see the link in ... Continue reading: OSM Guadeloupe trail relation http://dlvr.it/SyNp0r

Join our workshop on Using ChatGPT for Exploratory Data Analysis with Python, R and prompting, which is a part of our workshops for Ukraine series!  Here’s some more info:  Title:Using ChatGPT for Exploratory Data Analysis with Python, R and prompting Date: Thursday, November 30th, 18:00 – 20:00 CET (Rome, Berlin, Paris ... Continue reading: Using ChatGPT for Exploratory Data Analysis with Python, R and prompting http://dlvr.it/SyNnqK

Introduction The gamma distribution is a continuous probability distribution that is often used to model waiting times or other positively skewed data. It is a two-parameter distribution, where the shape parameter controls the skewness of the di... Continue reading: Fitting a Distribution to Data in R http://dlvr.it/SyNnYX

Say you have data measured at different weather stations, which in Argentina might look something like this estaciones[data, on = c("nombre" = "station")] |__ ggplot(aes(lon, lat)) + geom_point(aes(color = t)) + geom_... Continue reading: Kriging with metR http://dlvr.it/SyNnKH

While preparing materials for teaching Git a few months ago, I re-read Suzan Baert’s excellent post about Git and GitHub, where she mentioned having read “Git in Practice” by Mike McQuaid. I added the book to my Momox alerts, where it... Continue reading: Reading notes on Git in Practice by Mike McQuaid http://dlvr.it/SyGxRW

AI in R and Python Greetings, humanists, social and data scientists! Welcome to this enlightening journey to extract historical data from the Web using AI! In this lesson, we delve into the innovative ways of harnessing the power of ChatGPT to ... Continue reading: Harnessing AI in R and Python – Gather data with ChatGPT http://dlvr.it/SyGwyh

Excel BI’s Excel Challenge #313 — solved in RDefining the Puzzle:Today we need to transform table into its cummulative (someway) version. Every column have to include content of column lagged by 2.Generate the result table.Here, Tn = T(n-2) & Tn wh... Continue reading: Cummulate and concatenate http://dlvr.it/SyGwYf

Excel BI’s Excel Challenge #312 — solved in RDefining the Puzzle:In current puzzle we need to check if digits of our numbers has some magic properties. Seems easy, but it is not usually the case, when ExcelBI prepare riddle.List all Sumproduct numbers ... Continue reading: Sumproduct number http://dlvr.it/SyGw8m

Excel BI’s Excel Challenge #314 — solved in RDefining the Puzzle:This puzzle is searching Atbash Palindrome.ATBASH Palindrome — In ATBASH cipher, we replace a with z, b with y, c with x…..y with b, z with a.Find those texts which are palindrome after d... Continue reading: Cypher and turn around- Atbash palindrome http://dlvr.it/SyDQxF