الدوري الممتاز الهندي 2020

Last week we started out building the Google Analytics Dashboard for my blog. This week we are continuing with adding some functionality to the UI with a bit of JavaScript. I am going through the complete application on YouTube Part 1 is on YouTube and my GitHub We added panels with ... Continue reading: Building a Google Analytics Dashboard With R Shiny From Scratch – Part 2 http://dlvr.it/SXZLNC

The post Top 10 online data science programs appeared first on Data Science Tutorials Top 10 online data science programs, Are you trying to find the best data science courses available online? If so, you are in the proper location. The Top Online Data Science Programs are listed in this article. There ... Continue reading: Top 10 online data science programs http://dlvr.it/SXZ4Bv

SAS is losing its footing across industries due to the rise of Shiny, an R package giving users bespoke interactivity on top of their R routines. In this article, we’ll discuss SAS vs R Programming in the context of the pharmaceutical industry, but the topic of conversation applies to ... Continue reading: SAS vs R Programming: Which to Choose and How to Switch http://dlvr.it/SXVvF5

Introduction to using Git & GitHub with RStudio for MS (Business Analytics) Class of Fall 2022 Continue reading: Using GitHub with RStudio http://dlvr.it/SXT1xc

Really, the only problem with the simstudy package (😄) is that there is a hard limit to the possible probability distributions that are available (the current count is 15 - see here for a complete description). However, it turns out that there is mo... Continue reading: Flexible simulation in simstudy with customized distribution functions http://dlvr.it/SXSbXQ

A zorbing puzzle from the Riddler: cover the plane with four non-intersecting disks of radius one towards getting the highest probability (under the standard bivariate Normal distribution). As I could not see a simple connection between the disks and the standard Normal, beyond the probability of a disk being given ... Continue reading: optimal Gaussian zorbing http://dlvr.it/SXSbLq

Introduction to R Markdown for MS (Business Analytics) Class of Fall 2022 Continue reading: Up and Running with R Markdown http://dlvr.it/SXS102

Introduction The previous post showcases the rrapply() function in the minimal rrapply-package as a revised and extended version of base rapply() in the context of nested list recursion in R. For quick data exploration of a nested list it can make sense to keep the list in its original nested ... Continue reading: Efficient list melting and unnesting with {rrapply} http://dlvr.it/SXQS7w

The post How to Get a Job as a Data Engineer? appeared first on Data Science Tutorials How to Get a Job as a Data Engineer?, The study of data engineering is fascinating. You get to collaborate with numerous teams of data professionals and subject matter experts, as well as ... Continue reading: How to Get a Job as a Data Engineer? http://dlvr.it/SXPFS7

Github is collecting various images on their Instagram and Twitter that looks like a contribution graph. Well, why not create one in R with randomly generated data and the use of the ggplot library. Run the function by yourself: And…Read more › Continue reading: Little useless-useful R functions – Drawing randomly generated @Github contribution graph http://dlvr.it/SXNnz1

The post Python is superior to R for writing quality codes appeared first on finnstats. If you are interested to learn more about data science, you can find more articles here finnstats. Python is superior to R for writing quality codes!. R is good for short and dirty analysis, but ... Continue reading: Python is superior to R for writing quality codes http://dlvr.it/SXNFD6

The post What is the bias variance tradeoff? appeared first on Data Science Tutorials What is the bias-variance tradeoff? The bias-variance tradeoff is a crucial idea in supervised machine learning and predictive modeling, regardless of the situation. There are many supervised machine learning models from which to pick when training ... Continue reading: What is the bias variance tradeoff? http://dlvr.it/SXMwkp

During the last 5 years, I have accumulated various scripts with (personal) convenience functions for network analysis and I also implemented new methods from time to time which I could not find in any other package in R. The package netUtils gathers all these functions and makes them available for anyone ... Continue reading: Extending network analysis in R with netUtils http://dlvr.it/SXLlrv

Are spot market natural gas prices in Europe mainly determined by the available world-wide LNG supply or does a bottleneck in the number of usable European LNG terminals increase prices to even substantially higher levels? To get some insight into this... Continue reading: Natural Gas Prices for main Hubs in Europe, Asia, and US http://dlvr.it/SXLBJb

The post How to handle Imbalanced Data? appeared first on Data Science Tutorials How to handle Imbalanced Data?, What do datasets from industries like real-time marketing bidding, network intrusion detection, and fraud detection in banking have in common? Less than 1% of infrequent but “interesting” events are frequently included in the ... Continue reading: How to handle Imbalanced Data? http://dlvr.it/SXKs6F

I have a new short writeup, showing common R design patterns, implemented side-by-side in base-R and Tidy. As readers of this blog know, I strongly believe that Tidy is a poor tool for teaching R learners who have no coding background. Relative to learning in a base-R environment, learners using ... Continue reading: Base-R and Tidyverse Code, Side-by-Side http://dlvr.it/SXJlZR

Standard Kernel SHAP has arrived in R. We show how well it plays together with deep learning in Keras Continue reading: Kernel SHAP http://dlvr.it/SWXhs6

It’s easy to get down the basics of R and Shiny, but the learning curve becomes significantly steeper after a point. Reactive values? Reactive events? Reactive observers? Let’s face it – it’s easy to get lost. We’re here to help. Today you’ll learn all about the ... Continue reading: Observe Function in R Shiny – How to Implement a Reactive Observer http://dlvr.it/SWTlgl

I’ve just added data on schools in England to the {blimey} package. The raw data were obtained from gov.uk. Continue reading: Schools in England http://dlvr.it/SWSZLZ

George Ostrouchov, one of R’s top parallel computing experts, will run a workshop on cluster parallel computing in R next week. BTW, even a multicore laptop is a “cluster,” so anyone can apply this material to their own work even if ... Continue reading: Valuable Webinar in Parallel Computing in R http://dlvr.it/SWS28Y

Some poetry for the programmers Blest be the day, and blest be the month and year, Season and hour and very moment blest, The lovely IDE where first possessed By two percent signs I found me prisoner; (…) Francesco Petrarch, Sonnet 61. Translated by Joseph Auslander. Possibly with some spicing it up ... Continue reading: Sonnet to infix function http://dlvr.it/SWPF3B

In the last post, we used the qualtRics1 package to import survey data directly from Qualtrics accounts. I often use Qualtrics for survey data collected via Amazon’s Mechanical Turk, which is an automated system that connects online respondents to pai... Continue reading: Working with Qualtrics Data – Part 2: Excluding Data http://dlvr.it/SWM68j

This is a short post on how to count your followers on Kaggle, and who the current Kagglers are with the largest following. It also serves as preparation for my next blog post in which I will practice some network analysis on the table that we’ll create in this ... Continue reading: Counting Kaggle Followers through Meta Kaggle http://dlvr.it/SWLpBN

Learn how to develop from scratch an interactive web interface in R shiny on August 31st. Shiny is the ever more popular approach to share R work, especially to business users without a technical background, that are required to make data-driven dec... Continue reading: ‘Build your first Shiny App’ with us http://dlvr.it/SWLPsn

Summary A common task when working with transcriptomic data is the identification of differentially expressed (DE) genes or tags between groups. In this tutorial participants will learn how to perform biostatistical analysis with edgeR, including pairwise and analysis of variance (ANOVA) like comparisons to identify significantly DE genes. Questions What ... Continue reading: Downstream Bioinformatics Analysis of Omics Data with edgeR http://dlvr.it/SWKx3f

Trying to simulate data with non-linear relationships can be frustrating, since there is not always an obvious mathematical expression that will give you the shape you are looking for. I’ve come up with a relatively simple solution for somewhat comp... Continue reading: Simulating data from a non-linear function by specifying a handful of points http://dlvr.it/SWJQWC

What a week! Thank you for a fantastic rstudio::conf(2022). It was so exciting to learn and share with you during these eventful four days. This post will share some of the big announcements from RStudio. We will highlight amazing packages, resources, ... Continue reading: Four announcements from rstudio::conf(2022) http://dlvr.it/SWHny2

The Shiny app below allows to attribute a label to the points of a ‘ggplot’ by double-clicking on the points. library(shiny) library(rhandsontable) library(htmlwidgets) library(colourpicker) library... Continue reading: Labelling the points of a ‘ggplot’ with Shiny http://dlvr.it/SWHTxT

Introduction Recently, RStudio announced its name change to Posit. For many this name change was accepted with open arms, but for some-not so. Being the statistician that I am I decided to post a poll on LinkedIn to see the sentiment of my network. After running the poll for a ... Continue reading: RObservations # 36: Opinions on RStudio’s name change. A Bayesian approach with Stan http://dlvr.it/SWFXjN

I’m building a model which requires historical weather data from a selection of locations in South Africa. In this post I demonstrate the process of acquiring the data and doing some simple processing. Continue reading: Historical Weather Data http://dlvr.it/SWCPRF

As many readers of this blog know, I strongly believe that R learners should be taught base-R, not the tidyverse. Eventually the students may settle on using a mix of the two paradigms, but at the learning stage they will benefit from the fact that base-R is simple and more ... Continue reading: Base-R Is Alive and Well http://dlvr.it/SWBmdk

Many studies suggest that white, pink and brown noise can improve focus, help with relaxation and sleep and even reduce crying in babies. Due to these potential benefits many options are available to generate color noise, including sound machines, p... Continue reading: Generate hours of white, pink and brown noise in R http://dlvr.it/SW9WWf

Getting started with insertion sort The insertion sort algorithm works by constructing a sorted vector one element at a time: First element: a vector with one element is already trivially sorted. Second element: if the second element is less than ... Continue reading: How to write insertion sort in R http://dlvr.it/SW6tpf

From time to time we all need some fun, so why not make some funny graphs since we are R users, yeah! This post is based on the tutorials on R CHARTS, do not forget to pick a look. Bar dogs First I want to show you how to add ... Continue reading: Getting fun with ggdogs, ggcats and gganimate http://dlvr.it/SW53QT

Origins of deepdep Separation of woodendesc A new package is not always the answer Modularization of tidysq Summary “Would it be possible…?”, “I think it would be nice if…”, “Can you implement…?”. User feedback is a reliable source of valuable i... Continue reading: Case Study: Modularizing a Package http://dlvr.it/SW4Sgj

The post How to Scale Only Numeric Columns in R appeared first on Data Science Tutorials How to Scale Only Numeric Columns in R, To scale only the numeric columns in a data frame in R, use the dplyr package’s following syntax. Best Books to learn Tensorflow – Data Science ... Continue reading: How to Scale Only Numeric Columns in R http://dlvr.it/SW44ht

Quarto is next generation R Markdown that brings interactivity to documents using widgets, Observable, and Shiny. Let's see how to add server side execution to your Docker containers. Continue reading: How to Set Up Quarto with Docker, Part 2: Dynamic Content http://dlvr.it/SW3bz2

Te ayudaré a entender los fundamentos de R de manera que contribuya a tu trabajo diario. Puedes ver mi portafolio/CV en mi sitio pacha.dev. Si tienes conocimientos de hojas de cálculo, también te mostraré cómo aplicar estos conocimientos a la escrit... Continue reading: Capacitación R para LATAM, 4 clases (con descuento) http://dlvr.it/SW2XNS

Example 1: Concatenate a Vector of Strings Using cat() in R # create a vector with string values vector1 Continue reading: R Program to Concatenate a Vector of Strings http://dlvr.it/SW1Sc1

Originally posted in the RStudio R Community blog, written by Dr. Maria Prokofieva, professor, Victoria University Business School, Australia, and works with CPA Australia. Dr. Prokofieva is a member of... The post From the R Business Working Group – R is for actuaRies appeared first on R Consortium. Continue reading: From the R Business Working Group – R is for actuaRies http://dlvr.it/SW0n7l

Here we will be using the %in% operator match() function any() function. Example 1: Check if Element Exists in R Vector Using %in% # create two strings vowel_letters Continue reading: R Program to Check if a Vector Contains the Given Element http://dlvr.it/SW0JLb

The online survey system Qualtrics can be a great way to collect data from research participants, customers, and stakeholders. I use it frequently to conduct research studies with participants or just to poll students and collaborators. However, while... Continue reading: Working with Qualtrics Data – Part 1: Importing Data http://dlvr.it/SVynMW

Example: Find Statistical Model in R # create a vector of marks1 marks1 Continue reading: R Program to Find the Statistical Mode http://dlvr.it/SVxqcX

Where it all began Sometimes it takes just a passing comment to inspire a mountain of change. For this effort, it began with a discussion focused around addressing “confusing status differences on the homepage.” A greater collection of issu... Continue reading: Workbench Session Information Improvements http://dlvr.it/SVxRw6

Example 1: Write a Sentence to txt File in R sentence1 Continue reading: R Program to Write to a File http://dlvr.it/SVwyPH

Use a Script Monkey in your codebase at all locations where you need to change things manually. All that involves is writing an extra comment saying ‘Script Monkey’. Later on, search for all monkeys in the script and make the changes. Simple. Continue reading: Script monkey! 🐒 http://dlvr.it/SVvtbL

Color Scales Create Legend for a Continuous Scale Create Legend for Quantiles Create Legend for Bins and Change Legend Symbol Create Legend for Factors and Re-order Symbols and Size Scales Legend and Points with Size Encoding Legend and Points with Double Encoding Legend and Points with Size and Color Encoding ... Continue reading: leaflegend Recipes http://dlvr.it/SVvRcG

It was amazing to meet so many people at the RStudio Conference last week. If you’d like to keep the party going and are thinking of ways to keep in touch with people you met at talks, Birds of a Feather sessions, or just walking around the hallways (i... Continue reading: Keep the party going after rstudio::conf http://dlvr.it/SVtWpV

Concatenate means joining multiple strings into one. In R, we use the paste() function to concatenate two or more strings. Example 1: Concatenate Strings in R # create two strings string1 Continue reading: R Program to Concatenate Two Strings http://dlvr.it/SVt9Ww