We are excited to share this dataset publicly, to help bloggers who want to analyze COVID-19 data by unleashing R and the resources of its community by being able to research such posts.

How do we make heat-maps in R? A complete explanation on how to build heatmaps with R: how to use the heatmap() function, how to custom appearance, how to normalize data and more.

Create our data visualization more interactively. In this first post we will present a few examples using {leaflet}.

Twitter Data Visualization Using R. In this post I want to present a small case study where I analyze Twitter text data. Data exploration aims to get any information and insight from Twitter data.

Covid-19: Correlation Between Confirmed Cases and Deaths. After how many days we reach the Maximum Correlation between Confirmed (Covid-19) Cases and Deaths

Using XGBoost to predict hotel cancellations. An XGBoost model is built in R to predict incidences of customers cancelling their hotel booking. The analysis is based on data from Antonio, Almeida and Nunes (2019): Hotel booking demand datasets.

Estimate Pi With Monte Carlo. Example of how you can estimate Pi With Monte Carlo in four lines of code

Create professional web applications for your company. With this series, I share some advanced tips with the ambition to overcome these objections and to help you build robust/ sustainable/ scalable applications, ready for business usage in production!

The Patchwork Package In R: Patchwork is a package for the R programming language that simplifies data visualization layouts through a simple math-like syntax.

Learn to use if-else statements, for loops, and while loops to build complex conditional programs in R, a valuable skill for aspiring data scientists.

Data Visualization in R with ggplot2: A Beginner Tutorial. Learn to visualize your data using R and ggplot2 in this beginner-friendly tutorial that walks you through building a chart for data analysis.

Using The Predictive Power Score in R: Recently a post about Predictive Power Score attracted the attention of many data scientists. Let’s see what it is and how to use it in R.

Learn R programming for data analysis from right in your browser while writing real code and working with real data. Now, free for a limited time! Exciting news: for the next week, all of our R programming courses are free. In fact, every single course in our Data Analyst in R career path is free from July 20-27.

R is an increasingly popular programming language, particularly in the world of data analysis and data science. But learning R can be a frustrating challenge if you’re not sure how to approach it.

While Python and R used to be the two main go-to languages for data science, the former had been eclipsing the latter for some time. However, R appears to be making a strong comeback.

Pick up some top tips for learning R from Shelmith Kariuki, a certified Tidyverse instructor and a leader in the Africa R community.

Mortgage - This is one word that we hear every now and then all over the news, social media and newspapers and probably ponder about the rigorous math and calculations it entails.

An Analysis of Gender and Language in Songs on Spotify. Men and women are portrayed very differently in entertainment. The way they speak, how they are portrayed.

Do robust regressions always outperform OLS when analysing outliers? When it comes to regression analysis — outliers.

Get your R programming journey off on the right foot with this RStudio tutorial that walks through everything from installation to best practices.