R

An update to "An adventure in downloading books"

I received an email from Bernardo Lares as feedback on my previous article. You can also view some of the other cool work done by him in this link.

An adventure in downloading books

Earlier today, I noticed a tweet from well known R community member Jozef Hajnala. The tweet was about Springer releasing around 65 books related to data science and machine learning for free to download as PDFs.

A guide to encoding categorical features using R

In this article, we will look at various options for encoding categorical features. We will also present R code for each of the encoding techniques. Categorical feature encoding is an important data processing step required for using these features in many statistical modelling and machine learning algorithms.

Shiny splash screen using modules and shinyjs

A while ago I was researching on creating a splash screen for a Shiny application. My gut feel was that there will readily be a package available for this activity.

Of Sixes and Fours - Analyzing the IPL using the tidyverse

We are back with another post on the Indian Premier League. This is the fourth post in the series. We will assume that you have already read the previous article analyzing strike rates here.

Shiny application (with modules) - Saving and Restoring from RDS

I am working on a Shiny application which allows the user to upload data, do some analysis and processing on each variable in the data, and finally use the processed variables to build a statistical model.

Fun with Statistics - Is Usain Bolt really the fastest man on earth?

If you search for the phrase “fastest man on earth” in Google, chances are that it will return the answer “Usain Bolt”. It certainly does so for me, even though the results might be different if Google decides to personalize the results for you.

Easily explore your data using the summarytools package

Whenever we start working with data with which we are not familiar, our first step is usually some kind of exploratory data analysis. We may look at the structure of the data using the str function, or use a tool like the RStudio Viewer to examine the data.

Analysing Strike Rates in the IPL using the tidyverse

In this article, we analyse the strike rates of the top batsmen in the Indian Premier League. We will use the tidyverse packages for the analysis, primarily dplyr and ggplot2.

R Vocabulary - Part 4

This is the fourth and final part in the series of articles on R vocabulary. In this series, we explore most of the functions mentioned in Chapter 2 of the book Advanced R.