Publications by Anindya Mozumdar
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. As there may be hundreds of variables in the data, the user may want to process only a few variables in one sitting and later continue the wor...
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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. One change since the last article is that Cricsheet now has updated data available – so we have the details of all matches played up to 2019. The initial p...
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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. I was surprised to see that not much information is available based on a 10 minute Google search. The top StackOverflow question which comes up with a search for ‘r shiny splash scr...
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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. The material in the article is heavi...
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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. Following the link in his tweet, I learned that Springer has released 408 books in total, out of which 65 are related to the field of d...
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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. His script is provided below. He uses the rvest package and the %>% operator to keep it really short and simple. library(rvest) library(dplyr) library(stringr) list <- "https://towardsdatascience.com...
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