R
Monthly Summary of Selected Trends, Activities and Insights for R – October 2018
Abstract In October, the spike in activities observed in September across the R ecosystem was maintained. In the following article, a summary of selected trends, activities, and insights around the R language in October, 2018, are presented as the R language keeps trending. Data for the trends and activities... Read more
How Tidyverse Guides R Programmers Through Data Science Workflows
Whenever someone asks me how to get into data science using R, I invariably recommend checking out the tidyverse package. Tidyverse is a great launch pad for a language like R because it offers order and consistency. I studied programming language design as a CS undergrad. At the time,... Read more
Build a Multi-Class Support Vector Machine in R
Support Vector Machines (SVMs) are quite popular in the data science community. Data scientists often use SVMs for classification tasks, and they tend to perform well in a variety of problem domains. An SVM performs classification tasks by constructing hyperplanes in a multidimensional space that separates cases of different... Read more
Monthly Summary of Selected Trends, Activities, and Insights for R – September 2018
In September, there was a serious spike in activities across the R ecosystem. This article examines a summary of selected R trends, activities, and insights in September. Data for the trends and activities summarized here were obtained from popular websites used by the R community such as Google, GitHub, StackOverflow,... Read more
Sentiment Analysis in R Made Simple
Sentiment analysis is located at the heart of natural language processing, text mining/analytics, and computational linguistics. It refers to any measurement technique by which subjective information is extracted from textual documents. In other words, it extracts the polarity of the expressed sentiment in a range spanning from positive to... Read more
An Introduction to Sentence-Level Sentiment Analysis with sentimentr
Sentiment analysis algorithms understand language word by word, estranged from context and word order. But our languages are subtle, nuanced, infinitely complex, and entangled with sentiment. They defy summaries cooked up by tallying the sentiment of constituent words. Unsophisticated sentiment analysis techniques calculate sentiment/polarity by matching words back to a... Read more
Monthly Summary of Selected Trends, Activities and Insights for R – August 2018
Data for the trends and activities summarized here were obtained from popular websites used by the R community such as Google, GitHub, StackOverflow, Rstudio, METACRAN and R-Bloggers StackOverflow Number of StackOverflow Questions tagged R: 4,565 (8%  down from July) Number of Answers for R questions: 4,630 (3%  up from... Read more
Snakes in a Package: Combining Python and R with Reticulate
When I first started working as a data scientist (or something like it) I was told to program in C++ and Java. Then R came along and it was liberating; my ability to do data analysis increased substantially. As my applications grew in size and complexity, I started to... Read more
SQL Equivalents in R
Whenever I’m teaching introductory courses in data science using the R language, I often encounter students who use a different language like Python or Julia, and still others who are transitioning into data science from other fields and don’t know any data science language at all. The common thread... Read more
Monthly Summary of Selected Trends, Activities, and Insights for R – July 2018
R is a leading language in the data science domain. In the following article, a summary of selected trends, activities, and insights around the R language from July 2018 are presented. Data for the trends and activities summarized here were obtained from popular websites used by the R community such... Read more