Each month, we release tons of great content on R for Business. These are the 5 Top Articles in R for Business over the past month. We have some great ones in September. Let’s dive in. View the updated Top 5 R for Business Article at Business Science.
No. 1: Using Drake for ETL
Building A Shiny Real Estate App
“Using Drake for ETL by Building A Shiny Real Estate App”. Learn
drake an awesome technology for making reproducible data science workflows, which was used to build a
shiny real estate application. This article received a ton of love this month. It’s also my pleasure to say it was contributed by one of my all-star students, David Lucey – Consultant with Redwall Partners .
No. 2: How to Automate PowerPoint with R
“How to Automate PowerPoint with R”. Learn how to automate PowerPoint with
tidyverse. This includes a 10-minute video tutorial that walks you through the process of automating PowerPoint Slide Decks from R.
No. 3: Time Series Anomaly Detection
“Time Series in 5-Minutes, Part 5: Anomaly Detection”. Anomaly detection is the process of identifying items or events in data sets that are different than the norm. Anomaly detection is an important part of time series analysis: (1) Detecting anomalies can signify special events, and (2) Cleaning anomalies can improve forecast error.
No. 4: How to Scrape Word Documents with R
“How to Scrape Word Documents with R”. Here’s a common situation, you’re company has LOTS OF WORD FILES. They contain tables of information. Learn how to scrape Microsoft Word Documents with
tidyverse. This includes a 10-minute video tutorial that walks you through scraping Word Documents from R.
No. 5: Shiny vs Tableau with 3 Business Application Examples
“Shiny vs Tableau with 3 Business Application Examples”.
Shiny, a web framework that is written in
R, often gets lumped into the conversation with Tableau and PowerBI – Two popular Business Intelligence (BI Tools) used for “Dashboarding”.
Shiny is much more than just a dashboarding tool:
Shiny combine both machine learning and decision-making, packaging your data science analysis into a web application that businesses can use. Here we illustrate 3 powerful use cases for
R Shiny Apps in business.
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