Data Science Austria

How to easily automate R analysis, modeling and development work using CI/CD, with working examples

Automating the execution, testing and deployment of R work is a very powerful tool to ensure the reproducibility, quality and overall robustness of the code that we are building, be it for data analysis and modeling purposes, developing R packages or even blogging. Modern tools also provide a free an … Read moreHow to easily automate R analysis, modeling and development work using CI/CD, with working examples

Big Data: On RDDs, Dataframes,Hive QL with Pyspark and SparkR-Part 3

Out[90]: [[‘Runs’, ‘Mins’, ‘BF’, ‘4s’, ‘6s’, ‘SR’, ‘Pos’, ‘Dismissal’, ‘Inns’, ‘Opposition’, ‘Ground’, ‘Start Date’], [’15’, ’28’, ’24’, ‘2’, ‘0’, ‘62.5’, ‘6’, ‘bowled’, ‘2’, ‘v Pakistan’, ‘Karachi’, ’15-Nov-89′], [‘DNB’, ‘-‘, ‘-‘, ‘-‘, ‘-‘, ‘-‘, ‘-‘, ‘-‘, ‘4’, ‘v Pakistan’, ‘Karachi’, ’15-Nov-89′], [’59’, ‘254’, ‘172’, ‘4’, ‘0’, ‘34.3’, ‘6’, ‘lbw’, ‘1’, ‘v … Read moreBig Data: On RDDs, Dataframes,Hive QL with Pyspark and SparkR-Part 3

A Shiny Classroom Experiment with Real-Time Results Presentation

Overview Today, I used a shiny app to run a classroom experiment in the first class of my introductory cost accounting course. I uploaded code, data and materials to github so that everybody can reuse it to construct similar experiments and, of course, to replicate the results from our experiment. … Read moreA Shiny Classroom Experiment with Real-Time Results Presentation