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Tools of Choice for Data Science

A summary of the annual survey of tools and attitudes around data science conducted by Karl Rexer was released at Predictive Analytics World in Boston recently. The full report is expected to be available on RexerAnalytics.com in the next couple of months.

Screenshot-Rexer Data Science Survey Highlights Sep-2015.pdf - Adobe Reader

For primary tool usage:

#1 — 36.2% — R
#2 —   7.0% — SAS
#3 —   6.6% — IBM SPSS Modeler
#4 —   6.5% — KNIME (free version)
#5 (tie) — 5.1% — IBM SPSS Statistics
#5 (tie) — 5.1% — STATISTICA
#7 —   3.1% — SAS Enterpirse Miner
#8 —   2.8%  — RapidMiner (free version)
#9 —   2.7% — Weka
#10 — 2.3% — MATLAB
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R Visual Analytics using raptR

I saw a demo of a package for Rapid and Pretty Things in R earlier in the year when it was a work in progress. It is now live on GitHub (but not yet CRAN). It allows you to very quickly visualise data in R using a Shiny GUI to generate ggplot2 underneath. A nice app for some visual analytics.

devtools::install_github('cargomoose/raptR')
raptR::raptR()

Screenshot-raptR - Mozilla Firefox

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