| Author | Message | ||
Kindal Side Hero Username: Kindal Post Number: 4148 Registered: 09-2007 Posted From: 14.139.128.20 Rating: N/A |
The deployment of R on webservers for analytics is catching up, through support from other applications like Shiny and DeployR. https://www.r-bloggers.com/deploying-your-very-own-shiny-ser ver/ https://deployr.revolutionanalytics.com/documents/getting-st arted/about/ 5 mins after your birth, they decide your name, nationality, religion & sect & you spend rest of ur life defending something u didn't choose. | ||
Amaravathi Side Hero Username: Amaravathi Post Number: 8694 Registered: 04-2015 Posted From: 208.68.148.80 Rating: N/A |
Is it becoz, R is not a deploy-able version of code in production? Technically I oppose but Heartfully I accept - Pulp | ||
Kindal Side Hero Username: Kindal Post Number: 4147 Registered: 09-2007 Posted From: 14.139.128.20 Rating: |
Languages like Go, Julia, R, Scala, and even Python are riding the number-crunching wave. This growth invites the question whether R can ever unseat Python or Java as the top languages for big data. But while R has seen huge gains over the last few years, Python and Java really are 800-pound gorillas. For instance, we found roughly 15 times as many job listings for pythonistas as for R developers. And while we measured about 63,000 new GitHub repositories in the last year for R, there were close to 458,000 for Python. Although R may be great for visualization and exploratory analysis and is clearly popular with academics writing research papers, Python has significant advantages for users in production environments: It’s more easily integrated into production data pipelines, and as a general purpose language it simply has a broader array of uses http://spectrum.ieee.org/computing/software/top-programming- languages-trends-the-rise-of-big-data 5 mins after your birth, they decide your name, nationality, religion & sect & you spend rest of ur life defending something u didn't choose. |
