R - 30 métriques et score AHP
Introduction
R est un langage de programmation Multi-paradigm apparu en 1993, conçu par Ross Ihaka, Robert Gentleman. Cas d’usage principaux : Data Science, Scientific Computing, Statistics.
30 métriques
| Métrique | Valeur | Rang |
|---|---|---|
| GitHub Stars | 58302 | 20 |
| Stack Overflow Tags | 729989 | 25 |
| TIOBE Rank | 36 | |
| RedMonk Rank | 20 | |
| PYPL Rank | 24 | |
| Average Salary (USD) | 122736 | 23 |
| Job Postings | 38329 | 22 |
| Benchmarks Score | 1.0 | 4 |
| Learning Curve | Hard | |
| Community Size | Very Large | |
| Documentation Quality | 8 | |
| Ecosystem Maturity | 10 | |
| Industry Adoption | 8 | |
| Type System Complexity | 9 | |
| Concurrency Support | 8 | |
| Performance - Execution Speed | 8 | |
| Performance - Memory Usage | 9 | |
| Performance - Startup Time | 8 | |
| Tooling Quality | 8 | |
| Package Manager Quality | 9 | |
| IDE Support | 8 | |
| Debugging Experience | 9 | |
| GitHub Stars Rank | 20 | |
| Stack Overflow Tags Rank | 25 | |
| Average Salary Rank | 23 | |
| Job Postings Rank | 22 | |
| Benchmarks Rank | 4 | |
| Learning Curve Score | 2 | |
| Community Size Score | 9 | |
| AHP Score | 7.66 | 23 |
Exemple Hello World
print('Hello, World!')
Cas d’usage principaux
- Data Science
- Scientific Computing
- Statistics
- Visualization
Frameworks populaires
- tidyverse
- ggplot2
- Shiny
Score AHP
R Score AHP: 7.66 (#23)