Statistics and analysis.
WHAT IT IS
A language and environment designed specifically for statistical computing and graphics.
WHAT DISTINGUISHES IT
Statistics as a first-class concern, not a library addition Data frames as a core structure Extremely strong visualisation An enormous collection of statistical packages
WHAT IT IS USED FOR
Statistical analysis Academic research Epidemiology and clinical research Econometrics Data visualisation and reporting
WHY IT PERSISTS ALONGSIDE PYTHON
The statistical package ecosystem is unmatched, and many methods appear there first.
WHAT ITS STRENGTHS ARE
Statistical methods, comprehensively Publication-quality graphics Reproducible reports combining code, output and prose
WHAT ITS WEAKNESSES ARE
Inconsistent design across its history Performance on large data Less suitable for general programming and production systems
WHAT THAT MEANS PRACTICALLY
Analysis in R, production systems usually elsewhere.
WHAT THE MODERN ECOSYSTEM PROVIDES
A coherent collection of packages with consistent design, which addressed much of the inconsistency criticism.
WHO IT SUITS
Statisticians, researchers and analysts.
