Key Features

• Open Source: Free to use, modify, and distribute.
• Large community support and active development.
• Efficient handling and storage of large datasets.
• Rich set of built-in data structures: vectors, matrices, data frames, and lists.
• Designed specifically for statistics and data analysis.
• Supports linear and nonlinear modeling, time-series analysis, clustering, and classification.
• Extensive package ecosystem for specialized tasks.
  Integrates easily with C, C++, Python, and other languages.
  Powerful data visualization capabilities.
  Widely used in academia and industry for statistical computing.