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Why R? | Basic Syntax and Operations
R Introduction: Part I

Why R?

Hello and welcome! If you're here, you're likely curious about R and why it's such a big deal in the world of data science, so let's discuss why it is a fantastic tool for analyzing and visualizing data.

R is a powerful language and environment for statistical computing and graphics widely used among statisticians and data miners for developing statistical software and data analysis.

But what makes R stand out in a sea of programming languages?

Key Features of R

Statistical Powerhouse
Free and Open Source
Highly Extensible
Data Manipulation and Cleaning
Data Visualization
  • Statistical Powerhouse: R was designed by statisticians, for statisticians. Its rich library of statistical and graphical methods includes linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more;
  • Free and Open Source: R is free and open-source software, meaning you can use it without any cost. Additionally, it has a vibrant community that contributes to its extensive package ecosystem, constantly expanding R's capabilities;
  • Highly Extensible: The R environment can be extended via packages. There are over 15,000 packages available on CRAN (the Comprehensive R Archive Network), catering to a wide range of statistical, graphical, and machine learning tasks;
  • Data Manipulation and Cleaning: R excels at data manipulation and cleaning providing intuitive and powerful tools for transforming and organizing data;
  • Data Visualization: One of R's standout features is its data visualization capabilities. In particular, it is renowned for creating complex and aesthetically pleasing visualizations with minimal code.

Tudo estava claro?

Seção 1. Capítulo 1
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Conteúdo do Curso

R Introduction: Part I

Why R?

Hello and welcome! If you're here, you're likely curious about R and why it's such a big deal in the world of data science, so let's discuss why it is a fantastic tool for analyzing and visualizing data.

R is a powerful language and environment for statistical computing and graphics widely used among statisticians and data miners for developing statistical software and data analysis.

But what makes R stand out in a sea of programming languages?

Key Features of R

Statistical Powerhouse
Free and Open Source
Highly Extensible
Data Manipulation and Cleaning
Data Visualization
  • Statistical Powerhouse: R was designed by statisticians, for statisticians. Its rich library of statistical and graphical methods includes linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more;
  • Free and Open Source: R is free and open-source software, meaning you can use it without any cost. Additionally, it has a vibrant community that contributes to its extensive package ecosystem, constantly expanding R's capabilities;
  • Highly Extensible: The R environment can be extended via packages. There are over 15,000 packages available on CRAN (the Comprehensive R Archive Network), catering to a wide range of statistical, graphical, and machine learning tasks;
  • Data Manipulation and Cleaning: R excels at data manipulation and cleaning providing intuitive and powerful tools for transforming and organizing data;
  • Data Visualization: One of R's standout features is its data visualization capabilities. In particular, it is renowned for creating complex and aesthetically pleasing visualizations with minimal code.

Tudo estava claro?

Seção 1. Capítulo 1
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