## What is R? - A computer programming language and environment designed for statistical computing and graphics. - Modeled after the S programming language. - Introduced by Robert Gentleman and Robert Ihaka in 1993. - Free, open source, and runs on Windows, Macs, Linux, and other types of computers. - Interactive and highly extendable. ## What can you create with R? R’s versatility and extensive package ecosystem make it a powerful tool for a wide range of data-related tasks With R, you can create and accomplish a wide range of tasks, especially in the fields of data analysis, statistics, and visualization. Here are some key things you can do with R: 1. **Data Visualization** - R is renowned for its powerful data visualization capabilities. You can create a variety of plots and charts using packages like ggplot2 and plotly. These tools allow you to produce high-quality, customizable visualizations that can help you understand and communicate your data effectively. 2. **Statistical Analysis** - R was designed with statistics in mind. You can perform a wide array of statistical analyses, from basic descriptive statistics to complex modeling and hypothesis testing. Packages like [stats](https://rbasics.org/packages/stat-package-in-r/) and [MASS]() provide extensive tools for statistical analysis. 3. **Data Manipulation** - R’s [tidyverse](https://www.tidyverse.org/) suite, including packages like [dplyr](https://dplyr.tidyverse.org/) and [tidyr](https://tidyr.tidyverse.org/), makes it easy to clean, manipulate, and transform data. This is essential for preparing data for analysis and visualization. 4. **Reporting** - With [Quarto](https://quarto.org/) and [R Markdown](https://rmarkdown.rstudio.com/), you can create dynamic reports that integrate code, output, and text. This is useful for creating reproducible research and sharing your findings. 5. **Interactive Dashboards** - Using the [shiny package](https://www.rstudio.com/products/shiny/), you can create interactive web applications and dashboards. This allows you to share your analyses and visualizations with others in an interactive format. 6. **Automation** - R can be used to automate repetitive tasks, such as data cleaning, report generation, and more. This can save time and reduce the potential for human error. 8. **Web Scraping** - With packages like [rvest](https://rvest.tidyverse.org/), you can scrape data from websites. This is useful for gathering data that isn’t readily available in structured formats. 9. **Geospatial Analysis** - R has strong support for geospatial data analysis through packages like [sf](https://r-spatial.r-universe.dev/sf) and [sp](https://rspatial.org/raster/spatial/3-vectordata.html). You can analyze and visualize spatial data, making it a powerful tool for geographic information systems (GIS). 10. **Machine Learning** - R offers numerous packages for machine learning, such as [caret](https://rbasics.org/packages/caret-package-in-r/) and [randomForest](https://rbasics.org/packages/randomforest-package-in-r/). You can build and evaluate predictive models, perform clustering, and apply various machine learning algorithms to your data. Sources: [What can you do with R? 5 Top R Ideas | DataCamp](https://www.datacamp.com/blog/what-can-you-do-with-r); [What Can I Do With R? 6 Essential R Packages for Programmers | R-bloggers](https://www.r-bloggers.com/2020/12/what-can-i-do-with-r-6-essential-r-packages-for-programmers/);[What can you do with R? - GeeksforGeeks](https://www.geeksforgeeks.org/what-can-you-do-with-r/); [R Tutorial: a quick beginner's guide to using R](https://www.educative.io/blog/r-tutorial-beginners-guide); [R Programming Language: What Can You Do With it? | WOZ](https://woz-u.com/blog/what-you-can-do-with-r-programming-language/) ## How can you use R? - You can type and execute a command in the R Studio Console for immediate feedback in contrast to a compiled programming language, which compiles a program that is then executed. - You can create, save, and execute scripts. - You can write their own functions and easily add software libraries to R. User-created packages are available to extend the functionality beyond what is installed by default. ## What are the strengths of the R environment? * R’s strengths in statistical analysis, visualization, and community support make it a favored choice for researchers and data scientists. Source: [R: What is R?](https://www.r-project.org/about.html?src_trk=em6655c26988bd73.07612795366187512) and [Pros and Cons of R Programming Language - GeeksforGeeks](https://www.geeksforgeeks.org/pros-and-cons-of-r-programming-language/) * **Rich Ecosystem** - R has a vast ecosystem of packages contributed by users worldwide. The Comprehensive R Archive Network (CRAN) hosts over 18,000 packages that cover a wide range of domains such as statistics, machine learning, and data visualization. - **Statistical Analysis** - R was specifically designed for statistical computing and analysis. It provides a comprehensive set of built-in functions and libraries for performing various statistical tests, hypothesis testing, regression analysis, and more. - **Data Visualization** - R offers unparalleled capabilities for data visualization. Packages like ggplot2, plotly, and ggvis enable users to create highly customizable and publication-quality plots, charts, and graphs. - **Community Support** - R has a large and active community of users, including statisticians, data scientists, researchers, and educators. This community contributes to the development of new packages, shares knowledge, and provides support to both beginners and experienced users. - **Extensibility** - R is highly extensible, allowing users to add additional functionality by defining new functions. It also supports integration with other programming languages like C, C++, and Fortran for computationally intensive tasks. - **Open Source** - Being open-source, R is freely available and can be modified and distributed by anyone. This encourages collaboration and innovation within the community. ## How to get R? - R may be downloaded from the R Project’s website ([The Comprehensive R Archive Network (r-project.org)](https://cloud.r-project.org/)). - R Studio Desktop is a free “front end” for R provided by R Studio. R Studio Desktop makes doing data science with R much easier by adding an Integrated Development Environment (IDE) and providing many other features. Currently, you may download R Studio here: ([Download the RStudio IDE - RStudio](https://posit.co/download/rstudio-desktop/)). ## Learning R Paid Services: [R for the Rest of Us](https://rfortherestofus.com/courses), [R for Ecology](https://www.rforecology.com/), [Data Camp]([R Programming Courses | Online Courses for All Levels](https://www.datacamp.com/category/r)), [Code Academy]([R Courses & Tutorials | Codecademy](https://www.codecademy.com/catalog/language/r)), [eDX](https://www.edx.org/learn/r-programming), [Cousera](https://www.coursera.org/courses?query=r%20programming), etc. Free: [Stack Overflow](https://stackoverflow.com/questions/tagged/r), [Posit Community](https://forum.posit.co/), [Learn R - Online R Programming Tutorial](https://learn-r.org/), internet searches, etc. ## R Resources | Tool | Source | Location | | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | | R | CRAN | Repository. Use the cloud mirror, https://cloud.r-project.org, which automatically figures your location and the nearest repository. | | R Studio | Posit.com | [Posit.com - RStudio](https://posit.co/products/open-source/rstudio/) - RStudio is an integrated development environment (IDE) for R and Python. | | GitHub | Github.com | [GitHub](https://github.com/) - GitHub is a cloud-based platform where you can store, share, and work together with others to write code. | | Rattle | Togaware | [A Graphical User Interface for Data Mining using R (rattle.togaware.com)](https://rattle.togaware.com/) | | Kaggle | Kaggle | [Run Data Science & Machine Learning Code Online \| Kaggle](https://www.kaggle.com/code?language=R) | | Quarto | Posit.com | [Quarto](https://quarto.org/) - An open-source scientific and technical publishing system. | *** 2024 cloudedknowledge.net