2  Rstudio setting (Cloud)

RStudio Cloud is a cloud-based platform for data science and data analysis using the R programming language. It provides users with a full-featured RStudio IDE (Integrated Development Environment) in a browser, eliminating the need to install R and RStudio on their own computers. This makes it easy for users to work with R and RStudio from any device with an internet connection.

RStudio Cloud offers a collaborative environment for data analysis and provides a platform for teams to work together on projects. It also provides access to powerful computing resources, so users can work with large data sets and run complex analyses without worrying about the limitations of their own computers.

In addition to the RStudio IDE, RStudio Cloud also provides a platform for hosting and sharing R Shiny applications, R Markdown documents, and other data analysis projects. This makes it easy for data scientists and analysts to share their work with others, whether for collaboration or for sharing insights with stakeholders.

2.1 How to start Rstudio Cloud

Steps to start using Rstudio Cloud

  1. Go to the Rstudio Cloud website: https://rstudio.cloud/
  2. Click on the “Sign Up” button in the top right corner.
  3. Enter your email address and create a password to create an account.
  4. Verify your email address.
  5. Once you’re logged in, you can start a new project by clicking on the “New Project” button.
  6. Choose a name for your project, select a privacy setting, and click the “Create Project” button.
  7. The Rstudio environment will load in your browser, and you can start using R and Rstudio.

Note: If you already have an account, simply log in with your existing email and password to start using Rstudio Cloud.

I would like to share with you a video tutorial on how to start using Rstudio Cloud. This video will walk you through the process step-by-step, so you can start using that. The video can be found at the following link: https://www.youtube.com/watch?v=ssxbi9nqpU0. I encourage you to watch the video and follow along, as it will provide you with a clear understanding of how to get started with Rstudio Cloud. Let’s get started!

2.2 Install basic R packages

2.2.1 how to install R packages

To install an R package, you can use the install.packages() function in R. Here’s an example of how to install the ggplot2 package:

install.packages("ggplot2")

You only need to run this command once, and the package will be installed on your system. Once the package is installed, you can load it into your R session using the library() function:

library(ggplot2)

Using the if(!require(...)) statement can help you check if a package is installed and load it into your R session, all in one step. Here’s an example of how to use the if(!require(...)) statement to load the ggplot2 package:

if (!require("ggplot2")) {
  install.packages("ggplot2")
  library(ggplot2)
}

If the ggplot2 package is already installed, the require() function will load it into your R session, and the install.packages() and library() functions will not be executed. If the package is not installed, the require() function will return FALSE, triggering the installation and loading of the package.

Using the if(!require(…)) statement is a convenient way to ensure that the necessary packages are installed and loaded into your R session, without having to manually check for and install them each time you start a new R session.

2.2.2 Basic R packages for dashboard

To create a flexdashboard in R, you will need to use the flexdashboard package. This package provides a framework for creating interactive and dynamic dashboards using R. In addition to the flexdashboard package, the tidyverse package is also commonly used for data manipulation, exploration, and visualization. The tidyverse is a collection of R packages, including ggplot2, dplyr, and tidyr, that provide a consistent and convenient interface for data manipulation, exploration, and visualization.

In addition to the tidyverse, there are a number of other R packages that can be used to create visualizations for your dashboards. Some commonly used packages for data visualization in R include:

  • ggplot2: A powerful and flexible data visualization package that provides a wide range of visualizations, including bar charts, line charts, scatter plots, and more.

  • plotly: A package for creating interactive visualizations, including line charts, bar charts, scatter plots, and more.

  • shiny: A package for creating interactive web applications using R, including dashboards.

  • leaflet: A package for creating interactive maps and visualizations.

  • DT: A package for creating interactive data tables and visualizations.

So, Lets’ install those packages. You can use the same if (!require(…)) statement to check and install multiple packages at once. Here’s an example of how you can check and install the plotly, shiny, leaflet, DT, and flexdashboard packages:

packages <- c("tidyverse", "plotly", "shiny", "leaflet", "DT", "flexdashboard")

for (package in packages) {
  if (!require(package, character.only = TRUE)) {
    install.packages(package)
    library(package, character.only = TRUE)
  }
}

This code uses a loop to iterate over the list of packages, and for each package, it checks if it’s installed using the require function. If a package is not installed, it will install it and then load it using the library function. If a package is already installed, the code will simply load it without installing it again.