R is a programming language that can help you in your data analysis process. In this part of the course, you’ll learn about R and RStudio, the environment you’ll use to work in R. You’ll explore the benefits of using R and RStudio as well as the components of RStudio that will help you get started.
學習目標
- Compare and contrast the R programming environment and the RStudio programming environment
- Describe the RStudio programming environment including its components and benefits
- Describe the R programming language and its programming environment
- Describe programming languages and appropriate use including examples
- Download and install R assets to a computer
- Open R and execute a command
- Differentiate between the R Console and R programming environments
- Execute operations in R using mathematical operators such as +, -, *, and /
- Download and use RStudio Desktop
- Demonstrate how to complete basic tasks in R
inning a debate.
| Languages |
R |
Python |
| **Common |
|
|
| features** |
- Open-source |
|
- Data stored in data frames
- Formulas and functions readily available
- Community for code development and support | - Open-source
- Data stored in data frames
- Formulas and functions readily available
- Community for code development and support |
| Unique
advantages | - Data manipulation, data visualization, and
statistics packages
- "Scalpel" approach to data: find packages to do what you want with the data | - Easy syntax for machine learning needs
- Integrates with cloud platforms like Google Cloud,
Amazon Web Services, and Azure |
| Unique
challenges | - Inconsistent naming conventions make it
harder for beginners to select the right functions
- Methods for handling variables may be a little
complex for beginners to understand | - Many more decisions for beginners to make about
data input/output, structure, variables, packages,
and objects
- "Swiss army knife" approach to data: figure out a way to do what you want with the data |
Cleaning functions help you preview and rename data so that it’s easier to work with.
Organizational functions help you sort, filter, and summarize your data.
Transformational functions help you separate and combine data, as well as create new variables.
R 語法總整理