r
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🇺🇸
Original
English🇨🇳
Translation
ChineseR
R
A language and environment for statistical computing and graphics.
用于统计计算和绘图的语言与环境。
When to Use
使用场景
- Statistical Analysis
- Data Visualization (ggplot2)
- Bioinformatics
- Academic research
- 统计分析
- 数据可视化(ggplot2)
- 生物信息学
- 学术研究
Quick Start
快速入门
r
print("Hello, World!")r
print("Hello, World!")Vector
向量
x <- c(1, 2, 3, 4, 5)
x <- c(1, 2, 3, 4, 5)
Mean
平均值
mean(x)
mean(x)
Data Frame
数据框
df <- data.frame(
Name = c("Alice", "Bob"),
Age = c(25, 30)
)
undefineddf <- data.frame(
Name = c("Alice", "Bob"),
Age = c(25, 30)
)
undefinedCore Concepts
核心概念
Vectorization
向量化
R operations are designed to work on entire vectors at once, avoiding explicit loops.
r
x + 1 # Adds 1 to every element in xR的运算设计为可一次性处理整个向量,避免显式循环。
r
x + 1 # 为x中的每个元素加1Pipe Operator %>%
%>%管道操作符 %>%
%>%Used to clean code by passing output of one function as input to the next (Tidyverse).
r
data %>%
filter(users > 100) %>%
group_by(region) %>%
summarize(total = sum(users))用于简化代码,将一个函数的输出作为下一个函数的输入(Tidyverse工具集)。
r
data %>%
filter(users > 100) %>%
group_by(region) %>%
summarize(total = sum(users))Best Practices
最佳实践
Do:
- Use the Tidyverse (dplyr, ggplot2) for modern R
- Document functions with Roxygen2
- Use RStudio IDE
Don't:
- Use explicit loops if vectorization is possible (performance)
for - Mix naming conventions (snake_case is preferred in tidyverse)
建议:
- 使用Tidyverse(dplyr、ggplot2)进行现代R开发
- 使用Roxygen2为函数添加文档
- 使用RStudio IDE
不建议:
- 在可使用向量化的情况下使用显式循环(影响性能)
for - 混合命名规范(Tidyverse中优先使用snake_case)