init
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.gitignore
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.gitignore
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/.conda/
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.vscode/settings.json
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.vscode/settings.json
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/* VSCode 项目配置 */
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{
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"r.rpath.linux": ".conda/bin/R",
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"r.rterm.linux": "${workspaceFolder}/.conda/bin/R",
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"r.rterm.option": [
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"--no-save",
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"--no-restore"
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],
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"r.plot.useHttpgd": true,
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"r.libPaths": [
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".conda/bin/R/library"
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],
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"files.eol": "\n"
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}
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54
README.md
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README.md
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# Conda中的R语言环境
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## 安装准备
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- VSCode 代码编辑器
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VSCode中插件扩展安装:
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- Python
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- R
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- R Debugger
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- Miniconda/Anaconda 虚拟环境管理
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> [!NOTE]
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> 自行检查conda的镜像源配置,以加速库的下载安装。
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- Git 代码同步工具
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## 操作步骤
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0. 克隆本项目到指定的位置
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`git clone https://git.unvec.site/stevenhobs/R-with-Conda <项目路径>`
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1. 初始化conda虚拟环境
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创建虚拟环境,可以使用VSCode的Python解释器选择功能创建conda虚拟环境,创建完虚拟环境后选择对应的虚拟环境,使用conda安装对应的R依赖包
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`conda install -c conda-forge r-base r-languageserver r-httpgd r-devtools radian`
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或者使用命令创建虚拟环境并同时下载依赖包
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`conda create -p .condarc -c conda-forge r-base r-languageserver r-devtools r-httpgd radian`
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2. 初始化R Debugger
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VSCode命令面板搜索执行 `R Debugger: Update or install the required R Package`进行安装R的VSC调试库
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或者在R的控制台中执行指令
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`devtools::install_github("ManuelHentschel/vscDebugger")`
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> [!NOTE]
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> 此操作需要访问Github平台以获取源码编译安装,请确保 github.com 可正常访问
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3. 库的安装
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在当前的conda环境下,
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使用`conda search conda-forge::r-包名` 搜索对应的包
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使用`conda install conda-forge::r-包名` 安装对应的包
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或者采用R通用的安装(CRAN)
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24
src/test-plot.R
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src/test-plot.R
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# 设置随机种子以便重现
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set.seed(123)
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# 生成示例数据
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x <- rnorm(100) # 生成 100 个正态分布随机数作为 x 值
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y <- rnorm(100) # 生成 100 个正态分布随机数作为 y 值
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# 创建散点图
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plot(x, y,
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main = "Scatter Plot of Random Data", # 图表标题
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xlab = "X-axis Label", # X 轴标签
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ylab = "Y-axis Label", # Y 轴标签
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col = "blue", # 点的颜色
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pch = 19
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) # 点的形状
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# 添加回归线
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abline(lm(y ~ x), col = "red") # 添加线性回归线,红色
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# 添加图例
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legend("topright",
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legend = c("Data Points", "Regression Line"),
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col = c("blue", "red"), pch = c(19, NA), lty = c(NA, 1)
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)
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src/test-print.R
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src/test-print.R
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# 创建一个数字向量
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numbers <- c(1, 2, 3, 4, 5)
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print(numbers)
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# 创建一个字符向量
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fruits <- c("apple", "banana", "cherry")
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print(fruits)
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# 创建一个数据框
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data <- data.frame(
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Name = c("Alice", "Bob", "Charlie"),
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Age = c(25, 30, 35),
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Score = c(85.5, 90.0, 78.5)
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)
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print(data)
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