2 Rstudio环境配置 – 试验设计与数据分析: 基于R语言

2.1 建议采用pacman来管理你R包

2.1.1 安装`pacman`包

install.packages("pacman")

2.1.2 加载R包

pacman包的p_load函数很方便，会自动判断R环境中是否已安装所需要的包，若没有则自动安装后再加载；若已安装，则直接加载。

library(pacman)
pkgs <- c("tidyverse","agricolae","here","knitr","latex2exp","cowplot")                   
p_load(pkgs)

有一些时候我们需要从github上面来安装包，pacman包里面也有一个函数专门为从github上面安装包。

比如这里我们安装trinker的regexr包

p_load_gh("trinker/regexr")

2.1.3 刪除R包

p_delete("here")

2.1.4 检查R包依赖

p_depends("ggplot2")

$Imports
 [1] "cli"       "glue"      "grDevices" "grid"      "gtable"    "isoband"  
 [7] "lifecycle" "MASS"      "mgcv"      "rlang"     "scales"    "stats"    
[13] "tibble"    "vctrs"     "withr"    

$Suggests
 [1] "covr"          "dplyr"         "ggplot2movies" "hexbin"       
 [5] "Hmisc"         "knitr"         "mapproj"       "maps"         
 [9] "multcomp"      "munsell"       "nlme"          "profvis"      
[13] "quantreg"      "ragg"          "RColorBrewer"  "rmarkdown"    
[17] "rpart"         "sf"            "svglite"       "testthat"     
[21] "vdiffr"        "xml2"

通过上述代码，我们可以看到ggplot2包的安装需要提前安装好这些包，同时我们也可以查看本地已安装了哪些依赖。

p_depends("ggplot2",local = TRUE)

$Imports
 [1] "cli"       "glue"      "grDevices" "grid"      "gtable"    "isoband"  
 [7] "lifecycle" "MASS"      "mgcv"      "rlang"     "scales"    "stats"    
[13] "tibble"    "vctrs"     "withr"    

$Suggests
 [1] "covr"          "dplyr"         "ggplot2movies" "hexbin"       
 [5] "Hmisc"         "knitr"         "mapproj"       "maps"         
 [9] "multcomp"      "munsell"       "nlme"          "profvis"      
[13] "quantreg"      "ragg"          "RColorBrewer"  "rmarkdown"    
[17] "rpart"         "sf"            "svglite"       "testthat"     
[21] "vdiffr"        "xml2"

2.1.5 更新R包

p_unload() #更新所有包
p_unload(ggplot2, dplyr, stringr) #更新指定包

查看所有待更新的包，但不更新

p_update(update = FALSE)

 [1] "BH"           "bit"          "bit64"        "blavaan"      "bslib"       
 [6] "cpp11"        "curl"         "data.table"   "dbscan"       "dendextend"  
[11] "doBy"         "emmeans"      "evaluate"     "fastDummies"  "fontawesome" 
[16] "Hmisc"        "httr2"        "igraph"       "inline"       "later"       
[21] "lme4"         "lmodel2"      "lubridate"    "matrixStats"  "multcomp"    
[26] "mvtnorm"      "openssl"      "openxlsx"     "parallelly"   "pillar"      
[31] "pkgbuild"     "processx"     "promises"     "psych"        "purrr"       
[36] "quantreg"     "QuickJSR"     "Rcpp"         "RcppParallel" "reticulate"  
[41] "rlang"        "sessioninfo"  "shiny"        "systemfonts"  "testthat"    
[46] "textshaping"  "TH.data"      "usethis"      "vegan"        "xfun"        
[51] "XML"          "zip"          "class"        "cluster"      "foreign"     
[56] "KernSmooth"   "MASS"         "Matrix"       "nlme"         "nnet"        
[61] "rpart"        "spatial"      "survival"

2.2 更换Rstudio主题

# Rstudio环境配置

## 建议采用pacman来管理你R包
### 安装`pacman`包
```{r}
#| eval: false
install.packages("pacman")
```


### 加载R包
`pacman`包的`p_load`函数很方便，会自动判断R环境中是否已安装所需要的包，若没有则自动安装后再加载；若已安装，则直接加载。
```{r}
library(pacman)
pkgs <- c("tidyverse","agricolae","here","knitr","latex2exp","cowplot")                   
p_load(pkgs)
```

有一些时候我们需要从github上面来安装包，pacman包里面也有一个函数专门为从github上面安装包。

比如这里我们安装trinker的regexr包
```{r}
p_load_gh("trinker/regexr")
```

### 刪除R包
```{r}
p_delete("here")

```
### 检查R包依赖
```{r}
p_depends("ggplot2")

```
通过上述代码，我们可以看到ggplot2包的安装需要提前安装好这些包，
同时我们也可以查看本地已安装了哪些依赖。
```{r}
p_depends("ggplot2",local = TRUE)

```

### 更新R包
```{r}
p_unload() #更新所有包
p_unload(ggplot2, dplyr, stringr) #更新指定包 
```
查看所有待更新的包，但不更新
```{r}
p_update(update = FALSE)
```

## 更换Rstudio主题