{"id":51323,"date":"2024-12-03T10:29:23","date_gmt":"2024-12-03T02:29:23","guid":{"rendered":"https:\/\/fwq.ai\/blog\/51323\/"},"modified":"2024-12-03T10:29:23","modified_gmt":"2024-12-03T02:29:23","slug":"linux%e7%b3%bb%e7%bb%9f%e4%b8%8b%e4%bd%bf%e7%94%a8rstudio%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e5%8f%af%e8%a7%86%e5%8c%96%e7%9a%84%e8%ae%be%e7%bd%ae%e6%ad%a5%e9%aa%a4","status":"publish","type":"post","link":"https:\/\/fwq.ai\/blog\/51323\/","title":{"rendered":"Linux\u7cfb\u7edf\u4e0b\u4f7f\u7528RStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u8bbe\u7f6e\u6b65\u9aa4"},"content":{"rendered":"

<\/b> <\/p>\n

Linux\u7cfb\u7edf\u4e0b\u4f7f\u7528RStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u8bbe\u7f6e\u6b65\u9aa4<\/h1>\n

\u4ece\u73b0\u5728\u5f00\u59cb\uff0c\u6211\u4eec\u8981\u52aa\u529b\u5b66\u4e60\u5566\uff01\u4eca\u5929\u6211\u7ed9\u5927\u5bb6\u5e26\u6765\uff0c\u611f\u5174\u8da3\u7684\u670b\u53cb\u8bf7\u7ee7\u7eed\u770b\u4e0b\u53bb\u5427\uff01\u4e0b\u6587\u4e2d\u7684\u5185\u5bb9\u6211\u4eec\u4e3b\u8981\u4f1a\u6d89\u53ca\u5230<\/span>\u7b49\u7b49\u77e5\u8bc6\u70b9\uff0c\u5982\u679c\u5728\u9605\u8bfb\u672c\u6587\u8fc7\u7a0b\u4e2d\u6709\u9047\u5230\u4e0d\u6e05\u695a\u7684\u5730\u65b9\uff0c\u6b22\u8fce\u7559\u8a00\u5440\uff01\u6211\u4eec\u4e00\u8d77\u8ba8\u8bba\uff0c\u4e00\u8d77\u5b66\u4e60\uff01<\/p>\n

\u5728Linux\u7cfb\u7edf\u4e0a\u4f7f\u7528RStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u914d\u7f6e\u65b9\u6cd5<\/p>\n

\u6458\u8981\uff1a
RStudio\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u96c6\u6210\u5f00\u53d1\u73af\u5883\uff0c\u9002\u7528\u4e8eR\u8bed\u8a00\u7684\u5f00\u53d1\u548c\u6570\u636e\u5206\u6790\u3002\u672c\u6587\u5c06\u4ecb\u7ecd\u5982\u4f55\u5728Linux\u7cfb\u7edf\u4e0a\u5b89\u88c5\u548c\u914d\u7f6eRStudio\uff0c\u5e76\u5229\u7528\u5176\u6570\u636e\u53ef\u89c6\u5316\u529f\u80fd\u3002<\/p>\n

    \n
  1. \n

    \u5b89\u88c5R\u548cRStudio
    \u5728Linux\u7cfb\u7edf\u4e0a\u5b89\u88c5R\u548cRStudio\u662f\u5f00\u59cb\u914d\u7f6e\u8fc7\u7a0b\u7684\u7b2c\u4e00\u6b65\u3002\u6839\u636e\u4f60\u7684Linux\u53d1\u884c\u7248\u672c\uff0c\u53ef\u4ee5\u91c7\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b8c\u6210\u5b89\u88c5\uff1a
    1.1 Ubuntu\/Debian:<\/p>\n

    sudo apt-get update\nsudo apt-get install r-base r-base-dev<\/pre>\n
    1.2 CentOS\/Fedora:<\/p>\n
    sudo yum install R\n<\/pre>\n
    \u5b89\u88c5RStudio\u53ef\u4ee5\u901a\u8fc7\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u5bf9\u5e94\u7684\u5b89\u88c5\u5305\u8fdb\u884c\u5b89\u88c5\u3002\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/www.rstudio.com\/products\/rstudio\/download\/<\/p>\n<\/li>\n
  2. \n
    \u5b89\u88c5R\u5305\u548c\u4f9d\u8d56\u9879
     R\u5305\u662fR\u8bed\u8a00\u7684\u6269\u5c55\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u548c\u53ef\u89c6\u5316\u529f\u80fd\u3002\u5728RStudio\u4e2d\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u9700\u8981\u5b89\u88c5\u76f8\u5173\u7684R\u5305\u3002\u6253\u5f00RStudio\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5b89\u88c5\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5305\uff1a<\/p>\n
    install.packages(c(“ggplot2”, “plotly”, “leaflet”, “shiny”))<\/p>\n
    \u8fd9\u5c06\u4f1a\u5b89\u88c5ggplot2\u3001plotly\u3001leaflet\u548cshiny\u5305\u3002<\/p>\n<\/li>\n
  3. \n
    RStudio\u914d\u7f6e
     3.1 \u81ea\u5b9a\u4e49\u8bbe\u7f6e
    \u5728RStudio\u4e2d\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u9009\u62e9”Tools” -> “Global Options”\u6765\u8fdb\u884c\u81ea\u5b9a\u4e49\u8bbe\u7f6e\u3002\u5728”Appearance”\u9009\u9879\u5361\u4e0b\uff0c\u53ef\u4ee5\u8c03\u6574\u7f16\u8f91\u5668\u7684\u5b57\u4f53\u3001\u5927\u5c0f\u548c\u4e3b\u9898\u989c\u8272\u3002\u5728”Code”\u9009\u9879\u5361\u4e0b\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u4ee3\u7801\u7f29\u8fdb\u3001\u81ea\u52a8\u62fc\u5199\u68c0\u67e5\u548c\u81ea\u52a8\u5b8c\u6210\u7b49\u3002<\/p>\n
    3.2 \u914d\u7f6eRMarkdown
    RMarkdown\u662fRStudio\u4e2d\u7528\u4e8e\u751f\u6210\u62a5\u544a\u548c\u6587\u6863\u7684\u5f3a\u5927\u5de5\u5177\u3002\u5728”RMarkdown”\u9009\u9879\u5361\u4e0b\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u9ed8\u8ba4\u7684\u8f93\u51fa\u683c\u5f0f\u548c\u6837\u5f0f\uff0c\u5982HTML\u3001PDF\u3001Word\u7b49\u3002<\/p>\n<\/li>\n
  4. \n
    \u6570\u636e\u53ef\u89c6\u5316\u793a\u4f8b
     \u63a5\u4e0b\u6765\uff0c\u5c06\u901a\u8fc7\u51e0\u4e2a\u4f8b\u5b50\u6765\u5c55\u793aRStudio\u7684\u6570\u636e\u53ef\u89c6\u5316\u529f\u80fd\u3002<\/p>\n
    4.1 \u4f7f\u7528ggplot2\u7ed8\u5236\u6563\u70b9\u56fe
    ggplot2\u662f\u4e00\u4e2a\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5305\uff0c\u53ef\u4ee5\u7ed8\u5236\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7ed8\u5236\u6563\u70b9\u56fe\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/li>\n<\/ol>\n
       library(ggplot2)\n   data <- read.csv(\"data.csv\")\n   ggplot(data, aes(x=age, y=income, color=gender)) + geom_point()<\/pre>\n
    \u8fd9\u6bb5\u4ee3\u7801\u5c06\u4ece\u4e00\u4e2a\u540d\u4e3a”data.csv”\u7684\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e\uff0c\u7136\u540e\u4f7f\u7528age\u548cincome\u4f5c\u4e3a\u6a2a\u7eb5\u5750\u6807\uff0cgender\u4f5c\u4e3a\u989c\u8272\u6765\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u6563\u70b9\u56fe\u3002<\/p>\n
    4.2 \u4f7f\u7528plotly\u7ed8\u5236\u4ea4\u4e92\u5f0f\u56fe\u8868
     plotly\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u4ea4\u4e92\u5f0f\u6570\u636e\u53ef\u89c6\u5316\u5305\uff0c\u53ef\u4ee5\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u997c\u56fe\u548c\u70ed\u56fe\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7ed8\u5236\u6298\u7ebf\u56fe\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n
       library(plotly)\n   data <- read.csv(\"data.csv\")\n   plot_ly(data, x = ~date, y = ~value, type = 'scatter', mode = 'lines')<\/pre>\n
    \u8fd9\u6bb5\u4ee3\u7801\u5c06\u4ece”data.csv”\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e\uff0c\u5e76\u4f7f\u7528date\u548cvalue\u4f5c\u4e3ax\u548cy\u8f74\u6765\u521b\u5efa\u4e00\u4e2a\u6298\u7ebf\u56fe\u3002<\/p>\n
    4.3 \u4f7f\u7528leaflet\u521b\u5efa\u5730\u56fe\u53ef\u89c6\u5316
     leaflet\u662f\u4e00\u4e2a\u4e13\u6ce8\u4e8e\u5730\u56fe\u53ef\u89c6\u5316\u7684\u5305\uff0c\u53ef\u4ee5\u7ed8\u5236\u4ea4\u4e92\u5f0f\u5730\u56fe\u548c\u6807\u8bb0\u7269\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7ed8\u5236\u7b80\u5355\u5730\u56fe\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n
       library(leaflet)\n   data <- read.csv(\"data.csv\")\n   map <- leaflet() %>% addTiles() %>% setView(lng = 0, lat = 0, zoom = 2)\n   for (i in 1:nrow(data)) {\n       map <- map %>% addMarkers(lng = data[i, \"longitude\"], lat = data[i, \"latitude\"], popup = data[i, \"name\"])\n   }\n   map<\/pre>\n
    \u8fd9\u6bb5\u4ee3\u7801\u5c06\u4ece”data.csv”\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e\uff0c\u5e76\u6839\u636e\u7ecf\u7eac\u5ea6\u548c\u540d\u79f0\u5728\u5730\u56fe\u4e0a\u6dfb\u52a0\u6807\u8bb0\u7269\u3002<\/p>\n
      \n
    1. \u7ed3\u8bba
       \u672c\u6587\u4ecb\u7ecd\u4e86\u5728Linux\u7cfb\u7edf\u4e0a\u914d\u7f6eRStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u65b9\u6cd5\uff0c\u5305\u62ec\u5b89\u88c5R\u548cRStudio\u3001\u5b89\u88c5R\u5305\u548c\u4f9d\u8d56\u9879\u4ee5\u53caRStudio\u7684\u914d\u7f6e\u3002\u901a\u8fc7\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u4e86\u4f7f\u7528ggplot2\u3001plotly\u548cleaflet\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u65b9\u6cd5\u3002\u5e0c\u671b\u672c\u6587\u80fd\u591f\u5e2e\u52a9\u8bfb\u8005\u66f4\u597d\u5730\u5229\u7528RStudio\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u5de5\u4f5c\u3002<\/li>\n<\/ol>\n
      \u672c\u7bc7\u5173\u4e8e\u300aLinux\u7cfb\u7edf\u4e0b\u4f7f\u7528RStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u8bbe\u7f6e\u6b65\u9aa4\u300b\u7684\u4ecb\u7ecd\u5c31\u5230\u6b64\u7ed3\u675f\u5566\uff0c\u4f46\u662f\u5b66\u65e0\u6b62\u5883\uff0c\u60f3\u8981\u4e86\u89e3\u5b66\u4e60\u66f4\u591a\u5173\u4e8e\u6587\u7ae0\u7684\u76f8\u5173\u77e5\u8bc6\uff0c\u8bf7\u5173\u6ce8\u7c73\u4e91\u516c\u4f17\u53f7\uff01<\/p>\n
      \n
      <\/dt>\n
      \n   \u4ecb\u7ecd\u5e38\u7528\u7684Java\u8bed\u8a00\u4e0b\u7684\u6301\u7eed\u96c6\u6210\u5de5\u5177\n <\/dd>\n<\/dl>\n","protected":false},"excerpt":{"rendered":"
      Linux\u7cfb\u7edf\u4e0b\u4f7f\u7528RStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u8bbe\u7f6e\u6b65\u9aa4 \u4ece\u73b0\u5728\u5f00\u59cb\uff0c\u6211\u4eec\u8981\u52aa\u529b\u5b66\u4e60\u5566\uff01\u4eca\u5929\u6211\u7ed9\u5927\u5bb6\u5e26\u6765\uff0c\u611f\u5174\u8da3\u7684\u670b\u53cb\u8bf7\u7ee7\u7eed\u770b\u4e0b\u53bb\u5427\uff01\u4e0b\u6587\u4e2d\u7684\u5185\u5bb9\u6211\u4eec\u4e3b\u8981\u4f1a\u6d89\u53ca\u5230\u7b49\u7b49\u77e5\u8bc6\u70b9\uff0c\u5982\u679c\u5728\u9605\u8bfb\u672c\u6587\u8fc7\u7a0b\u4e2d\u6709\u9047\u5230\u4e0d\u6e05\u695a\u7684\u5730\u65b9\uff0c\u6b22\u8fce\u7559\u8a00\u5440\uff01\u6211\u4eec\u4e00\u8d77\u8ba8\u8bba\uff0c\u4e00\u8d77\u5b66\u4e60\uff01 \u5728Linux\u7cfb\u7edf\u4e0a\u4f7f\u7528RStudio\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u914d\u7f6e\u65b9\u6cd5 \u6458\u8981\uff1aRStudio\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u96c6\u6210\u5f00\u53d1\u73af\u5883\uff0c\u9002\u7528\u4e8eR\u8bed\u8a00\u7684\u5f00\u53d1\u548c\u6570\u636e\u5206\u6790\u3002\u672c\u6587\u5c06\u4ecb\u7ecd\u5982\u4f55\u5728Linux\u7cfb\u7edf\u4e0a\u5b89\u88c5\u548c\u914d\u7f6eRStudio\uff0c\u5e76\u5229\u7528\u5176\u6570\u636e\u53ef\u89c6\u5316\u529f\u80fd\u3002 \u5b89\u88c5R\u548cRStudio \u5728Linux\u7cfb\u7edf\u4e0a\u5b89\u88c5R\u548cRStudio\u662f\u5f00\u59cb\u914d\u7f6e\u8fc7\u7a0b\u7684\u7b2c\u4e00\u6b65\u3002\u6839\u636e\u4f60\u7684Linux\u53d1\u884c\u7248\u672c\uff0c\u53ef\u4ee5\u91c7\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b8c\u6210\u5b89\u88c5\uff1a1.1 Ubuntu\/Debian: sudo apt-get update sudo apt-get install r-base r-base-dev 1.2 CentOS\/Fedora: sudo yum install R \u5b89\u88c5RStudio\u53ef\u4ee5\u901a\u8fc7\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u5bf9\u5e94\u7684\u5b89\u88c5\u5305\u8fdb\u884c\u5b89\u88c5\u3002\u4e0b\u8f7d\u5730\u5740\uff1ahttps:\/\/www.rstudio.com\/products\/rstudio\/download\/ \u5b89\u88c5R\u5305\u548c\u4f9d\u8d56\u9879 R\u5305\u662fR\u8bed\u8a00\u7684\u6269\u5c55\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u548c\u53ef\u89c6\u5316\u529f\u80fd\u3002\u5728RStudio\u4e2d\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u9700\u8981\u5b89\u88c5\u76f8\u5173\u7684R\u5305\u3002\u6253\u5f00RStudio\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5b89\u88c5\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5305\uff1a install.packages(c(“ggplot2”, “plotly”, “leaflet”, “shiny”)) \u8fd9\u5c06\u4f1a\u5b89\u88c5ggplot2\u3001plotly\u3001leaflet\u548cshiny\u5305\u3002 RStudio\u914d\u7f6e 3.1 \u81ea\u5b9a\u4e49\u8bbe\u7f6e\u5728RStudio\u4e2d\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u9009\u62e9”Tools” -> “Global Options”\u6765\u8fdb\u884c\u81ea\u5b9a\u4e49\u8bbe\u7f6e\u3002\u5728”Appearance”\u9009\u9879\u5361\u4e0b\uff0c\u53ef\u4ee5\u8c03\u6574\u7f16\u8f91\u5668\u7684\u5b57\u4f53\u3001\u5927\u5c0f\u548c\u4e3b\u9898\u989c\u8272\u3002\u5728”Code”\u9009\u9879\u5361\u4e0b\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u4ee3\u7801\u7f29\u8fdb\u3001\u81ea\u52a8\u62fc\u5199\u68c0\u67e5\u548c\u81ea\u52a8\u5b8c\u6210\u7b49\u3002 3.2 \u914d\u7f6eRMarkdownRMarkdown\u662fRStudio\u4e2d\u7528\u4e8e\u751f\u6210\u62a5\u544a\u548c\u6587\u6863\u7684\u5f3a\u5927\u5de5\u5177\u3002\u5728”RMarkdown”\u9009\u9879\u5361\u4e0b\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u9ed8\u8ba4\u7684\u8f93\u51fa\u683c\u5f0f\u548c\u6837\u5f0f\uff0c\u5982HTML\u3001PDF\u3001Word\u7b49\u3002 \u6570\u636e\u53ef\u89c6\u5316\u793a\u4f8b \u63a5\u4e0b\u6765\uff0c\u5c06\u901a\u8fc7\u51e0\u4e2a\u4f8b\u5b50\u6765\u5c55\u793aRStudio\u7684\u6570\u636e\u53ef\u89c6\u5316\u529f\u80fd\u3002 4.1 \u4f7f\u7528ggplot2\u7ed8\u5236\u6563\u70b9\u56feggplot2\u662f\u4e00\u4e2a\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5305\uff0c\u53ef\u4ee5\u7ed8\u5236\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7ed8\u5236\u6563\u70b9\u56fe\u7684\u793a\u4f8b\u4ee3\u7801\uff1a library(ggplot2) data <- read.csv(“data.csv”) ggplot(data, aes(x=age, y=income, color=gender)) + geom_point() \u8fd9\u6bb5\u4ee3\u7801\u5c06\u4ece\u4e00\u4e2a\u540d\u4e3a”data.csv”\u7684\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e\uff0c\u7136\u540e\u4f7f\u7528age\u548cincome\u4f5c\u4e3a\u6a2a\u7eb5\u5750\u6807\uff0cgender\u4f5c\u4e3a\u989c\u8272\u6765\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u6563\u70b9\u56fe\u3002 4.2 \u4f7f\u7528plotly\u7ed8\u5236\u4ea4\u4e92\u5f0f\u56fe\u8868 plotly\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u4ea4\u4e92\u5f0f\u6570\u636e\u53ef\u89c6\u5316\u5305\uff0c\u53ef\u4ee5\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u997c\u56fe\u548c\u70ed\u56fe\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7ed8\u5236\u6298\u7ebf\u56fe\u7684\u793a\u4f8b\u4ee3\u7801\uff1a 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