{"id":454,"date":"2023-07-29T20:27:57","date_gmt":"2023-07-29T20:27:57","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d1%8f%d0%ba-%d0%bf%d0%be%d0%b1%d1%83%d0%b4%d1%83%d0%b2%d0%b0%d1%82%d0%b8-%d0%ba%d1%96%d0%bb%d1%8c%d0%ba%d0%b0-%d0%bb%d1%96%d0%bd%d1%96%d0%b8-%d1%80%d1%8f%d0%b4%d0%ba%d1%96%d0%b2-%d0%b4%d0%b0%d0%bd\/"},"modified":"2023-07-29T20:27:57","modified_gmt":"2023-07-29T20:27:57","slug":"%d1%8f%d0%ba-%d0%bf%d0%be%d0%b1%d1%83%d0%b4%d1%83%d0%b2%d0%b0%d1%82%d0%b8-%d0%ba%d1%96%d0%bb%d1%8c%d0%ba%d0%b0-%d0%bb%d1%96%d0%bd%d1%96%d0%b8-%d1%80%d1%8f%d0%b4%d0%ba%d1%96%d0%b2-%d0%b4%d0%b0%d0%bd","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d1%8f%d0%ba-%d0%bf%d0%be%d0%b1%d1%83%d0%b4%d1%83%d0%b2%d0%b0%d1%82%d0%b8-%d0%ba%d1%96%d0%bb%d1%8c%d0%ba%d0%b0-%d0%bb%d1%96%d0%bd%d1%96%d0%b8-%d1%80%d1%8f%d0%b4%d0%ba%d1%96%d0%b2-%d0%b4%d0%b0%d0%bd\/","title":{"rendered":"\u042f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 (\u0440\u044f\u0434\u0456\u0432 \u0434\u0430\u043d\u0438\u0445) \u043d\u0430 \u043e\u0434\u043d\u0456\u0439 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0456 \u0432 r"},"content":{"rendered":"

<\/p>\n

\n

\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0443 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 (\u0442\u043e\u0431\u0442\u043e \u0440\u044f\u0434\u0456\u0432 \u0434\u0430\u043d\u0438\u0445) \u043d\u0430 \u043e\u0434\u043d\u0456\u0439 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0456 \u0432 R.<\/span><\/p>\n

\u0429\u043e\u0431 \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u0433\u0440\u0430\u0444\u0456\u043a\u0443, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 R \u0430\u0431\u043e \u0432\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u0438 \u0431\u0456\u043b\u044c\u0448 \u0441\u043a\u043b\u0430\u0434\u043d\u0438\u0439 \u043f\u0430\u043a\u0435\u0442, \u044f\u043a-\u043e\u0442 ggplot2.<\/span><\/p>\n

\u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f BaseR<\/strong><\/h2>\n

\u041e\u0441\u044c \u0434\u0432\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u0442\u043e\u0433\u043e, \u044f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u043e\u0434\u043d\u043e\u043c\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0443 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e Base R.<\/span><\/p>\n

\u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f Matplot<\/span><\/strong><\/h3>\n

\u042f\u043a\u0449\u043e \u0443 \u0432\u0430\u0441 \u0454 \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445 \u0432\u0435\u043b\u0438\u043a\u043e\u0433\u043e \u0444\u043e\u0440\u043c\u0430\u0442\u0443<\/a> , \u043f\u0440\u043e\u0441\u0442\u0438\u0439 \u0441\u043f\u043e\u0441\u0456\u0431 \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u0433\u0440\u0430\u0444\u0456\u043a\u0443 \u2014 \u0446\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 matplot:<\/span><\/p>\n

 #Create a fake dataset with 3 columns (ncol=3) composed of randomly generated\n#numbers from a uniform distribution with minimum = 1 and maximum = 10\n<\/span>data <- matrix(runif(30,1,10), ncol=3)\ndata\n        [,1] [,2] [,3]\n#[1,] 5.371653 3.490919 3.953603\n#[2,] 9.551883 2.681054 9.506765\n#[3,] 3.525686 1.027758 8.059011\n#[4,] 9.923080 1.337935 1.112361\n#[5,] 7.273972 7.627546 1.174340\n#[6,] 8.859109 3.778144 9.384526\n#[7,] 9.614542 3.866029 7.301729\n#[8,] 9.288085 5.804041 8.347907\n#[9,] 1.696849 4.650687 7.220209\n#[10,] 5.820941 4.799682 5.243663\n\n#plot the three columns of the dataset as three lines and add a legend in<\/span>\n#the top right corner of the chart<\/span>\nmatplot(data, type = \"b\",pch=1,col = 1:3)\nlegend(\"topright\", legend = 1:3, col=1:3, pch=1)\n<\/strong><\/pre>\n
 \u0426\u0435\u0439 \u043a\u043e\u0434 \u0441\u0442\u0432\u043e\u0440\u044e\u0454 \u0442\u0430\u043a\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a:<\/span><\/p>\n
 \u041f\u0440\u0438\u043a\u043b\u0430\u0434 2: \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u0442\u043e\u0447\u043e\u043a \u0456 \u043b\u0456\u043d\u0456\u0439<\/span><\/strong><\/h3>\n
 \u0429\u0435 \u043e\u0434\u0438\u043d \u0441\u043f\u043e\u0441\u0456\u0431 \u043d\u0430\u043c\u0430\u043b\u044e\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u2014 \u0446\u0435 \u043d\u0430\u043c\u0430\u043b\u044e\u0432\u0430\u0442\u0438 \u0457\u0445 \u043f\u043e \u0447\u0435\u0440\u0437\u0456 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u0432\u0431\u0443\u0434\u043e\u0432\u0430\u043d\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0456\u0439 R points() \u0456 lines(). \u041a\u043e\u0434 \u043d\u0438\u0436\u0447\u0435 \u043f\u043e\u043a\u0430\u0437\u0443\u0454 \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u0446\u044c\u043e\u0433\u043e \u043f\u0456\u0434\u0445\u043e\u0434\u0443:<\/span><\/p>\n
 #generate an x-axis along with three data series\n<\/span>x <- c(1,2,3,4,5,6)\ny1 <- c(2,4,7,9,12,19)\ny2 <- c(1,5,9,8,9,13)\ny3 <- c(3,6,12,14,17,15)\n<\/strong>\n#plot the first data series using plot()<\/span>\nplot(x, y1, type=\"o\", col=\"blue\", pch=\"o\", ylab=\"y\", lty=1)\n\n#add second data series to the same chart using points() and lines()\n<\/span>points(x, y2, col=\"red\", pch=\"*\")\nlines(x, y2, col=\"red\",lty=2)\n\n#add third data series to the same chart using points() and lines()<\/span>\npoints(x, y3, col=\"dark red\",pch=\"+\")\nlines(x, y3, col=\"dark red\", lty=3)\n\n#add a legend in top left corner of chart at (x, y) coordinates = (1, 19)\n<\/span>legend(1,19,legend=c(\"y1\",\"y2\",\"y3\"), col=c(\"blue\",\"red\",\"black\"),\n                                   pch=c(\"o\",\"*\",\"+\"),lty=c(1,2,3), ncol=1)<\/strong><\/pre>\n
 \u0426\u0435\u0439 \u043a\u043e\u0434 \u0441\u0442\u0432\u043e\u0440\u044e\u0454 \u0442\u0430\u043a\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a:<\/span><\/p>\n
 \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f ggplot2<\/strong><\/h2>\n
 \u041e\u0441\u044c \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u0442\u043e\u0433\u043e, \u044f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u043e\u0434\u043d\u043e\u043c\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0443 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e ggplot2.<\/span><\/p>\n
 #install (if not already installed) and load ggplot2 package<\/span>\nif(!require(ggplot2)){install.packages(' ggplot2<\/span> ')}\n\n#generate fake dataset with three columns 'x', 'value', and 'variable'<\/span>\ndata <- data. frame<\/span> (x=rep(1:5, 3),\n                   value=sample(1:100, 15), \n                   variable=rep(paste0(' series<\/span> ', 1:3), each=5))\n\n#view dataset\n<\/span>head(data)\n  x value variable\n1 1 93 series1\n2 2 64 series1\n3 3 36 series1\n4 4 17 series1\n5 5 95 series1\n6 1 80 series2\n\n#plot all three series on the same chart using geom_line()<\/span>\nggplot(data = data, aes(x=x, y=value)) + geom_line(aes(color=variable))\n<\/strong><\/pre>\n
 \u0426\u0435 \u0433\u0435\u043d\u0435\u0440\u0443\u0454 \u0442\u0430\u043a\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a:<\/span><\/p>\n
 \u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h3>\n
 \u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0445 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0430\u0445 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u043f\u043e\u0448\u0438\u0440\u0435\u043d\u0456 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 \u043f\u043e\u0431\u0443\u0434\u043e\u0432\u0438 \u0432 ggplot2:<\/span><\/p>\n
 \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u043f\u043e\u043b\u043e\u0436\u0435\u043d\u043d\u044f \u043b\u0435\u0433\u0435\u043d\u0434\u0438 \u0432 ggplot2<\/a>
 \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u043d\u0430\u0437\u0432\u0443 \u043b\u0435\u0433\u0435\u043d\u0434\u0438 \u0432 ggplot2<\/a>
 \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u043f\u043e\u043b\u044f \u0432 ggplot2<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0443 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 (\u0442\u043e\u0431\u0442\u043e \u0440\u044f\u0434\u0456\u0432 \u0434\u0430\u043d\u0438\u0445) \u043d\u0430 \u043e\u0434\u043d\u0456\u0439 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0456 \u0432 R. \u0429\u043e\u0431 \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u0433\u0440\u0430\u0444\u0456\u043a\u0443, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 R \u0430\u0431\u043e \u0432\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u0438 \u0431\u0456\u043b\u044c\u0448 \u0441\u043a\u043b\u0430\u0434\u043d\u0438\u0439 \u043f\u0430\u043a\u0435\u0442, \u044f\u043a-\u043e\u0442 ggplot2. \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f BaseR \u041e\u0441\u044c \u0434\u0432\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u0442\u043e\u0433\u043e, \u044f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u043e\u0434\u043d\u043e\u043c\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0443 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e Base R. \u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f Matplot […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"\n\u042f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 (\u0440\u044f\u0434\u0456\u0432 \u0434\u0430\u043d\u0438\u0445) \u043d\u0430 \u043e\u0434\u043d\u0456\u0439 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0456 \u0432 R - Statorials<\/title>\n<meta name=\"description\" content=\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u043d\u0430\u043c\u0430\u043b\u044e\u0432\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0430 \u043b\u0456\u043d\u0456\u0439 \u043d\u0430 \u0433\u0440\u0430\u0444\u0456\u043a\u0443 \u0432 R, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 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