{"id":474,"date":"2023-07-29T19:19:54","date_gmt":"2023-07-29T19:19:54","guid":{"rendered":"https:\/\/statorials.org\/tr\/isi-haritasi-r-ggplot2\/"},"modified":"2023-07-29T19:19:54","modified_gmt":"2023-07-29T19:19:54","slug":"isi-haritasi-r-ggplot2","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/isi-haritasi-r-ggplot2\/","title":{"rendered":"Ggplot2 kullanarak r'de \u0131s\u0131 haritas\u0131 nas\u0131l olu\u015fturulur"},"content":{"rendered":"

<\/p>\n

\n

Bu e\u011fitimde, ggplot2 kullan\u0131larak R’de bir \u0131s\u0131 haritas\u0131n\u0131n nas\u0131l olu\u015fturulaca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n

\u00d6rnek: R’de Is\u0131 Haritas\u0131 Olu\u015fturma<\/span><\/strong><\/h3>\n

Bir \u0131s\u0131 haritas\u0131 olu\u015fturmak i\u00e7in yerle\u015fik R veri k\u00fcmesi mtcars’\u0131<\/strong> kullanaca\u011f\u0131z.<\/span><\/p>\n

 #view first six rows of mtcars\n<\/em><\/span>head(mtcars)\n\n# mpg cyl disp hp drat wt qsec vs am gear carb\n#Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4\n#Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4\n#Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1\n#Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1\n#Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2\n#Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1\n<\/strong><\/pre>\n
 \u015eu anda mtcars<\/strong> geni\u015f formatta ancak \u0131s\u0131 haritas\u0131n\u0131 olu\u015fturabilmek i\u00e7in onu uzun formatta harmanlamam\u0131z gerekiyor.<\/span><\/p>\n
 #load reshape2<\/em> package to use melt() function<\/span>\nlibrary(reshape2)\n\n#melt mtcars into long format<\/span>\nmelt_mtcars <- melt(mtcars)\n\n#add column for car name<\/span>\nmelt_mtcars$car <- rep(row.names(mtcars), 11)\n\n#view first six rows of melt_mtcars<\/em><\/span>\nhead(melt_mtcars)\n\n# variable value char\n#1 mpg 21.0 Mazda RX4\n#2 mpg 21.0 Mazda RX4 Wag\n#3 mpg 22.8 Datsun 710\n#4 mpg 21.4 Hornet 4 Drive\n#5 mpg 18.7 Hornet Sportabout\n#6 mpg 18.1 Valiant<\/strong><\/pre>\n
 Ggplot2’de \u0131s\u0131 haritas\u0131n\u0131 olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n
 library(ggplot2)\n\nggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = value),<\/strong> color = \"white\") +\n  scale_fill_gradient(low = \"white\",<\/strong> high = \"red\")<\/strong><\/pre>\n
 Ne yaz\u0131k ki disp<\/em> de\u011ferleri veri \u00e7er\u00e7evesindeki di\u011fer t\u00fcm de\u011fi\u015fkenlerin de\u011ferlerinden \u00e7ok daha b\u00fcy\u00fck oldu\u011fundan di\u011fer de\u011fi\u015fkenlerin renk de\u011fi\u015fimini g\u00f6rmek zordur.<\/span><\/p>\n
 Bu sorunu \u00e7\u00f6zmenin bir yolu, Scales() paketindeki rescale()<\/strong> fonksiyonunu ve plyr() paketindeki ddply()<\/strong> fonksiyonunu kullanarak her de\u011fi\u015fkenin de\u011ferini 0’dan 1’e yeniden \u00f6l\u00e7eklendirmektir:<\/span><\/p>\n
 #load libraries<\/span>\nlibrary(plyr)\nlibrary(scales)\n\n#rescale values for all variables in melted data frame<\/span>\nmelt_mtcars <- ddply(melt_mtcars, .(variable), transform, rescale = rescale(value))\n\n#create heatmap using rescaled values<\/span>\nggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"red\")\n<\/strong><\/pre>\n
 Scale_fill_gradient() ba\u011f\u0131ms\u0131z de\u011fi\u015fkeninde kullan\u0131lan renkleri de\u011fi\u015ftirerek \u0131s\u0131 haritas\u0131 renklerini de de\u011fi\u015ftirebiliriz:<\/span><\/p>\n
 #create heatmap using blue color scale\n<\/span>ggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"steelblue\")<\/strong><\/pre>\n
 Is\u0131 haritas\u0131n\u0131n \u015fu anda ara\u00e7 ad\u0131na g\u00f6re kategorize edildi\u011fini unutmay\u0131n. Bunun yerine a\u015fa\u011f\u0131daki kodu kullanarak \u0131s\u0131 haritas\u0131n\u0131 mpg<\/em> gibi de\u011fi\u015fkenlerden birinin de\u011ferlerine g\u00f6re s\u0131ralayabiliriz:<\/span><\/p>\n
 #define car name as a new column, then order by mpg<\/em> descending\n<\/span>mtcars$car <- row.names(mtcars)\nmtcars$car <- with(mtcars, reorder(car, mpg))\n\n#melt mtcars into long format\n<\/span>melt_mtcars <- melt(mtcars)\n\n#rescale values for all variables in melted data frame\n<\/span>melt_mtcars <- ddply(melt_mtcars, .(variable), transform, rescale = rescale(value))\n\n#create heatmap using rescaled values\n<\/span>ggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"steelblue\")<\/strong><\/pre>\n
 Is\u0131 haritas\u0131n\u0131 mpg<\/em> de\u011ferini art\u0131rarak s\u0131ralamak i\u00e7in, reorder() arg\u00fcman\u0131nda -mpg komutunu<\/strong> kullanman\u0131z yeterlidir:<\/span><\/p>\n
 #define car name as a new column, then order by mpg descending\n<\/span>mtcars$car <- row.names(mtcars)\nmtcars$car <- with(mtcars, reorder(car, -mpg<\/span> ))\n\n#melt mtcars into long format\n<\/span>melt_mtcars <- melt(mtcars)\n\n#rescale values for all variables in melted data frame\n<\/span>melt_mtcars <- ddply(melt_mtcars, .(variable), transform, rescale = rescale(value))\n\n#create heatmap using rescaled values\n<\/span>ggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"steelblue\")<\/strong><\/pre>\n
 Son olarak, e\u011fer g\u00f6r\u00fcn\u00fc\u015f\u00fcn\u00fc be\u011fenmezsek, labs() ve theme() arg\u00fcmanlar\u0131n\u0131 kullanarak a\u00e7\u0131klaman\u0131n yan\u0131 s\u0131ra x ve y ekseni etiketlerini de kald\u0131rabiliriz:<\/span><\/p>\n
 #create heatmap with no axis labels or legend\n<\/span>ggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"steelblue\") +\n  labs(x = \"\", y = \"\") +\n  theme(legend.position = \"none\")<\/span><\/strong><\/pre>\n","protected":false},"excerpt":{"rendered":"
Bu e\u011fitimde, ggplot2 kullan\u0131larak R’de bir \u0131s\u0131 haritas\u0131n\u0131n nas\u0131l olu\u015fturulaca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r. \u00d6rnek: R’de Is\u0131 Haritas\u0131 Olu\u015fturma Bir \u0131s\u0131 haritas\u0131 olu\u015fturmak i\u00e7in yerle\u015fik R veri k\u00fcmesi mtcars’\u0131 kullanaca\u011f\u0131z. #view first six rows of mtcars head(mtcars) # mpg cyl disp hp drat wt qsec vs am gear carb #Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-474","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nGgplot2 Kullanarak R'de Is\u0131 Haritas\u0131 Nas\u0131l Olu\u015fturulur - Statorials<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde, ggplot2 kullan\u0131larak R'de bir \u0131s\u0131 haritas\u0131n\u0131n nas\u0131l olu\u015fturulaca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/tr\/isi-haritasi-r-ggplot2\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Ggplot2 Kullanarak R'de Is\u0131 Haritas\u0131 Nas\u0131l Olu\u015fturulur - 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