{"id":472,"date":"2023-07-29T19:19:54","date_gmt":"2023-07-29T19:19:54","guid":{"rendered":"https:\/\/statorials.org\/hi\/%e0%a4%b9%e0%a5%80%e0%a4%9f%e0%a4%ae%e0%a5%88%e0%a4%aa-%e0%a4%86%e0%a4%b0-ggplot2\/"},"modified":"2023-07-29T19:19:54","modified_gmt":"2023-07-29T19:19:54","slug":"%e0%a4%b9%e0%a5%80%e0%a4%9f%e0%a4%ae%e0%a5%88%e0%a4%aa-%e0%a4%86%e0%a4%b0-ggplot2","status":"publish","type":"post","link":"https:\/\/statorials.org\/hi\/%e0%a4%b9%e0%a5%80%e0%a4%9f%e0%a4%ae%e0%a5%88%e0%a4%aa-%e0%a4%86%e0%a4%b0-ggplot2\/","title":{"rendered":"Ggplot2 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 r \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u0915\u0948\u0938\u0947 \u092c\u0928\u093e\u090f\u0902"},"content":{"rendered":"

<\/p>\n

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\u092f\u0939 \u091f\u094d\u092f\u0942\u091f\u094b\u0930\u093f\u092f\u0932 \u092c\u0924\u093e\u0924\u093e \u0939\u0948 \u0915\u093f ggplot2 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 R \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u0915\u0948\u0938\u0947 \u092c\u0928\u093e\u092f\u093e \u091c\u093e\u090f\u0964<\/span><\/p>\n

\u0909\u0926\u093e\u0939\u0930\u0923: \u0906\u0930 \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u092c\u0928\u093e\u0928\u093e<\/span><\/strong><\/h3>\n

\u0939\u0940\u091f\u092e\u0948\u092a \u092c\u0928\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f, \u0939\u092e \u0905\u0902\u0924\u0930\u094d\u0928\u093f\u0939\u093f\u0924 R \u0921\u0947\u091f\u093e\u0938\u0947\u091f mtcars<\/strong> \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0947\u0902\u0917\u0947\u0964<\/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
 \u0935\u0930\u094d\u0924\u092e\u093e\u0928 \u092e\u0947\u0902 \u090f\u092e\u091f\u0940\u0915\u093e\u0930\u094d\u0938<\/strong> \u090f\u0915 \u0935\u093f\u0938\u094d\u0924\u0943\u0924 \u092a\u094d\u0930\u093e\u0930\u0942\u092a \u092e\u0947\u0902 \u0939\u0948, \u0932\u0947\u0915\u093f\u0928 \u0939\u0940\u091f\u092e\u0948\u092a \u092c\u0928\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0939\u092e\u0947\u0902 \u0907\u0938\u0947 \u090f\u0915 \u0932\u0902\u092c\u0947 \u092a\u094d\u0930\u093e\u0930\u0942\u092a \u092e\u0947\u0902 \u092e\u093f\u0936\u094d\u0930\u093f\u0924 \u0915\u0930\u0928\u0947 \u0915\u0940 \u0906\u0935\u0936\u094d\u092f\u0915\u0924\u093e \u0939\u0948\u0964<\/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
 \u0939\u092e ggplot2 \u092e\u0947\u0902 \u0939\u0940\u091f\u092e\u0948\u092a \u092c\u0928\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0915\u094b\u0921 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/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
 \u0926\u0941\u0930\u094d\u092d\u093e\u0917\u094d\u092f \u0938\u0947, \u0915\u094d\u092f\u094b\u0902\u0915\u093f \u0921\u093f\u0938\u094d\u092a<\/em> \u0915\u093e \u092e\u093e\u0928 \u0921\u0947\u091f\u093e \u092b\u093c\u094d\u0930\u0947\u092e \u092e\u0947\u0902 \u0905\u0928\u094d\u092f \u0938\u092d\u0940 \u0935\u0947\u0930\u093f\u090f\u092c\u0932\u094d\u0938 \u0915\u0947 \u092e\u093e\u0928\u094b\u0902 \u0938\u0947 \u092c\u0939\u0941\u0924 \u092c\u0921\u093c\u093e \u0939\u0948, \u0907\u0938\u0932\u093f\u090f \u0905\u0928\u094d\u092f \u0935\u0947\u0930\u093f\u090f\u092c\u0932\u094d\u0938 \u0915\u0947 \u0930\u0902\u0917 \u092d\u093f\u0928\u094d\u0928\u0924\u093e \u0915\u094b \u0926\u0947\u0916\u0928\u093e \u092e\u0941\u0936\u094d\u0915\u093f\u0932 \u0939\u0948\u0964<\/span><\/p>\n
 \u0907\u0938 \u0938\u092e\u0938\u094d\u092f\u093e \u0915\u094b \u0939\u0932 \u0915\u0930\u0928\u0947 \u0915\u093e \u090f\u0915 \u0924\u0930\u0940\u0915\u093e \u0938\u094d\u0915\u0947\u0932\u094d\u0938() \u092a\u0948\u0915\u0947\u091c \u092e\u0947\u0902 \u0930\u0940\u0938\u094d\u0915\u0947\u0932()<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0914\u0930 plyr() \u092a\u0948\u0915\u0947\u091c \u092e\u0947\u0902 ddply()<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 \u092a\u094d\u0930\u0924\u094d\u092f\u0947\u0915 \u0935\u0947\u0930\u093f\u090f\u092c\u0932 \u0915\u0947 \u092e\u093e\u0928\u094b\u0902 \u0915\u094b 0 \u0938\u0947 1 \u0924\u0915 \u092a\u0941\u0928\u0903 \u0938\u094d\u0915\u0947\u0932 \u0915\u0930\u0928\u093e \u0939\u0948:<\/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
 \u0939\u092e \u0938\u094d\u0915\u0947\u0932_\u092b\u093f\u0932_\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f() \u0924\u0930\u094d\u0915 \u092e\u0947\u0902 \u0909\u092a\u092f\u094b\u0917 \u0915\u093f\u090f \u0917\u090f \u0930\u0902\u0917\u094b\u0902 \u0915\u094b \u092c\u0926\u0932\u0915\u0930 \u0939\u0940\u091f\u092e\u0948\u092a \u0915\u0947 \u0930\u0902\u0917 \u092d\u0940 \u092c\u0926\u0932 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/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
 \u0927\u094d\u092f\u093e\u0928 \u0926\u0947\u0902 \u0915\u093f \u0939\u0940\u091f\u092e\u0948\u092a \u0915\u094b \u0935\u0930\u094d\u0924\u092e\u093e\u0928 \u092e\u0947\u0902 \u0915\u093e\u0930 \u0915\u0947 \u0928\u093e\u092e \u0938\u0947 \u0935\u0930\u094d\u0917\u0940\u0915\u0943\u0924 \u0915\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u0907\u0938\u0915\u0947 \u092c\u091c\u093e\u092f \u0939\u092e \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0915\u094b\u0921 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 mpg<\/em> \u091c\u0948\u0938\u0947 \u0915\u093f\u0938\u0940 \u090f\u0915 \u0935\u0947\u0930\u093f\u090f\u092c\u0932 \u0915\u0947 \u092e\u093e\u0928 \u0915\u0947 \u0905\u0928\u0941\u0938\u093e\u0930 \u0939\u0940\u091f\u092e\u0948\u092a \u0915\u094b \u0911\u0930\u094d\u0921\u0930 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/span><\/p>\n
 #define car name as a new column, then order by mpg<\/em> descending\n<\/span>mtcars$car <- row.names(mtcars)\nmtcars$car <- with(mtcars, reorder(car, mpg))\n\n#melt mtcars into long format\n<\/span>melt_mtcars <- melt(mtcars)\n\n#rescale values for all variables in melted data frame\n<\/span>melt_mtcars <- ddply(melt_mtcars, .(variable), transform, rescale = rescale(value))\n\n#create heatmap using rescaled values\n<\/span>ggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"steelblue\")<\/strong><\/pre>\n
 mpg<\/em> \u0915\u094b \u092c\u0922\u093c\u093e\u0915\u0930 \u0939\u0940\u091f\u092e\u0948\u092a \u0915\u094b \u0938\u0949\u0930\u094d\u091f \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f, \u092c\u0938 reorder() \u0924\u0930\u094d\u0915 \u092e\u0947\u0902 -mpg \u0915\u093e<\/strong> \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0947\u0902:<\/span><\/p>\n
 #define car name as a new column, then order by mpg descending\n<\/span>mtcars$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
 \u0905\u0902\u0924 \u092e\u0947\u0902, \u092f\u0926\u093f \u0939\u092e\u0947\u0902 labs() \u0914\u0930 \u0925\u0940\u092e() \u0924\u0930\u094d\u0915\u094b\u0902 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0928\u0947 \u0915\u093e \u0924\u0930\u0940\u0915\u093e \u092a\u0938\u0902\u0926 \u0928\u0939\u0940\u0902 \u0939\u0948 \u0924\u094b \u0939\u092e x \u0914\u0930 y \u0905\u0915\u094d\u0937 \u0932\u0947\u092c\u0932 \u0915\u0947 \u0938\u093e\u0925-\u0938\u093e\u0925 \u0932\u0947\u091c\u0947\u0902\u0921 \u0915\u094b \u092d\u0940 \u0939\u091f\u093e \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/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":"
\u092f\u0939 \u091f\u094d\u092f\u0942\u091f\u094b\u0930\u093f\u092f\u0932 \u092c\u0924\u093e\u0924\u093e \u0939\u0948 \u0915\u093f ggplot2 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 R \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u0915\u0948\u0938\u0947 \u092c\u0928\u093e\u092f\u093e \u091c\u093e\u090f\u0964 \u0909\u0926\u093e\u0939\u0930\u0923: \u0906\u0930 \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u092c\u0928\u093e\u0928\u093e \u0939\u0940\u091f\u092e\u0948\u092a \u092c\u0928\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f, \u0939\u092e \u0905\u0902\u0924\u0930\u094d\u0928\u093f\u0939\u093f\u0924 R \u0921\u0947\u091f\u093e\u0938\u0947\u091f mtcars \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0947\u0902\u0917\u0947\u0964 #view first six rows of mtcars head(mtcars) # mpg cyl disp hp drat wt qsec vs am gear carb #Mazda RX4 […]<\/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":[],"class_list":["post-472","post","type-post","status-publish","format-standard","hentry","category-3"],"yoast_head":"\nGgplot2 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 R \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u0915\u0948\u0938\u0947 \u092c\u0928\u093e\u090f\u0902 - \u0938\u094d\u091f\u0947\u091f\u094b\u0932\u0949\u091c\u0940<\/title>\n<meta name=\"description\" content=\"\u092f\u0939 \u091f\u094d\u092f\u0942\u091f\u094b\u0930\u093f\u092f\u0932 \u092c\u0924\u093e\u0924\u093e \u0939\u0948 \u0915\u093f ggplot2 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 R \u092e\u0947\u0902 \u0939\u0940\u091f \u092e\u0948\u092a \u0915\u0948\u0938\u0947 \u092c\u0928\u093e\u092f\u093e \u091c\u093e\u090f\u0964\" \/>\n<meta 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