{"id":472,"date":"2023-07-29T19:19:54","date_gmt":"2023-07-29T19:19:54","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%a1%e1%80%95%e1%80%b0%e1%80%99%e1%80%bc%e1%80%b1%e1%80%95%e1%80%af%e1%80%b6-r-ggplot2\/"},"modified":"2023-07-29T19:19:54","modified_gmt":"2023-07-29T19:19:54","slug":"%e1%80%a1%e1%80%95%e1%80%b0%e1%80%99%e1%80%bc%e1%80%b1%e1%80%95%e1%80%af%e1%80%b6-r-ggplot2","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/%e1%80%a1%e1%80%95%e1%80%b0%e1%80%99%e1%80%bc%e1%80%b1%e1%80%95%e1%80%af%e1%80%b6-r-ggplot2\/","title":{"rendered":"Ggplot2 \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d r \u1010\u103d\u1004\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038"},"content":{"rendered":"

<\/p>\n

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\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a ggplot2 \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d R \u1010\u103d\u1004\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u1025\u1015\u1019\u102c- R \u1016\u103c\u1004\u1037\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1001\u103c\u1004\u103a\u1038\u104b<\/span><\/strong><\/h3>\n

\u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u101e\u100a\u103a \u1010\u1015\u103a\u1006\u1004\u103a\u1011\u102c\u1038\u101e\u100a\u1037\u103a R dataset mtcars \u1000\u102d\u102f<\/strong> \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1015\u102b\u1019\u100a\u103a\u104b<\/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
 \u101c\u1031\u102c\u101c\u1031\u102c\u1006\u101a\u103a mtcars<\/strong> \u101e\u100a\u103a \u1000\u103b\u101a\u103a\u1015\u103c\u1014\u1037\u103a\u101e\u1031\u102c\u1016\u1031\u102c\u103a\u1019\u1010\u103a\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104a \u101e\u102d\u102f\u1037\u101e\u1031\u102c\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a\u1021\u1010\u103d\u1000\u103a \u104e\u1004\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u100a\u103a\u101c\u103b\u102c\u1038\u101e\u1031\u102c\u1016\u1031\u102c\u103a\u1019\u1010\u103a\u1021\u1016\u103c\u1005\u103a \u1015\u1031\u102b\u1004\u103a\u1038\u1005\u1015\u103a\u101b\u1014\u103a \u101c\u102d\u102f\u1021\u1015\u103a\u1015\u102b\u101e\u100a\u103a\u104b<\/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 \u1010\u103d\u1004\u103a heatmap \u1000\u102d\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/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
 \u1000\u1036\u1019\u1000\u1031\u102c\u1004\u103a\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a\u104a disp<\/em> \u104f\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u101e\u100a\u103a data frame \u101b\u103e\u102d \u1021\u1001\u103c\u102c\u1038\u101e\u1031\u102c variable \u1019\u103b\u102c\u1038\u1021\u102c\u1038\u101c\u102f\u1036\u1038\u104f\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1011\u1000\u103a \u1019\u103b\u102c\u1038\u1005\u103d\u102c\u1000\u103c\u102e\u1038\u1019\u102c\u1038\u101e\u1031\u102c\u1000\u103c\u1031\u102c\u1004\u1037\u103a\u104a \u1021\u1001\u103c\u102c\u1038 variable \u1019\u103b\u102c\u1038\u104f \u1021\u101b\u1031\u102c\u1004\u103a\u1000\u103d\u1032\u101c\u103d\u1032\u1019\u103e\u102f\u1000\u102d\u102f \u1019\u103c\u1004\u103a\u101b\u1014\u103a\u1001\u1000\u103a\u1001\u1032\u1015\u102b\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1024\u1015\u103c\u103f\u1014\u102c\u1000\u102d\u102f\u1016\u103c\u1031\u101b\u103e\u1004\u103a\u1038\u101b\u1014\u103a\u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1019\u103e\u102c 0 \u1019\u103e 1 \u1021\u1010\u103d\u1004\u103a\u1038\u101b\u103e\u102d variable \u1010\u1005\u103a\u1001\u102f\u1005\u102e\u104f\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f scale() \u1015\u1000\u103a\u1000\u1031\u1037\u1002\u103b\u103a\u101b\u103e\u102d scale( )<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1014\u103e\u1004\u1037\u103a plyr() \u1015\u1000\u103a\u1000\u1031\u1037\u1001\u103a\u103b\u101b\u103e\u102d ddply()<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u1015\u103c\u1014\u103a\u101c\u100a\u103a\u1001\u103b\u102d\u1014\u103a\u100a\u103e\u102d\u1001\u103c\u1004\u103a\u1038\u1016\u103c\u1005\u103a\u101e\u100a\u103a-<\/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() \u1021\u1004\u103c\u1004\u103a\u1038\u1021\u1001\u102f\u1036\u1010\u103d\u1004\u103a \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101e\u100a\u1037\u103a \u1021\u101b\u1031\u102c\u1004\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u103c\u1031\u102c\u1004\u103a\u1038\u101c\u1032\u1001\u103c\u1004\u103a\u1038\u1016\u103c\u1004\u1037\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1021\u101b\u1031\u102c\u1004\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101c\u100a\u103a\u1038 \u1015\u103c\u1031\u102c\u1004\u103a\u1038\u101c\u1032\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/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
 \u1021\u1015\u1030\u1015\u1031\u1038\u1019\u103c\u1031\u1015\u102f\u1036\u1000\u102d\u102f \u101c\u1000\u103a\u101b\u103e\u102d\u1010\u103d\u1004\u103a \u1000\u102c\u1038\u1021\u1019\u100a\u103a\u1016\u103c\u1004\u1037\u103a \u1021\u1019\u103b\u102d\u102f\u1038\u1021\u1005\u102c\u1038\u1001\u103d\u1032\u1001\u103c\u102c\u1038\u1011\u102c\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u1000\u102d\u102f\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d mpg<\/em> \u1000\u1032\u1037\u101e\u102d\u102f\u1037\u101e\u1031\u102c variable \u1019\u103b\u102c\u1038\u1011\u1032\u1019\u103e \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1021\u1010\u102d\u102f\u1004\u103a\u1038 \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1000\u102d\u102f \u1019\u103e\u102c\u101a\u1030\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n
 #define car name as a new column, then order by mpg<\/em> descending\n<\/span>mtcars$car <- row.names(mtcars)\nmtcars$car <- with(mtcars, reorder(car, mpg))\n\n#melt mtcars into long format\n<\/span>melt_mtcars <- melt(mtcars)\n\n#rescale values for all variables in melted data frame\n<\/span>melt_mtcars <- ddply(melt_mtcars, .(variable), transform, rescale = rescale(value))\n\n#create heatmap using rescaled values\n<\/span>ggplot(melt_mtcars, aes(variable, char)) +\n  geom_tile(aes(fill = rescale), color = \"white\") +\n  scale_fill_gradient(low = \"white\", high = \"steelblue\")<\/strong><\/pre>\n
 \u1005\u102d\u102f\u1004\u103a\u1038\u1005\u102d\u102f\u1004\u103a\u1038\u1001\u1019\u103a\u1038\u101c\u103e\u102d\u102f\u1004\u103a \u1000\u102d\u102f<\/em> \u1010\u102d\u102f\u1038\u1019\u103c\u103e\u1004\u1037\u103a\u1001\u103c\u1004\u103a\u1038\u1016\u103c\u1004\u1037\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1000\u102d\u102f \u1005\u102e\u101b\u1014\u103a\u104a \u101b\u102d\u102f\u1038\u101b\u103e\u1004\u103a\u1038\u1005\u103d\u102c \u1015\u103c\u1014\u103a\u1005\u102e\u101b\u1014\u103a() \u1021\u1004\u103c\u1004\u103a\u1038\u1021\u1001\u102f\u1036\u1010\u103d\u1004\u103a -mpg \u1000\u102d\u102f<\/strong> \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 #define car name as a new column, then order by mpg descending\n<\/span>mtcars$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
 \u1014\u1031\u102c\u1000\u103a\u1006\u102f\u1036\u1038\u1010\u103d\u1004\u103a\u104a labs() \u1014\u103e\u1004\u1037\u103a theme() \u1021\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1015\u103c\u1001\u103b\u1000\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u104e\u1004\u103a\u1038\u104f\u1015\u102f\u1036\u1015\u1014\u103a\u1038\u101e\u100f\u1039\u100d\u102c\u1014\u103a\u1000\u102d\u102f \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1019\u1000\u103c\u102d\u102f\u1000\u103a\u1015\u102b\u1000 x \u1014\u103e\u1004\u1037\u103a y \u101d\u1004\u103a\u101b\u102d\u102f\u1038\u1021\u100a\u103d\u103e\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1021\u1015\u103c\u1004\u103a \u1012\u100f\u1039\u100d\u102c\u101b\u102e\u1000\u102d\u102f \u1016\u101a\u103a\u101b\u103e\u102c\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/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":"
\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a ggplot2 \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d R \u1010\u103d\u1004\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b \u1025\u1015\u1019\u102c- R \u1016\u103c\u1004\u1037\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1001\u103c\u1004\u103a\u1038\u104b \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u101e\u100a\u103a \u1010\u1015\u103a\u1006\u1004\u103a\u1011\u102c\u1038\u101e\u100a\u1037\u103a R dataset mtcars \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1015\u102b\u1019\u100a\u103a\u104b #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 0 1 4 4 #Mazda RX4 Wag […]<\/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":"\nggplot2 - Statology \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d R \u1010\u103d\u1004\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a ggplot2 \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d R \u1010\u103d\u1004\u103a \u1021\u1015\u1030\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f 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