ggplot2 tutorial

Introduction We can also handle the axes of the graph, including x, y-axis swapping, setting axis range, tick mark modification and removal, and so on. In order to play the graphics, axis processing proficiency is indispensable. Axis Swap We use the Coord_flip () function to swap the axes. Library (GGPLOT2) Library (Gcookbook) Ggplot (Plantgrowth, AES (X=group, Y=weight)) + Geom_boxplot () Ggplot (Plantgrowth, AES (X=group, Y=weight)) + geom_boxplot (

diagram. Facets can be compared by placing different subclasses in different graphs:Qplot (carat, data = diamonds, facets = Color ~., Geom = "Histogram", Binwidth = 0.1, Xlim = C (0, 3))Qplot (carat, data = diamonds, facets = Color ~., Geom = "Histogram", Binwidth = 0.1, Xlim = C (0, 3))The following graphic adds new elements based on the beginning: faceted, multiple layers, and statistics. Facets and layers extend the data structures mentioned above: each layer of each facet has its own datase

Ggplot2 Scale Related SettingsScale settings: Mainly used to adjust settings for each layer after Ggplot drawing.1. Related attribute scale settingIncludes Scale_size (), Scale_alpha (), Scale_shape ()As you can see from the name above, these three settings are primarily related to the Ggplot layer properties, including size, transparency, and shape.The main parameters for this setting are listed below:SCALE_XXX (name = Waiver (), breaks = waiver (),

Plotting Roc curves with Ggplot2 packagesrocplot R language Drawing: Ggplot2 plotting Roc

Distribution in R should be regarded as a relatively important content, and by drawing to show the distribution of data, you can more intuitively let us understand the distribution of dataHistogramGeom_histogram (mapping = NULL, data = NULL, stat = "bin", Position = "stack", ..., binwidth = null, bins = NULL, NA.RM = F Alse, show.legend = NA, Inherit.aes = TRUE)Density mapgeom_density (mapping = NULL, data = NULL, stat = "density", Position = "identity", ..., na.rm = FALSE, show.legend = na, I N

1. There are currently four types of themesTheme_gray (), THEME_BW (), Theme_minimal (), Theme_classic ()2. x-Axis Setting scaleScale_x_continuous (Limits=c (1950,2000), Breaks=seq (1950,2000,5))3. Bar LineGgplot2 () +geom_bar (Aes (Y=x,fill=factor (GROUP.2)), stat="identity", position=' Dodge') +scale_x_continuous (Limits=c (38,50), Breaks=seq (38,50,1)) + geom_line (position= "identity", AES (Y=X))4. Ggplot-pieGgplot (Wm,aes (x="", Fill=type) + Geom_bar (width=1) + coord_polar (theta='y') )

#生成数据, used to demonstrate DAT Drawing a mirrored bar chart with Ggplot2

Data sampleFlanking mean SD CNV03651595510036715101820036915.1102530037015.1102740037215.2103150037315.3103260037515.3103370037715.3103480037815.4103490038015.41037A=read.table ("SDandCNV.txt", header=T) lilbrary ("ggplot2 " 1) layer1=ggplot (A,aes (Flanking,mean)) +geom_point (position=pd,size=3) +geom_errorbar ( AES (YMIN=MEAN-SD,YMAX=MEAN+SD), width=0.1, POSITION=PD) +geom_line (position=PD) Layer2=geom_ Line (Aes (y=CNV)) Layer3=geom_point (Aes

Introduction A line chart is generally used to describe a variable of one-dimensional variables as a continuous variable, which is usually time. In other words, a line chart is best suited to describe changes in time series data. Of course, with the change of discrete variables is also possible, but this discrete variable must be ordered. Draw a line chart A basic line chart is relatively simple, as long as the AES in the Ggplot x,y data and Geom designated as line. If x is a continuous variable

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