r ggplot2

In the process of drawing, sometimes we may need to add some lines, so that the visualization of the graph becomes better, such as some trend lines and so on.Let's take a look at some of the ways the lines are added.Geom_abline (mapping = NULL, data = NULL, ..., slope, intercept, na.rm = FALSE, show.legend = NA) geom_hline (mapping = NULL, data = null, ..., yintercept, na.rm = FALSE, show.legend = NA) geom_vline (mapping = NULL, data = NULL, ..., xintercept, NA . RM = FALSE, show.legend = NA) Th

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 (

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

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 (),

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

Ggplot2 () function Ggplot2 is a powerful mapping tool that allows you to create any graphics that will help you solve your problems without being limited by existing graphics types. Qplot () Qplot () belongs to Ggplot2 () and can be understood as a simplified version of it.Qplot is "rapid mapping" (quick plot), as the name suggests, can quickly data visualizatio

---restore content starts---Install the package and load> install.packages (' Gcookbook ')>install.packages (' Ggplot2 ')> Library (GGPLOT2)Or: Install.packages (' Ggplot2 ', ' Gcokbook ')> Library (Gcookbook)To set the working path:SETWD ("D:/data")GETWD ()[1] "D:/data"Read file> Data > DataX1 X3.8.1941 X1.1.20071 2 1/24/1972 1/1/20072 3 6/1/1932 1/1/20073 4 5/1

factor as an example:> Levels (Singer$voice.part) [1] "Bass 2" "Bass 1" "Tenor 2" "Tenor 1" "Alto 2" "Alto 1" " Soprano 2 "[8]" Soprano 1 "16.3 Ggplot2 BagThe Ggplot2 package provides a drawing system based on a comprehensive and coherent syntax. It makes up for the lack of consistency in creating graphics in RThe ability to create innovative and novel graphic types. The simplest way to dra

.vcf Mills_and_1000G_gold_standard.indels.hg19.vcf.idx (3) R settingsGatk Some of the steps require the use of R to draw some graphs, some r packages are called at this point. If you use r without these packages, you will not be able to generate PDF files. Therefore, some necessary r packages must be installed, including (but not limited to) the following: Bitops Catools ColorSpace Gdata Ggplot2 Gplots

, FloatVectorfrom rpy2.robjects.lib import gridfrom rpy2.robjects.packages import importr, dataimport rpy2.robjects.lib.ggplot2 as ggplot2 # The R 'print' functionrprint = robjects.globalenv.get("print")stats = importr('stats')grdevices = importr('grDevices')base = importr('base')datasets = importr('datasets') mtcars = data(datasets).fetch('mtcars')['mtcars'] pp = ggplot2.ggplot(mtcars) + \

.robjects.lib.ggplot2 as ggplot2 # The R 'print' functionrprint = robjects.globalenv.get("print")stats = importr('stats')grdevices = importr('grDevices')base = importr('base')datasets = importr('datasets') mtcars = data(datasets).fetch('mtcars')['mtcars'] pp = ggplot2.ggplot(mtcars) + \ ggplot2.aes_string(x='wt', y='mpg', col='factor(cyl)') + \

Canadian team, based on HTML5 and D3, unfortunately for various reasons failed to market) Now more and more people are starting to use Python to do data analysis, IPython notebook is particularly popular, its real-time interaction to the scripting language advantage to play to the extreme. So how can you use Ggplot in Ipython notebook? I am here to share with you three different ways for you to choose.RPy2 The first is to use Rpy2, Rpy2 is a rewrite and redesign of Rpy, designed to provide Pyth

.robjects.lib.ggplot2 as Ggplot2 # the R ' print ' function rprint = Robjects.globalenv.get (" print ") stats = importr (' stats ') grdevices = Importr (' grdevices ') base = Importr (' base ') datasets = IMPORTR (' Datasets ') mtcars = data (datasets). Fetch (' mtcars ') [' Mtcars '] pp = Ggplot2.ggplot (mtcars) + \ ggplot2.aes_string (x= ' wt ', y= ' m

, respectively, is bou2_4p.dbf,dou2_4p.shp,bou2_4p.shx, the number 1~4 respectively represents the state, province, city, county, 4 administrative division, the letter P end of the expression polygon data, used to draw the area, BOU2 is the boundary of Provincial administrative division. This data is not the latest data, the latest data in the National Basic Geographic Information Center can not be found, probably to buy to get, but for the general drawing, this data has been able to meet the re

12858 available packages. "The package on CRAN involves all aspects of Bayesian analysis, operations research, finance, genetic analysis, genetics, and continues to be new and iterative. Programmable: R itself is an interpreted language that can be used to control execution through code, and can be invoked with Python and the Java language through software packages such as Rpython and Rjava. Powerful data-handling capabilities: Data source access: Through Rmysql, Sparkr, elas

Typical data analysis steps:R Language: Language and environment for statistical calculations and plottingData analysis: Statistics, machine learningUse of R1. Case-sensitive, interpreted language2. R Statement Assignment: 3. R Comment: #4. Create vector C ()5. Watch Demo List demo (), Graphic demo demo (graphics)6. Help function7. GETWD () View current working directory, SETWD () set Current working directorySETWD (' e:\\ ') GETWD () [1] "e:/"8. Working space management functions9. Input and ou