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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
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
1. Pearson Pearson correlation coefficientPearson's correlation coefficient is also known as Pearson's correlation coefficient, which is used to reflect the statistical similarity between the two variables. Or to represent the similarity of two vectors. Pearson's correlation coefficient is calculated as follows: The
First, what is Pearson product-moment correlation coefficient (simple correlation coefficient)?Related tables andRelated diagramscan reflect the relationship between the two variables and their related directions, but it is not possible to indicate exactlyTwo variablesbetweenrelatedthe degree. So the famous statisticianCarl Piersonhas designedStatistical indicators--cor
Kendall rank (Kendel level) correlation coefficient 1. Introduction In statistics, the Kendel correlation coefficient is named after Maurice Kendall, and is often expressed by the Greek letter Tau (Tau. The kender correlation coefficient is a statistical value used to measure the correlation between two random variable
About LoadRunner AssociationsFirst, when to associate1. Meaning of the AssociationAssociation (correlation): InDuring the script playback process,The client makes a request through the left and right boundary values (that is, association rules) defined by the correlation function,The server responds by looking in the content, gets the corresponding value, replaces the variable in the formThe static value at
Linear correlation of the first section vector group A Mathematical Concepts Defines 1.1 n ordered numbers, the array of which is called an n-dimensional vector, which is called n components of the vector, and the number I is called the first component. Definition 1. 2 to the directional measure group A:, for any set of real numbers, vectors A linear combination called a vector group A, called the coefficient of this linear combination. Define 3 to t
For example, "the higher the intelligence of the Three Kingdoms, the higher the politics", or "whether the higher the Force, the higher the command;"Prepare the data Analysis environment:SELECT * from FactSanguo11 WHERE inch (n' xunyu ', n' zhow ', n' brag ' , n' cheng Yufan ', n' guo Jia ' )Cao Wei adviser, refers to Xunyu, Zhow, brag, Cheng Yufan, Guo Jia five people. Because these five people have great contribution to the establishment and consolidation of Cao Wei forces, so they are
can be ignored, such as thinking time ). After this option is selected, click "correlation" to automatically associate it. After Association, open the Script View and view the web_reg_save_param_ex function. The dynamic values between lb and rbare saved to correlationparameter_1. However, if we find that the user session ID cannot be the same if it is saved Based on the automatically associated left and right boundaries, this only means that the us
Gcta, described in the article "Genome-wide Complex Trait Analysis (GCTA)-genome-wide complexity profiling", is an analytical tool based on the development of Genome-wide association analysis, in addition to calculating genetic correlations between different traits/phenotype (traits) , you can also calculate the relationship, the near-cross coefficient ..., the following is a brief introduction to the use of gcta to calculate the genetic correlation o
The relationship between a person and an identity card is a typical one-to-one association. There are two ways to implement a one-to-one correlation mapping, which is based on the foreign key, and one is based on the primary key, and we look at the foreign key-based correlation method.First look at their entity classes.Person classPackage Entity;public class Person {private Integer id;private String name;pr
>> One-way: Write only one end of the mapping attribute, the other end is not written (one end is not necessary); bidirectional: Write mapped properties on both sidesThere are two types of >> one-to association: a class of primary key-based ( generally not used ), a class of foreign key-based (key learning);Foreign key: is a normal field, and the value of the field is the primary key of the other table. For example, a field in a table is the primary key of table B, so he can be a foreign key to
The correlation coefficient of measurement correlation is many, the calculation method and characteristics of various parameters are different.Related indicators for continuous variables:At this time, the correlation coefficient of product difference is generally used, also called Pearson Correlation coefficient, and t
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