r ggplot2

=ToothGrowth, group.by = "dose", paired = TRUE)#可视化p Other graphical bar and line graphs (a grouping variable)#有误差棒的条形图，实际上我以前的文章里有纯粹用ggplot2实现ggbarplot(ToothGrowth, x="dose", y="len", add = "mean_se")+ stat_compare_means()+ stat_compare_means(ref.group = "0.5", label = "p.signif", label.y = c(22, 29))#有误差棒的线图ggline(ToothGrowth, x="dose", y="len", add = "mean_se")+stat_compare_means()+ stat_compare_means(ref.group = "0.5", label = "p.signif", label.y

language used for data exploration, statistical analysis and mapping, but more like a mathematical computing environment. It is rich in modules and provides a very convenient programming method for mathematical calculations, especially for matrix calculations.Advantages of the R language:1, the R language has many elegant and intuitive charts, the common Data Visualization toolkit is:· Interactive chart Rcharts, plotly, interactive sequence diagram dygraphs, interactive tree view TreeMap·

)Set.seed (1234)Devasknewpage (Ask=true)NcTable (Nc$best.n[1,])Barplot (Table (nc$best.n[1,]), xlab= "Number of Clusters", ylab= "number of Criteria", main= "number of Clusters Chosen by 26 Criteria ")Set.seed (1234)Fit.kmFit.km$sizeFit.km$centersCt.kmct.km1 2 31 59 0 02 3 65 33 0 0 48Library (Flexclust)Randindex (ct.km)Ari0.897495#围绕中心点的划分Library (Cluster)Set.seed (1234)Fit.pamFit.pam$methodClusplot (fit.pam,main= "bivariate Cluster Plot")Library (Flexclust)Randindex (Ct.pam)Ari0.6994957#围绕中心点的

Common packages:--Data processing: Lubridata, Plyr, RESHAPE2,STRINGR,FORMATR,MCMC;--Machine learning: nnet,rpart,tree,party,lars,boost,e1071,bayestree,gafit,arules;--Visual package: Ggplot2,lattice,googlevis;--Map package: Ggmap,rgooglemaps,rworldmap;Financial package:--time series: zoo,xts,chorn,its,timedate;--Financial Analysis: Quantmod,rquantlib,portfolio,performanceanalytics,ttr,sde,yieldcurve;--risk management: PARMA,EVD,EVDBAYES,EVIR,EXTREMES,I

R free to use; statistical tools;# NotesBlock Comment: anything= ""Editor: Rsutdio,tinn-r,eclipse+statet; Chinese will be garbled?, Help: BoxPlot, Help (BoxPlot), Help ("[[")Source (' ABC. R ')Library (GGPLOT2)Install.packages ()Q ()SETWD ("e:\\xxx\\yyy\\")RM (List=ls (all=true))Log natural logarithm; log10;ScalarAssignment Value: Variable name can be used.c () vector; win[1], Win[1:5], win[-2], subscript starting from 1;C () can be connected to multi

When learning the derivative, the teacher explains this, assuming y=f (x), the derivative process of the point (X0,Y0) is as follows:Set DX is a very small number= Y0+dy=f (X0+DX)= Dy=f (X0+DX)-y0Then at this point the derivative a=dy/dxThis assumes that the DX is very small, so x0 to (X0+DX) is short, can be approximated to a straight line, then DY/DX can be regarded as the slope of the point (X0,y0) and the point (X0+dx,y0+dy) connected to a straight lineSo the meaning of the derivative of a p

statistical model for calculations, you might find it on Cran-you know, Cran called the integrated R-File network (Comprehensive r Archive Networks) is not for no reason. When it comes to analysis and plotting, nothing is better than Ggplot2. And if you want to take advantage of features that are more powerful than what your machine provides, you can use SPARKR bindings to run Spark on R.However, if you are not a data scientist and have not used Matl

select Bokeh and Seaborn modules. In the previous blog post, I have explained the Matplotlib library in the box diagram module function. # import the module for plotting Import Matplotlib.pyplot as Plt plt.show (df.plot (kind = ' box ')) Now, we can use the Pandas module to integrate R's Ggplot theme to beautify the chart. To use Ggplot, we just need to add one more line to the code above, Import Matplotlib.pyplot as plt pd.options.display.mpl_style = ' Default ' # Set

Here only the data analysis commonly used graphic drawing, as for the complex graphics is not in the scope of this discussion, a few of the graphics to meet the requirements of the data analysis process, as for reporting materials or other high-quality graphics, and then write another about the simple use of ggplot2.Python's drawing tools are mainly matplotlib, which is not complex to use, but simple to use. There are two ways to use matplotlib drawin

Introduction We often want to observe a batch of data distribution patterns, histograms, density map, box line map, violin map and point map are very good to achieve the form. Here, we briefly introduce histograms, density graphs and box-line graphs, which are more commonly used by us. Histogram A lot of people don't understand the difference between a bar chart and a histogram. The bar chart is mainly used to display classified data, that is, nominal data, each group is separated. And the histo

Plyr Package Introduction The PLYR package is a package written by Hadley Wickham to solve the split–apply–combine problem, with the motivation to provide a package solution that transcends the for loop and the built-in apply function family. Using the Plyr package, you can complete the split–apply–combine three steps simultaneously within a function to achieve maximum efficiency and simplicity for different data types.The PLYR package is especially suitable for dealing with large dataset proble

The dataset used in this article is the GGPLOT2 packet Diamonds dataset, which contains information about the price and quality of about 54000 diamonds. This set of data covers four "C"-carat weight (carat), which reflects the quality of diamonds, cut, color and clarity (clarity), and five physical indicators-depth (depth), diamond width (table), x, Y, Z. The following figure: Another dataset used in this article is a random sample with a capacity o

Book Publishing The members of the statistical capital have authored and translated a large number of books on statistical analysis and R language. has been published Readers can click on each of the following links to the book's page, download with the book Code, we will not regularly publish books errata, also welcome the reader to ask questions. "R Language Combat" "Ggplot2: Data analysis and Graphic arts" "R Language Program

the software that logs on to UNIX or Linux server hosts under Windows) How 3.Rstudio server is deployed. (official deployment Help documentation) To download and install the package: The help document gives a EPEL link (epel:extra Packages for Enterprise Linux), logs on to the Linux server, and downloads the package with root privileges. (wget command Download) Find the package downloads that match your server version, r and Rstudio server's installation package are all inside, and some common

Turn http://www.cnblogs.com/jiangmiaomiao/p/6991632.html0 IntroductionR supports 4 types of graphics: base graphics, grid graphics, lattice graphics, Ggplot2. Where the Base graphics is the default graphics system for R.1 Basic graphics Functions plot ()The type parameter in the plot () command is used to clarify how the drawing is drawn, using the following type values: "P" for "points" "L" for "lines" "O" for "overlaid" (e.g., lines

Getting Started video tutorialsBasic R Language Course (1)-Quick Start for R language http://cos.name/videos/intro-2-r/Code#对象1 +1*3c (1,2,3,4,5) C (' HelloWorld ', ' I am a R user ') C ("hehe", "haha") 1:66:1exp (1:4) log (1:3) aRun results> #对象 > 1+1*3[1] 4> C (1,2,3,4,5) [1] 1 2 3 4 5> C (' HelloWorld ', ' I am a R user ') [1] "HelloWorld" "I am a R use R "> C (" hehe "," haha ") [1]" hehe "" haha "> 1:6[1] 1 2 3 4 5 6> 6:1[1] 6 5 4 3 2 1> exp (1:4) [1] 2.718282 7.389056 20.085537 54.598150>

array manipulation and formula setting is relatively more verbose. Matlab/octave's syntax for array manipulation is still more popular (for example, this is why it was used by Stanford University's machine Learning course), and the syntax of the R language is pretty good in formula settings.2. Furthermore, it is the corresponding Python library of the static graphics library Ggplot2 and the interactive graphics library D3. The Matplotlib library is n

#-*-Coding:utf-8-*-"""Created on Sat 18 11:08:38 2018@author: Acadsoc"""Import Pandas as PDImport NumPy as NPImport MatplotlibImport Matplotlib.pyplot as PltFrom pyecharts import Bar, line, Page, overlapImport Statsmodels.api as SMFrom sklearn.preprocessing import Standardscaler# import PymssqlFrom Dateutil Import ParserImport CopyImport OSImport SysFrom featureselection import featureselectionPlt.style.use (' Ggplot ') # set GGPLOT2 paint style# Set

what do not know, funny, like a cold joke, really cold, and then began without planning tools to learn, R, lucky to meet Lu Wenjun teacher, he is the great God of economic college, but also learned some learning methods, I belong to the kind of anxious character, the result. You know.. Is a tragedy, just no heroine, think Ha, have studied what, I am not easy to get started, oh right, now do not know how to get started, 罒 Omega 罒 steal laughter.The books are as follows : | | (time or double, for

Using Ggplot2 to draw a box line chart######*****绘制箱线图代码*****#######data1$学区房 R Language Drawing: Box-line diagram