ggplot2 boxplot

'] = 'sans-serif 'mpl. rcParams ['font. sans-serif'] = [u'simhei'] mpl. rcParams ['axes. unicode_minus '] = Falsedata = np. random. randint (1, 5, [3, 4]) index = np. arange (data. shape [1]) color_index = ['R', 'G', 'B'] fig, (ax1, ax2, ax3) = plt. subplots (3, 1, figsize = (5, 12) for I in range (data. shape [0]): ax1.bar (index + I *. 25 +. 1, data [I], width =. 25, color = color_index [I], \ alpha =. 5) for I in range (data. shape [0]): ax2.bar (index +. 25, data [I], width =. 5, color = co

= version. DATE#以上为系统自带的包From Stars Import *Import ESDAImport MarkovImport inequalityImport MobilityImport DataImport MarkovImport EDAFrom table Import table as RtableFrom the history import *From Sdialog Import *From PDF Import *Import HelpImport Dataviewer as DVFrom Kmean import KmeansImport Sdialogue as SDImport UtilityImport starssmoothing as Smooth#以上为stars目录下的包Starshome=options.getstarshome ()Platform=options.getplatform ()Sstop = Tk ()Sstop.title ("Welcome to Stars!")Ss=splashscreen (Mas

Graphic display is the most efficient and image of the data description means, so the smart image display is a high-quality data analysis report of the necessary content, so the powerful graphical display function is also a statistical analysis software necessary features. The R language provides a powerful display of vomiting blood. Today I'm going to share with my small partners how to draw the graphics you want with the R language from simple to complex.Let's start by listing all the availabl

")hist (WT, main= "histogram of WT")BoxPlot (wt,mian= "boxplot of WT")Par (OPAR)Detach (Mtcars)Case TWO:Attach (Mtcars)OparPar (Mfrow=c (3,1) # divides the canvas into 3 rows, 1 columns of landscapehist (WT)hist (MPG)hist (disp)Par (OPAR)Detach (Mtcars)Case THREE:Attach (Mtcars)Layout (Matrix (c (1,1,2,3), 2,2,byrow = TRUE))hist (WT)hist (MPG)hist (disp)Detach (Mtcars)??3. Split.screen functionSplit.screen

# #数据获取X1=round (runif (100,min=80,max=100))X2=round (Rnorm (100,mean=80, sd=7))X3=round (Rnorm (100,mean=80,sd=18))X3[which (x3>100)]=100Num=seq (2005138101,length=100)X=data.frame (NUM,X1,X2,X3)Write.table (x, "Grade.txt")# #数据分析Y=read.table ("Grade.txt")Mean (y)Colmeans (y)Colmeans (Y) (C ("x1", "X2", "x3"))#//2 represents the average by columnApply (x, 2, mean)Apply (x, 2, Max)Apply (x, 2, min)Apply (X[c ("x1", "X2", "x3")], 2, sum)#常用分布函数Uniform distribution: runif ()Normal distribution: Rn

In a recent project, I used a lot of charts and found that the pure JS chart plug-in highcharts is very useful and powerful. Make a note. The basic structure is shown in the following figure: In, the following items are displayed: Xaxis X coordinate Yaxis Y coordinate Credits Copyright information Legend Legend Exporting Export options Title Title Tooltip Tip prompt Series One or more data series o

: Rengine.jar and Rserveengine.jar, and it's not clear why the API could not be placed in a jar package for easy deployment.3. Write Java code to invoke RserveThe simplest of several invocation methods:Assigning an array to a variableRconnection.assign ("Dataa", arrayobject);Here Dataa and Datab are two array variable names that will perform a T-Test on both the DATAA and Datab data and return the corresponding console output for the R end.Rconnection.eval ("Paste" (Capture.output (T.test ("+ Da

: Title Componentb) ToolTip: Prompt Box componentc) Legend: Legend component, showing different series of tags (symbol), color and named) Xaxis: The x axis in the rectangular coordinate system grid, where a single grid component can only be placed up to two X axes.e) YAxis: the y axis in a rectangular coordinate system grid, where a single grid component can only be placed about two Y axes.F) Series: Series list. Each series determines its own chart type by type.Series[i]-line ——-Line ChartSerie

. %--------------------------------------------------------------------------%% calculate sample covariance r= CoV (z '); %1 means dividing by N to calculate covariance %% whitening Z [UNBSP;DNBSP;~]NBSP;=NBSP;SVD (r, ' econ '); % with EIG, [U,d]=eig (R); %% The following whitening matrix t=u*inv (sqrt (D)) *u ';% is called the inverse RMS of the covariance matrix, The INV calculation is not too time consuming because D is a diagonal array. Inv (sqrt (D)) *u ' is also a viable whitening matrix

very popular language for data science, originally built by/for statisticians and now very widely used. Htmlwidgets-previously discussed in the post, htmlwidgets for Rich Data visualizations in R. allows for tons of interact Ion and great for the web. Ggplot2-a very popular plotting system for R. It is widely used and can create just about every type of graph.However, the plots is not interactive. R Visualization is a sample application

package. Numba-Python's low-level Virtual Machine JIT compiler, compiled by cython and numpy developers for scientific computing Networkx-efficient software for complex networks. Pandas-This database provides high-performance, easy-to-use data structures and data analysis tools. Open Mining-the pandas web interface in Python ). Pymc-MCMC sampling toolkit. Zipline-Python algorithm trading library. Pydy-Full name: Python dynamics, which assists in Dynamic Modeling workflows Based on numpy,

database provides high-performance, easy-to-use data structures and data analysis tools. Open Mining-the pandas web interface in Python ). Pymc-MCMC sampling toolkit. Zipline-Python algorithm trading library. Pydy-Full name: Python dynamics, which assists in Dynamic Modeling workflows Based on numpy, scipy, ipython, and matplotlib. Sympy-Python library for symbolic mathematics. Statsmodels-Python statistical modeling and library of metered economics. Astropy-Python astronomy library, com

work Ggvis, Lattice, and ggplot2 for data visualization Caret Machine Learning How does python work? If your data Analysis task requires the use of a Web application, or code statistics need to be incorporated into the production database for integration, you can use Python as a fully fledged programming language, which is a great tool for implementing algorithms. Although Python packages have been in the early stages of data analysis in the past,

/PREDBLOG.RMD# #载入需要的包require (XML) require (DPLYR) require (Tidyr) require (READR) require (mosaic) require (Rcurl) require (GGPLOT2) Require (lubridate) require (Rjsonio) # #数据拉取url = "http://projects.fivethirtyeight.com/2016-election-forecast/ national-polls/"Doc View all selection data: AllolldataFast VisualizationIt is necessary to simply look at the data before figuring out the proportion of the projected votes for the 2016 U.S. presidential cam

story. Practical adviceMany statistical beamer templates for home latex make slides. It's handy for editing equations, and it's beautifully formatted. And it has great flexibility in the making of text colors, font selection, navigation bars, and graphics and animations. But I prefer the keynote of the Apple Computer. It's much more flexible in formatting, and it's able to use very personal fonts (such as my handwriting), and it can seamlessly combine animations and movies. There is a "Tmp

Plyr. Step 4: Learn specific packages in r–data.table and DplyrThis is the WHERE fun begins! Here are a brief introduction to various libraries. Let ' s start practicing some common operations. Practice the Data.table tutorial thoroughly here. Print and study the cheat sheet for data.table Next, you can has a look at the Dplyr tutorial here. For text mining, start with creating a word cloud in R and then learn learn through this series of Tutorial:part 1 and Pa RT 2. For so

The R language draws maps, which are often used in data analysis and can achieve very good results, and this section provides examples of how to use the R language tools to draw the ideal map.Examples of this section run smoothly under the R version 2.15.3 release, and other versions are pending.The code is as follows: The first small example# load the appropriate package, read the data, and then draw. Library (maptools), library (Ggplot2), China_map

with the GGPLOT2 in the R language, it seems that two packages are used and the likelihood is developed by the same person! The original author also said on GITHUB that the PYTHON library will no longer be updated! However, ggplot2 is really a drawing artifact, which is almost the only reason I am still using the R language. Therefore, matplotlib is required no matter which library you want to use. Altho

operator string • zoo performs regular and irregular time series operations • Ggvis, lattice, and ggplot2 for data visualization • Caret machine learning How to use Python? If your data analysis tasks require Web applications or code statistics to be integrated into the production database, you can use python as a fully sophisticated programming language, it is a great tool for implementing algorithms. Although the python package is still in its ea

Currently, ggplot2 is mainly used for data visualization analysis. However, ggplot2 does not support 3D plotting, so you need to find other alternatives. The two alternatives found below are good, and the test is feasible, which is recorded here. Interactive 3D Library (RGL) with (mtcars, {plot3d (wt, DISP, mpg, Col="Red", Size = 3)}) Static 3D Library (scatterplot3d) with (mtcars, {scatterplot3d