histogram ggplot2

Introduction There is no doubt about the quality of the Ggplot2 package, but its drawing grammar is still a little difficult for beginners, Ggplot2: Data analysis and Graphic Art This book also introduces the basic philosophy and operation of Ggplot2 package, and the personal feeling examples are not rich enough, So the use of the package is still stuck at the da

the original histogram of the x-axis, the x-axis of the scale of the text can be removedPHow to add a percentage to the graph:Library (ggplot2) dt = Data.frame (A = C (2,7,4,Ten,1), B = C (' B ',' A ',' C ',' D ',' E ')) dt = Dt[order (dt$a, decreasing =TRUE),]mylabel = as. Vector (dt$b) MyLabel = Paste (MyLabel,"(",round(Dt$a/sum(dt$a) * -,2),"%)", Sep ="") p = ggplot (DT, AES (x ="", y = A, fill = B)) +

June has been busy in the final exam, today to quickly learn the Ggplot2 package of simple drawing.There are also many drawing functions in the base package of R, such as plot (); Barplot (); Qqplot ();But there is also the famous Ggplot2 bag, using the function of this package to draw a beautiful picture, and the use of flexible. In Ggplot's Official Handbook, a statistical graph is made up of data to geom

The purpose of this paper is to introduce some fine operation of Ggplot2 package in R language, which is mainly applicable to people who have a certain understanding of R-Drawing and need to be more finely transformed into diagrams, especially those who have just turned ggplot2 from Excel, and have more frequent drawing needs. No discussion of those very cool charts, with practical commercial charts as the

The gray histogram of digital image is described earlier, and the application of histogram is now tried. Histogram equalization Histogram equalization (histogram equalization) is the most typical application of histogram, which is

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 laye

data:The Diamonds dataset in Ggplot2, using a random sample to fetch 1000 samples, the code is as follows:> Library (GGPLOT2)> Data ("Diamonds")> Head (Diamonds)> set.seed (1234)> Small Histogram> Ggplot (Small) +geom_histogram (Aes (X=price), fill= "Cornflowerblue", colour= "Black", binwidth= 1000)Stacked HistogramUse the "Cut" column in the data (divided into 5

The following plots take the Weibull distribution (Weber distribution, Weibull distribution) as an exampleFor Weibull distribution (Weber distribution, Weibull distribution), please refer to my blog http://www.cnblogs.com/wwxbi/p/6141501.htmlLibrary (GGPLOT2)# both D and Y here are in order of sizedYDfGgplot (Df,aes (x=d,y)) +Geom_line (colour= "green") +Ggtitle ("Weibull distribution \ n probability density map")# Here's H no size orderH Ggplot (Null

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

Histogram equalizationHistogram equalization (histogram equalization) is the most typical application of histogram, which is a kind of image point operation . For an input image, an output image is generated by the operation, which means that the grayscale value of each pixel of the output image is determined by the input pixel point, i.e.:

Install.packages ("Ggplot2")Library (GGPLOT2)# WINDROSE.R Http://stackoverflow.com/questions/17266780/wind-rose-with-ggplot-rRequire (GGPLOT2)Require (Rcolorbrewer)Plot.windrose SpdDirSpdres = 10,Dirres = 30,Spdmin = 0,Spdmax = 90,Spdseq = NULL,palette = "Ylgnbu",Countmax = NA,debug = 0) {# look-to-see-what data is passed in to the functionif (Is.numeric (SPD) I

ggplot2– Practice (change of legend: Take the frequency scatter graph as an example) Ggplot2 direct realization Paint code:The data is two columns and the second is the factor type. > Head (plotdat) Soc Soc Low alarm 1 0 normal 2 2 error 3 0 Normal 4 1 error 5 0 normal # # #大小和高度都代表频率 ### g # #设定名字 Problem There are three questions about the legend:1. How to remove t

Preface:Everyone should know that ggplot2 and shiny are all seven of the R language weapons, although their ability is very fluid force, but also out "Walk the lake" for many years, but in the domestic relevant knowledge sharing is relatively small. Many times encountered problems have to search the wall, so despite their qualifications is still shallow, but I would like to be able to make a summary of their own knowledge to share, I hope to be helpfu

Directory: Initial pattern How to modify the width of bar bars How to modify the order of bar bars How do I add text to the bar (For more information on legends, coordinate systems, etc. see: R, Ggplot2, shiny summary)Initial pattern:library(ggplot2)library(ggthemes)dtdata.frame(obj = c(‘A‘,‘D‘,‘B‘,‘E‘,‘C‘), val = c(2,15,6,9,7))p = ggplot(dt, aes(x = obj, y = val, fill = obj, group

Directory:Initial pattern How to modify the width of a bar how to change the order of bars how to add text to a bar (For more on the legend, coordinate system, etc. see: R, Ggplot2, shiny summary) Initial pattern: Library (GGPLOT2) Library (ggthemes) dt = data.frame (obj = C (' A ', ' D ', ' B ', ' E ', ' C '), val = C (2,15,6,9,7)) p = Ggplot (DT, AES (x = obj, y = val, fill = obj, group = factor (1))) +

Some header files: #include First, create a class: Class histogram1d {PRIVATE: // number of points in the histogram int histsize [1]; // the histogram range is float hranges [2]; // pointer to this range const float * ranges [1]; // channel int channels [1]; public: // constructor histogram1d () {histsize [0] = 256; hranges [0] = 0.0; hranges [1] = 255.0; ranges [0] = hranges; channels [0] = 0 ;} In open

Library (GGPLOT2)############################################## summaryse############################################### Summarizes data.## Gives count, mean, standard deviation, standard error of the mean, and confidence interval (default 95% ). # # DATA:A Data frame.## measurevar:the name of a column that contains the variable to be summariezed## groupvars : A vector containing names of columns that contain grouping variables## Na.rm:a Boolean that

R3.2.2 Version Installation Ggplot2 installed Ggplot2 Today, began to use the R3.2.1 version, but has been an error. The back of a new R3.2.2, but the installation is still the same error, the reason is Munsell this package incompatibility problem, find the way to solve this problem is the local zip installation Munsell Package: The following: Remove the Ggplot2

we are probably not unfamiliar with the following infographic, which uses 100% stacked area charts to represent the proportions of different countries in different periods of time. This is a very interesting expression, and the area chart is a very common data graph, now let's look at how to use Ggplot2 and Plot.area in R to make an area chart. before making a chart, let's first create some random sample data . The R code is as follows: 1 # C

For more information, see: R, Ggplot2, shiny summaryInitial pattern:Library(GGPLOT2)DT= data. Frame(a = c(2, 7, 4, ten, 1), B = C('b', 'A ', 'C', 'D', 'E'))windowsfonts(MyFont = Windowsfont ("in italics") # # Bound FontP= Ggplot (DT, AES (x =B, y =A, fill =B) + Geom_bar (stat ="Identity", alpha =0.7) + Coord_polar ()Pthe rose chart after repair:Library (ggplot2)