histogram

问题 I have the histogram shown below: In order to get the image data, I used this matlab command: [h,bins]=hist(data) The output that I got was as follows: h = 221 20 6 4 1 1 2 0 0 1 bins = Columns 1 through 7 8.2500 24.7500 41.2500 57.7500 74.2500 90.7500 107.2500 Columns 8 through 10 123.7500 140.2500 156.7500 What does h refer to? 回答1: h is the number of elements of data that fall into the respective bin in the histogram. 来源： https://stackoverflow.com/questions/13487768/matlab-h-bins-histdata

问题 I would like to superimpose, on each lattice histogram panel, an additional histogram (which will be the same in each panel). I want the overlayed histogram to have solid borders but empty fill ( col ), to allow comparison with the underlying histograms. That is, the end result will be a series of panels, each with a different colored histogram, and each with the same extra outline histogram on top of the colored histogram. Here's something that I tried, but it just produces empty panels: foo

问题 I want to make 20000 sample from a data which is quite big,based on the each value size in order to fill the NA values: so I use the output of histogram, but it wasn't successful, and get me an error, how to avoid it ? y=hist(maindata,col="red",breaks=length(unique(maindata)) for(k in 1:20000){ data=maindata for(i in 1:nrow(data)){ if (data[i]="Na"){ data[i]=sample(y$breaks,size=1,replace=FALSE,prob=y$density)}}} I get this error : Error in sample.int(length(x), size, replace, prob) :

问题 I tried to understand what is image histogram but I'm stuck in it. I would appreciate an easy explanation for it and the meaning of intensity value because I don't know what is it. 回答1: I guess the Matlab help function will have a pretty good explanation with some examples, so that should always be your first stop. But here's my attempt: An image is composed of pixels. For simplicitly let's consider a grayscale image. Each pixel has a certain brightness to the eye, which is expressed in the

问题 How to highlight the entire bar in which the observations obs.A and obs.B respectively are being allocated using ggplot? The exact same thing has been done for the regular hist() function but what is the ggplot way? Below some code to illustrate library(ggplot2) data <- data.frame(Var=c(rep("A",50),rep("B",50)), Value=round(rnorm(100,10,2),0)) obs.A<-8 obs.B<-10 ggplot(data)+ geom_histogram(aes(x=Value))+ facet_grid(Var ~ .) Edit: It needs to work for large and small sample sizes and really

问题 I have a matrix that consists of integers from 0 to N , and I want to obtain a data matrix of size N+1 where each element has the number of occurences of each number. So if the input matrix is 0 0 0 1 1 0 0 0 2 Then my output should be // occurences of 0 1 2 hist = [6, 2, 1] Is there an easy (built-in) way to accomplish this in C++ OpenCV, like the hist function in MATLAB? Thanks ! 回答1: This code reads all the grayscale values from an image and results in frequent occurring values (Number of

问题 !The image shows the screen shot of the .txt file of the data. The data consists of 2,075,259 rows and 9 columns Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available. Only data from the dates 2007-02-01 and 2007-02-02 is needed. I was trying to plot a histogram of "Global_active_power" in the above mentioned dates. Note that in this dataset missing

问题 This question already has answers here : Closed 8 years ago . Possible Duplicate: Fitting a density curve to a histogram in R I'm trying to add a best fit normal over a histogram in R. Right now, I have the following: x<-table[table$position==1,]$rt hist(x,breaks=length(x)) And now I'd like to plot a normal curve over this plot which allows for skew and for kurtosis. How can I do this? This is what my curve looks like: 回答1: I would suggest not using the terms "skew" and "kurtosis" in the same

问题 I'm having trouble scaling my Y axis histogram by frequencies rather than by counts (which is what I have now). I want it to go from 0 - 1 rather than 0 - 10000. Because it's a histogram, I can't simply divide by 10,000. Any suggestions? This is my code & graph 回答1: From the pyplot.hist documentation we see that hist has an argument normed , which is an alias for density : density : boolean, optional If True, the first element of the return tuple will be the counts normalized to form a

问题 I have sampled data in the interval [0,1] in an Array transitions=zeros(101,101) which I want to plot as a 3D-histogram. transitions is filled with data similar to the example data provided at the end of this thread. The first columns refers to the first observed variable X , the second column to the second variable Y and the third column is the normalized frequency. I.e. for the first row: the observed normalized frequency of the variable pair (0,0) is 0.9459. The sum of the normalized