histogram

问题 I'm trying to create a histogram plot in python, normalizing with some custom values the y-axis values. For this, I was thinking to do it like this: import numpy as np import matplotlib.pyplot as plt data = np.loadtxt('foo.bar') fig = plt.figure() ax = fig.add_subplot(111) hist=np.histogram(data, bins=(1.0, 1.5 ,2.0,2.5,3.0)) x=[hist[0]*5,hist[1]] ax.plot(x[0], x[1], 'o') but of course, the last line gives: ValueError: x and y must have same first dimension Is there a way to force np.hist to

问题 I am trying to produce a plot with histogram and scatter plot in just one plot using a secondary axis. In detail, here is an example data: #generate example data set.seed(1) a <- rnorm(200,mean=500,sd=35) data <- data.frame(a = a, b = rnorm(200, mean=10, sd=2), c = c(rep(1,100), rep(0,100))) # produce a histogram of data$a hist(a, prob=TRUE, col="grey") #add a density line lines(density(a), col="blue", lwd=2) #scatter plot plot(data$a,data$b,col=ifelse(data$c==1,"red","black")) What I want to

问题 I have gnuplot script like this: set term pos eps set style data histogram set style histogram clustered gap 1 set grid y set boxwidth 0.8 absolute set style fill transparent solid 0.8 noborder #set key outside right top vertical Left #component stuff set output 'eps/component.eps' set title "Component in interesting Issues" set xlabel "Components" set xtics nomirror rotate by -270 plot 'dat/!component' using 2:xtic(1) t "Count" lc rgbcolor "blue" lt 1 and data: Cmp count AM 167 NM 90 RM 83

问题 I have a series of numbers that I bin with the code above. Is it possible to return the maximum number in each bin? Have a look at the example code: from numpy import * a=array([1,4,5,6,7.8,9,3.4,5.,6,3.5,6,8,9,10]) bins=arange(0,11,1) h=hist(a,bins=bins) h=hist(a,bins=bins,weights=a) This is what it is return (array([ 0. , 1. , 0. , 6.9, 4. , 10. , 18. , 7.8, 8. , 28. ]), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) I was wondering if it was possible to get 3.5 (which is the maximum number

问题 I'm trying to write a generic histogram function that operates on an Array , but I'm running into difficulties as Type 'Element' does not conform to protocol 'Hashable' . extension Array { func histogram() -> [Array.Element: Int] { return self.reduce([Array.Element: Int]()) { (acc, key) in let value = (acc[key] == nil) ? 1 : (acc[key]! + 1) return acc.dictionaryByUpdatingKey(key: key, value: value) } } } where dictionaryByUpdatingKey(...) mutates an existing dictionary as follows: extension

问题 For example, if A = [7,8,1,1,2,2,2]; % the bins (or subscripts) B = [2,1,1,1,1,1,2]; % the array then the desired function "binsum" has two outputs, one is the bins, and the other is the sum. It is just adding values in B according to subscripts in A. For example, for 2, the sum is 1 + 1 + 2 = 4, for 1 it is 1 + 1 = 2. [bins, sums] = binsum(A,B); bins = [1,2,7,8] sums = [2,4,2,1] The elements in "bins" need not be ordered but must correspond to elements in "sums". This can surely be done by

问题 I've explored similar questions asked about this topic but I am having some trouble producing a nice curve on my histogram. I understand that some people may see this as a duplicate but I haven't found anything currently to help solve my problem. Although the data isn't visible here, here is some variables I am using just so you can see what they represent in the code below. Differences <- subset(Score_Differences, select = Difference, drop = T) m = mean(Differences) std = sqrt(var

问题 I am trying to plot a histogram that lines up every x value with the y value on the plot. I have tried to use multiple resources, but unfortunately I wasn't able to find anything. This is the best way I could code to make a histogram. x = (1,2,3,4,5) y = (1,2,3,4,5) h=plt.hist(x,y) plt.axis([0, 6, 0, 6]) plt.show() I want a graph that looks like the image below without those a's on x-axis: 回答1: From your plot and initial code, I could gather that you already have the bin and the frequency

问题 When I create a histogram, it looks a lot like this: set.seed(1) x <- 1:100 y <- x + rnorm(50) y=round(y) hist(y) Is there a way to make a histogram look a bit like this? I can only get a histogram with bins, which I don't need for my plot. I don't want the black bins, I actually only want the blue, green and red lines. Can stackoverflow point me in the right direction? 回答1: Put your histogram in an object, and use type="s" to get the stepwise plot : x <- rnorm(1000) y <- hist(x) plot(y

问题 This question already has answers here : Creating a histogram using aggregated data (4 answers) Closed 6 years ago . HI Guys I'm trying to plot a frequency graph of a simple 2d file file:data.csv terms,count 1,10 5,17 3,28 9,30 I want the first col(terms) to be the x-axis and the col(count) be the height/percentage. I've tried this: d<-read.csv(data.csv) hist(d) Error in hist.default(d) : 'x' must be numeric dc<-table(d) hist(dc) <-- wrong result. 回答1: The problem is that hist() needs a