histogram

问题 I am having trouble plotting a histogram as a pdf (probability) I want the sum of all the pieces to equal an area of one so it's easier to compare across datasets. For some reason, whenever I specify the breaks (the default of 4 or whatever is terrible), it no longer wants to plot bins as a probability and instead plots bins as a frequency count. hist(data[,1], freq = FALSE, xlim = c(-1,1), breaks = 800) What should I change this line to? I need a probability distribution and a large number

问题 I have plotted a histogram in Jupyter (Python 2) and was expecting to see the outlines of my bars but this is not the case. I'm using the following code: import matplotlib.pyplot as plt from numpy.random import normal gaussian_numbers = normal(size=1000) plt.hist(gaussian_numbers) plt.title("Gaussian Histogram") plt.xlabel("Value") plt.ylabel("Frequency") plt.show() 回答1: It looks like either your linewidth was set to zero or your edgecolor was set to 'none' . Matplotlib changed the defaults

问题 I have 400 files, each one contains about 500000 character, and those 500000 characters consists only from about 20 letters. I want to make a histogram indicating the most 10 letters used (x-axis) and number of times each letter is used (y-axis). how can i make it. 回答1: Since you have an array of uchar , you know that your elements will always be in the range 0:255 . After seeing Tamás Szabó's answer here I realized that the null character is exceedingly unlikely in a text file, so I will

问题 [Update] I find more example and i can do it now Can I plot several histograms in 3d? I know this question is already ask and i try this How to calculate 3D histogram in python using open CV but it doesn't work I want something like this 3D histogram this is what i have now My Graph hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) h,s,v = cv2.split(hsv_image) fig = plt.figure(figsize=(8,7)) ax = plt.axes(projection='3d'), plt.title("Histogram 3D") plt.hist(h.ravel(), 256, [0, 256]) plt.hist

问题 I have this data: data = pd.DataFrame().from_dict([r for r in response]) print data _id total 0 213 1 1 194 3 2 205 156 ... Now, if I call: data.hist() I will get two separate histograms, one for each column. This is not what I want. What I want is a single histogram made using those two columns, where one column is interpreted as a value and another one as a number of occurrences of this value. What should I do to generate such a histogram? I tried: data.hist(column="_id", by="total") But

问题 So I have some data - gene expression in several samples - that I want to plot as an histogram binned in a way that makes sense, and then overlaying a density curve. Something along the lines of this plot: Plotting_distributions_(ggplot2) ggplot(df, aes(x=rating)) + geom_histogram(aes(y=..density..), # Histogram with density instead of count on y-axis binwidth=.5, colour="black", fill="white") + geom_density(alpha=.2, fill="#FF6666") # Overlay with transparent density plot but with the bins

问题 i m make App in netbeans platform. i want to draw hisrogram. i have Red, Green ,and Blue color's pixel of image. so, please any one suugest to me that how can i plot histogram using this pixels value? my code is below ,in which i take RED,GREEN, and BLUE pixel value of image. enter code here import java.awt.Component; import java.awt.image.BufferedImage; import java.io.File; import java.io.IOException; import javax.imageio.ImageIO; public class WalkImageTest10 extends Component { public

问题 This is a follow-up to my previous couple of questions. Here's the code I'm playing with: import pandas as pd import matplotlib.pyplot as plt import scipy.stats as stats import numpy as np dictOne = {'Name':['First', 'Second', 'Third', 'Fourth', 'Fifth', 'Sixth', 'Seventh', 'Eighth', 'Ninth'], "A":[1, 2, -3, 4, 5, np.nan, 7, np.nan, 9], "B":[4, 5, 6, 5, 3, np.nan, 2, 9, 5], "C":[7, np.nan, 10, 5, 8, 6, 8, 2, 4]} df2 = pd.DataFrame(dictOne) column = 'B' df2[df2[column] > -999].hist(column,

问题 I have a set of data that I'm trying to plot using a FacetGrid in seaborn. Each data point has a weight associated with it, and I want to plot a weighted histogram in each of the facets of the grid. For example, say I had the following (randomly created) data set: import seaborn as sns import pandas as pd import numpy as np import matplotlib.pyplot as plt d = pd.DataFrame(np.array([np.random.randint(0, 6, 5000), np.random.normal(0, 1., 5000), np.random.uniform(0, 1, 5000)]).T, columns=('cat',

问题 I'm trying to show the histogram of an image and show only some colors. I've already done that with JFreeChart and createXYLineChart and getting all the data by iterating over all pixels. To speed it up I'm trying to do it with "createHistogram". I've followed this code. To update the chart with the new values I've used this two methods: XYPlot plot = (XYPlot) chart.getPlot(); plot.setDataset(setHistogram(red, green, blue)); Being setHistogram a method which returns a HistogramDataset