histogram

I would like to make a histogram where the fill color changes depending on the low end of the bin. I do not want a manual fill. This answer seems promising, but I could not transition it successfully to a histogram and two-value (not gradient) color scheme. I believe the solution may be some ifelse logic within geom_histogram(fill= ) but I don't know how to access the bin starting value. For example, in the below histogram, I would like to color revenue bins over $100,000 red to show the high-revenue customers. library(ggplot2) library(scales) n <- 10000 cust <- data.frame(cust_id=1:n,cust_rev

I want to change the values on the x axis in my histogram in R. The computer currently has it set as 0, 20, 40, 60, 80, 100. I want the x axis to go by 10 as in: 0,10,20,30,40,50,60,70,80,90,100. I know to get rid of the current axis I have to do this (hist(x), .... xaxt = 'n') and then axis(side = 1) ..... But how do I get it to show the numbers that I need it to show? Thanks. The answer is right there in ?axis ... dat <- sample(100, 1000, replace=TRUE) hist(dat, xaxt='n') axis(side=1, at=seq(0,100, 10), labels=seq(0,1000,100)) 来源： https://stackoverflow.com/questions/8481610/r-customizing-x

I have the following animated subplots that simulate histograms of four different distributions: import numpy from matplotlib.pylab import * import matplotlib.animation as animation n = 100 # generate 4 random variables from the random, gamma, exponential, and uniform distributions x1 = np.random.normal(-2.5, 1, 10000) x2 = np.random.gamma(2, 1.5, 10000) x3 = np.random.exponential(2, 10000)+7 x4 = np.random.uniform(14,20, 10000) fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) def updateData(curr): if curr == n: a.event_source.stop() ax1.hist(x1[:curr], normed=True, bins=20, alpha=0.5) ax2

I have a data frame that has a format like the following: Month Frequency 2007-08 2 2010-11 5 2011-01 43 2011-02 52 2011-03 31 2011-04 64 2011-05 73 I would like to create a histogram from this data, using X bins (X will probably be around 15, but the actual data has over 200 months), and using the data from the frequency column as the frequency for each bin of the histogram. How can I accomplish this? I've tried two approaches so far, with the hist() and barplot() commands. The problem with hist() is that it does not seem to give me any way to specify that I want to use the frequency column

Edit: Alright, so I answered my own question, by reading older questions a bit more. I apologize for asking the question! Using the code Y = rand(10,1); C = hist(Y); C = C ./ sum(C); bar(C) with the corresponding data instead of the random data worked fine. Just need to optimize the bin size now. Good day, Now I know that you must be thinking that this has been asked a thousand times. In a way, you are probably right, but I could not find the answer to my specific question from the posts that I found on here, so I figured I might as well just ask. I'll try to be as clear as possible, but

I have question probably similar to Fitting a density curve to a histogram in R . Using qplot I have created 7 histograms with this command: (qplot(V1, data=data, binwidth=10, facets=V2~.) For each slice, I would like to add a fitting gaussian curve. When I try to use lines() method, I get error: Error in plot.xy(xy.coords(x, y), type = type, ...) : plot.new has not been called yet What is the command to do it correctly? joran Have you tried stat_function ? + stat_function(fun = dnorm) You'll probably want to plot the histograms using aes(y = ..density..) in order to plot the density values