histogram

I have a problem making histograms from pandas series objects and I can't understand why it does not work. The code has worked fine before but now it does not. Here is a bit of my code (specifically, a pandas series object I'm trying to make a histogram of): type(dfj2_MARKET1['VSPD2_perc']) which outputs the result: pandas.core.series.Series Here's my plotting code: fig, axes = plt.subplots(1, 7, figsize=(30,4)) axes[0].hist(dfj2_MARKET1['VSPD1_perc'],alpha=0.9, color='blue') axes[0].grid(True) axes[0].set_title(MARKET1 + ' 5-40 km / h') Error message: AttributeError Traceback (most recent

I know how to draw histograms or other frequency/percentage related tables. But now I want to know, how can I get those frequency values in a table to use after the fact. I have a massive dataset, now I draw a histogram with a set binwidth. I want to extract the frequency value (i.e. value on y-axis) that corresponds to each binwidth and save it somewhere. Can someone please help me with this? Thank you! The hist function has a return value (an object of class histogram ): R> res <- hist(rnorm(100)) R> res $breaks [1] -4 -3 -2 -1 0 1 2 3 4 $counts [1] 1 2 17 27 34 16 2 1 $intensities [1] 0.01

I'm new with R. I need to generate a simple Frequency Table (as in books) with cumulative frequency and relative frequency. So I want to generate from some simple data like > x [1] 17 17 17 17 17 17 17 17 16 16 16 16 16 18 18 18 10 12 17 17 17 17 17 17 17 17 16 16 16 16 16 18 18 18 10 [36] 12 15 19 20 22 20 19 19 19 a table like: frequency cumulative relative (9.99,11.7] 2 2 0.04545455 (11.7,13.4] 2 4 0.04545455 (13.4,15.1] 1 5 0.02272727 (15.1,16.9] 10 15 0.22727273 (16.9,18.6] 22 37 0.50000000 (18.6,20.3] 6 43 0.13636364 (20.3,22] 1 44 0.02272727 I know it should be simple, but I don't know

I am working on an assignment using R and the fitted density curve that is overlaid on the histogram is cut off at it's peak. Example: x <- rexp(1000, 0.2) hist(x, prob = TRUE) lines(density(x), col = "blue", lty = 3, lwd = 2) I have done a search on the internet for this but didn't find anything addressing this problem. I have tried playing with the margins, but that doesn't work. Am I missing something in my code? Thank you for your help! Here's the simple literal answer to the question. Make an object to hold the result of your density call and use that to set the ylim of the histogram. x <

I have a simple problem. How to plot histogram with ggplot2 with fixed binwidth and filled with rainbow colors (or any other palette)? Lets say I have a data like that: myData <- abs(rnorm(1000)) I want to plot histogram, using e.g. binwidth=.1 . That however will cause different number of bins, depending on data: ggplot() + geom_histogram(aes(x = myData), binwidth=.1) If I knew number of bins (e.g. n=15 ) I'd use something like: ggplot() + geom_histogram(aes(x = myData), binwidth=.1, fill=rainbow(n)) But with changing number of bins I'm kind of stuck on this simple problem. If you really want

I'm interested in creating a histogram in R that will contain two (or more) population on top of each other, meaning - I don't want a two histograms sharing the same graph but a bar containing two colors or more. Found the image below - this is what I want to accomplish. Any ideas? That is actually the annoying default in ggplot2: library(ggplot2) ggplot(iris, aes(x=Sepal.Length, fill=Species)) + geom_histogram() GuestBruce Here is another option without using ggplot: #plot the entire data set (everything) hist(everything, breaks=c(1:10), col="Red") #then everything except one sub group (1 in

If I have a vector (e.g., v<-runif(1000) ), I can plot its histogram (which will look, more or less, as a horizontal line because v is a sample from the uniform distribution). However, suppose I have a vector and its associated weights (e.g., w<-seq(1,1000) in addition to v<-sort(runif(1000)) ). E.g., this is the result of table() on a much larger data set. How do I plot the new histogram? (it should look more of less like the y=x line in this example). I guess I could reverse the effects of table by using rep ( hist(rep(v,w)) ) but this "solution" seems ugly and resource-heavy (creates an

First, I have an array int a[1000][1000] . All these integers are between 0 and 32767 ,and they are known constants: they never change during a run of the program. Second, I have an array b[32768], which contains integers between 0 and 32. I use this array to map all arrays in a to 32 bins: int bins[32]{}; for (auto e : a[i])//mapping a[i] to 32 bins. bins[b[e]]++; Each time, array b will be initialized with a new array, and I need to hash all those 1000 arrays in array a (each contains 1000 ints) to 1000 arrays each contains 32 ints represents for how many ints fall into its each bin . int