histogram

I'm working on visualizing term frequencies for some Twitter data I've collected about the Winter Olympics. I'd like to make a histogram using d3 that will visualize these counts and allow users to toggle between datasets for each day of the games. I have an initial visualization I'm fairly happy with here , modified from this example. However, when clicking the "Update" button in the lower right corner, this simply overlays a new histogram on top of the existing one. Both datasets are CSV's, and there are seven of them total that I'd like to be able to toggle through. I've searched Stack

I want to calculate histogram of an image hows pixels are of type 32F (32 bit floating point). What should be the parameter values of "calcHist" function for: - dims - bins - range Well I've done this many times. Something like so: cv::Mat matSrc; // this is a CV_32FC1 normalised image int nHistSize = 65536; float fRange[] = { 0.0f, 1.0f }; const float* fHistRange = { fRange }; cv::Mat matHist; cv::calcHist(&matSrc, 1, 0, cv::Mat(), matHist, 1, &nHistSize, &fHistRange); As it says in the documentation describing the source arrays: Source arrays. They all should have the same depth, CV_8U or CV

i'm receiving requests/events from a large number of client applications. i'd like to use elasticsearch to find out when my highest traffic point is. one thing i've tried is a filter aggregation with a nested histogram and then a nested "terms" aggregation that gets the distinct hour of the day via a script field. the following is my attempt, and it performs terribly (as I'd expect since I'm executing a script per document). { "aggs": { "sites_within_range": { "filter" : { "range" : { "occurred" : { "gt" : "now-1M" } } }, "aggs": { "sites_over_time": { "date_histogram": { "field": "occurred",

I have a large dataset with the lifespan of threads on an discussion board. I want a histogram that shows the distribution of lifespan, so I did this: dall <- read.csv("lifespan.csv") colnames(dall) <- c("thread.id", "seconds.alive", "start.time") hist(dall$seconds.alive) which generated this hard to read image: My questions are a) is changing y-axis to a log-scale a good way to make it more readable? Apparently some people think is a bad idea to change y-axis to log. b) how do I do that? I would try using hist(log10(dall$seconds.alive)) instead. Also try specifying breaks=100 or smaller