I'm using Plotly's graphic_objects.Histogram. I am trying to draw several histograms on the same plot. I'm not satisfied with the results of the 'overlay' option. I would like to draw histograms with no fill colour like in this example, with only the borders of the boxes drawn. I was trying to fiddle with "marker.pattern" options but this doesn't seem to work. What would be the way to accomplish this, if this is possible?
I would like to draw a histogram for each of the columns in my data.frame without having to write the the names of all of them, similar to what I did for inspect their unique values with: sapply(data, unique) So I tried sapply(data, hist) This command draws the histogram correctly, but the title for each of them is "Histogram of X[[i]]": How can I draw the histograms but with the correct title?
I would like to understand how the MaxDiff algorithm works. The only example that I could find online was a set of slides by Chris Crifton. Given An attribute C 12, 5, 5, 5, 12, 1, 1, 20, 20, 2, 2, 12, 20, 14, 20, 5, 5, 20, 15, 15, 2, 2, 1, 3, 3,5, 5, 5 I'd like to Identify the range and frequency of each bucket creating a Max-Diff histogram for C using beta=7. I would be able …
I turn a directed labeled graph to histogram. for example if there is one node with label 'a', one with 'b' and two edges between them with label 'x', I turned it to axb and it's value is 2: H('axb')=2. I have some graphs that they belong to same operation but their nodes have different labels (for example if one node belongs to a process in system with pid 100, this process in another graph has different pid) I want …
Having the following distributions (actual and predicted), Hist 1 to 3 (left to right). I would like to get a score ranging from 0-1 of how close the actual distribution is to be normal. I've found a couple of statistical normality tests: Shapiro-Wilk Test D’Agostino’s K^2 Test My DataSet is large therefore I've decided to check the skew and kurtosis statistics and got the following results: hist-1 Skewness is 0.028386209063816035 and Kurtosis is 2.4224694251429764 <-- Most normal hist-2 Skewness is …