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Hubs rankings were collected because Git.Hub stopped providing them.This quarters run features the first major change in how these rankings are conducted since then.To help understand how this change was made and why it was necessary, heres a brief explanation of our Git.Hub ranking process.The Process to Date.In our early language ranking runs we pulled the data directly from Git.Hubs Explore page.Git. Hub ceased publishing the rankings there, however, and in 2.Git. Hub Archive public dataset on Google Big.Query. Our query counted repository languages excluding forked repos by aggregating total created events.Though now defunct, our previous query was similar to the one in this Stack Overflow answer.This query worked from 2.June 2. 01. 6. However, we again needed to adjust our query due to changes in the Git.Hub Archive table structure as well as changes in Git.Hubs API that impacted Git.Hub Archives language data.These changes provided the opportunity to evaluate our data source.Our Updated Process.In June 2. 01. 6, Git.Hub and Google announced a second public data set for publicly licensed repos.We initially explored the languages table on this dataset as our new potential source.This data had that benefit of providing multiple languages for a repository based on the number of bytes used per language, which in theory could give a more accurate representation of languages rather than using a repos primary language.However, we found that the results from this data were suboptimal because This data only includes licensed repositories, a much smaller subset than the public repositories of Git.Hub Archive. Furthermore, the process of recognizing licenses is occasionallybrittle, even further limiting the available data.The definition of languages expanded beyond what we have historically represented and included things like config files and typesetting systems.In what was our ultimate deciding factor, the results of this query were significantly less correlated with previous Git.Hub language data as well as Stack Overflow data.We also briefly explored the GH Torrent project.While this was an interesting data set that could be a great resource for curious individuals, its licensing prohibited our use in this instance.This ultimately led us back to Git.Hub Archive. Though we could not access the same language data that we had previously, we were able to query language by pull request.Our query resembles the one Git.Hub used to assemble the 2.State of the Octoverse.We endeavored to make the new query as comparable as possible to the previous process.Language is based on the base repository language.While this continues to have the caveats outlined below, it does have the benefit of cohesion with our previous methodology.We exclude forked repos.We use the aggregated history to determine ranking though based on the table structure changes this can no longer be accomplished via a single query.The primary change is that the Git.Hub portion of the language ranking is now based on pull requests rather than repos.While this means we couldnt replicate the rankings as they were before, the results were generally correlated with our past runs and were the best method available.On the positive side, it also eliminates the most common complaint regarding the rankings historically that measurements by repo might overestimate a given languages importance Java.Script, most frequently.The Net. The obvious question in the wake of this procedural change concerns impact.How do this quarters rankings compare with our last run There are two answers to that first, the change within the Git.Hub portion of our rankings second, the change in our rankings overall with the unaffected Stack Overflow results weighted in.In both cases, it depends on where in the Top 2.Within our Top 1.Git. Hub only results was a significant but not enormous 1.In the back half of the Top 2.When we weight in the Stack Overflow results, predictably, these differentials are somewhat more modest.Within the Top 1.And even in the much more volatile back half, the end change in the overall rankings was a mere three spots.This is, to be sure, the most significant change since we started performing this analysis.But as mentioned, after testing various approaches, this is the one most tightly correlated and thus offering the greatest continuity between our previous rankings.With that major update out of the way, please keep in mind the other usual caveats.To be included in this analysis, a language must be observable within both Git.Hub and Stack Overflow.No claims are made here that these rankings are representative of general usage more broadly.They are nothing more or less than an examination of the correlation between two populations we believe to be predictive of future use, hence their value.There are many potential communities that could be surveyed for this analysis.Git. Hub and Stack Overflow are used here first because of their size and second because of their public exposure of the data necessary for the analysis.We encourage, however, interested parties to perform their own analyses using other sources.All numerical rankings should be taken with a grain of salt.We rank by numbers here strictly for the sake of interest.In general, the numerical ranking is substantially less relevant than the languages tier or grouping.In many cases, one spot on the list is not distinguishable from the next.The separation between language tiers on the plot, however, is generally representative of substantial differences in relative popularity.In addition, the further down the rankings one goes, the less data available to rank languages by.Beyond the top tiers of languages, depending on the snapshot, the amount of data to assess is minute, and the actual placement of languages becomes less reliable the further down the list one proceeds.With that, here is the first quarter plot for 2.Click to embiggenBesides the above plot, which can be difficult to parse even at full size, we offer the following numerical rankings.As will be observed, this run produced several ties which are reflected below they are listed out here alphabetically rather than consolidated as ties because the latter approach led to misunderstandings.Note that this is actually a list of the Top 2.Top 2. 0, because of said ties.Java. Script. 2 Java. Crack Sudden Strike 2 Descargar Itunes . Python. 4 PHP5 C5 C7 CSS7 Ruby.C1. 0 Objective C1.Scala. 11 Shell. 11 Swift.R1. 5 Go. 15 Perl.Type. Script. 18 Power.Shell. 19 Haskell.Clojure. 20 Coffee.Script. 20 Lua. 20 Matlab.Updated process or no, Java.Script and Java retain their respective positions atop our rankings.The lack of movement in Java.Script is particularly notable given that some argued that measuring by repo overweighted Java.Scripts actual significance versus a metric like pull requests, the basis for the new query.PHP has dropped a spot for the first time in the history of our rankings, but remains enormously popular even at the number four spot.Out of all of the languages in the top ten, on the other hand, Python benefitted the most from the change in our Git.Hub ranking process where the average movement was one spot, Python jumped three spots, hence its leapfrogging of PHP.Outside of that, the only really notable movement in the top ten was Ruby dropping from five to seven.Lower down in the order, however, things get more interesting.A few comments on languages with notable movement, in no particular order. 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