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Get & plot one month of package download stats for every Bioconductor package and write to csv file
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| bioc_repos <- BiocManager::repositories()[["BioCsoft"]] | |
| pkgs <- rownames(utils::available.packages(repos = bioc_repos)) | |
| #pkgs <- head(pkgs, 100) # for testing | |
| stats <- bioC.logs::bioC_downloads(pkgs, from = "08-2025", to = "09-2025") | |
| names(stats) <- pkgs | |
| stats.df <- Reduce(rbind, stats) | |
| rownames(stats.df) <- pkgs | |
| write.csv(stats.df, file = "bioc-pkg-downloads.csv") | |
| stats.df <- read.csv("bioc-pkg-downloads.csv", row.names = 1) | |
| stats.df <- stats.df[order(stats.df[, "Nb_of_distinct_IPs"], decreasing = TRUE), ] | |
| library(ggplot2) | |
| library(scales) | |
| ggplot(stats.df, aes(x = 1:nrow(stats.df), y = cumsum(Nb_of_distinct_IPs))) + | |
| # Made points smaller by setting size = 0.5 | |
| geom_point(stat = "identity", size = 0.5) + | |
| # Set a finer y-scale by providing more breaks and comma-formatted labels | |
| scale_y_continuous( | |
| labels = scales::comma, # Use commas (e.g., 1,000,000) for readability | |
| breaks = scales::pretty_breaks(n = 10) # Request ~10 breaks for a finer grid | |
| ) + | |
| xlab("# packages") + | |
| ylab("# downloads") + | |
| ggtitle("Cumulative sum of downloads by # packages") |
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