Joined February 2014
An elegant way to share variables across #rshiny modules via R6 objects, courtesy of @jiwanheo. A practical way to learn about R6 class. jiwanheo.rbind.io/post/2022-…
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#rstats #shiny (noun) #spotfire to draw shapefile for geofencing analyses.
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Dev's ideal friend - persistent storage without the chains - courtesy of @CockroachDB.
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Is bugs.r-project.org the right place to file a minor documentation in #RStats {base} 📦? If not, where should it be filed? 🙏🏻 @R_Contributors
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TIL {purrr} partial() with the `...` argument; weird syntax but it's🤩 Imagine creating many styles in {openxlsx} with a common center `halign`: ctr <- partial(createStyle, halign = "center", ... = ) ctr(numFmt = "0.0%") # same as createStyle(halign = "center", numFmt = "0.0%")
When {clipr} fails and you're too tired to mess with X11, {datapasta} got you covered😎 🙏 to @MilesMcBain GH: milesmcbain.github.io/datapa…
T.I.L. _session_ can be exported from a {shiny} module to allow updating input widgets across other modules🤩 Courtesy of @strboul for the inspiration 🙏 Gist: gist.github.com/strboul/01c9…
#rstats #ggplot in the wild; not suitable for production, eh? 🤔again. Courtesy of @EnverusEnergy
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#rstats puzzle. Given: val <- c(a = 1, b = 2) as.list(val) $a [1] 1 $b [1] 2 Question: val2 <- ??? list(val2) What should val2 be to get the same outcome?
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Have seen makefile enough that it’s time to learn; thankful for the valuable and soothing shorts by @fishnets88 🙏🏼 calmcode.io/makefiles/the-pr…
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First time using {future} in a #Rstats📦 & really 🙏for the valuable 📖by @henrikbengtsson. Some of the tips convered in the Common Issues vignette are 👌 🙇‍♂️ for the 📦too!
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More kudos to Philipp Schauberger and co. for {openxlsx}. TIL there's a fillMergedCells arg in openxlsx::read.xlsx() that detects and fills in the blanks for merged cells in .xlsx 😍 Guess everyone goes through the same excel pain at some point eh 🤷‍♂️
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Almost had a mental breakdown when asked to replicate an analysis from #rstats to #python 🙏 @chowthedog & @ericmjl for {siuba} + {pyjanitor} 😍🤗 otu_wide = (otu_df .clean_names() >> select(-_.taxonomy) >> gather("id", "value", -_.otu_id) >> spread(_.otu_id, _.value) )
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Can’t thank Philipp Schauberger and co. enough for {openxlsx} 🙏🏼🙇🏻‍♂️ To satisfy the uncanny output reqs from my coworkers😌 Nice tabulated .xlsx with: df %>% write.xlsx( asTable = T, tableStyle = “TableStyleLight9”, colWidths = “auto” ) ycphs.github.io/openxlsx/
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