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1000 results for “r_data_table”
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CW: unpopular opinion about Tidyverse
@kernpanik Usually, I also try to stick to base #rstats or lightweight packages (#tinyplot, #tinytable, #rdatatable, ...). Methinks, since most tutorial promote the tidyverse, some do not know base equivalent. However, base data frame operations may require more careful handling of row order, factor levels, and preserving the data frame structure. dplyr maintains a consistent behavior across grouped operations.
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@pglpm The only reason I don't use {collapse} is because usually what I want is already covered by #RDataTable
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data.table giving bizarre results on my system when compiled with the intel compiler. This is just a simple mean by time. The the GForce version goes all wacky. Using base::mean() returns to sanity.
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I see the hardware is of course an important aspect.
You could also try fread from #rdatatable and see if this works better for you.
Since I have quite powerful laptop, I rarely come to the limits. But this was different in the past. I did my doctoral thesis (R package development included) in part on an #EeePC. That was fun.
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Pela primeira vez, fiz revisão de "pull request" no GitHub. A mudança sendo revista era uma atualização da tradução do #RDataTable por @rafaelff
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@johnmackintosh My 1/2 a cent as heavy user of #rdatatable for the package name: short is not so important (you only write it once). I would have gone with data.table.utils or data.table.extras to make it absolutely obvious. There is probably some room for a left_join, inner_join, full_join, asof_join wrapper as well (should you look for features)
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Someone said she felt undatable and I had to read twice, thrice because I thought it was un-data.table! 😅 #RDataTable
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#rdatatable would be sufficient for most of my demands I guess.
Therefore, I can unfortunately not offer a better comment.
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The #fcase function from #rdatatable is such a pleasure to work with.
https://rdatatable.gitlab.io/data.table/reference/fcase.html
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The #fcase function from #rdatatable is such a pleasure to work with.
https://rdatatable.gitlab.io/data.table/reference/fcase.html
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The #fcase function from #rdatatable is such a pleasure to work with.
https://rdatatable.gitlab.io/data.table/reference/fcase.html
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The #fcase function from #rdatatable is such a pleasure to work with.
https://rdatatable.gitlab.io/data.table/reference/fcase.html
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The #fcase function from #rdatatable is such a pleasure to work with.
https://rdatatable.gitlab.io/data.table/reference/fcase.html
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#rdatatable is a pleasure to work with. Sometimes mind bending (why does it not work? 🤔 … ahh, lists 🤦♂️)
but most of the time great.I use it in combination with #tinyplot. I had situations where my code got faster and shorter by doing this.
Enjoy
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Anyone knows about a #rstats #rdatatable skills file for claude?
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Gráficos feitos com #RStats, usando #RDataTable para ler e tabular os dados, e #TinyPlot (@gmcd) para plotar
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#rstats what wouldn't I give for a package that would bring #rdatatable syntax to #polars
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#tinyverse starter pack
|> pipeOp {base}
#tinyplot https://doi.org/10.32614/CRAN.package.tinyplot
#rdatatable https://doi.org/10.32614/CRAN.package.data.table
#poorman https://doi.org/10.32614/CRAN.package.poormanWhat did I forget?
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📢 News! A new version update of #biopixR is now available 🎉
🔍 biopixR - Package for analysis of bioimage image data: Make your bioimaging workflow easier and more efficient with this tool.
🌐 Just a few days ago, biopixR made its first public appearance on CRAN! Check it out here: <https://cran.r-project.org/package=biopixR>
🤝 We've already received valuable feedback from the #rdatatable community with a pull request. Thanks! 🙏
Let's keep this project growing and evolving together! 🚀 #BioImaging #rstats
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📢 News! A new version update of #biopixR is now available 🎉
🔍 biopixR - Package for analysis of bioimage image data: Make your bioimaging workflow easier and more efficient with this tool.
🌐 Just a few days ago, biopixR made its first public appearance on CRAN! Check it out here: <https://cran.r-project.org/package=biopixR>
🤝 We've already received valuable feedback from the #rdatatable community with a pull request. Thanks! 🙏
Let's keep this project growing and evolving together! 🚀 #BioImaging #rstats
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📢 News! A new version update of #biopixR is now available 🎉
🔍 biopixR - Package for analysis of bioimage image data: Make your bioimaging workflow easier and more efficient with this tool.
🌐 Just a few days ago, biopixR made its first public appearance on CRAN! Check it out here: <https://cran.r-project.org/package=biopixR>
🤝 We've already received valuable feedback from the #rdatatable community with a pull request. Thanks! 🙏
Let's keep this project growing and evolving together! 🚀 #BioImaging #rstats
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📢 News! A new version update of #biopixR is now available 🎉
🔍 biopixR - Package for analysis of bioimage image data: Make your bioimaging workflow easier and more efficient with this tool.
🌐 Just a few days ago, biopixR made its first public appearance on CRAN! Check it out here: <https://cran.r-project.org/package=biopixR>
🤝 We've already received valuable feedback from the #rdatatable community with a pull request. Thanks! 🙏
Let's keep this project growing and evolving together! 🚀 #BioImaging #rstats
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#tinyverse starter pack
|> pipeOp {base}
#tinyplot https://doi.org/10.32614/CRAN.package.tinyplot
#rdatatable https://doi.org/10.32614/CRAN.package.data.table
#poorman https://doi.org/10.32614/CRAN.package.poormanWhat did I forget?
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#tinyverse starter pack
|> pipeOp {base}
#tinyplot https://doi.org/10.32614/CRAN.package.tinyplot
#rdatatable https://doi.org/10.32614/CRAN.package.data.table
#poorman https://doi.org/10.32614/CRAN.package.poormanWhat did I forget?
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#tinyverse starter pack
|> pipeOp {base}
#tinyplot https://doi.org/10.32614/CRAN.package.tinyplot
#rdatatable https://doi.org/10.32614/CRAN.package.data.table
#poorman https://doi.org/10.32614/CRAN.package.poormanWhat did I forget?