#tinyplot — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #tinyplot, aggregated by home.social.
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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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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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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.
-
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.
-
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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Gráficos feitos com #RStats, usando #RDataTable para ler e tabular os dados, e #TinyPlot (@gmcd) para plotar
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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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#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?