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check for 2.0
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@ -299,7 +299,7 @@ if (require("dplyr")) {
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select(penicillins()) # only the 'J01CA01' column will be selected
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}
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if (require("dplyr")) {
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# with recent versions of dplyr this is all equal:
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# with recent versions of dplyr, this is all equal:
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x <- example_isolates[carbapenems() == "R", ]
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y <- example_isolates \%>\% filter(carbapenems() == "R")
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z <- example_isolates \%>\% filter(if_all(carbapenems(), ~ .x == "R"))
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@ -310,29 +310,33 @@ if (require("dplyr")) {
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# data.table --------------------------------------------------------------
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# data.table is supported as well, just use it in the same way as with
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# base R, but add `with = FALSE` if using a single AB selector:
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# base R, but add `with = FALSE` if using a single AB selector.
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if (require("data.table")) {
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dt <- as.data.table(example_isolates)
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print(
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dt[, carbapenems()] # incorrect, returns column *names*
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)
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print(
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dt[, carbapenems(), with = FALSE] # so `with = FALSE` is required
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)
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# for multiple selections or AB selectors, `with = FALSE` is not needed:
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print(
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dt[, c("mo", aminoglycosides())]
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)
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print(
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dt[, c(carbapenems(), aminoglycosides())]
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)
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# row filters are also supported:
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print(dt[any(carbapenems() == "S"), ])
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print(dt[any(carbapenems() == "S"), penicillins(), with = FALSE])
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# this does not work, it returns column *names*
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dt[, carbapenems()]
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}
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if (require("data.table")) {
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# so `with = FALSE` is required
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dt[, carbapenems(), with = FALSE]
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}
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# for multiple selections or AB selectors, `with = FALSE` is not needed:
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if (require("data.table")) {
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dt[, c("mo", aminoglycosides())]
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}
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if (require("data.table")) {
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dt[, c(carbapenems(), aminoglycosides())]
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}
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# row filters are also supported:
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if (require("data.table")) {
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dt[any(carbapenems() == "S"), ]
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}
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if (require("data.table")) {
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dt[any(carbapenems() == "S"), penicillins(), with = FALSE]
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}
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}
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}
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