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new tibble export
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@ -158,12 +158,12 @@ proportion_R(example_isolates$AMX)
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\donttest{
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if (require("dplyr")) {
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example_isolates \%>\%
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group_by(hospital_id) \%>\%
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group_by(ward) \%>\%
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summarise(r = resistance(CIP),
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n = n_rsi(CIP)) # n_rsi works like n_distinct in dplyr, see ?n_rsi
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example_isolates \%>\%
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group_by(hospital_id) \%>\%
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group_by(ward) \%>\%
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summarise(R = resistance(CIP, as_percent = TRUE),
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SI = susceptibility(CIP, as_percent = TRUE),
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n1 = count_all(CIP), # the actual total; sum of all three
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@ -195,7 +195,7 @@ if (require("dplyr")) {
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example_isolates \%>\%
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group_by(hospital_id) \%>\%
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group_by(ward) \%>\%
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summarise(cipro_p = susceptibility(CIP, as_percent = TRUE),
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cipro_n = count_all(CIP),
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genta_p = susceptibility(GEN, as_percent = TRUE),
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@ -211,8 +211,8 @@ if (require("dplyr")) {
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# It also supports grouping variables
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# (use rsi_df to also include the count)
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example_isolates \%>\%
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select(hospital_id, AMX, CIP) \%>\%
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group_by(hospital_id) \%>\%
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select(ward, AMX, CIP) \%>\%
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group_by(ward) \%>\%
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rsi_df(translate = FALSE)
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}
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}
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