library(dplyr)
library(dtrackr)
# Subset the data by the maximum of a given value
iris %>% track() %>% group_by(Species) %>%
slice_max(prop=0.5, order_by = Sepal.Width,
.messages="{.count.out} / {.count.in} = {prop} (with ties)",
.headline="Widest 50% Sepals") %>%
history()
# The narrowest 25% of the iris data set by group can be calculated in the
# slice_min() function. Recording this is a matter of tracking and
# using glue specs.
iris %>%
track() %>%
group_by(Species) %>%
slice_min(prop=0.25, order_by = Sepal.Width,
.messages="{.count.out} / {.count.in} (with ties)",
.headline="narrowest {sprintf('%1.0f',prop*100)}% {Species}") %>%
history()
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