Un-grouping a data set logically combines the different arms. In the history
this joins any stratified branches and acts as a specific type of status(),
allowing you to generate some summary statistics about the un-grouped data.
See dplyr::ungroup().
Usage
p_ungroup(
x,
...,
.messages = .defaultMessage(),
.headline = .defaultHeadline(),
.tag = NULL
)Arguments
- x
A
tbl()- ...
variables to remove from the grouping.
- .messages
a set of glue specs. The glue code can use any any global variable, or {.count}. the default is "total {.count} items"
- .headline
a headline glue spec. The glue code can use {.count} and {.strata}.
- .tag
if you want the summary data from this step in the future then give it a name with .tag.
Value
the .data dataframe but ungrouped with the history graph updated showing the ungroup operation as a new stage.
Examples
library(dplyr)
library(dtrackr)
tmp = iris %>% group_by(Species) %>% comment("A test")
tmp %>% ungroup(.messages="{.count} items in combined") %>% history()
#> dtrackr history:
#> number of flowchart steps: 2 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> └ "150 items in combined"