This may reset the grouping of the tracked data if the grouping structure
has changed since the data frame was paused. If you try and resume tracking a
data frame with too many groups (as defined by options("dtrackr.max_supported_groupings"=XX)
)
then the resume will fail and the data frame will still be paused. This can
be overridden by specifying a value for the .maxgroups
parameter.
Arguments
- .data
a tracked dataframe
- ...
Named arguments passed on to
p_group_by
.messages
a set of glue specs. The glue code can use any global variable, or {.cols} which is the columns that are being grouped by.
.headline
a headline glue spec. The glue code can use any global variable, or {.cols}.
.tag
if you want the summary data from this step in the future then give it a name with .tag.
.maxgroups
the maximum number of subgroups allowed before the tracking is paused.
...
In
group_by()
, variables or computations to group by. Computations are always done on the ungrouped data frame. To perform computations on the grouped data, you need to use a separatemutate()
step before thegroup_by()
. Computations are not allowed innest_by()
. Inungroup()
, variables to remove from the grouping. Named arguments passed on todplyr::group_by
.add
When
FALSE
, the default,group_by()
will override existing groups. To add to the existing groups, use.add = TRUE
.This argument was previously called
add
, but that prevented creating a new grouping variable calledadd
, and conflicts with our naming conventions..drop
Drop groups formed by factor levels that don't appear in the data? The default is
TRUE
except when.data
has been previously grouped with.drop = FALSE
. Seegroup_by_drop_default()
for details.x
A
tbl()