Resume tracking the data frame.

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.

Usage

p_resume(.data, ...)

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 separate mutate() step before the group_by(). Computations are not allowed in nest_by(). In ungroup(), variables to remove from the grouping.

Value

the .data data frame with history graph tracking resumed

Examples

library(dplyr)
library(dtrackr)
iris %>% track() %>% pause() %>% resume() %>% history()
#> dtrackr history:
#> number of flowchart steps: 1 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> └ "150 items"