Summarise a data set

Summarising a data set acts in the normal dplyr manner to collapse groups to individual rows. Any columns resulting from the summary can be added to the history graph. In the history this also joins any stratified branches and allows you to generate some summary statistics about the un-grouped data. See dplyr::summarise().

p_reframe(.data, ..., .messages = "", .headline = "", .tag = NULL)

Arguments

.data

A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details.

...

Arguments passed on to dplyr::reframe

.by

<tidy-select> Optionally, a selection of columns to group by for just this operation, functioning as an alternative to group_by(). For details and examples, see ?dplyr_by.

.messages

a set of glue specs. The glue code can use any summary variable defined in the ... parameter, or any global variable, or {.strata}

.headline

a headline glue spec. The glue code can use any summary variable defined in the ... parameter, or any global variable, or {.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 summarised with the history graph updated showing the summarise operation as a new stage

See also

dplyr::reframe()

Examples

library(dplyr)
library(dtrackr)

tmp = iris %>% group_by(Species) %>% track()
tmp %>% reframe(tibble(
  param = c("mean","min","max"),
  value = c(mean(Petal.Length), min(Petal.Length), max(Petal.Length))
  ), .messages="length {param}: {value}") %>% history()
#> dtrackr history:
#> number of flowchart steps: 2 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> ├ [Species:setosa]: "length mean: 1.462", "length min: 1", "length max: 1.9"
#> ├ [Species:versicolor]: "length mean: 4.26", "length min: 3", "length max: 5.1"
#> └ [Species:virginica]: "length mean: 5.552", "length min: 4.5", "length max: 6.9"