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().

Usage

# S3 method for class 'trackr_df'
summarise(.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.

...

<data-masking> Name-value pairs of summary functions. The name will be the name of the variable in the result.

The value can be:

• A vector of length 1, e.g. min(x), n(), or sum(is.na(y)).

• A data frame, to add multiple columns from a single expression.

Returning values with size 0 or >1 was deprecated as of 1.1.0. Please use reframe() for this instead.

.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::summarise()

Examples

library(dplyr)
library(dtrackr)

tmp = iris %>% group_by(Species) %>% track()
tmp %>% summarise(avg = mean(Petal.Length), .messages="{avg} length") %>% history()
#> dtrackr history:
#> number of flowchart steps: 2 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> ├ [Species:setosa]: "1.462 length"
#> ├ [Species:versicolor]: "4.26 length"
#> └ [Species:virginica]: "5.552 length"