See dplyr::mutate()
, dplyr::add_count()
, dplyr::add_tally()
,
dplyr::transmute()
, dplyr::select()
, dplyr::relocate()
,
dplyr::rename()
dplyr::rename_with()
, dplyr::arrange()
for more details
on underlying functions. dtrackr
provides equivalent functions for
mutating, selecting and renaming a data set which act in the same way as
dplyr
. mutate
/ select
/ rename
generally don't add anything in terms
of provenance of data so the default behaviour is to miss these out of the
dtrackr
history. This can be overridden with the .messages
, or
.headline
values in which case they behave just like a comment()
.
Arguments
- x
A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr).
- ...
<
data-masking
> Variables to group by.- .messages
a set of glue specs. The glue code can use any global variable, grouping variable, {.new_cols} or {.dropped_cols} for changes to columns, {.cols} for the output column names, or {.strata}. Defaults to nothing.
- .headline
a headline glue spec. The glue code can use any global variable, grouping variable, {.new_cols}, {.dropped_cols}, {.cols} or {.strata}. Defaults to nothing.
- .tag
if you want the summary data from this step in the future then give it a name with .tag.
Value
the .data
dataframe after being modified by the dplyr
equivalent
function, but with the history graph updated with a new stage if the
.messages
or .headline
parameter is not empty.
Examples
library(dplyr)
library(dtrackr)
# mutate and other functions are unitary operations that generally change
# the structure but not size of a dataframe. In dtrackr these are by ignored
# by default but we can change that so that their behaviour is obvious.
# add_count
# adding in a count or tally column as a new column
iris %>%
track() %>%
add_count(Species, name="new_count_total",
.messages="{.new_cols}",
# .messages="{.cols}",
.headline="New columns from add_count:") %>%
history()
#> dtrackr history:
#> number of flowchart steps: 2 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> └ "New columns from add_count:", "new_count_total"
# add_tally
iris %>%
track() %>%
group_by(Species) %>%
dtrackr::add_tally(wt=Petal.Length, name="new_tally_total",
.messages="{.new_cols}",
.headline="New columns from add_tally:") %>%
history()
#> dtrackr history:
#> number of flowchart steps: 3 (approx)
#> tags defined: <none>
#> items excluded so far: <not capturing exclusions>
#> last entry / entries:
#> ├ [Species:setosa]: "New columns from add_tally:", "new_tally_total"
#> ├ [Species:versicolor]: "New columns from add_tally:", "new_tally_total"
#> └ [Species:virginica]: "New columns from add_tally:", "new_tally_total"