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_pkgdown.yml
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_pkgdown.yml
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destination: docs
url: https://terminological.github.io/dtrackr/index.html
template:
bootstrap: 5
reference:
- title: "Controlling dtrackr"
desc: >
Functions that control `dtrackr`
contents:
- track
- untrack
- pause
- resume
- print.trackr_graph
- plot.trackr_graph
- flowchart
- history
- capture_exclusions
- excluded
- tagged
- title: "Pipeline annotations"
desc: >
`dtrackr` has functions that are specific additions to a data pipeline.
These are novel data pipeline functions that don't have a direct equivalent
in `dplyr` or `tidyr`.
contents:
- comment
- status
- count_subgroup
- exclude_all
- include_any
- title: "S3 dplyr function extensions"
desc: >
S3 functions extend the behaviour of a subset of the `dplyr` or `tidyr` commands
that operate on dataframes, and return dataframes, to include a history graph. In general
these work the same as the normal `dplyr` functions but allow additional
parameters that allow us to configure how the history is captured as they
are executed. `dplyr` functions that are not listed here can still be used
as normal with a tracked dataframe as input and give you the same output
but simply do not give you the additional functionality to store a entry
in the history graph. This may be because the operations are terminal
such as `count()`, `tally()`, `glimpse()`, `pull()`, or they
modify subsequent behaviour (e.g `rowwise()`), or they do not output dataframes
(e.g. `group_map()` and `group_walk()`). If a function is not supported in
`dtrackr` it can still be used, but that step of the pipeline will not be
captured in the history graph.
contents:
- add_count.trackr_df
- add_tally
- arrange.trackr_df
- distinct.trackr_df
- filter.trackr_df
- group_by.trackr_df
- group_modify.trackr_df
- mutate.trackr_df
- relocate.trackr_df
- rename.trackr_df
- rename_with.trackr_df
- select.trackr_df
- summarise.trackr_df
- reframe.trackr_df
- transmute.trackr_df
- ungroup.trackr_df
- anti_join.trackr_df
- full_join.trackr_df
- inner_join.trackr_df
- left_join.trackr_df
- right_join.trackr_df
- semi_join.trackr_df
- nest_join.trackr_df
- slice.trackr_df
- slice_head.trackr_df
- slice_tail.trackr_df
- slice_min.trackr_df
- slice_max.trackr_df
- slice_sample.trackr_df
- bind_rows
- bind_cols
- intersect.trackr_df
- union.trackr_df
- union_all.trackr_df
- setdiff.trackr_df
- title: "S3 function extensions in other packages"
desc: >
`dtrackr` support for functions from other tidyverse packages is evolving.
The focus is on functions that take a dataframe as input and produce a
dataframe as output, and naturally fit within a data pipeline. `pivot_longer()`
and `pivot_wider()` are good examples which are already implemented. Tracking
of `nest()` and `unnest()` is not yet implemented (but this does not stop you
from using these functions in a pipeline), and `purrr` functions such as `map_df()`,
`map_dfc()`, `map_dfr()`, `pmap()`, `pmap_dfr()`, `pmap_dfc()` are potential
candidates for future implementation, as are functions that acquire data
such as those from the `readr` package.
contents:
- pivot_longer.trackr_df
- pivot_wider.trackr_df
- title: "Dot graph rendering."
desc: >
Rendering of a `dtrackr` history once converted to
`GraphViz` dot format. These can be also used for non-dtrackr dot content
contents:
- dot2svg
- save_dot
- std_size
- title: "Legacy interface"
desc: >
The following operations are all aliases for functions above. They are
generally backend functions, and should not be used for new projects.
contents:
- starts_with("p_")