Summarize the composition of target categories.
summary_by_target.Rd
This function summarizes the composition of each target to
category
in a set of from
, to
, weight
links.
If a data.frame of links is provided, crossmap properties are not checked.
This can be useful when combined with add_placeholder_weights()
to highlight
where weights must be chosen.
Usage
summary_by_target(links, ...)
# S3 method for data.frame
summary_by_target(
links,
from,
to,
weights,
parts_into = "parts",
collapse = "+",
na_placeholder = "___",
frac_formula = "{from}*{weights}",
unit_formula = "{from}",
warn = TRUE
)
# S3 method for xmap_df
summary_by_target(
links,
parts_into = "parts",
collapse = "+",
frac_formula = "{from}*{weights}",
unit_formula = "{from}"
)
Arguments
- links
A data frame or
xmap_df
.- from, to
Columns in
x
specifying the source and target nodes- weights
Column in
x
specifying the weight applied to data passed along the directed link between source and target node- parts_into
A string specifying the new column to pass the summarised composition into. Default is "parts".
- collapse
A string specifying the separator to use when collapsing the unit values. Default is "+".
- frac_formula
A glue formula specifying how to calculate the fraction of each target value using the weighting variable. Default is "{from}*{weights}".
- unit_formula
A glue formula specifying how to calculate the unit of each target value using the weighting variable. Default is "{from}".
- na_placeholder.
A string character to replace NA weights with.
Examples
mock$xmap_abc |>
summary_by_target()
#> # A tibble: 5 × 2
#> upper parts
#> <chr> <glue>
#> 1 AA a
#> 2 BB b+c
#> 3 CC d
#> 4 DD d
#> 5 EE d
df <- data.frame(
parent = c("A", "A", "A", "B", "B", "B", "C"),
child = c("x", "y", "z", "x", "y", "z", "k")
)
df |>
add_placeholder_weights(from = parent, to = child, weights_into = "weights") |>
summary_by_target(from = parent, to = child, weights = weights,
frac_formula = "{from}*{weights}")
#> Warning: Summary completed without verifying crossmap properties.
#> ℹ To silence set `warn = FALSE`
#> # A tibble: 4 × 2
#> child parts
#> <chr> <glue>
#> 1 k C
#> 2 x A*___+B*___
#> 3 y A*___+B*___
#> 4 z A*___+B*___