The transition from a metadata-rich dataframe consisting of
projectable_cols to an ordinary dataframe that is fit for presentation is
guided by the shadow attributes attached to each column of the initial
dataframe. The prj_shadow() function is designed to make it easy to
specify those shadow attributes for multiple columns at once.
prj_shadow(.data, ..., .shadow)A dataframe, ideally one containing projectabel_cols
tidy-select
One or more unquoted expressions separated by commas. Variable names can be
used as if they were positions in the data frame, so expressions like x:y
can be used to select a range of variables.
A character vector containing glue-like specifications to
which to set the shadow attribute of the relevant columns.
A dataframe, the columns of which have updated shadow attributes.
# Create a table made up of `projectable_col`s
my_tbl <- prj_tbl_rows(
.data = mtcars,
Cylinders = cyl,
Transmission = list(Automatic = am %in% 0, Manual = am %in% 1),
)
my_tbl <- prj_tbl_cols(
.data = my_tbl,
`V-Shaped` = col_freq(n = vs %in% 1, N = vs %in% 0:1),
`Not V-shaped` = col_freq(n = vs %in% 0, N = vs %in% 0:1)
)
my_tbl <- prj_tbl_summarise(.data = my_tbl)
# Update the `shadow` attributes
shadow <- c(Count = "{n}", Proportion = "{signif(p, 2)}")
my_tbl <- prj_shadow(my_tbl, where(is_col_freq), .shadow = shadow)
# Project it back into an ordinary dataframe
prj_project(my_tbl)
#> # A tibble: 5 × 6
#> row_spanner rows `V-Shaped.Count` `V-Shaped.Proportion` `Not V-shaped.…`
#> * <col_row> <col_row> <glue> <glue> <glue>
#> 1 Cylinders 4 10 0.91 1
#> 2 Cylinders 6 4 0.57 3
#> 3 Cylinders 8 0 0 14
#> 4 Transmission Automatic 7 0.37 12
#> 5 Transmission Manual 7 0.54 6
#> # … with 1 more variable: `Not V-shaped.Proportion` <glue>