View source: R/modify_columns.R
cols_merge_n_pct | R Documentation |
cols_merge_n_pct()
is a specialized variant of cols_merge()
,
It operates by taking two columns that constitute both a count (col_n
) and
a fraction of the total population (col_pct
) and merges them into a single
column. What results is a column containing both counts and their associated
percentages (e.g., 12 (23.2%)
). The column specified in col_pct
is
dropped from the output table.
cols_merge_n_pct(data, col_n, col_pct, rows = everything(), autohide = TRUE)
data |
The gt table data object
This is the gt table object that is commonly created through use of the
|
col_n |
Column to target for counts
The column that contains values for the count component. While select
helper functions such as |
col_pct |
Column to target for percentages
The column that contains values for the percentage component. While select
helper functions such as |
rows |
Rows to target
In conjunction with |
autohide |
Automatic hiding of the
An option to automatically hide the column specified as |
An object of class gt_tbl
.
This function could be somewhat replicated using cols_merge()
, however,
cols_merge_n_pct()
employs the following specialized semantics for NA
and zero-value handling:
NA
s in col_n
result in missing values for the merged
column (e.g., NA
+ 10.2%
= NA
)
NA
s in col_pct
(but not col_n
) result in
base values only for the merged column (e.g., 13
+ NA
= 13
)
NA
s both col_n
and col_pct
result in
missing values for the merged column (e.g., NA
+ NA
= NA
)
If a zero (0
) value is in col_n
then the formatted output will be
"0"
(i.e., no percentage will be shown)
Any resulting NA
values in the col_n
column following the merge
operation can be easily formatted using sub_missing()
.
Separate calls of sub_missing()
can be used for the col_n
and
col_pct
columns for finer control of the replacement values. It is the
responsibility of the user to ensure that values are correct in both the
col_n
and col_pct
columns (this function neither generates nor
recalculates values in either). Formatting of each column can be done
independently in separate fmt_number()
and fmt_percent()
calls.
This function is part of a set of four column-merging functions. The other
three are the general cols_merge()
function and the specialized
cols_merge_uncert()
and cols_merge_range()
functions. These functions
operate similarly, where the non-target columns can be optionally hidden from
the output table through the hide_columns
or autohide
options.
Using a summarized version of the pizzaplace
dataset, let's create a
gt table that displays the counts and percentages of the top 3 pizzas
sold by pizza category in 2015. The cols_merge_n_pct()
function is used to
merge the n
and frac
columns (and the frac
column is formatted using
fmt_percent()
).
pizzaplace |> dplyr::group_by(name, type, price) |> dplyr::summarize( n = dplyr::n(), frac = n/nrow(pizzaplace), .groups = "drop" ) |> dplyr::arrange(type, dplyr::desc(n)) |> dplyr::group_by(type) |> dplyr::slice_head(n = 3) |> gt( rowname_col = "name", groupname_col = "type" ) |> fmt_currency(price) |> fmt_percent(frac) |> cols_merge_n_pct( col_n = n, col_pct = frac ) |> cols_label( n = md("*N* (%)"), price = "Price" ) |> tab_style( style = cell_text(font = "monospace"), locations = cells_stub() ) |> tab_stubhead(md("Cat. and \nPizza Code")) |> tab_header(title = "Top 3 Pizzas Sold by Category in 2015") |> tab_options(table.width = px(512))
5-17
v0.3.0
(May 12, 2021)
Other column modification functions:
cols_add()
,
cols_align()
,
cols_align_decimal()
,
cols_hide()
,
cols_label()
,
cols_label_with()
,
cols_merge()
,
cols_merge_range()
,
cols_merge_uncert()
,
cols_move()
,
cols_move_to_end()
,
cols_move_to_start()
,
cols_nanoplot()
,
cols_unhide()
,
cols_units()
,
cols_width()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.