Add summary rows to one or more row groups by using the table data and any
suitable aggregation functions. You choose how to format the values in the
resulting summary cells by use of a formatter
function (e.g, fmt_number
,
etc.) and any relevant options.
summary_rows(
data,
groups = NULL,
columns = everything(),
fns,
missing_text = "---",
formatter = fmt_number,
...
)
An object of class gt_tbl
.
A table object that is created using the gt()
function.
The groups to consider for generation of groupwise summary
rows. By default this is set to NULL
, which results in the formation of
grand summary rows (a grand summary operates on all table data). Providing
the names of row groups in c()
will create a groupwise summary and
generate summary rows for the specified groups. Setting this to TRUE
indicates that all available groups will receive groupwise summary rows.
The columns for which the summaries should be calculated.
Functions used for aggregations. This can include base functions
like mean
, min
, max
, median
, sd
, or sum
or any other
user-defined aggregation function. The function(s) should be supplied
within a list()
. Within that list, we can specify the functions by use of
function names in quotes (e.g., "sum"
), as bare functions (e.g., sum
),
or as one-sided R formulas using a leading ~
. In the formula
representation, a .
serves as the data to be summarized (e.g., sum(., na.rm = TRUE)
). The use of named arguments is recommended as the names
will serve as summary row labels for the corresponding summary rows data
(the labels can derived from the function names but only when not providing
bare function names).
The text to be used in place of NA
values in summary
cells with no data outputs.
A formatter function name. These can be any of the fmt_*()
functions available in the package (e.g., fmt_number()
, fmt_percent()
,
etc.), or a custom function using fmt()
. The default function is
fmt_number()
and its options can be accessed through ...
.
Values passed to the formatter
function, where the provided
values are to be in the form of named vectors. For example, when using the
default formatter
function, fmt_number()
, options such as decimals
,
use_seps
, and locale
can be used.
Use sp500
to create a gt table with row groups. Create the summary
rows labeled min
, max
, and avg
by row group (where each each row group
is a week number) with the summary_rows()
function.
sp500 %>%
dplyr::filter(date >= "2015-01-05" & date <="2015-01-16") %>%
dplyr::arrange(date) %>%
dplyr::mutate(week = paste0( "W", strftime(date, format = "%V"))) %>%
dplyr::select(-adj_close, -volume) %>%
gt(
rowname_col = "date",
groupname_col = "week"
) %>%
summary_rows(
groups = TRUE,
columns = c(open, high, low, close),
fns = list(
min = ~min(.),
max = ~max(.),
avg = ~mean(.)),
formatter = fmt_number,
use_seps = FALSE
)
5-1
Should we need to obtain the summary data for external purposes, the
extract_summary()
function can be used with a gt_tbl
object where summary
rows were added via summary_rows()
.
Other row addition/modification functions:
grand_summary_rows()
,
row_group_order()