View source: R/tidyHtmlTable.R
tidyHtmlTable | R Documentation |
This function maps columns from the input data, x
, to htmlTable()
parameters.
It's designed to provide a fluent interface for those familiar with the tidyverse
ecosystem.
tidyHtmlTable(
x,
value,
header,
rnames,
rgroup,
hidden_rgroup,
cgroup,
tspanner,
hidden_tspanner,
skip_removal_warning = getOption("htmlTable.skip_removal_warning", FALSE),
rnames_unique,
table_fn = htmlTable,
...
)
x |
Tidy data used to build the |
value |
Column containing values for individual table cells. Defaults to "value" (same as tidyr::pivot_wider). |
header |
Column in |
rnames |
Column in |
rgroup |
Column in |
Strings indicating | |
cgroup |
Columns in |
tspanner |
Column in |
Strings indicating | |
skip_removal_warning |
Boolean to suppress warnings when removing |
rnames_unique |
Designates unique row names when regular names lack uniqueness. |
table_fn |
Function to format the table, defaults to |
... |
Additional arguments passed to |
Returns the HTML code that, when rendered, displays a formatted table.
Columns from x
are mapped (transformed) to specific parameters of the htmlTable()
The following columns are converted to match the intended input structure:
value
header
rnames
rgroup
cgroup
tspanner
Each combination of the variables in x
should be unique to map correctly to the output table.
Usually each row should have a unique combination of the mappers. Sometimes though rows come in a distinct order and the order identifies the row more than the name. E.g. if we are identifying bone fractures using the AO-classification we will have classes ranging in the form of:
A
A1
A1.1
A2
A2.1
A2.2
B
...
we can simplify the names while retaining the key knowledge to:
A
.1
...1
.2
...1
...2
B
...
This will though result in non-unique rows and thus we need to provide the original
names in addition to the rnames
argument. To do this we have rnames_unique
as a parameter,
without this tidyHtmlTable
we risk unintended merging of cells, generating > 1 value per cell.
Note it is recommended that you verify with the full names just to make sure that any unexpected row order change has happened in the underlying pivot functions.
Rows can be pre-sorted using dplyr::arrange()
before passing to tidyHtmlTable
.
Column sorting is based on arrange(cgroup, header)
. If you want to sort in non-alphabetic
order you can provide a factor variable and that information will be retained.
htmlTable
Allows for some values within rgroup
,
cgroup
, etc. to be specified as ""
. The following parameters
allow for specific values to be treated as if they were a string of length
zero in the htmlTable
function.
hidden_rgroup
hidden_tspanner
The tibble discourages the use of row names. There is therefore a convenience
option for tidyHtmlTable
where you can use the function just as you
would with htmlTable()
where rnames
is populated with
the rnames
argument provided using tidyselect
syntax (defaults to
the "names" column if present int the input data).
In order to run this function you also must have dplyr, tidyr, tidyselect and purrr packages installed. These have been removed due to the additional 20 Mb that these dependencies added (issue #47). Note: if you use tidyverse it will already have all of these and you do not need to worry.
htmlTable()
library(tibble)
library(dplyr)
library(tidyr)
# Prep and select basic data
data("mtcars")
base_data <- mtcars %>%
rownames_to_column() %>%
mutate(gear = paste(gear, "Gears"),
cyl = paste(cyl, "Cylinders")) %>%
select(rowname, cyl, gear, wt, mpg, qsec)
base_data %>%
pivot_longer(names_to = "per_metric",
cols = c(wt, mpg, qsec)) %>%
group_by(cyl, gear, per_metric) %>%
summarise(value_Mean = round(mean(value), 1),
value_Min = round(min(value), 1),
value_Max = round(max(value), 1),
.groups = "drop") %>%
pivot_wider(names_from = per_metric,
values_from = starts_with("value_")) %>%
# Round the values into a nicer format where we want the weights to have two decimals
txtRound(ends_with("_wt"), digits = 2) %>%
txtRound(starts_with("value") & !ends_with("_wt"), digits = 1) %>%
# Convert into long format
pivot_longer(cols = starts_with("value_"), names_prefix = "value_") %>%
separate(name, into = c("summary_stat", "per_metric")) %>%
# Without sorting the row groups wont appear right
# If the columns end up in the wrong order you may want to change the columns
# into factors
arrange(per_metric) %>%
addHtmlTableStyle(align = "r") %>%
tidyHtmlTable(
header = gear,
cgroup = cyl,
rnames = summary_stat,
rgroup = per_metric,
skip_removal_warning = TRUE)
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