Introduction
tatoo is designed for creating excel reports from lists of
data.frames with minimal effort, while still providing some
basic formatting capabilities. tatoo functions can combine data.frames
in ways that require additional effort in base R, and to add metadata
(id, title, …) that can be used for printing and xlsx export. The
Tatoo_report class is provided as a convenient helper to write several
such tables to a workbook, one table per worksheet.
Tatoo tables and reports can directly be saved to .xlsx files, or
convert to Workbook objects with as_workbook()
so that you can process them further using the openxlsx
package. While tatoo implements convenient print methods so that you can
preview the tables you created in the console, most of the functionality
provided by this package only makes real sense for xlsx export.
df1 <- data.frame(
Species = c("setosa", "versicolor", "virginica"),
length = c(5.01, 5.94, 6.59),
width = c(3.43, 2.77, 2.97)
)
df2 <- data.frame(
Species = c("setosa", "versicolor", "virginica"),
length = c(0.35, 0.52, 0.64),
width = c(0.38, 0.31, 0.32)
)
Tagged tables
tag_table() allows you to attach different levels of
captioning to a data.frame or Tatoo_table. Those captions are used for
printing and .xlsx export.
# Create metadata object
ex_meta <- tt_meta(
table_id = 'T01',
title = 'Example Table',
longtitle = 'This is an example for tables created with the tatool package',
subtitle = 'It features a lot of titles and very little data',
footer = c('This table was created from the iris dataset',
'It consists of 3 different types of irises’',
'(Setosa, Versicolour, and Virginica)')
)
# Create metadata object
tagged_table <- tag_table(
df1,
meta = ex_meta
)
print(tagged_table)
## T01: Example Table - This is an example for tables created with the tatool package
## It features a lot of titles and very little data
## Species length width
## setosa 5.01 3.43
## versicolor 5.94 2.77
## virginica 6.59 2.97
## This table was created from the iris dataset
## It consists of 3 different types of irises’
## (Setosa, Versicolour, and Virginica)
Metadata can also be assigned an modified via set function.
meta(df1) <- ex_meta # df1 gets automatically converted to a Tagged_table
title(df1) <- 'A table with a title'
table_id(df1) <- NULL
longtitle(df1) <- NULL
subtitle(df1) <- NULL
footer(df1) <- NULL
print(df1)
## A table with a title
## Species length width
## setosa 5.01 3.43
## versicolor 5.94 2.77
## virginica 6.59 2.97
Mashed tables
Tables combined with alternating rows or columns
Combine two data.frames in such a way that you and up with
alternating rows or columns. Internally, a Mashed_table is just a list
of two or more tables, and metadata on how to combine them.
Mashed_tables can be constructed from individual data.frames or a
list of data.frames
mashed_table <- mash_table(df1, df2)
mashed_table <- mash_table_list(list(df1, df2)) # same as above
title(mashed_table) <- 'A mashed table'
subtitle(mashed_table) <-
'Two or more tables mashed together so that rows or columns alternate'
print(mashed_table)
## A mashed table
## Two or more tables mashed together so that rows or columns alternate
## Species length width
## setosa 5.01 3.43
## setosa 0.35 0.38
## versicolor 5.94 2.77
## versicolor 0.52 0.31
## virginica 6.59 2.97
## virginica 0.64 0.32
Additional formatting parameters can be saved as attributes to a mash
table. Those attributes honored by the print and (more significantly)
the as_workbook() methods.
A row-mashed table
mashed_table_row <- mash_table(
df1, df2,
mash_method = 'row',
insert_blank_row = FALSE,
meta = tt_meta(title = 'A row-mashed table')
)
print(mashed_table_row)
## A row-mashed table
## Species length width
## setosa 5.01 3.43
## setosa 0.35 0.38
## versicolor 5.94 2.77
## versicolor 0.52 0.31
## virginica 6.59 2.97
## virginica 0.64 0.32
A col-mashed table
mashed_table_col <- mash_table(
mean = df1, sd = df2,
mash_method = 'col',
id_vars = 'Species',
meta = tt_meta(title = 'A col-mashed table')
)
print(mashed_table_col)
## A col-mashed table
## .......... ..length.. ..width...
## Species mean sd mean sd
## setosa 5.01 0.35 3.43 0.38
## versicolor 5.94 0.52 2.77 0.31
## virginica 6.59 0.64 2.97 0.32
The display parameters are just saved as attributes, and can be
modified conveniently via set functions. Named mashed tables will have
two layers of colnames in print and xlsx output.
mash_method(mashed_table) <- 'col'
id_vars(mashed_table) <- 'Species'
names(mashed_table) <- c('mean', 'sd')
print(mashed_table)
## A mashed table
## Two or more tables mashed together so that rows or columns alternate
## .......... ..length.. ..width...
## Species mean sd mean sd
## setosa 5.01 0.35 3.43 0.38
## versicolor 5.94 0.52 2.77 0.31
## virginica 6.59 0.64 2.97 0.32
You can also directly override the display parameters saved in the
Mashed_table object for printing and xlsx export
print(mashed_table, mash_method = 'row', insert_blank_row = TRUE)
## A mashed table
## Two or more tables mashed together so that rows or columns alternate
## Species length width
## setosa 5.01 3.43
## setosa 0.35 0.38
##
## versicolor 5.94 2.77
## versicolor 0.52 0.31
##
## virginica 6.59 2.97
## virginica 0.64 0.32
All Tatoo table classes can be converted to openxlsx Workbooks via
as_workbook(). Examples for finished .xlsx files
are beyond the scope of this vignette.
as_workbook(mashed_table)
## A Workbook object.
##
## Worksheets:
## Sheet 1: "1"
##
##
##
## Worksheet write order: 1
## Active Sheet 1: "1"
## Position: 1
Convenience functions
rmash() and cmash() are convenient shortcut
functions if you just need to quickly mash together a data.frame
(similar to rbind() and cbind()). Note that
the result is a data.table and not a data.frame, so if you are not
familiar with the data.table package you might want to manually convert
the result to a data.frame to prevent headaches.
rmash
rmash() can be used on several data.frames or on an
existing Mashed table.
rmash(df1, df2)
rmash(mashed_table)
## Species length width
## 1: setosa 5.01 3.43
## 2: setosa 0.35 0.38
## 3: versicolor 5.94 2.77
## 4: versicolor 0.52 0.31
## 5: virginica 6.59 2.97
## 6: virginica 0.64 0.32
rmash() also supports the insert_blank_row
argument of Mashed_table() for consistency.
rmash(df1, df2, insert_blank_row = TRUE)
## Species length width
## 1: setosa 5.01 3.43
## 2: setosa 0.35 0.38
## 3:
## 4: versicolor 5.94 2.77
## 5: versicolor 0.52 0.31
## 6:
## 7: virginica 6.59 2.97
## 8: virginica 0.64 0.32
cmash
The interface of cmash() is very similar to
rmash()
cmash(df1, df2)
cmash(mashed_table)
## Species Species length length width width
## 1: setosa setosa 5.01 0.35 3.43 0.38
## 2: versicolor versicolor 5.94 0.52 2.77 0.31
## 3: virginica virginica 6.59 0.64 2.97 0.32
More polished output can be produced by naming the inputs and using
the id_vars argument.
cmash(mean = df1, sd = df2, id_vars = 'Species')
## Species length.mean length.sd width.mean width.sd
## 1: setosa 5.01 0.35 3.43 0.38
## 2: versicolor 5.94 0.52 2.77 0.31
## 3: virginica 6.59 0.64 2.97 0.32
Composite tables
comp_table() works like cbind(), but
separate super-headings are preserved for each table. Names for each
table can be provided directly, or alternatively the
comp_table_list() constructor can be used as above with
mash_table.
composite_table <- comp_table(mean = df1, sd = df2)
composite_table <- comp_table_list(list(mean = df1, sd = df2)) # same as above
title(composite_table) <- 'A composite table'
subtitle(composite_table) <-
'Two or more tables put side by side, with multi-column-headings'
print(composite_table)
## A composite table
## Two or more tables put side by side, with multi-column-headings
## ..........mean........... ...........sd............
## Species length width Species length width
## setosa 5.01 3.43 setosa 0.35 0.38
## versicolor 5.94 2.77 versicolor 0.52 0.31
## virginica 6.59 2.97 virginica 0.64 0.32
When creating a Composite table, the id_vars argument
can be used to combine the tables via merge, rather than via cbind.
comp_table(mean = df1, sd = df2, id_vars = 'Species')
## .......... ....mean..... .....sd......
## Species length width length width
## setosa 5.01 3.43 0.35 0.38
## versicolor 5.94 2.77 0.52 0.31
## virginica 6.59 2.97 0.64 0.32
Stacked tables
Stacked tables simply stack two tables above each other. The only
meaningful usecase for this at the moment is to put several tables above
each other on the same .xlsx sheet. A stack table can be
consist of an arbitrary number of data.frames or Tatoo_tables – except
other Stacked_tables.
stacked_table <- stack_table(df1, mashed_table, composite_table)
stacked_table <- stack_table_list(list(df1, mashed_table, composite_table)) # same as above
title(stacked_table) <- 'A stacked table'
subtitle(stacked_table) <-
'A list of multiple tables, mainly useful for xlsx export'
print(stacked_table)
## A stacked table
## A list of multiple tables, mainly useful for xlsx export
## ```````````````````````````````````````````````````````````````````````
## ` A table with a title
## ` Species length width
## ` setosa 5.01 3.43
## ` versicolor 5.94 2.77
## ` virginica 6.59 2.97
## ____________________________________________________________________
## ` A mashed table
## ` Two or more tables mashed together so that rows or columns alternate
## ` .......... ..length.. ..width...
## ` Species mean sd mean sd
## ` setosa 5.01 0.35 3.43 0.38
## ` versicolor 5.94 0.52 2.77 0.31
## ` virginica 6.59 0.64 2.97 0.32
## ____________________________________________________________________
## ` A composite table
## ` Two or more tables put side by side, with multi-column-headings
## ` ..........mean........... ...........sd............
## ` Species length width Species length width
## ` setosa 5.01 3.43 setosa 0.35 0.38
## ` versicolor 5.94 2.77 versicolor 0.52 0.31
## ` virginica 6.59 2.97 virginica 0.64 0.32
## `
## ```````````````````````````````````````````````````````````````````````
Tatoo Report
A tatoo report is a list of an arbitrary number of Tatoo tables. When
exported to xlsx, a separate worksheet will be created for each element
table.
tatoo_report <- compile_report(
tagged = tagged_table,
mashed_row = mashed_table_row,
mashed_col = mashed_table_col,
composite = composite_table,
stacked = stacked_table
)
print(tatoo_report)
## tagged <Tagged_table> <Tatoo_table>
## :: T01: Example Table - This is an example for tables created with the tatool package
## :: It features a lot of titles and very little data
## :: Species length width
## :: setosa 5.01 3.43
## :: versicolor 5.94 2.77
## :: virginica 6.59 2.97
## :: This table was created from the iris dataset
## :: It consists of 3 different types of irises’
## :: (Setosa, Versicolour, and Virginica)
##
##
## mashed_row <Tagged_table> <Mashed_table>
## :: A row-mashed table
## :: Species length width
## :: setosa 5.01 3.43
## :: setosa 0.35 0.38
## :: versicolor 5.94 2.77
## :: versicolor 0.52 0.31
## :: virginica 6.59 2.97
## :: virginica 0.64 0.32
##
##
## mashed_col <Tagged_table> <Mashed_table>
## :: A col-mashed table
## :: .......... ..length.. ..width...
## :: Species mean sd mean sd
## :: setosa 5.01 0.35 3.43 0.38
## :: versicolor 5.94 0.52 2.77 0.31
## :: virginica 6.59 0.64 2.97 0.32
##
##
## composite <Tagged_table> <Composite_table>
## :: A composite table
## :: Two or more tables put side by side, with multi-column-headings
## :: ..........mean........... ...........sd............
## :: Species length width Species length width
## :: setosa 5.01 3.43 setosa 0.35 0.38
## :: versicolor 5.94 2.77 versicolor 0.52 0.31
## :: virginica 6.59 2.97 virginica 0.64 0.32
##
##
## stacked <Tagged_table> <Stacked_table>
## :: A stacked table
## :: A list of multiple tables, mainly useful for xlsx export
## :: ```````````````````````````````````````````````````````````````````````
## :: ` A table with a title
## :: ` Species length width
## :: ` setosa 5.01 3.43
## :: ` versicolor 5.94 2.77
## :: ` virginica 6.59 2.97
## :: ____________________________________________________________________
## :: ` A mashed table
## :: ` Two or more tables mashed together so that rows or columns alternate
## :: ` .......... ..length.. ..width...
## :: ` Species mean sd mean sd
## :: ` setosa 5.01 0.35 3.43 0.38
## :: ` versicolor 5.94 0.52 2.77 0.31
## :: ` virginica 6.59 0.64 2.97 0.32
## :: ____________________________________________________________________
## :: ` A composite table
## :: ` Two or more tables put side by side, with multi-column-headings
## :: ` ..........mean........... ...........sd............
## :: ` Species length width Species length width
## :: ` setosa 5.01 3.43 setosa 0.35 0.38
## :: ` versicolor 5.94 2.77 versicolor 0.52 0.31
## :: ` virginica 6.59 2.97 virginica 0.64 0.32
## :: `
## :: ```````````````````````````````````````````````````````````````````````
