Provide a "+" operator for rbind of tangram tables

Description

The plus operator provides an rbind for tangram tables

Usage

## S3 method for class 'tangram'
x + y

Arguments

Value

A row wise merged tangram object

A left/right branch in an Abstract Syntrax Tree. This inherits from ASTNode, and is intended to be a base class as well. Should never be instantiated directly as once again the semantic information is contained in the class name.

Description

A left/right branch in an Abstract Syntrax Tree. This inherits from ASTNode, and is intended to be a base class as well. Should never be instantiated directly as once again the semantic information is contained in the class name.

A left/right branch in an Abstract Syntrax Tree. This inherits from ASTNode, and is intended to be a base class as well. Should never be instantiated directly as once again the semantic information is contained in the class name.

Format

R6Class object.

Super class

tangram::ASTNode -> ASTBranch

Public fields

Methods

Public methods

• ASTBranch$distribute()

• ASTBranch$reduce()

• ASTBranch$clone()

Method distribute()

Call to distribute multiplication nodes, just recursively calls left and right node distribute functions

Usage

ASTBranch$distribute()

Method reduce()

Attached data to nodes by processing data.frame appropriatly. Recursively calls left and right nodes to reduces on data.frame

Usage

ASTBranch$reduce(df)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTBranch$clone(deep = FALSE)

Arguments

A specified function call as an ASTNode

Description

A specified function call as an ASTNode

A specified function call as an ASTNode

Format

R6Class object.

Super class

tangram::ASTNode -> ASTFunction

Public fields

Methods

Public methods

• ASTFunction$new()

• ASTFunction$factors()

• ASTFunction$name()

• ASTFunction$string()

• ASTFunction$reduce()

• ASTFunction$clone()

Method new()

Construct a node representing a function call

Usage

ASTFunction$new(value, r_expr)

Arguments

Method factors()

Returns all terminal nodes, this is a terminal node so returns self

Usage

ASTFunction$factors()

Method name()

Returns the function call as character

Usage

ASTFunction$name()

Method string()

Returns a re-parsable representation of the node

Usage

ASTFunction$string()

Method reduce()

Given a data.frame execute the function in that environment and associate the result as data.

Usage

ASTFunction$reduce(data)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTFunction$clone(deep = FALSE)

Arguments

Examples

ASTFunction$new("log", "x+2")$string()

The multiplication of two terms, as an ASTNode.

Description

The multiplication of two terms, as an ASTNode.

The multiplication of two terms, as an ASTNode.

Format

R6Class object.

Super classes

tangram::ASTNode -> tangram::ASTBranch -> ASTMultiply

Public fields

Methods

Public methods

• ASTMultiply$new()

• ASTMultiply$distribute()

• ASTMultiply$factors()

• ASTMultiply$string()

• ASTMultiply$clone()

Method new()

Construct a multiplication node

Usage

ASTMultiply$new(left, right)

Arguments

Method distribute()

Rearrange nodes distribution multiplication across parenthesis

Usage

ASTMultiply$distribute()

Method factors()

return all terminal nodes on left and right

Usage

ASTMultiply$factors()

Method string()

Return a re-parseable string

Usage

ASTMultiply$string()

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTMultiply$clone(deep = FALSE)

Arguments

Examples

ASTMultiply$new(ASTVariable$new("x"), ASTVariable$new("y"))$string()

A Node in an Abstract Syntax Tree (AST)

Description

A Node in an Abstract Syntax Tree (AST)

A Node in an Abstract Syntax Tree (AST)

Details

This is the root R6 class of any term of the AST which is created when parsing a table formula. This should only be used as a base class as the class information carries the semantic meaning of a given node.

Public fields

Methods

Public methods

• ASTNode$terms()

• ASTNode$distribute()

• ASTNode$string()

• ASTNode$reduce()

• ASTNode$set_format()

• ASTNode$clone()

Method terms()

Returns this node

Usage

ASTNode$terms()

Method distribute()

Distributes data across multiplications and rearranges nodes

Usage

ASTNode$distribute()

Method string()

Returns string representation of node

Usage

ASTNode$string()

Method reduce()

Given a set of data, associates it with AST nodes

Usage

ASTNode$reduce(data)

Arguments

Method set_format()

Override the formatting directive for this node

Usage

ASTNode$set_format(x)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTNode$clone(deep = FALSE)

Arguments

The addition of two terms, in an ASTNode.

Description

The addition of two terms, in an ASTNode.

The addition of two terms, in an ASTNode.

Format

R6Class object.

Super classes

tangram::ASTNode -> tangram::ASTBranch -> ASTPlus

Public fields

Methods

Public methods

• ASTPlus$new()

• ASTPlus$terms()

• ASTPlus$string()

• ASTPlus$clone()

Method new()

Construct a new node that represents addition

Usage

ASTPlus$new(left, right)

Arguments

Method terms()

Returns a vector of the left and right terms

Usage

ASTPlus$terms()

Method string()

A reparsable string representation of this node.

Usage

ASTPlus$string()

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTPlus$clone(deep = FALSE)

Arguments

Examples

ASTPlus$new(ASTVariable$new("x"), ASTVariable$new("y"))$string()

The root ASTNode of a formula.

Description

The root ASTNode of a formula.

The root ASTNode of a formula.

Format

R6Class object.

Super classes

tangram::ASTNode -> tangram::ASTBranch -> ASTTableFormula

Public fields

Methods

Public methods

• ASTTableFormula$new()

• ASTTableFormula$terms()

• ASTTableFormula$string()

• ASTTableFormula$clone()

Method new()

Create a new formula node

Usage

ASTTableFormula$new(left, right)

Arguments

Method terms()

Returns all terminal nodes from left and right

Usage

ASTTableFormula$terms()

Method string()

A re-parseable string representing the AST

Usage

ASTTableFormula$string()

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTTableFormula$clone(deep = FALSE)

Arguments

Examples

ASTTableFormula$new(ASTVariable$new("x"), ASTVariable$new("y"))$string()

A Variable in an Abstract Syntax Tree (AST)

Description

A Variable in an Abstract Syntax Tree (AST)

A Variable in an Abstract Syntax Tree (AST)

Format

R6Class object.

Details

This node represents a variable of interest in the AST. A variable's name is recorded in the value field, and must conform to the rules of identifiers in R. This class inherits from ASTNode.

Methods

new(identifier, format=NA, type=NA)

terms()

Returns the node

distribute()

Applies the distributive property to the node, and returns the resulting node.

string()

Returns the string formula of the node

name()

Return a human representation of a node

reduce(data)

Given a set of data, perform the logical reduction of the current node.

Super class

tangram::ASTNode -> ASTVariable

Public fields

Methods

Public methods

• ASTVariable$new()

• ASTVariable$factors()

• ASTVariable$name()

• ASTVariable$string()

• ASTVariable$reduce()

• ASTVariable$clone()

Method new()

This method creates an AST node representing a variable of a given identifier. An optional format consisting of a string of a number or a c-style printf string. An option type denoting a forced type cast of that variable.

Usage

ASTVariable$new(identifier, format = NA, type = NA)

Arguments

Method factors()

Returns all terminal nodes under this. Since this is a terminal node, returns self

Usage

ASTVariable$factors()

Method name()

Returns the text name of this node. For an intercept, returns "All"

Usage

ASTVariable$name()

Method string()

Returns name of variable with optional format and type information

Usage

ASTVariable$string()

Method reduce()

Given a data.frame, associates correct variable with this node

Usage

ASTVariable$reduce(d)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

ASTVariable$clone(deep = FALSE)

Arguments

Examples

ASTVariable$new("x", "2", "Continuous")$string()

The parser class for generating abstract syntax trees for given table formulas.

Description

The parser class for generating abstract syntax trees for given table formulas.

The parser class for generating abstract syntax trees for given table formulas.

Format

R6Class object.

References

Aho, A. V., Lam, M. S., Sethi, R., and Ullman, J. D. (2006) Compilers: Principles, Techniques, and Tools, 2nd edition. Addison Wesley.

Public fields

Methods

Public methods

• Parser$new()

• Parser$expect()

• Parser$peek()

• Parser$eat_whitespace()

• Parser$next_token()

• Parser$format()

• Parser$r_expression()

• Parser$factor()

• Parser$term()

• Parser$expression()

• Parser$table_formula()

• Parser$run()

• Parser$clone()

Method new()

Create a parser

Usage

Parser$new()

Method expect()

Specify expectation of next token from lexer

Usage

Parser$expect(id)

Arguments

Method peek()

Peek at the next token from parser

Usage

Parser$peek()

Method eat_whitespace()

Remove white space to find start of next token

Usage

Parser$eat_whitespace()

Method next_token()

Returns next lexical token

Usage

Parser$next_token()

Method format()

Return format string as token from lexical stream

Usage

Parser$format()

Method r_expression()

Return R expression as token from lexical stream

Usage

Parser$r_expression()

Method factor()

Return next factor as token.

Usage

Parser$factor()

Method term()

Parse and return next term in stream

Usage

Parser$term()

Method expression()

Parse and return next expression in stream

Usage

Parser$expression()

Method table_formula()

Parse and return table formula from stream

Usage

Parser$table_formula()

Method run()

Run the parser

Usage

Parser$run(x)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

Parser$clone(deep = FALSE)

Arguments

Examples

Parser$new()$run("col1 + col2 + col3 ~ drug*age+spiders")

A token in the formula grammar

Description

A token in the formula grammar

A token in the formula grammar

Format

R6Class object.

Public fields

Methods

Public methods

• Token$new()

• Token$clone()

Method new()

Construct a lexical token

Usage

Token$new(id, name = "")

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

Token$clone(deep = FALSE)

Arguments

Add a footnote to a table

Description

Add a footnote to a table

Usage

add_footnote(table, footnote)

Arguments

Value

the modified table

Add indentations to left column row headers

Description

Add indentations to left column row headers. Note: will only work on cell_header cells.

Usage

add_indent(table, amounts = 2, rows = NULL, columns = NULL)

Arguments

Value

the modified table

Examples

x <- tangram(drug ~ bili + albumin, pbc)
add_indent(x)
add_indent(x, amounts=10)
add_indent(x, amounts=c(0, 0, 2, 4))
add_indent(x, rows=c(3))
add_indent(x, rows=c(3, 4), amounts=c(4, 2))

Flatten variable arguments

Description

Take variable arguments, flatten vectors and lists, but do not flatten cells (which are lists) e.g. args_flatten(NA, list(1,2,3), 4:6, c(7,8,9))

Usage

args_flatten(...)

Arguments

Value

a list of the arguments, with vectors and lists flattened

Convert data type to a factor if it's not already

Description

Convert data type to a factor if it's not already

Usage

as.categorical(x)

Arguments

Value

Data as a factor

Examples

as.categorical(1:3)

A cbind for generated table tangram objects.

Description

Execute the equivalent of an cbind for generated tables

Usage

## S3 method for class 'tangram'
cbind(..., deparse.level = 1)

Arguments

Value

A merged tangram object

Construct a table cell from an object

Description

Any R object can be used as a cell value. Attributes are used to store additional classs of that cell attached to the object. This is a helper function to attach all the additional attributes to the provided object

Usage

cell(x, ...)

Arguments

Details

Certain attributes have special meaning: - 'names' is appended to the front of a value, e.g. "P=" for a p-value. - 'sep' is used to join values, e.g. ", " for a list of values. - 'class' denotes special rendering handling, e.g. generally passed as CSS class to HTML5 - 'reference' a list of reference symbols to put inside the cell - 'row' and 'col' should refer to the row / column if key generation is needed - 'subrow' and 'subcol' further delinate the key value of a cell for key generation

Value

The modified R object

Create a cell_header object of the given text.

Description

A cell_header object represents a label cell inside a table. It can also contain units.

Usage

cell_header(text, units = NULL, class = NULL, ...)

Arguments

Value

A cell_header object

Examples

cell_header("Yahoo")
cell_header("Concentration", "mg/dl")
cell_header("Concentration", "mg/dl", src="A")

Create an cell_label (S3) object of the given text.

Description

A cell_label object represents a label cell inside a table. It can also contain units.

Usage

cell_label(text, units = NULL, class = NULL, ...)

Arguments

Value

A tangram object

Examples

cell_label("Compaction Method")
cell_label("Concentration", "mg/dl")
cell_label("Concentration", "mg/dl", subcol="A")

Create an cell_n (S3) object of the given statistic

Description

A cell_n object contains an n value. Essentially, this is just a helper that appends the cell_n class to the given object and makes sure it's a cell S3 object as well.

Usage

cell_n(n, class = NULL, hdr = FALSE, possible = NULL, ...)

Arguments

Value

A cell_n object.

Examples

cell_n(20)

Create a cell_subheader object of the given text.

Description

A cell_subheader object represents a label cell inside a table. It can also contain units.

Usage

cell_subheader(text, units = NULL, class = NULL, ...)

Arguments

Value

A cell_subheader object.

Examples

cell_subheader("Concentration")
cell_subheader("Concentration", "mg/dl")
cell_subheader("Concentration", "mg/dl", src="A")

Create a function to transform all cells of a table

Description

Given a function that operates on a table cell and returns the modified cell, return a function that given a table applies that function to all cells and returns the modified table.

Usage

cell_transform(FUN, ...)

Arguments

Value

a table modification function

A set of magrittr operators for tangram tables

Description

A set of magrittr operators for tangram tables

Usage

col_header(table, ..., sub = TRUE)

row_header(table, ..., sub = TRUE)

write_cell(table, x, ...)

home(table)

cursor_up(table, n = 1)

cursor_down(table, n = 1)

cursor_left(table, n = 1)

cursor_right(table, n = 1)

cursor_pos(table, nrow, ncol)

carriage_return(table)

line_feed(table, n = 1)

new_line(table)

new_row(table)

new_col(table)

table_apply(table, x, FUN, ...)

add_col(table, ...)

add_row(table, ...)

set_footnote(table, footnote)

set_id(table, id)

set_caption(table, caption)

set_style(table, style)

set_colspan(table, span)

set_rowspan(table, span)

Arguments

Generate an csv from a tangram or cell object

Description

Given a tangram object create an index representation.

Usage

csv(object, ...)

## S3 method for class 'tangram'
csv(object, file = NULL, sep = ",", ...)

## Default S3 method:
csv(object, ...)

Arguments

Value

A string containing the csv file

Return a CSS file as a string

Description

Given a filename, this function will load the file name from the current working directory. If it is not found from the current working directory it will search in the package for a a matching filename and load that instead. If an id is specified, that will be prepended to all CSS selectors (TODO: make this substitution more robust). The result is returned as a string.

Usage

custom_css(filename, id = NA)

Arguments

Value

String of possibly modified CSS file

Examples

custom_css("lancet.css", "tbl1")

Delete given column(s) from a table

Description

Given a table, remove the specified column

Usage

del_col(table, col)

Arguments

Value

the modified table

Delete a row(s) from a table

Description

Given a table, remove the specified row

Usage

del_row(table, row)

Arguments

Value

the modified table

Derive label of AST node.

Description

Determine the label of a given AST node. NOTE: Should have data attached via reduce before calling.

Usage

derive_label(node, capture_units = FALSE, ...)

Arguments

Value

A string with a label for the node

Drop all statistics columns from a table.

Description

Delete from a table all columns that contain statistics

Usage

drop_statistics(table)

Arguments

Value

the modified table

Guess the best format for a given set of numerical data

Description

Given a vector of data, default to 3 significant digits or all if maximum is greater than zero

Usage

format_guess(x)

Arguments

Value

numeric; the digits past the decimal recommended for display

Examples

format_guess(rnorm(100))
format_guess(rnorm(100, sd=1e-6))

Determine data type of a vector loosely consistent with Hmisc.

Description

Determine data type of a vector loosely consistent with Hmisc.

Usage

hmisc_data_type(x, category_threshold = NA)

Arguments

Value

One of the following strings: Binomial, Categorical, or Numerical.

See Also

hmisc

Examples

hmisc_data_type(c(1,2,3))
hmisc_data_type(factor(c("A","B","C")))
hmisc_data_type(factor(c("A","B","B","A")))
hmisc_data_type(factor(c(TRUE, FALSE, TRUE, FALSE)))

Cleanup an intercept only model

Description

Cleanup an intercept only table that was generated from the hmisc default transform. This drops the statistics column, and modifies the header to eliminate blank space.

Usage

hmisc_intercept_cleanup(table)

Arguments

Value

the modified table

Cell Generation functions for hmisc default

Description

Each function here is called when a cell is generated. Overriding these in a formula call will allows one to customize exactly how each cell's contents are generated. While this serves as the base template for transforms, it is by no means required if one develops their own bundle of data transforms. One can create ay number of cell level styling choices.

Usage

hmisc_p(p, pformat = "%1.3f", include_p = TRUE)

hmisc_iqr(
  x,
  format = NA,
  na.rm = TRUE,
  names = FALSE,
  type = 8,
  msd = FALSE,
  quant = c(0.25, 0.5, 0.75),
  ...
)

hmisc_fraction(numerator, denominator, format = 3, ...)

hmisc_fstat(f, df1, df2, p, class = NULL, ...)

hmisc_chi2(chi2, df, p, class = NULL, ...)

hmisc_spearman(S, rho, p, class = NULL, ...)

hmisc_wilcox(V, p, class = NULL, ...)

hmisc_cell

Arguments

Format

An object of class list of length 8.

Value

A formatted string or cell as appropriate

hmisc_p

Given a style in number of digits or a sprintf style specifier it renders the p-value and checks to see if it's all zeros, then switches the output to a less than.

hmisc_iqr

Construct a cell which has the interquartile ranges specified.

hmisc_fraction

Construct a cell which has the fraction specified in an hmisc format

hmisc_fstat

Construct a cell which has the fstat specified in an hmisc format.

hmisc_chi2

Construct a cell which has the chi^2 specified in an hmisc format

hmisc_spearman

Construct a cell which has the spearman specified in an hmisc format

hmisc_wilcox

Construct a cell which has the Wilcoxon specified in an hmisc format

hmisc_cell

List of data transforms for a cell of a table.

hmisc_cell <- list(
  n        = cell_n,
  iqr      = hmisc_iqr,
  fraction = hmisc_fraction,
  fstat    = hmisc_fstat,
  chi2     = hmisc_chi2,
  spearman = hmisc_spearman,
  wilcox   = hmisc_wilcox,
  p        = hmisc_p
)

See Also

hmisc

Examples

hmisc_p(1e-6)
hmisc_p(0.234)
hmisc_p(1.234e-6, 5)
hmisc_p(1.234e-6, 6)
require(stats)
hmisc_iqr(rnorm(100), '3')
hmisc_fraction(1, 4, 3)
hmisc_fstat(4.0, 10, 20, 0.004039541)
hmisc_chi2(5.33, 6, 0.2)
hmisc_spearman(20, 0.2, 0.05)
hmisc_wilcox(20, 0.2)

S3 html5 Method function for use on a tangram to generate HTML5

Description

S3 html5 Method function for use on a tangram to generate HTML5

Usage

html5(object, id, ...)

Arguments

Convert an abstract cell object into an HTML5 string

Description

Given a cell class create an HTML5 representation.

Usage

## S3 method for class 'cell'
html5(object, id, ..., class = NULL)

Arguments

Value

A text string rendering of the given cell as a <td> with several <span>'s.

Convert an abstract cell_header object into an HTML5 string

Description

Given a cell_header class create an HTML5 representation.

Usage

## S3 method for class 'cell_header'
html5(object, id, ..., class = NULL)

Arguments

Value

A text string rendering of the given subheader as a <td> with several <span>'s.

Convert a cell_label object into an HTML5 string

Description

Given a cell_label class create an HTML5 representation.

Usage

## S3 method for class 'cell_label'
html5(object, id, ..., class = NULL)

Arguments

Value

A text string rendering of the given label as a <td> with several <span>'s.

Convert an abstract cell_n object into an HTML5 string

Description

Given a cell_n class create an HTML5 representation.

Usage

## S3 method for class 'cell_n'
html5(object, id, ..., class = NULL)

Arguments

Value

A text string rendering of the given n as a <td> with several <span>'s.

Convert an abstract cell_subheader object into an HTML5 string

Description

Given a cell_subheader class create an HTML5 representation.

Usage

## S3 method for class 'cell_subheader'
html5(object, id, ..., class = NULL)

Arguments

Value

A text string rendering of the given subheader as a <td> with several <span>'s.

Default conversion to HTML5 for a character cell

Description

Produces table cell

Usage

## S3 method for class 'character'
html5(object, id, ..., class = NA)

Arguments

Value

An empty html5 td of the given class

Default conversion to HTML5 for an abstract table element

Description

Gives a warning and produces an empty <td></td> cell

Usage

## Default S3 method:
html5(object, id, ..., class = NA)

Arguments

Value

An empty html5 td of the given class

Default conversion to HTML5 for a logical cell

Description

Produces table cell or nothing if it's an NA. This is useful for dealing with rowspan and colspan.

Usage

## S3 method for class 'logical'
html5(object, id, ..., class = NA)

Arguments

Value

An empty html5 td of the given class

Convert a tangram class into an HTML5 string

Description

Given a tangram class, a series of conversion creates an HTML5 representation of the table. It may be an HTML5 fragment or it may be a complete web page.

Usage

## S3 method for class 'tangram'
html5(
  object,
  id = NULL,
  caption = NULL,
  fragment = NULL,
  style = NULL,
  footnote = NULL,
  inline = NULL,
  fixed_thead = NULL,
  ...
)

Arguments

Details

The package includes several css files for styling. At present the following exist: 'hmisc.css', 'lancet.css', 'lancet-stripped.css' and 'nejm.css'

Value

A text string rendering of the given table in HTML5

Generate an index from a tangram or cell object

Description

Given a tangram object create an index representation.

Usage

index(object, ...)

Arguments

Value

A matrix or list of strings containing key, source and value

Generate an index from a label object

Description

Overrides to generate no indexing on labels

Usage

## S3 method for class 'cell_label'
index(object, id = "tangram", key.len = 4, ...)

Arguments

Value

A list of strings containing key, source and value

Generate an index from a cell object

Description

Given a cell class create an index representation. If no source is specified no index will be generated.

Usage

## Default S3 method:
index(object, id = "tangram", name = NULL, key.len = 4, ...)

Arguments

Value

A list of strings containing key, source and value

Generate an index from a list object

Description

Given a cell class create an index representation. If no source is specified no index will be generated.

Usage

## S3 method for class 'list'
index(object, id = "tangram", key.len = 4, ...)

Arguments

Value

A list of strings containing key, source and value

Generate an an index from a tangram object

Description

Given a tangram class create an index representation.

Usage

## S3 method for class 'tangram'
index(object, id = "tangram", key.len = 4, ...)

Arguments

Value

A matrix of strings containing key, source and value

Insert a column into a tangram table

Description

Insert a column into a tangram table. Will fill with empty cells is not enough cells are specified.

Usage

insert_column(table, after, ..., class = NULL)

Arguments

Value

the modified table

Insert a row into a tangram table

Description

Insert a row into a tangram table. Will fill with empty cells is not enough cells are specified.

Usage

insert_row(table, after, ..., class = NULL)

Arguments

Value

the modified table

Determine if a vector is binomial or not

Description

Determine if a vector is binomial or not

Usage

is.binomial(x, threshold = NA)

Arguments

Value

a Boolean: TRUE / FALSE

Examples

is.binomial(c(1,2,3))
is.binomial(factor(c("A","B","C")))
is.binomial(factor(c("A","B","B","A")))
is.binomial(factor(c(TRUE, FALSE, TRUE, FALSE)))
is.binomial(c('M', 'F', 'M', 'F'), 10)

Determine if a vector is categorical or not

Description

Determine if a vector is categorical or not

Usage

is.categorical(x, threshold = NA)

Arguments

Value

A Boolean: TRUE / FALSE

Examples

is.categorical(c(1,2,3))
is.categorical(c(rep(1,20), rep(2, 20), rep(3, 20)), threshold=5)
is.categorical(c("A","B","B"))
is.categorical(factor(c("A","B","C")))
is.categorical(factor(c("A","B","B","A")))
is.categorical(factor(c(TRUE, FALSE, TRUE, FALSE)))

Key derivation helper function

Description

This function should generate a string that uniquely identifies a piece of data present in a table. In a report with multiple tables the id is used to preserve uniqueness.

Usage

key(x, id)

Arguments

Details

This function relies on the object being keyed having at a minimum character attributes for row and col. Additional specifies for embedded tables are given with subrow and subcol. The row and col are automatically appended when using a table_builder. However the subrow and subcol must be added by the user to a cell of a table.

Style Bundle for Lancet style

Description

List of lists, should contain a "Type" entry with a function to determine type of vector passed in. Next entries are keyed off returned types from function, and represent the type of a row. The returned list should contain the same list of types, and represents the type of a column. Thus it now returns a function to process the intersection of those two types.

Usage

lancet

Format

An object of class list of length 5.

Cell Generation functions for Lancet styling

Description

Each function here is called when a cell is generated. Overriding these in a formula call will allows one to customize exactly how each cell's contents are generated.

Usage

lancet_cell

Format

An object of class list of length 8.

Create an cell_fraction (S3) in NEJM style of the given data

Description

A cell object contains a statistical result of a fraction/percentage in nejm style

Usage

lancet_fraction(numerator, denominator, format = NULL, ...)

Arguments

Value

A cell_fraction object.

Examples

lancet_fraction(1, 4, 3)

Create a mean/sd cell object of the given data in Lancet style

Description

Create a mean/sd cell object of the given data in Lancet style.

Usage

lancet_mean_sd(
  x,
  format = NA,
  na.rm = TRUE,
  names = FALSE,
  type = 8,
  msd = FALSE,
  quant = c(0.25, 0.5, 0.75),
  ...
)

Arguments

Value

A cell object.

Examples

require(stats)
lancet_mean_sd(rnorm(100), '3')

Render to LaTeX methods for tangram cell objects

Description

Each of these methods will render the cell object as a LaTeX fragment

Usage

latex(object, ...)

## Default S3 method:
latex(object, ...)

## S3 method for class 'cell'
latex(object, na.blank = TRUE, ...)

## S3 method for class 'cell_label'
latex(object, ...)

## S3 method for class 'logical'
latex(object, ...)

## S3 method for class 'cell_header'
latex(object, ...)

## S3 method for class 'cell_subheader'
latex(object, ...)

## S3 method for class 'tangram'
latex(object, fragment = TRUE, filename = NULL, append = FALSE, ...)

Arguments

Details

There are addition arguments possible to control the rendering, but due to some oddities between CRAN requirements and how R handles defaults (for full details see the source code) they are as follows

* cgroup.just character; The text of the column justification used in the table

* arraystretch numeric; The arraystretch parameter used for vertical spacing

* style character; can be null or "nejm" for different table styling

* rel_size numeric; a scaling to be applied to the entire table, e.g. rel_size=-2

* placement character; placement directive, defaults to "H"

Value

the LaTeX rendering

Examples

latex(cell_label("123"))
latex(hmisc_iqr(rnorm(20)))
latex(hmisc_fraction(45, 137))
tbl <- tangram(drug~bili, pbc, "tbl")
latex(tbl)

Return a LaTeX template that works with tangram

Description

Pandoc in the current version of RStudio does not allow for setting package options to xcolor and this has made it incompatible with the LaTeX generated by this package. This provides a known working template.

Usage

latex_template()

Details

An example header would look like the following:

— title: "A Document Full of Beautiful Tables" output: pdf_document: "'r tangram::latex_template()'" —

Value

filename of LaTeX template

LaTeX safe string conversion

Description

LaTeX safe string conversion. This transforms a string handling Markdown characters and UNICODE as best it can with an automated pass.

Usage

latexify(x)

Arguments

Value

valid LaTeX code

Style Bundle for Closer to NEJM style

Description

List of lists, should contain a "Type" entry with a function to determine type of vector passed in. Next entries are keyed off returned types from function, and represent the type of a row. The returned list should contain the same list of types, and represents the type of a column. Thus it now returns a function to process the intersection of those two types.

Usage

nejm

Format

An object of class list of length 5.

Cell Generation functions for nejm default

Description

Each function here is called when a cell is generated. Overriding these in a formula call will allows one to customize exactly how each cell's contents are generated.

Usage

nejm_cell

Format

An object of class list of length 9.

Details

While this serves as the base template for transforms, it is by no means required if one develops their own bundle of data transforms. One can create ay number of cell level styling choices.

Create an cell_fraction (S3) in NEJM style of the given data

Description

A cell object contains a statistical result of a fraction/percentage in nejm style

Usage

nejm_fraction(numerator, denominator, format = NULL, ...)

Arguments

Value

A cell_fraction object.

Examples

nejm_fraction(1, 4, 3)

Create a interquartile range cell object of the given data NEJM style

Description

Construct a cell which has the 3 interquartile ranges specified.

Usage

nejm_iqr(
  x,
  format = NA,
  na.rm = TRUE,
  names = FALSE,
  type = 8,
  msd = FALSE,
  quant = c(0.25, 0.5, 0.75),
  ...
)

Arguments

Value

A cell_quantile object.

Examples

require(stats)
nejm_iqr(rnorm(100), '3')

Create a NEJM style range

Description

Construct a cell which has the range of the given data in NEJM style

Usage

nejm_range(x, format, ...)

Arguments

Mayo Clinic Primary Biliary Cirrhosis Data

Description

D This data is from the Mayo Clinic trial in primary biliary cirrhosis (PBC) of the liver conducted between 1974 and 1984. A total of 424 PBC patients, referred to Mayo Clinic during that ten-year interval, met eligibility criteria for the randomized placebo controlled trial of the drug D-penicillamine. The first 312 cases in the data set participated in the randomized trial and contain largely complete data. The additional 112 cases did not participate in the clinical trial, but consented to have basic measurements recorded and to be followed for survival. Six of those cases were lost to follow-up shortly after diagnosis, so the data here are on an additional 106 cases as well as the 312 randomized participants.

Usage

pbc

Format

An object of class data.frame with 418 rows and 19 columns.

Details

A nearly identical data set found in appendix D of Fleming and Harrington; this version has fewer missing values.

Included for use in example from Hmisc.

Provide a "|" operator for cbind of tangram tables

Description

The pipe operator provides an cbind for tangram tables

Usage

## S3 method for class 'tangram'
x | y

Arguments

Value

A column wise merged tangram object

Print methods for tangram objects

Description

Print methods for tangram objects

Usage

## S3 method for class 'cell'
print(x, ...)

## S3 method for class 'tangram'
print(x, ...)

## S3 method for class 'summary.tangram'
print(x, ...)

Arguments

Value

the text summary

Examples

print(cell_label("123"))
print(hmisc_iqr(rnorm(20)))
print(hmisc_fraction(45, 137))
print(tangram(1,1)   %>%
        row_header("row") %>%
        col_header(1,2,3) %>%
        add_col("A","B","C"))
print(tangram(drug~bili, pbc))

Tangram transform for proc_tab style summaries via a function

Description

Given a function that produces a vector of tangram cells, will generate a table

Usage

proc_tab(table, row, column, fun = NULL, overall = FALSE, ...)

Arguments

An rbind for generated tables tangram objects.

Description

Execute the equivalent of an rbind for generated tables

Usage

## S3 method for class 'tangram'
rbind(..., deparse.level = 1)

Arguments

Value

A merged tangram object

Format a vector of provided numeric values

Description

Given a vector of data return as strings formatted as requested

Usage

render_f(x, format)

Arguments

Value

character; formatted values as character strings

Examples

render_f(rnorm(5), 3)
render_f(round(rnorm(5), 2), "%010.03f")

Router for rendering method

Description

This functions detects if knitr is loaded, and does it's best to determine the output format from knitr and returns the appropriate rendering function.

Usage

render_route_tangram()

Value

A rendering function to use

Replace a cell's contents

Description

Replace a cell in a table

Usage

replace_cell(table, row, col, object, ...)

Arguments

Value

the modified table

Generate an Rmd table entry from a cell object

Description

Given a cell object generate the corresponding piece of an Rmd table

Usage

rmd(object, key = FALSE, ...)

## Default S3 method:
rmd(object, key = FALSE, ...)

## S3 method for class 'cell'
rmd(object, key = FALSE, ...)

## S3 method for class 'cell_n'
rmd(object, key = FALSE, ...)

## S3 method for class 'tangram'
rmd(object, key = NULL, append = FALSE, pad = 10, ...)

Arguments

Value

A string representation of the table

Examples

 rmd(tangram(drug ~ bili, pbc))

S3 object to return number of rows/cols in object

Description

Number of rows/cols in provided object

Usage

rows(x)

cols(x)

## S3 method for class 'list'
rows(x)

## S3 method for class 'list'
cols(x)

Arguments

S3 rtf Method function for use on abstract table class

Description

S3 rtf Method function for use on abstract table class

Usage

rtf(object, id, ...)

Arguments

Value

A text string rendering of the given table

Given a cell class create an RTF representation.

Description

Given a cell class create an RTF representation.

Usage

## S3 method for class 'cell'
rtf(object, id, ...)

Arguments

Value

An RTF string rendering of the given cell.

Convert an abstract cell_chi2 object into an rtf string

Description

Given a cell_chi2 class create an rtf representation.

Usage

## S3 method for class 'cell_chi2'
rtf(object, id, ...)

Arguments

Value

A text string rendering of the given chi2 in rtf

Convert an abstract cell_fstat object into an RTF string

Description

Given a cell_fstat class create an RTF representation.

Usage

## S3 method for class 'cell_fstat'
rtf(object, id, ...)

Arguments

Value

A text string rendering of the given fstat as a <td> with several <span>'s.

Convert an abstract cell_header object into an RTF string

Description

Given a cell_header class create an RTF representation.

Usage

## S3 method for class 'cell_header'
rtf(object, id, ...)

Arguments

Value

An RTF string rendering of the given header

Convert an abstract cell_iqr object into an RTF string

Description

Given a cell_quantile class create an RTF representation.

Usage

## S3 method for class 'cell_iqr'
rtf(object, id, ..., point = 9)

Arguments

Value

An RTF string rendering of the given quantile.

Given a cell_label class create an RTF representation.

Description

Given a cell_label class create an RTF representation.

Usage

## S3 method for class 'cell_label'
rtf(object, id, ..., point = 18)

Arguments

Value

An RTF text string rendering of the given label.

Convert an abstract cell_n object into an RTF string

Description

Given a cell_n class create an RTF representation.

Usage

## S3 method for class 'cell_n'
rtf(object, id, ...)

Arguments

Value

An RTF string rendering of the given n.

Convert an abstract cell_subheader object into an RTF string

Description

Given a cell_subheader class create an RTF representation.

Usage

## S3 method for class 'cell_subheader'
rtf(object, id, ..., point = 9)

Arguments

Value

An RTF string rendering of the given header

Default conversion to RTF for an abstract table element

Description

Gives a warning and produces an empty cell

Usage

## Default S3 method:
rtf(object, id, ...)

Arguments

Value

A RTF string rendering of the given cell

Convert a tangram into an RTF string or file

Description

Given a tangram class, a series of conversion creates an rtf representation of the table.

Usage

## S3 method for class 'tangram'
rtf(
  object,
  id = NA,
  caption = NA,
  fragment = FALSE,
  widths = NA,
  footnote = NA,
  filename = NA,
  append = FALSE,
  point = 9,
  ...
)

Arguments

Value

A text string rendering of the given table

Select given column(s) from a table

Description

Given a table, select the specified column(s)

Usage

select_col(table, col)

Arguments

Value

the modified table

Select given row(s) from a table

Description

Given a table, select the specified rows

Usage

select_row(table, row)

Arguments

Value

the modified table

List of lists, should contain a "Type" entry with a function to determine type of vector passed in. Next entries are keyed off returned types from function, and represent the type of a row. The returned list should contain the same list of types, and represents the type of a column. Thus it now returns a function to process the intersection of those two types.

Description

List of lists, should contain a "Type" entry with a function to determine type of vector passed in. Next entries are keyed off returned types from function, and represent the type of a row. The returned list should contain the same list of types, and represents the type of a column. Thus it now returns a function to process the intersection of those two types.

Usage

smd

Format

An object of class list of length 5.

Cell Generation functions for SMD comparisons of categorical to numerical

Description

Each function here is called when a cell is generated. Overriding these in a formula call will allows one to customize exactly how each cell's contents are generated.

Usage

smd_cell

Format

An object of class list of length 7.

Details

While this serves as the base template for transforms, it is by no means required if one develops their own bundle of data transforms. One can create ay number of cell level styling choices.

Create a SMD for a categorical set of column versus a numerical row

Description

Given a row and column object from the parser apply a Kruskal test and output the results horizontally. 1 X (n + no. categories + test statistic)

Usage

smd_compare(
  table,
  row,
  column,
  cell_style,
  style,
  smdformat = NULL,
  pformat = NULL,
  weight = NULL,
  test = FALSE,
  ...
)

Arguments

Value

The modified table object

Create a contingency table with SMD given a row column of a formula

Description

Create a contingency table with SMD given a row column of a formula

Usage

smd_contingency(
  table,
  row,
  column,
  cell_style,
  style,
  smdformat = NULL,
  collapse_single = TRUE,
  weight = NULL,
  test = FALSE,
  pformat = NULL,
  ...
)

Arguments

Value

The resulting sub table constructed

Create an SMD distance cell

Description

Create an SMD distance cell. It calls the smd function then formats the result. If the result rounds to all zeros then it appends a less than sign and bumps the least significant digit to one.

Usage

smd_dist(x, group, format, weight = NULL, ...)

Arguments

Value

a tangram cell

Create a fraction cell in the smd transform

Description

Create a fraction cell in the smd transform. In this instance it print the numerator followed by percentage in parenthesis.

Usage

smd_fraction(num, den, format, ...)

Arguments

Value

a tangram cell

Create an SMD mean and standard deviation cell

Description

Create an SMD mean and standard deviation cell. In this case it prints the mean with the standard deviation in parenthesis

Usage

smd_meansd(x, format, ...)

Arguments

Value

a tangram cell

Compute the standardized mean distance between 2 groups for numerical or categorical information. Using method described in 'A unifed approach to measuring the effect size between two groups using SAS' by Dongsheng Yand and Jarrod E. Dalton, 2012. SAS Global Forum 2012

Description

Compute the standardized mean distance between 2 groups for numerical or categorical information. Using method described in 'A unifed approach to measuring the effect size between two groups using SAS' by Dongsheng Yand and Jarrod E. Dalton, 2012. SAS Global Forum 2012

Usage

standard_difference(x, group, weight = NULL)

Arguments

Style Bundle for Hmisc defaults

Description

List of lists, should contain a "Type" entry with a function to determine type of vector passed in. Next entries are keyed off returned types from function, and represent the type of a row. The returned list should contain the same list of types, and represents the type of a column. Thus it now returns a function to process the intersection of those two types. There are additionally a list of cell tranforms that can be overridden and a default footnote if none is specified.

Usage

summarize_kruskal_horz(
  table,
  row,
  column,
  cell_style,
  pformat = NULL,
  msd = FALSE,
  quant = c(0.25, 0.5, 0.75),
  overall = NULL,
  test = FALSE,
  ...
)

summarize_kruskal_vert(
  table,
  row,
  column,
  cell_style,
  collapse_single = TRUE,
  pformat = NULL,
  msd = FALSE,
  test = FALSE,
  ...
)

summarize_chisq(
  table,
  row,
  column,
  cell_style,
  pformat = NULL,
  collapse_single = TRUE,
  overall = NULL,
  test = FALSE,
  row_percents = FALSE,
  useNA = "no",
  ...
)

summarize_spearman(
  table,
  row,
  column,
  cell_style,
  pformat = NULL,
  test = FALSE,
  ...
)

hmisc

Arguments

Format

An object of class list of length 5.

Value

The modified table object

summarize_kruskal_horz

Given a row and column object apply a Kruskal test and output the results horizontally. 1 X (n + no. categories + test statistic)

summarize_kruskal_vert

Given a row and column object from the parser apply a Kruskal test and output the results vertically (#Categories+1) X (N, Summary, Statistic)

summarize_chisq

Given a row and column object from the parser apply a chi^2 test and output the results

summarize_spearman

Given a row and column object from the parser apply a Spearman test and output the results in a 1X3 format.

hmisc

hmisc <- list(
 Type        = hmisc_data_type,
 Numerical   = list(
   Numerical   = summarize_spearman,
   Categorical = summarize_kruskal_horz
 ),
 Categorical = list(
   Numerical   = summarize_kruskal_vert,
   Categorical = summarize_chisq
 ),
 Cell        = hmisc_cell,
 Footnote    = "N is the number of non-missing value. ^1^Kruskal-Wallis. ^2^Pearson. ^3^Wilcoxon."
)

See Also

hmisc_data_type, tangram, hmisc_cell

Create a summarization for a categorical set of column versus a numerical row in NEJM style

Description

Given a row and column object from the parser apply a Kruskal test and output the results horizontally. 5 X (n + no. categories + test statistic)

Usage

summarize_nejm_horz(
  table,
  row,
  column,
  cell_style,
  pformat = NULL,
  msd = FALSE,
  quant = c(0.25, 0.5, 0.75),
  overall = NULL,
  test = FALSE,
  useNA = "no",
  ...
)

Arguments

Value

The modified table object

Create a summarization for a categorical row versus X numerical column

Description

Given a row and column object from the parser apply a Kruskal test and output the results vertically (#Categories+1) X (N, Summary, Statistic)

Usage

summarize_nejm_vert(
  table,
  row,
  column,
  cell_style,
  collapse_single = TRUE,
  pformat = NULL,
  msd = FALSE,
  test = FALSE,
  quant = c(0.25, 0.5, 0.75),
  ...
)

Arguments

Value

The modified table object

The default method for rendering tangram objects

Description

A tangram is a summary, so it returns itself. Otherwise convert to a text representation.

Usage

## S3 method for class 'tangram'
summary(object, ...)

## S3 method for class 'cell'
summary(object, ...)

Arguments

Value

the text summary

Examples

summary(cell_label("123"))
summary(hmisc_iqr(rnorm(20)))
summary(hmisc_fraction(45, 137))
summary(tangram(1,1)   %>%
        row_header("row") %>%
        col_header(1,2,3) %>%
        add_col("A","B","C"))
summary(tangram(drug~bili, pbc))

Given a tangram object with embedded tables, flattens to a single table.

Description

Flattening function to expanded embedded tables inside table cells.

Usage

table_flatten(table)

Arguments

Value

the flattened table object

Table creation methods

Description

The tangram method is the principal method to create tables. It uses R3 method dispatch. If one specifies rows and columns, one gets an empty table of the given size. A formula or character will invoke the parser and process the specified data into a table like Hmisc::summaryM. Given an rms object it will summarize that model in a table. A data.frame is converted directly into a table as well for later rendering. Can create tables from summary.rms(), anova.rms(), and other rms object info to create a single pretty table of model results. The rms and Hmisc packages are required.

Usage

## S3 method for class 'clmm2'
tangram(
  x,
  id = NULL,
  style = "hmisc",
  caption = NULL,
  footnote = NULL,
  digits = NULL,
  ...
)

## S3 method for class 'summary.clmm2'
tangram(
  x,
  id = NULL,
  style = "hmisc",
  caption = NULL,
  footnote = NULL,
  digits = NULL,
  pformat = "%1.3f",
  include_p = FALSE,
  ...
)

tangram(x, ...)

## S3 method for class 'numeric'
tangram(
  x,
  cols,
  id = NULL,
  caption = NULL,
  style = "hmisc",
  footnote = NULL,
  fixed_thead = NULL,
  ...
)

## S3 method for class 'anova.lme'
tangram(
  x,
  id = NULL,
  style = "hmisc",
  caption = NULL,
  footnote = NULL,
  digits = NULL,
  fixed_thead = NULL,
  ...
)

## S3 method for class 'data.frame'
tangram(
  x,
  id = NULL,
  colheader = NA,
  caption = NULL,
  style = "hmisc",
  footnote = NULL,
  after = NA,
  quant = seq(0, 1, 0.25),
  msd = TRUE,
  as.character = NULL,
  fixed_thead = NULL,
  exclude = NULL,
  ...
)

## S3 method for class 'formula'
tangram(
  x,
  data = NULL,
  id = NULL,
  transforms = NULL,
  caption = NULL,
  style = "hmisc",
  footnote = NULL,
  after = NA,
  digits = NA,
  fixed_thead = NULL,
  exclude = NULL,
  ...
)

## S3 method for class 'character'
tangram(x, ...)

## S3 method for class 'table'
tangram(
  x,
  id = NULL,
  percents = FALSE,
  digits = 1,
  test = FALSE,
  footnote = NULL,
  ...
)

## S3 method for class 'ftable'
tangram(x, id = NULL, ...)

## S3 method for class 'matrix'
tangram(x, digits = NULL, ...)

## S3 method for class 'tbl_df'
tangram(x, ...)

## S3 method for class 'lm'
tangram(x, ...)

## S3 method for class 'summary.lm'
tangram(x, id = NULL, format = NULL, pformat = NULL, tformat = NULL, ...)

## S3 method for class 'rms'
tangram(
  x,
  data = NULL,
  short.labels = NULL,
  footnote = NULL,
  rnd.digits = 2,
  rnd.stats = rnd.digits,
  ...
)

Arguments

Details

Note that additional arguments are passed to any subsequent transform. This means that a lot of possible arguments are not documented here but in the transform applied. Examine their documentations for additional possible arguments if needed.

Value

A tangram object (a table).

See Also

Possible transforms are (see hmisc) (*default*), nejm and lancet.

Examples

tangram(1, 1)
tangram(data.frame(x=1:3, y=c('a','b','c')), id="mytbl1")
tangram(drug ~ bili + albumin + protime + sex + age + spiders, pbc, id="mytbl2")
tangram("drug~bili+albumin+stage::Categorical+protime+sex+age+spiders", pbc,"mytbl3")