data_codebook: Generate a codebook of a data frame.

In datawizard: Easy Data Wrangling and Statistical Transformations

Generate a codebook of a data frame.

Description

data_codebook() generates codebooks from data frames, i.e. overviews of all variables and some more information about each variable (like labels, values or value range, frequencies, amount of missing values).

Usage

data_codebook(
  data,
  select = NULL,
  exclude = NULL,
  variable_label_width = NULL,
  value_label_width = NULL,
  max_values = 10,
  range_at = 6,
  ignore_case = FALSE,
  regex = FALSE,
  verbose = TRUE,
  ...
)

## S3 method for class 'data_codebook'
print_html(
  x,
  font_size = "100%",
  line_padding = 3,
  row_color = "#eeeeee",
  ...
)

Arguments

data	A data frame, or an object that can be coerced to a data frame.
select	Variables that will be included when performing the required tasks. Can be either a variable specified as a literal variable name (e.g., column_name), a string with the variable name (e.g., "column_name"), or a character vector of variable names (e.g., c("col1", "col2", "col3")), a formula with variable names (e.g., ~column_1 + column_2), a vector of positive integers, giving the positions counting from the left (e.g. 1 or c(1, 3, 5)), a vector of negative integers, giving the positions counting from the right (e.g., -1 or -1:-3), one of the following select-helpers: starts_with(), ends_with(), contains(), a range using : or regex(""). starts_with(), ends_with(), and contains() accept several patterns, e.g starts_with("Sep", "Petal"). or a function testing for logical conditions, e.g. is.numeric() (or is.numeric), or any user-defined function that selects the variables for which the function returns TRUE (like: foo <- function(x) mean(x) > 3), ranges specified via literal variable names, select-helpers (except regex()) and (user-defined) functions can be negated, i.e. return non-matching elements, when prefixed with a -, e.g. -ends_with(""), -is.numeric or -(Sepal.Width:Petal.Length). Note: Negation means that matches are excluded, and thus, the exclude argument can be used alternatively. For instance, select=-ends_with("Length") (with -) is equivalent to exclude=ends_with("Length") (no -). In case negation should not work as expected, use the exclude argument instead. If NULL, selects all columns. Patterns that found no matches are silently ignored, e.g. find_columns(iris, select = c("Species", "Test")) will just return "Species".
exclude	See select, however, column names matched by the pattern from exclude will be excluded instead of selected. If NULL (the default), excludes no columns.
variable_label_width	Length of variable labels. Longer labels will be wrapped at variable_label_width chars. If NULL, longer labels will not be split into multiple lines. Only applies to labelled data.
value_label_width	Length of value labels. Longer labels will be shortened, where the remaining part is truncated. Only applies to labelled data or factor levels.
max_values	Number of maximum values that should be displayed. Can be used to avoid too many rows when variables have lots of unique values.
range_at	Indicates how many unique values in a numeric vector are needed in order to print a range for that variable instead of a frequency table for all numeric values. Can be useful if the data contains numeric variables with only a few unique values and where full frequency tables instead of value ranges should be displayed.
ignore_case	Logical, if TRUE and when one of the select-helpers or a regular expression is used in select, ignores lower/upper case in the search pattern when matching against variable names.
regex	Logical, if TRUE, the search pattern from select will be treated as regular expression. When regex = TRUE, select must be a character string (or a variable containing a character string) and is not allowed to be one of the supported select-helpers or a character vector of length > 1. regex = TRUE is comparable to using one of the two select-helpers, select = contains("") or select = regex(""), however, since the select-helpers may not work when called from inside other functions (see 'Details'), this argument may be used as workaround.
verbose	Toggle warnings and messages on or off.
...	Arguments passed to or from other methods.
x	A (grouped) data frame, a vector or a statistical model (for unstandardize() cannot be a model).
font_size	For HTML tables, the font size.
line_padding	For HTML tables, the distance (in pixel) between lines.
row_color	For HTML tables, the fill color for odd rows.

Value

A formatted data frame, summarizing the content of the data frame. Returned columns include the column index of the variables in the original data frame (ID), column name, variable label (if data is labelled), type of variable, number of missing values, unique values (or value range), value labels (for labelled data), and a frequency table (N for each value). Most columns are formatted as character vectors.

Note

There are methods to print() the data frame in a nicer output, as well methods for printing in markdown or HTML format (print_md() and print_html()).

Examples

data(iris)
data_codebook(iris, select = starts_with("Sepal"))

data(efc)
data_codebook(efc)

# shorten labels
data_codebook(efc, variable_label_width = 20, value_label_width = 15)

# automatic range for numerics at more than 5 unique values
data(mtcars)
data_codebook(mtcars, select = starts_with("c"))

# force all values to be displayed
data_codebook(mtcars, select = starts_with("c"), range_at = 100)

datawizard documentation built on Sept. 15, 2023, 9:06 a.m.