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).
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 data_codebook
print_html(
x,
font_size = "100%",
line_padding = 3,
row_color = "#eeeeee",
...
)
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.
A data frame, or an object that can be coerced to a data frame.
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. extract_column_names(iris, select = c("Species", "Test"))
will just return "Species".
See select, however, column names matched by the pattern
from exclude will be excluded instead of selected. If NULL (the default),
excludes no columns.
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.
Length of value labels. Longer labels will be shortened, where the remaining part is truncated. Only applies to labelled data or factor levels.
Number of maximum values that should be displayed. Can be used to avoid too many rows when variables have lots of unique values.
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.
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.
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.
Toggle warnings and messages on or off.
Arguments passed to or from other methods.
A (grouped) data frame, a vector or a statistical model (for
unstandardize() cannot be a model).
For HTML tables, the font size.
For HTML tables, the distance (in pixel) between lines.
For HTML tables, the fill color for odd rows.
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)
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