Compactly display the content and structure of a data.frame, including
variable labels. str() is optimized for lists and its output is
relatively technical, when it comes to e.g. attributes. summary() on
the other side already calculates some basic statistics.
Abstract(
x,
sep = ", ",
zero.form = ".",
maxlevels = 5,
trunc = TRUE,
list.len = 999
)
# S3 method for abstract
print(x, sep = NULL, width = NULL, trunc = NULL, print.gap = 2, ...)a data.frame to be described
the separator for concatenating the levels of a factor
a symbol to be used, when a variable has zero NAs.
(integer, Inf) Max. number of factor levels to display.
Default is 5. Set this to Inf, if all levels are needed.
logical, defining if level names exceeding the column with
should be truncated. Default is TRUE.
numeric; maximum number of list elements to display.
Console width. If NULL, defaults to
options("width").
(integer) Number of spaces between columns.
Further arguments to print method.
an object of class abstract, essentially a character matrix
with 5 or 6 columns containing:
a column number (Nr),
the name of the column (ColName),
the column class (Class),
the number of NAs (NAs),
the levels if the variable is a factor (Levels),
(if there are any) descriptive labels for the column (Labels).
The levels of a factor and describing variable labels (as created by
Label()) will be wrapped within the columns.
The first 4 columns are printed with the needed fix width, the last 2
(Levels and Labels) are wrapped within the column. The width is calculated
depending on the width of the screen as given by getOption("width").
ToWord has an interface for the class abstract.
utils::str(), base::summary(), ColumnWrap(), Desc()
Other Statistical summary functions:
Desc()
d.mydata <- d.pizza
# let's use some labels
Label(d.mydata) <- "Lorem ipsum dolor sit amet, consetetur sadipscing elitr,
sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat,
sed diam voluptua. At vero eos et accusam."
Label(d.mydata$temperature) <- "Amet, consetetur sadipscing elitr, sed diam nonumy "
Abstract(d.mydata)
#> ------------------------------------------------------------------------------
#> d.mydata :
#> Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam
#> nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam
#> erat, sed diam voluptua. At vero eos et accusam.
#>
#> data frame: 1209 obs. of 16 variables
#> 917 complete cases (75.8%)
#>
#> Nr ColName Class NAs Levels Label
#> 1 index integer . -
#> 2 date Date 32 (2.6%) -
#> 3 week numeric 32 (2.6%) -
#> 4 weekday numeric 32 (2.6%) -
#> 5 area factor 10 (0.8%) (3): -
#> 1-Brent,
#> 2-Camden,
#> 3-Westminst...
#> 6 count integer 12 (1.0%) -
#> 7 rabate logical 12 (1.0%) -
#> 8 price numeric 12 (1.0%) -
#> 9 operator factor 8 (0.7%) (3): -
#> 1-Allanah,
#> 2-Maria,
#> 3-Rhonda
#> 10 driver factor 5 (0.4%) (7): -
#> 1-Butcher,
#> 2-Carpenter...
#> 3-Carter,
#> 4-Farmer,
#> 5-Hunter,
#> ...
#> 11 delivery_min numeric . -
#> 12 temperature numeric 39 (3.2%) Amet,
#> consetetur
#> sadipscing
#> elitr, sed
#> diam
#> nonumy
#> 13 wine_ordered integer 12 (1.0%) -
#> 14 wine_delivered integer 12 (1.0%) -
#> 15 wrongpizza logical 4 (0.3%) -
#> 16 quality ordered, factor 201 (16.6%) (3): -
#> 1-low,
#> 2-medium,
#> 3-high
#>