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Summary Descriptive Statistics for List or Data Frame

Source: R/sumry.default.R
sumry.default.Rd

Computes and prints summary descriptive statistics for each variable in a data frame, list, or vector including counts, numeric summaries (min, quartiles, mean, max, standard deviation), and factor summaries (levels and frequencies).

Usage

# Default S3 method
sumry(
  x,
  ...,
  transpose = FALSE,
  pad = 2,
  maxsum = 10,
  opts = list(digits = 4, scipen = 2)
)

Arguments

x

A data frame, list, or vector containing variables to summarize. A vector is treated as a single variable data frame. Unnamed variables receive generic names like V1, V2, etc.

...

Additional arguments (not currently used).

transpose

A logical controlling report format. By default the table printed is organized to show variables in columns and their statistic values in rows. Setting transpose = TRUE prints the transposed table with variables in rows and statistics in columns.

pad

A positive integer for the number of spaces between output columns.

maxsum

A positive integer limiting the number of levels for factor reports.

opts

A key=value type list, optional input for options values on output. Existing values are restored on exit.

Value

Invisibly returns a list containing a summary data frame for each variable with no rounding. For example, smry <- sumry.df(df[c("A", "B", "C")]); smry$A$std.dev gives the standard deviation of variable A in data frame df

Details

For each variable in x, the function computes the count of non-missing and missing values. Numeric variables are summarized by minimum, first quartile, median, mean, third quartile, maximum, and standard deviation. Factor, logical, and character variables are summarized by level frequencies, where level names may be abbreviated for readability. Results are formatted in a table and printed. The function returns a list containing numeric or factor summaries for each variable.

Examples

sumry(penguins)
#>              species       island  bill_len  bill_dep  flipper_len  body_mass
#> n.val            344          344       342       342          342        342
#> n.na               0            0         2         2            2          2
#> min      n.lvl  :  3  n.lvl  :  3      32.1      13.1          172       2700
#> Q1       Adelie :152  Biscoe :168      39.2     15.45          190       3550
#> median   Gentoo :124  Dream  :124     44.45      17.3          197       4050
#> mean     Chnstrp: 68  Torgrsn: 52     43.92     17.15        200.9       4202
#> Q3                                     48.5      18.7          214       4800
#> max                                    59.6      21.5          231       6300
#> std.dev                                5.46     1.975        14.06        802
#>                 sex    year
#> n.val           333     344
#> n.na             11       0
#> min      n.lvl :  2    2007
#> Q1       male  :168    2007
#> median   female:165    2008
#> mean                   2008
#> Q3                     2009
#> max                    2009
#> std.dev              0.8184
sumry(data.frame(a = rnorm(100),
                 b = c(NA, 1:98, NA),
                 c = sample(letters[4:6], 100, TRUE)),
                 transpose = TRUE, pad = 1)
#>     n.val n.na    min      Q1 median    mean     Q3   max std.dev
#> a     100    0 -2.592 -0.5068 0.1168 0.08056 0.7844 2.649   1.014
#> b      98    2      1      25   49.5    49.5     74    98   28.43
#> c n.lvl:3    0      3    d:38   e:34    f:28