Summarize a decimal vector — summary.decimal • decimal

The six-number summary that summary() gives for a numeric vector, computed in exact decimal arithmetic and returned as a decimal vector rather than a vector of doubles.

Usage

# S3 method for class 'decimal'
summary(object, ..., maxsum = 100L, digits = NULL)

Arguments

object: A decimal vector.
...: These dots must be empty.
maxsum, digits: Accepted for compatibility with summary.data.frame(), which passes them to every column, and ignored. digits in particular is not honored: rounding an exact decimal for display is the surprise this package exists to avoid.

Value

A named decimal vector holding Min., 1st Qu., Median, Mean, 3rd Qu. and Max., followed by NA's when the input contains missing values.

Details

Missing values are removed before the statistics are computed and reported as an NA's entry, matching summary.default(). As in base R, NaN counts as missing here, because is.na() is true for it.

The quartiles use the type 7 definition, the default of stats::quantile(). A quantile that falls between two elements is interpolated, and the mean divides by the number of elements, so both run under the active decimal context and may raise inexact and rounded signals like any other division. The minimum, the maximum, and any quantile that lands exactly on an element are always exact.

Because a decimal vector carries one shared scale, every entry is padded to the widest one present – including the NA's count, which is a count rather than a measured value. Interpolating a quartile can need more digits than the input carries, which widens that shared scale.

Interpolating between -Infinity and Infinity is an invalid operation, and the default context traps it, so summarizing a vector that spans both signed infinities raises an error rather than returning NaN quartiles. That is the same error decimal("Infinity") - decimal("Infinity") raises. Clear the trap with with_decimal_context() to get base R's NaN instead.

Examples

summary(decimal(c("1.25", "2.50", "3.75", "10.00")))
#> <decimal[6]>
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>  1.2500  2.1875  3.1250  4.3750  5.3125 10.0000 

# Missing values are counted, not propagated.
summary(decimal(c("1.5", NA, "2.5")))
#> <decimal[7]>
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
#>   1.500   1.750   2.000   2.000   2.250   2.500   1.000