f_denom: Abbreviate Numbers

In trinker/numform: Tools to Format Numbers for Publication

Description

Use the denomination abbreviations K (thousands), M (millions), and B (billions) with abbreviated numbers.
f_denom - Auto-detect the maximum denomination and attempt to use it (if max(x) is < 1K then x is returned).

f_trills - Force the abbreviation to the trillions denomination (B).

f_bills - Force the abbreviation to the billions denomination (B).

f_mills - Force the abbreviation to the millions denomination (B).

f_thous - Force the abbreviation to the thousands denomination (B).

Usage

f_denom(
  x,
  relative = 0,
  prefix = "",
  pad.char = ifelse(prefix == "", NA, " "),
  less.than.replace = FALSE,
  mix.denom = FALSE,
  ...
)

ff_denom(...)

f_trills(
  x,
  relative = 0,
  digits = -12,
  prefix = "",
  pad.char = ifelse(prefix == "", NA, " "),
  less.than.replace = FALSE,
  ...
)

ff_trills(...)

f_bills(
  x,
  relative = 0,
  digits = -9,
  prefix = "",
  pad.char = ifelse(prefix == "", NA, " "),
  less.than.replace = FALSE,
  ...
)

ff_bills(...)

f_mills(
  x,
  relative = 0,
  digits = -6,
  prefix = "",
  pad.char = ifelse(prefix == "", NA, " "),
  less.than.replace = FALSE,
  ...
)

ff_mills(...)

f_thous(
  x,
  relative = 0,
  digits = -3,
  prefix = "",
  pad.char = ifelse(prefix == "", NA, " "),
  less.than.replace = FALSE,
  ...
)

ff_thous(...)

Arguments

x	A vector of large numbers.
relative	A factor relative to the current digits being rounded. For example relative = -1 moves one to the left while relative = 1 moves one to the right.
prefix	A string to append to the front of elements.
pad.char	A character to use for leading padding if lengths of output are unequal. Use NA to forgo padding.
less.than.replace	logical. If TRUE values lower than lowest place value will be replaced with a less than sign followed by the integer representation of the place value. For example, if "$0K" then replacement will be "<1K".
mix.denom	logical. If TRUE then denominations can be mixed. Typically this is not a good idea for the sake of comparison. It is most useful when there is a total row which is a sum of the column and this value's denomination exceeds the denomination of the rest of the column.
digits	The number of digits to round to. Actual digits calculated as digits + relative.
...	ignored.

Value

Returns an abbreviated vector of numbers.

Examples

f_denom(c(12345, 12563, 191919), prefix = '$')
f_denom(c(12345, 12563, 191919), prefix = '$', pad.char = '')
f_denom(c(1234365, 122123563, 12913919), prefix = '$')
f_denom(c(12343676215, 122126763563, 1291673919), prefix = '$')
f_denom(c(NA, 2, 12343676215, 122126763563, 1291673919), prefix = '$')
f_denom(c(NA, 2, 123436, 122126763, 1291673919), prefix = '$', mix.denom = TRUE)
f_denom(c(NA, 2, 12343676215, 122126763563, 1291673919), prefix = '$', pad.char = '')
f_denom(c(NA, 2, 12343676215, 122126763563, 1291673919), relative = 1, prefix = '$')
f_denom(c(NA, 2, 12343676215, 122126763563, 1291673919), relative = 9, prefix = '$')
f_denom(c(NA, 2, 12343676215, 122126763563, 1291673919), less.than.replace = TRUE)

f_thous(1234)
f_thous(12345)
f_thous(123456)
f_mills(1234567)
f_mills(12345678)
f_mills(123456789)
f_bills(1234567891)
f_bills(12345678912)
f_bills(123456789123)

f_bills(123456789123, -1) # round to tens
f_bills(123456789123, -2) # round to hundreds
f_bills(123456789123, +1) # round to tenths
f_bills(123456789123, +2) # round to hundreths

x <- c(3886902.8696, 4044584.0424, 6591893.2104, 591893.2104, -3454678)
f_mills(x)
f_mills(x, 1)
f_mills(x, 1, prefix = '$')
f_mills(x, 1, prefix = '$', pad.char = '0')

## Not run: 
if (!require("pacman")) install.packages("pacman")
pacman::p_load(tidyverse, magrittr)

f_bills(123456789123, -2) %>%
    f_prefix("$")


data_frame(
    revenue = rnorm(100, 500000, 50000),
    deals = sample(20:50, 100, TRUE)
) %>%
    mutate(
        dollar = f_dollar(revenue, digits = -3),
        thous = f_thous(revenue),
        thous_dollars = f_thous(revenue, prefix = '$')
    ) %T>%
    print() %>%
    ggplot(aes(deals, revenue)) +
        geom_point() +
        geom_smooth() +
        scale_y_continuous(label = ff_thous(prefix = '$') )

data_frame(
    revenue = rnorm(10000, 500000, 50000),
    date = sample(seq(as.Date('1999/01/01'), as.Date('2000/01/01'), by="day"), 10000, TRUE),
    site = sample(paste("Site", 1:5), 10000, TRUE)
) %>%
    mutate(
        dollar = f_dollar(revenue, digits = -3),
        thous = f_thous(revenue),
        thous_dollars = f_thous(revenue, prefix = '$'),
        abb_month = f_month(date),
        abb_week = factor(f_weekday(date, distinct = TRUE),
        levels = c('Su', 'M', 'T', 'W', 'Th', 'F', 'S'))
    ) %T>%
    print() %>%
    ggplot(aes(abb_week, revenue)) +
        geom_jitter(width = .2, height = 0, alpha = .2) +
        scale_y_continuous(label = ff_thous(prefix = '$'))+
        facet_wrap(~site)

set.seed(10)
data_frame(
    w = paste(constant_months, rep(2016:2017, each = 12))[1:20] ,
    x = rnorm(20, 200000, 75000)
) %>%
    {
        a <- .
        rbind(
            a,
            a %>%
                mutate(w = 'Total') %>%
                group_by(w) %>%
                summarize(x = sum(x))
        )
    } %>%
    mutate(
        y = f_denom(x, prefix = '$'),
        z = f_denom(x, mix.denom = TRUE, prefix = '$')
    )  %>%
    data.frame(stringsAsFactors = FALSE, check.names = FALSE) %>%
    pander::pander(split.tables = Inf, justify = alignment(.))

## Scale with mixed units
library(tidyverse)
library(numform)

dat <- data_frame(
    Value = c(111, 2345, 34567, 456789, 1000001, 1000000001),
    Time = 1:6
)

## Uniform units
ggplot(dat, aes(Time, Value)) +
    geom_line() +
    scale_y_continuous(labels = ff_denom( prefix = '$'))

## Mixed units
ggplot(dat, aes(Time, Value)) +
    geom_line() +
    scale_y_continuous(labels = ff_denom(mix.denom = TRUE, prefix = '$', pad.char = ''))

## End(Not run)

trinker/numform documentation built on Oct. 12, 2021, 11:17 a.m.