Overview

Rbearcat provides six bcat_fmt_* functions for formatting numbers in inline R expressions and tables. They wrap functions from the scales package with sensible defaults.

Function Formats as
bcat_fmt_dollar() Currency ($1,234.56)
bcat_fmt_percent() Percentage (12.3%)
bcat_fmt_comma() Comma-separated (1,234)
bcat_fmt_scientific() Scientific notation (1.23e+06)
bcat_fmt_date() Human-readable date (March 10, 2026)
bcat_fmt_pvalue() P-value with </> notation 
library(Rbearcat)

Dollar Formatting — bcat_fmt_dollar()

bcat_fmt_dollar(c(1234.5, 67890, 0.99))
#> [1] "$1,234.50"  "$67,890.00" "$0.99"

Negative Values

The default uses a hyphen. Set style_negative = "parens" for accounting style:

bcat_fmt_dollar(c(-500, 1200))
#> [1] "-$500"  "$1,200"
bcat_fmt_dollar(c(-500, 1200), style_negative = "parens")
#> [1] "($500)" "$1,200"

Scaling

Use scale to convert units (e.g., raw cents to dollars):

bcat_fmt_dollar(c(150000, 275000), scale = 1e-3, accuracy = 1, suffix = "K")
#> [1] "$150K" "$275K"

Percent Formatting — bcat_fmt_percent()

Multiplies by 100 by default (assumes proportions as input):

bcat_fmt_percent(c(0.0523, 0.1, 0.9871))
#> [1] "5.2%"  "10.0%" "98.7%"

Pre-scaled Values

If values are already in percentage form, set scale = 1:

bcat_fmt_percent(c(5.23, 10, 98.71), scale = 1)
#> [1] "5.2%"  "10.0%" "98.7%"

Controlling Precision

bcat_fmt_percent(c(0.05234, 0.10011), accuracy = 0.01)
#> [1] "5.23%"  "10.01%"

Comma Formatting — bcat_fmt_comma()

bcat_fmt_comma(c(1000, 50000, 1234567))
#> [1] "1,000"     "50,000"    "1,234,567"

With Suffix

bcat_fmt_comma(c(5000, 10000, 80000), scale = 1e-3, accuracy = 1, suffix = "K")
#> [1] "5K"  "10K" "80K"

Scientific Notation — bcat_fmt_scientific()

bcat_fmt_scientific(c(0.00012, 3456789, 1.5e10))
#> [1] "1.20e-04" "3.46e+06" "1.50e+10"

Controlling Digits

bcat_fmt_scientific(c(123456, 789012), digits = 2)
#> [1] "1.2e+05" "7.9e+05"

Date Formatting — bcat_fmt_date()

Converts character or Date objects to a human-readable format. The default format is "%B %e, %Y" (e.g., “January 5, 2026”).

bcat_fmt_date(Sys.Date())
#> [1] "March 17, 2026"
bcat_fmt_date(c("2024-01-15", "2025-06-30"))
#> [1] "January 15, 2024" "June 30, 2025"

Custom Format Strings

Use standard strptime codes:

bcat_fmt_date("2025-12-25", format = "%d %b %Y")
#> [1] "25 Dec 2025"
bcat_fmt_date("2025-12-25", format = "%m/%d/%Y")
#> [1] "12/25/2025"

P-value Formatting — bcat_fmt_pvalue()

Uses < and > notation for extreme values:

bcat_fmt_pvalue(c(0.54, 0.045, 0.001, 0.00001))
#> [1] "0.540"  "0.045"  "0.001"  "<0.001"

With “p=” Prefix

Useful in inline reporting:

bcat_fmt_pvalue(c(0.032, 0.0001), add_p = TRUE)
#> [1] "p=0.032" "p<0.001"

Controlling Precision

bcat_fmt_pvalue(c(0.0456, 0.00012), accuracy = 0.01)
#> [1] "0.05"  "<0.01"

Inline Reporting Example

These formatters are most powerful inside inline R expressions in RMarkdown or Quarto. For example, suppose you compute some values:

avg_price <- 12345.67
pct_change <- 0.052
my_pval <- 0.003

bcat_fmt_dollar(avg_price)
#> [1] "$12,345.67"
bcat_fmt_percent(pct_change)
#> [1] "5%"
bcat_fmt_pvalue(my_pval, add_p = TRUE)
#> [1] "p=0.003"

In your RMarkdown document you would reference these with inline R code like `r bcat_fmt_dollar(avg_price)` to produce formatted numbers directly in your prose:

The average price was $12,345.67 with a 5% year-over-year change. The coefficient was significant (p=0.003).

Using Formatters as ggplot2 Scale Labels

The bcat_fmt_* functions can also serve as label functions for ggplot2 axis scales:

library(ggplot2)
set_UC_geoms()

ggplot(economics, aes(date, pce)) +
  geom_line() +
  scale_y_continuous(labels = bcat_fmt_dollar) +
  labs(title = "Personal Consumption Expenditure",
       x = NULL, y = "Billions ($)") +
  theme_UC()