prettyunits

The prettyunits package formats quantities in human readable form.

• Time intervals: ‘1337000’ -> ‘15d 11h 23m 20s’.
• Vague time intervals: ‘2674000’ -> ‘about a month ago’.
• Bytes: ‘1337’ -> ‘1.34 kB’.
• Rounding: ‘99’ with 3 significant digits -> ‘99.0’
• p-values: ‘0.00001’ -> ‘<0.0001’.
• Colors: ‘#FF0000’ -> ‘red’.
• Quantities: ‘1239437’ -> ‘1.24 M’.

Installation

You can install the package from CRAN:

install.packages("prettyunits")

If you need the development version, install it from GitHub:

pak::pak("r-lib/prettyunits")

Bytes

pretty_bytes formats number of bytes in a human readable way:

pretty_bytes(1337)

##> [1] "1.34 kB"

pretty_bytes(133337)

##> [1] "133.34 kB"

pretty_bytes(13333337)

##> [1] "13.33 MB"

pretty_bytes(1333333337)

##> [1] "1.33 GB"

pretty_bytes(133333333337)

##> [1] "133.33 GB"

Here is a simple function that emulates the Unix ls command, with nicely formatted file sizes:

uls <- function(path = ".") {
  files <- dir(path)
  info <- files |>
    lapply(file.info) |>
    do.call(what = rbind)
  info$size <- pretty_bytes(info$size)
  df <- data.frame(d = ifelse(info$isdir, "d", " "),
    mode = as.character(info$mode), user = info$uname, group = info$grname,
    size = ifelse(info$isdir, "", info$size), modified = info$mtime, name = files)
  print(df, row.names = FALSE)
}
uls()

##>  d mode        user group     size            modified         name
##>     644 gaborcsardi staff    264 B 2025-04-26 17:24:48 _pkgdown.yml
##>     644 gaborcsardi staff      0 B 2025-04-28 09:00:42     air.toml
##>     644 gaborcsardi staff    232 B 2023-09-24 11:37:28  codecov.yml
##>  d  755 gaborcsardi staff          2025-04-28 09:03:47     data-raw
##>     644 gaborcsardi staff  1.30 kB 2025-04-28 09:04:57  DESCRIPTION
##>     644 gaborcsardi staff     49 B 2025-04-26 17:24:48      LICENSE
##>     644 gaborcsardi staff  1.08 kB 2025-04-26 17:24:48   LICENSE.md
##>     644 gaborcsardi staff    111 B 2023-09-23 16:44:21     Makefile
##>  d  755 gaborcsardi staff          2025-04-28 09:00:33          man
##>     644 gaborcsardi staff    391 B 2025-04-26 17:24:39    NAMESPACE
##>     644 gaborcsardi staff  1.55 kB 2025-04-28 09:00:33      NEWS.md
##>  d  755 gaborcsardi staff          2025-04-28 09:00:33            R
##>     644 gaborcsardi staff 40.66 kB 2025-04-28 09:06:22  README.html
##>     644 gaborcsardi staff  8.16 kB 2025-04-28 09:06:19    README.md
##>     644 gaborcsardi staff  4.48 kB 2025-04-28 09:06:08   README.Rmd
##>  d  755 gaborcsardi staff          2025-04-26 17:24:48        tests

Quantities

pretty_num formats number related to linear quantities in a human readable way:

pretty_num(1337)

##> [1] "1.34 k"

pretty_num(-133337)

##> [1] "-133.34 k"

pretty_num(1333.37e-9)

##> [1] "1.33 u"

Be aware that the result is wrong in case of surface or volumes, and for any non-linear quantity.

Here is a simple example of how to prettify a entire tibble

library(tidyverse)

##> ── Attaching core tidyverse packages ───────────────────── tidyverse 2.0.0 ──
##> ✔ dplyr     1.1.4     ✔ readr     2.1.5
##> ✔ forcats   1.0.0     ✔ stringr   1.5.1
##> ✔ ggplot2   3.5.2     ✔ tibble    3.2.1
##> ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
##> ✔ purrr     1.0.4     
##> ── Conflicts ─────────────────────────────────────── tidyverse_conflicts() ──
##> ✖ tidyr::extract()   masks magrittr::extract()
##> ✖ dplyr::filter()    masks stats::filter()
##> ✖ dplyr::lag()       masks stats::lag()
##> ✖ purrr::set_names() masks magrittr::set_names()
##> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

tdf <- tribble( ~name, ~`size in m`, ~`speed in m/s`,
                "land snail", 0.075, 0.001,
                "photon", NA,  299792458,
                "African plate", 10546330, 0.000000000681)
tdf |> mutate(across(where(is.numeric), pretty_num))

##> # A tibble: 3 × 3
##>   name          `size in m` `speed in m/s`
##>   <chr>         <chr>       <chr>         
##> 1 land snail    "   75 m"   "     1 m"    
##> 2 photon        "    NA "   "299.79 M"    
##> 3 African plate "10.55 M"   "   681 p"

Time intervals

pretty_ms formats a time interval given in milliseconds. pretty_sec does the same for seconds, and pretty_dt for difftime objects. The optional compact argument turns on a compact, approximate format.

pretty_ms(c(1337, 13370, 133700, 1337000, 1337000000))

##> [1] "1.3s"            "13.4s"           "2m 13.7s"        "22m 17s"        
##> [5] "15d 11h 23m 20s"

pretty_ms(c(1337, 13370, 133700, 1337000, 1337000000),
  compact = TRUE)

##> [1] "~1.3s"  "~13.4s" "~2m"    "~22m"   "~15d"

pretty_sec(c(1337, 13370, 133700, 1337000, 13370000))

##> [1] "22m 17s"          "3h 42m 50s"       "1d 13h 8m 20s"    "15d 11h 23m 20s" 
##> [5] "154d 17h 53m 20s"

pretty_sec(c(1337, 13370, 133700, 1337000, 13370000),
  compact = TRUE)

##> [1] "~22m"  "~3h"   "~1d"   "~15d"  "~154d"

Vague time intervals

vague_dt and time_ago formats time intervals using a vague format, omitting smaller units. They both have three formats: default, short and terse. vague_dt takes a difftime object, and time_ago works relatively to the specified date.

vague_dt(format = "short", as.difftime(30, units = "secs"))

##> [1] "<1 min"

vague_dt(format = "short", as.difftime(14, units = "mins"))

##> [1] "14 min"

vague_dt(format = "short", as.difftime(5, units = "hours"))

##> [1] "5 hours"

vague_dt(format = "short", as.difftime(25, units = "hours"))

##> [1] "1 day"

vague_dt(format = "short", as.difftime(5, units = "days"))

##> [1] "5 day"

now <- Sys.time()
time_ago(now)

##> [1] "moments ago"

time_ago(now - as.difftime(30, units = "secs"))

##> [1] "less than a minute ago"

time_ago(now - as.difftime(14, units = "mins"))

##> [1] "14 minutes ago"

time_ago(now - as.difftime(5, units = "hours"))

##> [1] "5 hours ago"

time_ago(now - as.difftime(25, units = "hours"))

##> [1] "a day ago"

Rounding

pretty_round() and pretty_signif() preserve trailing zeros.

pretty_round(1, digits=6)

##> [1] "1.000000"

pretty_signif(c(99, 0.9999), digits=3)

##> [1] "99.0" "1.00"

p-values

pretty_p_value() rounds small p-values to indicate less than significance level for small values.

pretty_p_value(c(0.05, 0.0000001, NA))

##> [1] "0.0500"  "<0.0001" NA

Colors

pretty_color converts colors from other representations to human-readable names.

pretty_color("black")

##> [1] "black"
##> attr(,"alt")
##> [1] "black" "gray0" "grey0" "Black"

pretty_color("#123456")

##> [1] "Prussian Blue"
##> attr(,"alt")
##> [1] "Prussian Blue"