MyNixOS website logo
Description

Pretty, Human Readable Formatting of Quantities.

Pretty, human readable formatting of quantities. 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'.

R-CMD-check Codecov test coverage CRAN RStudio mirror downloads

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")

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   232 B 2023-09-24 10:37:41 codecov.yml
##>  d  755 gaborcsardi staff         2023-09-24 10:37:41    data-raw
##>     644 gaborcsardi staff 1.06 kB 2023-09-24 10:40:32 DESCRIPTION
##>     644 gaborcsardi staff    42 B 2022-06-17 13:59:46     LICENSE
##>     644 gaborcsardi staff   111 B 2023-09-23 16:44:21    Makefile
##>  d  755 gaborcsardi staff         2023-09-24 10:37:59         man
##>     644 gaborcsardi staff   523 B 2023-09-24 10:39:58   NAMESPACE
##>     644 gaborcsardi staff 1.46 kB 2023-09-24 10:42:01     NEWS.md
##>  d  755 gaborcsardi staff         2023-09-24 11:25:00           R
##>     644 gaborcsardi staff 7.90 kB 2023-09-24 11:27:42   README.md
##>     644 gaborcsardi staff 4.31 kB 2023-09-24 11:28:23  README.Rmd
##>  d  755 gaborcsardi staff         2022-06-17 13:59:46       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     1.1.2     ✔ readr     2.1.4
##> ✔ forcats   1.0.0     ✔ stringr   1.5.0
##> ✔ ggplot2   3.4.2     ✔ tibble    3.2.1
##> ✔ lubridate 1.9.2     ✔ tidyr     1.3.0
##> ✔ purrr     1.0.1     
##> ── 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"
Metadata

Version

1.2.0

License

Unknown

Platforms (75)

    Darwin
    FreeBSD
    Genode
    GHCJS
    Linux
    MMIXware
    NetBSD
    none
    OpenBSD
    Redox
    Solaris
    WASI
    Windows
Show all
  • aarch64-darwin
  • aarch64-genode
  • aarch64-linux
  • aarch64-netbsd
  • aarch64-none
  • aarch64_be-none
  • arm-none
  • armv5tel-linux
  • armv6l-linux
  • armv6l-netbsd
  • armv6l-none
  • armv7a-darwin
  • armv7a-linux
  • armv7a-netbsd
  • armv7l-linux
  • armv7l-netbsd
  • avr-none
  • i686-cygwin
  • i686-darwin
  • i686-freebsd
  • i686-genode
  • i686-linux
  • i686-netbsd
  • i686-none
  • i686-openbsd
  • i686-windows
  • javascript-ghcjs
  • loongarch64-linux
  • m68k-linux
  • m68k-netbsd
  • m68k-none
  • microblaze-linux
  • microblaze-none
  • microblazeel-linux
  • microblazeel-none
  • mips-linux
  • mips-none
  • mips64-linux
  • mips64-none
  • mips64el-linux
  • mipsel-linux
  • mipsel-netbsd
  • mmix-mmixware
  • msp430-none
  • or1k-none
  • powerpc-netbsd
  • powerpc-none
  • powerpc64-linux
  • powerpc64le-linux
  • powerpcle-none
  • riscv32-linux
  • riscv32-netbsd
  • riscv32-none
  • riscv64-linux
  • riscv64-netbsd
  • riscv64-none
  • rx-none
  • s390-linux
  • s390-none
  • s390x-linux
  • s390x-none
  • vc4-none
  • wasm32-wasi
  • wasm64-wasi
  • x86_64-cygwin
  • x86_64-darwin
  • x86_64-freebsd
  • x86_64-genode
  • x86_64-linux
  • x86_64-netbsd
  • x86_64-none
  • x86_64-openbsd
  • x86_64-redox
  • x86_64-solaris
  • x86_64-windows