Theprettyunits 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’.
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")pretty_bytes formats number of bytes in a human readable way:
pretty_bytes(133333333337)
Here is a simple function that emulates the Unixls command, withnicely 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
pretty_num formats number related to linear quantities in a humanreadable way:
Be aware that the result is wrong in case of surface or volumes, and forany non-linear quantity.
Here is a simple example of how to prettify a entire tibble
##> ── 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"
pretty_ms formats a time interval given in milliseconds.pretty_secdoes the same for seconds, andpretty_dt fordifftime objects. Theoptionalcompact 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_dt andtime_ago formats time intervals using a vague format,omitting smaller units. They both have three formats:default,shortandterse.vague_dt takes adifftime object, andtime_ago worksrelatively to the specified date.
vague_dt(format="short", as.difftime(30,units="secs"))
vague_dt(format="short", as.difftime(14,units="mins"))
vague_dt(format="short", as.difftime(5,units="hours"))
vague_dt(format="short", as.difftime(25,units="hours"))
vague_dt(format="short", as.difftime(5,units="days"))
now<- Sys.time()time_ago(now)
time_ago(now- as.difftime(30,units="secs"))
##> [1] "less than a minute ago"
time_ago(now- as.difftime(14,units="mins"))
time_ago(now- as.difftime(5,units="hours"))
time_ago(now- as.difftime(25,units="hours"))
pretty_round() andpretty_signif() preserve trailing zeros.
pretty_signif(c(99,0.9999),digits=3)
pretty_p_value() rounds small p-values to indicate less thansignificance level for small values.
pretty_p_value(c(0.05,0.0000001,NA))
##> [1] "0.0500" "<0.0001" NA
pretty_color converts colors from other representations tohuman-readable names.
##> [1] "black"##> attr(,"alt")##> [1] "black" "gray0" "grey0" "Black"
##> [1] "Prussian Blue"##> attr(,"alt")##> [1] "Prussian Blue"
