f_denom: Abbreviate Numbers
In numform: Tools to Format Numbers for Publication
Description
Usage
Arguments
Value
Examples
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
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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 "$0K"
then replacement will be "<1K".
mix.denom
logical. If TRUE then denominations can be mixed.
Typically this is not a good idea for the sake of comparison. It is most
useful when there is a total row which is a sum of the column and this value's
denomination exceeds the denomination of the rest of the column.
digits
The number of digits to round to. Actual digits
calculated as digits + relative.
...
ignored.
Value
Returns an abbreviated vector of numbers.
Examples
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f_denom(c(12345, 12563, 191919), prefix = '$')
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 = '$', pad.char = ''))
## End(Not run)
Example output
[1] "$ 12K" "$ 13K" "$192K"
[1] "$12K" "$13K" "$192K"
[1] "$ 1M" "$122M" "$ 13M"
[1] "$ 12B" "$122B" "$ 1B"
[1] NA "$ 0B" "$ 12B" "$122B" "$ 1B"
[1] NA "$ 2" "$123K" "$122M" "$ 1B"
[1] NA "$0B" "$12B" "$122B" "$1B"
[1] NA "$ .0B" "$ 12.3B" "$122.1B" "$ 1.3B"
[1] NA "$ .000000002B" "$ 12.343676215B" "$122.126763563B"
[5] "$ 1.291673919B"
[1] NA "<1B" "12B" "122B" "1B"
[1] "1K"
[1] "12K"
[1] "123K"
[1] "1M"
[1] "12M"
[1] "123M"
[1] "1B"
[1] "12B"
[1] "123B"
[1] "120B"
[1] "100B"
[1] "123.5B"
[1] "123.46B"
[1] "4M" "4M" "7M" "1M" "-3M"
[1] "3.9M" "4.0M" "6.6M" ".6M" "-3.5M"
[1] "$ 3.9M" "$ 4.0M" "$ 6.6M" "$ .6M" "$-3.5M"
[1] "$03.9M" "$04.0M" "$06.6M" "$00.6M" "$-3.5M"
Loading required package: pacman
[1] "$100B"
# A tibble: 100 x 5
revenue deals dollar thous thous_dollars
<dbl> <int> <chr> <chr> <chr>
1 423088. 20 $423000 423K $423K
2 419251. 25 $419000 419K $419K
3 570116. 29 $570000 570K $570K
4 513192. 39 $513000 513K $513K
5 495684. 28 $496000 496K $496K
6 621413. 36 $621000 621K $621K
7 543114. 37 $543000 543K $543K
8 612597. 35 $613000 613K $613K
9 435416. 38 $435000 435K $435K
10 473370. 23 $473000 473K $473K
# ... with 90 more rows
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
Warning message:
`data_frame()` is deprecated, use `tibble()`.
This warning is displayed once per session.
# A tibble: 10,000 x 8
revenue date site dollar thous thous_dollars abb_month abb_week
<dbl> <date> <chr> <chr> <chr> <chr> <chr> <fct>
1 480994. 1999-05-31 Site 5 $481000 481K $481K M M
2 547592. 1999-03-26 Site 5 $548000 548K $548K M F
3 466275. 1999-02-28 Site 4 $466000 466K $466K F Su
4 475457. 1999-11-08 Site 5 $475000 475K $475K N M
5 527192. 1999-12-24 Site 4 $527000 527K $527K D F
6 428555. 1999-05-12 Site 2 $429000 429K $429K M W
7 471544. 1999-05-01 Site 5 $472000 472K $472K M S
8 481073. 1999-05-27 Site 4 $481000 481K $481K M Th
9 532061. 1999-04-10 Site 5 $532000 532K $532K A S
10 505910. 1999-04-19 Site 4 $506000 506K $506K A M
# ... with 9,990 more rows
----------------------------------------
w x y z
---------------- --------- ----- -------
January 2016 201406 $0M $201K
February 2016 186181 $0M $186K
March 2016 97150 $0M $ 97K
April 2016 155062 $0M $155K
May 2016 222091 $0M $222K
June 2016 229235 $0M $229K
July 2016 109394 $0M $109K
August 2016 172724 $0M $173K
September 2016 78000 $0M $ 78K
October 2016 180764 $0M $181K
November 2016 282633 $0M $283K
December 2016 256684 $0M $257K
January 2017 182132 $0M $182K
February 2017 274058 $0M $274K
March 2017 255604 $0M $256K
April 2017 206701 $0M $207K
May 2017 128379 $0M $128K
June 2017 185364 $0M $185K
July 2017 269414 $0M $269K
August 2017 236223 $0M $236K
Total 3909201 $4M $ 4M
----------------------------------------
Warning messages:
1: In digit_warn(x, "f_mills", 3) :
Detected one or more elements with a larger denomination.
Consider using `f_mills` function instead.
2: In digit_warn(x, "f_mills", 3) :
Detected one or more elements with a larger denomination.
Consider using `f_mills` function instead.
numform documentation built on Oct. 10, 2021, 1:10 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Examples
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | 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 |
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 |
less.than.replace |
logical. If |
mix.denom |
logical. If |
digits |
The number of digits to round to. Actual |
... |
ignored. |
Value
Returns an abbreviated vector of numbers.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | 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)
|
Example output
[1] "$ 12K" "$ 13K" "$192K"
[1] "$12K" "$13K" "$192K"
[1] "$ 1M" "$122M" "$ 13M"
[1] "$ 12B" "$122B" "$ 1B"
[1] NA "$ 0B" "$ 12B" "$122B" "$ 1B"
[1] NA "$ 2" "$123K" "$122M" "$ 1B"
[1] NA "$0B" "$12B" "$122B" "$1B"
[1] NA "$ .0B" "$ 12.3B" "$122.1B" "$ 1.3B"
[1] NA "$ .000000002B" "$ 12.343676215B" "$122.126763563B"
[5] "$ 1.291673919B"
[1] NA "<1B" "12B" "122B" "1B"
[1] "1K"
[1] "12K"
[1] "123K"
[1] "1M"
[1] "12M"
[1] "123M"
[1] "1B"
[1] "12B"
[1] "123B"
[1] "120B"
[1] "100B"
[1] "123.5B"
[1] "123.46B"
[1] "4M" "4M" "7M" "1M" "-3M"
[1] "3.9M" "4.0M" "6.6M" ".6M" "-3.5M"
[1] "$ 3.9M" "$ 4.0M" "$ 6.6M" "$ .6M" "$-3.5M"
[1] "$03.9M" "$04.0M" "$06.6M" "$00.6M" "$-3.5M"
Loading required package: pacman
[1] "$100B"
# A tibble: 100 x 5
revenue deals dollar thous thous_dollars
<dbl> <int> <chr> <chr> <chr>
1 423088. 20 $423000 423K $423K
2 419251. 25 $419000 419K $419K
3 570116. 29 $570000 570K $570K
4 513192. 39 $513000 513K $513K
5 495684. 28 $496000 496K $496K
6 621413. 36 $621000 621K $621K
7 543114. 37 $543000 543K $543K
8 612597. 35 $613000 613K $613K
9 435416. 38 $435000 435K $435K
10 473370. 23 $473000 473K $473K
# ... with 90 more rows
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
Warning message:
`data_frame()` is deprecated, use `tibble()`.
This warning is displayed once per session.
# A tibble: 10,000 x 8
revenue date site dollar thous thous_dollars abb_month abb_week
<dbl> <date> <chr> <chr> <chr> <chr> <chr> <fct>
1 480994. 1999-05-31 Site 5 $481000 481K $481K M M
2 547592. 1999-03-26 Site 5 $548000 548K $548K M F
3 466275. 1999-02-28 Site 4 $466000 466K $466K F Su
4 475457. 1999-11-08 Site 5 $475000 475K $475K N M
5 527192. 1999-12-24 Site 4 $527000 527K $527K D F
6 428555. 1999-05-12 Site 2 $429000 429K $429K M W
7 471544. 1999-05-01 Site 5 $472000 472K $472K M S
8 481073. 1999-05-27 Site 4 $481000 481K $481K M Th
9 532061. 1999-04-10 Site 5 $532000 532K $532K A S
10 505910. 1999-04-19 Site 4 $506000 506K $506K A M
# ... with 9,990 more rows
----------------------------------------
w x y z
---------------- --------- ----- -------
January 2016 201406 $0M $201K
February 2016 186181 $0M $186K
March 2016 97150 $0M $ 97K
April 2016 155062 $0M $155K
May 2016 222091 $0M $222K
June 2016 229235 $0M $229K
July 2016 109394 $0M $109K
August 2016 172724 $0M $173K
September 2016 78000 $0M $ 78K
October 2016 180764 $0M $181K
November 2016 282633 $0M $283K
December 2016 256684 $0M $257K
January 2017 182132 $0M $182K
February 2017 274058 $0M $274K
March 2017 255604 $0M $256K
April 2017 206701 $0M $207K
May 2017 128379 $0M $128K
June 2017 185364 $0M $185K
July 2017 269414 $0M $269K
August 2017 236223 $0M $236K
Total 3909201 $4M $ 4M
----------------------------------------
Warning messages:
1: In digit_warn(x, "f_mills", 3) :
Detected one or more elements with a larger denomination.
Consider using `f_mills` function instead.
2: In digit_warn(x, "f_mills", 3) :
Detected one or more elements with a larger denomination.
Consider using `f_mills` function instead.
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