Added to_words2 function to convert from number to spanish words

[PavoDive]

A function to_words2() was created to overcome some limitations and errors of to_words.

to_words2 can take a number up to 1e22 or a string of digits up to 60 digits long, and convert it to words, thus expanding the capabilities of to_words.

It also fixes some errors of to_words, particularly the conversion of quantities ending in "millions", that were converted to "millones y mil" by to_words().

devtools::document() was run in order to update the documentation of the package, but some adjustments may be needed in the original functions, as the following error was displayed:

✖ spanish.R:28: @docType "package" is deprecated.
ℹ Please document "_PACKAGE" instead.

[PavoDive]

Hi Jose Manuel,

Please consider this tests:

## This file is made to compare the output of functions
## spanish::to_words() and to_words2() on some numbers.

values <- c(1:99,
            seq(100, 900, 100),
            seq(1000, 9000, 1000),
            seq(1e4, 9e4, 1e4),
            seq(1e5, 9e5, 1e5),
            seq(1e6, 9e6, 1e6),
            seq(1e7, 9e7, 1e7),
            seq(1e8, 9e8, 1e8),
            seq(1e9, 9e9, 1e9),
            seq(1e10, 9e10, 1e10),
            seq(1e11, 9e11, 1e11),
            seq(1e12, 9e12, 1e12),
            seq(1e13, 9e13, 1e13),
            seq(1e14, 9e14, 1e14),
            seq(1e15, 9e15, 1e15),
            seq(1e16, 9e16, 1e16),
            seq(1e17, 9e17, 1e17),
            seq(1e18, 9e18, 1e18),
            seq(1e19, 9e19, 1e19),
            seq(1e20, 9e20, 1e20),
            seq(1e21, 9e21, 1e21),
            seq(1e22, 9e22, 1e22), ## from here some arbitrary numbers:
            102,
            1003,
            1030,
            10004,
            10040,
            10400,
            100005,
            100050,
            100500,
            105000,
            150000,
            1000006,
            1000060,
            1000600,
            1006000,
            1060000,
            1600000,
            31415927, # pi*1e7
            271828183 # exp(1)*1e8
            )

df = data.frame(values = values)

df$string_rep = format(df$values, scientific = FALSE)

df$to_words = lapply(
    df$values,
    function(x) {
        ifelse(x > 999999999,
               as.character(NA),
               spanish::to_words(x)
               )
    }
)

df$to_words2 = lapply(df$values, to_words2)

## OBSERVED ERRORS AND NOTES:
## spanish::to_words adds 1000 to all numbers ending in "millones": 
##      20e6 --> "veinte millones mil"; 5e6 --> cinco millones mil.
## spanish::to_words adds untrimed spaces to the right of the words.
## spanish::to_words has two spaces between words: 900e8 --> 
##     "novecientos  millones mil ".
## spanish::to_words stops working just before 1e9 (mil millones).
## to_words2 fails above 4e22 (cuarenta mil trillones), but it's due to precision errors in the 
##    machine, as can be seen in the string representation of the number.
## spanish::to_words represents wrongly the numbers 1000006, 1000060 and 10006000, 
##    adding 1000 to each of them: "un millón mil y seis"

## TEXT INPUT
## In order to circunvent the precision errors for big numbers, to_words2() can
## take strings of numbers as input:

set.seed(77)
## a number with 22 digits:
j = sapply(1:22,
           function(x) as.character(sample(0:9, 1))) |>
    paste(collapse = "")
print(j)
to_words2(j)

## > [1] "1484757575318806025265"
## > [1] "mil cuatrocientos ochenta y cuatro trillones setecientos cincuenta y siete mil 
##              quinientos setenta y cinco billones trescientos diez y ocho mil ochocientos y seis 
##              millones veinte y cinco mil doscientos sesenta y cinco"

## a number with 60 digits:
j = sapply(1:60,
           function(x) as.character(sample(0:9, 1))) |>
    paste(collapse = "")
print(j)
to_words2(j)

## > [1] "212430083327760288597253958069365214126894321836306109691803"
## > [1] "doscientos doce mil cuatrocientos treinta nonillones ochenta y tres mil trescientos 
##              veinte y siete octillones setecientos sesenta mil doscientos ochenta y ocho 
##              septillones quinientos noventa y siete mil doscientos cincuenta y tres sextillones 
##              novecientos cincuenta y ocho mil sesenta y nueve quintillones trescientos 
##              sesenta y cinco mil doscientos catorce cuatrillones ciento veinte y seis mil 
##              ochocientos noventa y cuatro trillones trescientos veinte y un mil ochocientos 
##              treinta y seis billones trescientos y seis mil ciento y nueve millones seiscientos 
##              noventa y un mil ochocientos y tres"