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If we have numbers then we might want to convert those numbers into words. For example, converting 1 to one. This might be required in cases where we have text data and numbers are part of the text. Therefore, it would be better to represent the numbers in text form to make the uniformity in the text. This can be done by using replace_number function qdap package.

Installing and loading qdap package−

install.packages("qdap") library("qdap")

replace_number("1") [1] "one" replace_number("10") [1] "ten" replace_number("100") [1] "one hundred" replace_number("1000") [1] "one thousand" replace_number("1001") [1] "one thousand one" replace_number("12000") [1] "twelve thousand" replace_number("12214") [1] "twelve thousand two hundred fourteen" replace_number("15748") [1] "fifteen thousand seven hundred forty eight" replace_number("2361414") [1] "two million three hundred sixty one thousand four hundred fourteen" replace_number("321457") [1] "three hundred twenty one thousand four hundred fifty seven" replace_number(c("1","2","3","4","5","6","7","8","9","10")) [1] "one" "two" "three" "four" "five" "six" "seven" "eight" "nine" [10] "ten" replace_number(c("321457","214521","365841")) [1] "three hundred twenty one thousand four hundred fifty seven" [2] "two hundred fourteen thousand five hundred twenty one" [3] "three hundred sixty five thousand eight hundred forty one" replace_number(c("264155","154512","344512","2144","221","14542","35915112","1454221","147232321","14789523")) [1] "two hundred sixty four thousand one hundred fifty five" [2] "one hundred fifty four thousand five hundred twelve" [3] "three hundred forty four thousand five hundred twelve" [4] "two thousand one hundred forty four" [5] "two hundred twenty one" [6] "fourteen thousand five hundred forty two" [7] "thirty five million nine hundred fifteen thousand one hundred twelve" [8] "one million four hundred fifty four thousand two hundred twenty one" [9] "one hundred forty seven million two hundred thirty two thousand three hundred twenty one" [10] "fourteen million seven hundred eighty nine thousand five hundred twenty three"

x<-c("There are 29 states in india") replace_number(x)

[1] "There are twenty nine states in india"

y<-c("1025454 people suffered from covid-19") replace_number(y)

[1] "one million twenty five thousand four hundred fifty four people suffered from covid-nineteen"

z<-c("We have 22 Arab countries in the world") replace_number(z)

[1] "We have twenty two Arab countries in the world"

v1<-sample(0:5000,20) v1

[1] 1845 4438 4664 1803 1131 4254 4880 4267 4764 4168 222 3880 534 1319 4998 [16] 370 2657 78 1056 620 replace_number(v1) [1] "one thousand eight hundred forty five" [2] "four thousand four hundred thirty eight" [3] "four thousand six hundred sixty four" [4] "one thousand eight hundred three" [5] "one thousand one hundred thirty one" [6] "four thousand two hundred fifty four" [7] "four thousand eight hundred eighty" [8] "four thousand two hundred sixty seven" [9] "four thousand seven hundred sixty four" [10] "four thousand one hundred sixty eight" [11] "two hundred twenty two" [12] "three thousand eight hundred eighty" [13] "five hundred thirty four" [14] "one thousand three hundred nineteen" [15] "four thousand nine hundred ninety eight" [16] "three hundred seventy" [17] "two thousand six hundred fifty seven" [18] "seventy eight" [19] "one thousand fifty six" [20] "six hundred twenty"

v2<-sample(100001:999999,20)

v2

[1] 359487 994098 458703 474531 106581 905167 373805 288612 614544 591035 [11] 632526 649772 711979 785355 720779 678609 843081 679009 593148 801554

replace_number(v2)

[1] "three hundred fifty nine thousand four hundred eighty seven" [2] "nine hundred ninety four thousand ninety eight" [3] "four hundred fifty eight thousand seven hundred three" [4] "four hundred seventy four thousand five hundred thirty one" [5] "one hundred six thousand five hundred eighty one" [6] "nine hundred five thousand one hundred sixty seven" [7] "three hundred seventy three thousand eight hundred five" [8] "two hundred eighty eight thousand six hundred twelve" [9] "six hundred fourteen thousand five hundred forty four" [10] "five hundred ninety one thousand thirty five" [11] "six hundred thirty two thousand five hundred twenty six" [12] "six hundred forty nine thousand seven hundred seventy two" [13] "seven hundred eleven thousand nine hundred seventy nine" [14] "seven hundred eighty five thousand three hundred fifty five" [15] "seven hundred twenty thousand seven hundred seventy nine" [16] "six hundred seventy eight thousand six hundred nine" [17] "eight hundred forty three thousand eighty one" [18] "six hundred seventy nine thousand nine" [19] "five hundred ninety three thousand one hundred forty eight" [20] "eight hundred one thousand five hundred fifty four"

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