fkr generates realistic-looking, made-up (fake) data for the Philippines – names, addresses, phone numbers, ages, job titles, ID-style numbers, and more – for building and testing software, writing tutorials, or teaching, without using any real person’s information.
Nothing this package produces is looked up from a real database. Every value – including anything formatted to look like a government ID number (SSS, TIN, PhilHealth, Pag-IBIG, PhilSys) – is randomly made up on the spot. It does not belong to any real person, business, or record, and won’t work anywhere official.
# CRAN
install.packages('fkr')
# GitHub
# install.packages("devtools")
# pak::pak("yng-me/fkr")
install.packages("fkr", repos = c('https://yng-me.r-universe.dev', 'https://cloud.r-project.org'))
Every function starts with fkr_. The first thing you tell it is always
how many fake values you want:
library(fkr)
fkr_full_name(3)
#> [1] "Pancho Ocampo" "Quintessa Isip" "Orella De Castro"
fkr_age(3)
#> [1] 12 8 9
fkr_mobile_number(3)
#> [1] "09283870905" "09060471203" "08976742579"
fkr_address(3)
#> street barangay city province region zip
#> 1 79 Marcos Highway Extension Katipunan Valenzuela Metro Manila National Capital Region (NCR) 1440
#> 2 218 Marcos Highway Avenue Buenavista Maasin City Southern Leyte Region VIII (Eastern Visayas) 6600
#> 3 622 Luna Extension Tibig Vigan City Ilocos Sur Region I (Ilocos Region) 2700
Want a whole pretend dataset – many columns, many rows – in one go? Use
fkr() and list which generator fills each column:
fkr(5, list(
first_name = fkr_first_name,
last_name = fkr_last_name,
sex = fkr_sex,
age = fkr_age,
date_of_birth = fkr_birthday
))
#> first_name last_name sex age date_of_birth
#> 1 Iman Dela Cruz Female 22 2004-01-31
#> 2 Hubert Barrera Female 11 2015-08-18
#> 3 Cybille Santos Female 36 1990-08-14
#> 4 Jaybee De Dios Female 1 2025-10-09
#> 5 Rolando Garcia Male 41 1985-04-16
age and date_of_birth automatically agree with each other – fkr
makes sure a person’s birthdate actually matches the age shown for them.
For a friendlier, step-by-step walkthrough (including how to attach
extra settings to a column, or make one column depend on another), see
vignette("fkr") after installing.
| Category | Examples |
|---|---|
| People | first/last/full name, sex, civil status, age, birthday |
| Contact details | email, mobile number, landline number |
| Addresses | region, province, city, barangay, street address, ZIP code, full address |
| Government ID-style numbers | SSS, TIN, PhilHealth, Pag-IBIG, PhilSys (see disclaimer above) |
| Official PH classifications | PSGC geographic codes, PSOC occupations, PSIC industries |
| Business | company name, job title, industry, product, price, business permit number |
| General-purpose helpers | plain numbers, whole numbers, yes/no, “select all that apply”, labeled categories, unique IDs, coordinates |
| Whole datasets |
fkr() – build a complete fake table in one call |
Every function has its own help page with more detail and examples, e.g.
?fkr_address.
Names, surnames, addresses, and job titles are drawn from real Philippine reference data where possible (e.g. actual region/province/city names, and the official PSGC, PSOC, and PSIC classification systems), so the shape of the data is realistic – but the specific combination assigned to any one fake record is always random and fictional.
MIT © Bhas Abdulsamad