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.
install.packages("remotes")
remotes::install_github("yng-me/fkr")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] "Tanisha Magsino" "Socorro Cunanan" "Joyce Alcantara"
fkr_age(3)
#> [1] 2 50 1
fkr_mobile_number(3)
#> [1] "09910021516" "09187189635" "09489378455"
fkr_address(3)
#> street barangay city province
#> 1 464 Legarda Avenue San Isidro Iligan City Lanao del Norte
#> 2 366 Recto Extension Maligaya Butuan City Agusan del Norte
#> 3 342 Shaw Boulevard Highway Tibig Las Piñas Metro Manila
#> region zip
#> 1 Region X (Northern Mindanao) 9200
#> 2 Region XIII (Caraga) 8600
#> 3 National Capital Region (NCR) 1740Want 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 Jordan Abubakar Female 6 2020-10-07
#> 2 Iris Gonzales Male 6 2020-02-28
#> 3 Editha Dela Cruz Male 6 2020-07-12
#> 4 Warren Natividad Male 5 2021-07-25
#> 5 Loretta Mahinay Male 15 2011-10-13age 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