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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
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.