charlatan
makes fake data, inspired from and borrowing some code from Python's faker
Make fake data for:
- person names
- jobs
- phone numbers
- colors: names, hex, rgb
- credit cards
- DOIs
- numbers in range and from distributions
- gene sequences
- geographic coordinates
- emails
- URIs, URLs, and their parts
- IP addresses
- more coming ...
Possible use cases for charlatan
:
- Students in a classroom setting learning any task that needs a dataset.
- People doing simulations/modeling that need some fake data
- Generate fake dataset of users for a database before actual users exist
- Complete missing spots in a dataset
- Generate fake data to replace sensitive real data with before public release
- Create a random set of colors for visualization
- Generate random coordinates for a map
- Get a set of randomly generated DOIs (Digital Object Identifiers) to assign to fake scholarly artifacts
- Generate fake taxonomic names for a biological dataset
- Get a set of fake sequences to use to test code/software that uses sequence data
Reasons to use charlatan
:
- Lite weight, few dependencies
- Relatively comprehensive types of data, and more being added
- Comprehensive set of languages supported, more being added
- Useful R features such as creating entire fake data.frame's
cran version
install.packages("charlatan")
dev version
devtools::install_github("ropensci/charlatan")
library("charlatan")
... for all fake data operations
x <- fraudster()
x$job()
#> [1] "Engineer, communications"
x$name()
#> [1] "Ms. Fleeta Bashirian"
x$color_name()
#> [1] "Aquamarine"
Adding more locales through time, e.g.,
Locale support for job data
ch_job(locale = "en_US", n = 3)
#> [1] "Investment banker, operational" "Psychologist, forensic"
#> [3] "Magazine features editor"
ch_job(locale = "fr_FR", n = 3)
#> [1] "Diététicien"
#> [2] "Auteur interprète"
#> [3] "Ingénieur maintenance aéronautique"
ch_job(locale = "hr_HR", n = 3)
#> [1] "Voditelj skele u nacionalnoj plovidbi"
#> [2] "Čuvar prirode"
#> [3] "Viši arhivist"
ch_job(locale = "uk_UA", n = 3)
#> [1] "Режисер" "Математик" "Ріелтор"
ch_job(locale = "zh_TW", n = 3)
#> [1] "多媒體開發主管" "公共衛生醫師" "產品企劃開發人員"
For colors:
ch_color_name(locale = "en_US", n = 3)
#> [1] "MediumSlateBlue" "Chocolate" "HotPink"
ch_color_name(locale = "uk_UA", n = 3)
#> [1] "Морквяний" "Яскраво-фіолетовий" "Брунато-малиновий"
More coming soon ...
ch_generate()
#> # A tibble: 10 x 3
#> name job phone_number
#> <chr> <chr> <chr>
#> 1 Hervey Luettgen Consulting civil engineer (135)742-8104x9887
#> 2 Mr. Deontae Herzog Further education lecturer 426.369.0824
#> 3 Vicki Denesik Solicitor, Scotland 1-535-887-8338x39579
#> 4 Mrs. Elvera Heidenreich Secretary/administrator 577.988.6970x0455
#> 5 Bambi Sanford Equities trader 1-861-301-3087x38656
#> 6 Garrison Jones Field seismologist 824-865-3964
#> 7 Alia Grant Occupational hygienist 08896842450
#> 8 Kyree Koss Equities trader (086)781-0334
#> 9 Bama Christiansen DDS Forensic scientist 582-048-8116
#> 10 Alfie Koepp Police officer (645)984-3611x1223
ch_generate('job', 'phone_number', n = 30)
#> # A tibble: 30 x 2
#> job phone_number
#> <chr> <chr>
#> 1 Youth worker 615-108-9165
#> 2 Charity officer 1-917-206-3061x001
#> 3 Museum/gallery curator 08799787859
#> 4 Social researcher (436)081-1417x20183
#> 5 Ship broker 840-520-7103
#> 6 Electrical engineer 1-166-486-7102
#> 7 Games developer 240-503-6455x54793
#> 8 Multimedia programmer +78(5)8476399438
#> 9 Engineer, maintenance (IT) 03183289534
#> 10 Conservator, museum/gallery +32(0)2448780352
#> # ... with 20 more rows
ch_name()
#> [1] "Pauline Renner"
ch_name(10)
#> [1] "Jon Anderson PhD" "Dirk Hagenes"
#> [3] "Iola Hills" "Ms. Merna Kilback PhD"
#> [5] "May Hermann" "Dr. Zavier Kassulke III"
#> [7] "Mr. Yancy Stiedemann" "Ms. Melina Dach"
#> [9] "Ms. Janine Kunde" "Lovett Greenfelder"
ch_phone_number()
#> [1] "799.053.8298x03215"
ch_phone_number(10)
#> [1] "1-795-047-3421" "01683058041" "(199)253-2025"
#> [4] "442-608-7772x39728" "006.994.5557" "566.052.5676x69403"
#> [7] "+93(5)4894763387" "1-067-264-4141x90001" "1-891-855-7961"
#> [10] "334.562.6526"
ch_job()
#> [1] "Careers adviser"
ch_job(10)
#> [1] "Midwife"
#> [2] "Solicitor"
#> [3] "Engineer, maintenance (IT)"
#> [4] "Lecturer, higher education"
#> [5] "Scientist, research (physical sciences)"
#> [6] "Hydrogeologist"
#> [7] "Editor, commissioning"
#> [8] "Research officer, political party"
#> [9] "Estate manager/land agent"
#> [10] "Brewing technologist"
ch_credit_card_provider()
#> [1] "JCB 15 digit"
ch_credit_card_provider(n = 4)
#> [1] "JCB 15 digit" "Voyager" "Discover" "JCB 16 digit"
ch_credit_card_number()
#> [1] "3766356690332082"
ch_credit_card_number(n = 10)
#> [1] "55520251460378052" "561252701122526" "3337396755300677029"
#> [4] "4321262613647302" "4500978817193750" "869995174334936019"
#> [7] "869976711099048283" "54335568117639643" "210023110046558888"
#> [10] "6011082845864142715"
ch_credit_card_security_code()
#> [1] "546"
ch_credit_card_security_code(10)
#> [1] "772" "273" "192" "316" "769" "536" "041" "3830" "133" "991"
- Please report any issues or bugs.
- License: MIT
- Get citation information for
charlatan
in R doingcitation(package = 'charlatan')
- Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.