The peeps
dataset contains records for one hundred people residing in ten
different countries. Each person in the table has address information along
with their email address and phone number. There are also personal
characteristics like date of birth, height, and weight. This data has been
synthesized, and so the names within the table have not been taken or based
on individuals in real life. The street addresses were generated from actual
street names within real geographic localities, however, the street numbers
were assigned randomly from a constrained number set. While these records do
not relate to real people, efforts were made to make the data as realistic as
possible.
Format
A tibble with 100 rows and 14 variables:
- name_given, name_family
The given and family name of individual.
- address
The street address of the individual.
- city
The name of the city or locality in which the individual resides.
- state_prov
The state or province associated with the
city
andaddress
. This isNA
for individuals residing in countries where subdivision data is not needed for generating a valid mailing address.- postcode
The post code associated with the
city
andaddress
.- country
The 3-letter ISO 3166-1 country code representative of the individual's country.
- email_addr
The individual's email address.
- phone_number, country_code
The individual's phone number and the country code associated with the phone number.
- gender
The gender of the individual.
- dob
The individual's date of birth (DOB) in the ISO 8601 form of
YYYY-MM-DD
.- height_cm, weight_kg
The height and weight of the individual in centimeters (cm) and kilograms (kg), respectively.
Examples
dplyr::glimpse(peeps)
#> Rows: 100
#> Columns: 14
#> $ name_given <chr> "Ruth", "Peter", "Fanette", "Judyta", "Leonard", "Maymun"…
#> $ name_family <chr> "Conte", "Möller", "Gadbois", "Borkowska", "Jacobs", "Kho…
#> $ address <chr> "4299 Bobcat Drive", "3705 Hidden Pond Road", "4200 Swick…
#> $ city <chr> "Baileys Crossroads", "Red Boiling Springs", "New Orleans…
#> $ state_prov <chr> "MD", "TN", "LA", "NY", "CA", "OH", "IN", "MA", "CA", "TX…
#> $ postcode <chr> "22041", "37150", "70112", "14125", "90036", "45013", "46…
#> $ country <chr> "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "…
#> $ email_addr <chr> "rcconte@example.com", "pmoeller@example.com", "fan_gadbo…
#> $ phone_number <chr> "240-783-7630", "615-699-3517", "985-205-2970", "585-948-…
#> $ country_code <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 32, 32, 32, 32, 32, 32, 32,…
#> $ gender <chr> "female", "male", "female", "female", "male", "male", "fe…
#> $ dob <date> 1949-03-16, 1939-11-22, 1970-12-20, 1965-07-19, 1985-10-…
#> $ height_cm <int> 153, 175, 167, 156, 177, 172, 168, 165, 181, 187, 164, 15…
#> $ weight_kg <dbl> 76.4, 74.9, 61.6, 54.5, 113.2, 88.4, 63.5, 61.3, 99.7, 10…