Generate Random Vector of Ages

Description

Generate a random vector of ages within the provided range. The default age range is set between 18 and 89, to match the age ranges which appear (see e.g., https://gssdataexplorer.norc.org/variables/53/vshow).

Usage

age(n, x = 18:89, prob = NULL, name = "Age")

Arguments

Value

Returns a random integer vector of ages within the provided range (defaults to 18:89).

See Also

Other variable functions: animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

age(10) # draw 10 ages with default values
hist(age(n=10000))  
interval(age, 3, n = 1000)

Generate Random Vector of animals

Description

animal - Generate a random vector of animals.

pet - Generate a random vector of pets.

Usage

animal(n, k = 10, x = wakefield::animal_list, prob = NULL, name = "Animal")

pet(
  n,
  x = c("Dog", "Cat", "None", "Bird", "Horse"),
  prob = c(0.365, 0.304, 0.258, 0.031, 0.015),
  name = "Pet"
)

Arguments

Details

The household pets and probabilities:

Value

Returns a random factor vector of animal elements.

See Also

Other variable functions: age(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

animal(10)
pie(table(animal(10000)))

pet(10)
pie(table(pet(10000)))

Animal List

Description

A dataset containing a character vector animals

Usage

data(animal_list)

Format

A character vector with 591 elements

References

https://a-z-animals.com/animals

Generate Random Vector of Answers (Yes/No)

Description

Generate a random vector of answers (yes/no).

Usage

answer(n, x = c("No", "Yes"), prob = NULL, name = "Answer")

Arguments

Value

Returns a random factor vector of answers (yes/no) outcome elements.

See Also

Other variable functions: age(), animal(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

answer(10)
100*table(answer(n <- 10000))/n

Generate Random Vector of Areas

Description

Generate a random vector of areas ("Suburban", "Urban", "Rural").

Usage

area(n, x = c("Suburban", "Urban", "Rural"), prob = NULL, name = "Area")

Arguments

Value

Returns a random vector of area status elements.

See Also

Other variable functions: age(), animal(), answer(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

area(10)
barplot(table(area(10000)))

Convert a Factor Data Frame to Integer

Description

Converts a data.frame of factors to integers.

Usage

as_integer(x, cols = NULL, fun = as.integer)

Arguments

Value

Returns a data.frame equal to the class of x with integer columns rather than factor.

See Also

r_series

Examples

as_integer(r_series(likert_7, 5, 10))
as_integer(r_series(likert_7, 5, 10), cols = c(2, 4))

library(dplyr)
r_data_frame(n=100,
    age,
    political,
    sex,
    grade
) %>%
    as_integer(2:3)

Generate Random Vector of Cars

Description

Generate a random vector of cars (see ?mtcars).

Usage

car(n, x = rownames(datasets::mtcars), prob = NULL, name = "Car")

Arguments

Value

Returns a random vector of car elements.

See Also

Other variable functions: age(), animal(), answer(), area(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

car(10)
table(car(10000))

Generate Random Vector of Number of Children

Description

Generate a random vector of number of children.

Usage

children(
  n,
  x = 0:10,
  prob = c(0.25, 0.25, 0.15, 0.15, 0.1, 0.02, 0.02, 0.02, 0.02, 0.01, 0.01),
  name = "Children"
)

Arguments

Value

Returns a random vector of number of children elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

children(10)
pie(table(children(100)))

Generate Random Vector of Coin Flips

Description

Generate a random vector of coin flips (heads/tails).

Usage

coin(n, x = c("Tails", "Heads"), prob = NULL, name = "Coin")

Arguments

Value

Returns a random factor vector of coin flip outcome elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

coin(10)
100*table(coin(n <- 10000))/n

Generate Random Vector of Colors

Description

color - Generate a random vector of colors (sampled from colors()).

color - Generate a random vector of psycological primary colors (sampled from colors()).

Usage

color(n, k = 10, x = grDevices::colors(), prob = NULL, name = "Color")

primary(
  n,
  x = c("Red", "Green", "Blue", "Yellow", "Black", "White"),
  prob = NULL,
  name = "Color"
)

Arguments

Value

Returns a random factor vector of color elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

color(10)
pie(tab <- table(color(10000)), col = names(tab))

primary(10)
pie(tab <- table(primary(10000)), col = names(tab))
barplot(tab <- table(primary(10000, prob = probs(6))), col = names(tab))

Generate Random Vector of Dates

Description

Generate a random vector of dates.

Usage

date_stamp(
  n,
  random = FALSE,
  x = NULL,
  start = Sys.Date(),
  k = 12,
  by = "-1 months",
  prob = NULL,
  name = "Date"
)

Arguments

Value

Returns a random factor vector of date elements.

See Also

seq.Date

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

date_stamp(10)
pie(table(date_stamp(2000, prob = probs(12))))

## Supply dates to `x` to sample from
date_stamp(10, x = seq(as.Date("1980-11-16"), length = 30, by = "1 years"))

Generate Random Vector of Deaths Outcomes

Description

Generate a random logical vector of deaths (TRUE/FALSE).

Usage

death(n, prob = NULL, name = "Death")

died(n, prob = NULL, name = "Died")

Arguments

Value

Returns a random logical vector of death outcome elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

death(10)
died(10)
100*table(death(n <- 10000))/n
100*table(death(n <- 10000, prob = c(.3, .7)))/n
r_data_frame(10, died)

Generate Random Vector of Dice Throws

Description

Generate a random vector of dice throws.

Usage

dice(n, x = 1:6, prob = NULL, name = "Dice")

Arguments

Value

Returns a random vector of dice throw elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

dice(10)
barplot(table(dice(10000)))

Generate Random Vector of DNA Nucleobases

Description

Generate a random vector of DNA nucleobases ("Guanine", "Adenine", "Thymine", "Cytosine").

Usage

dna(
  n,
  x = c("Guanine", "Adenine", "Thymine", "Cytosine"),
  prob = NULL,
  name = "DNA"
)

Arguments

Value

Returns a random vector of DNA nucleobase elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

dna(10)
barplot(table(dna(10000)))

Generate Random Vector of Birth Dates

Description

Generate a random vector of birth dates.

Usage

dob(
  n,
  random = TRUE,
  x = NULL,
  start = Sys.Date() - 365 * 15,
  k = 365 * 2,
  by = "1 days",
  prob = NULL,
  name = "DOB"
)

birth(
  n,
  random = TRUE,
  x = NULL,
  start = Sys.Date() - 365 * 15,
  k = 365 * 2,
  by = "1 days",
  prob = NULL,
  name = "Birth"
)

Arguments

Value

Returns a random vector of birth date elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

dob(10)
barplot(table(birth(15)))
barplot(table(birth(30)))

Generate Random Dummy Coded Vector

Description

Generate a random dummy coded (0/1) vector.

Usage

dummy(n, prob = NULL, name = "Dummy")

Arguments

Value

Returns a random dummy vector of (0/1) elements.

See Also

sample.int

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

dummy(100, name = "Var")
table(dummy(1000))

Generate Random Vector of Educational Attainment Level

Description

Generate a random vector of educational attainment level.

Usage

education(
  n,
  x = c("No Schooling Completed", "Nursery School to 8th Grade",
    "9th Grade to 12th Grade, No Diploma", "Regular High School Diploma",
    "GED or Alternative Credential", "Some College, Less than 1 Year",
    "Some College, 1 or More Years, No Degree", "Associate's Degree",
    "Bachelor's Degree", "Master's Degree", "Professional School Degree",
    "Doctorate Degree"),
  prob = c(0.013, 0.05, 0.085, 0.246, 0.039, 0.064, 0.15, 0.075, 0.176, 0.072, 0.019,
    0.012),
  name = "Education"
)

Arguments

Details

The educational attainments and probabilities used match approximate U.S. educational attainment make-up (http://www.census.gov):

Value

Returns a random vector of educational attainment level elements.

References

http://www.census.gov

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

education(10)
pie(table(education(10000)))

Generate Random Vector of Employment Statuses

Description

Generate a random vector of employment statuses.

Usage

employment(
  n,
  x = c("Full Time", "Part Time", "Unemployed", "Retired", "Student"),
  prob = c(0.6, 0.1, 0.1, 0.1, 0.1),
  name = "Employment"
)

Arguments

Details

The following arbitrary probabilities are used:

Value

Returns a random vector of employment status elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

employment(10)
pie(table(employment(10000)))
barplot(table(employment(10000)))

Generate Random Vector of Eye Colors

Description

Generate a random vector of eye colors.

Usage

eye(
  n,
  x = c("Brown", "Blue", "Green", "Hazel", "Gray"),
  prob = c(0.44, 0.3, 0.13, 0.09, 0.04),
  name = "Eye"
)

Arguments

Details

The eye colors and probabilities:

Value

Returns a random vector of eye color elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

eye(10)
barplot(v <- table(eye(10000)), col = replace(names(v), 4, "yellowgreen"))

Generate Random Vector of Grades

Description

grade - Generate a random normal vector of percent grades.

grade - Generate a random normal vector of letter grades.

grade - Generate a random normal vector of grade point averages (GPA; 0.0 - 4.0 scale).

Usage

grade(n, mean = 88, sd = 4, name = "Grade", digits = 1)

grade_letter(n, mean = 88, sd = 4, name = "Grade_Letter")

gpa(n, mean = 88, sd = 4, name = "GPA")

Arguments

Details

The conversion between percent range, letter grade, and GPA is:

Value

Returns a random normal vector of grade elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

grade(10)
hist(grade(10000))
interval(grade, 5, n = 1000)

grade_letter(10)
barplot(table(grade_letter(10000)))

gpa(10)
hist(gpa(10000))

Generate Random Vector of Grade Levels

Description

Generate a random vector of grade levels.

Usage

grade_level(
  n,
  x = c("K", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12"),
  prob = NULL,
  name = "Grade_Level"
)

Arguments

Value

Returns a random vector of grade level elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

grade_level(10)
barplot(table(grade_level(10000)))

Augmented List of Grady Ward's English Words and Mark Kantrowitz's Names List

Description

A dataset containing a vector of Grady Ward's English words augmented with qdapDictionaries's DICTIONARY, Mark Kantrowitz's names list, other proper nouns, and contractions.

Usage

data(grady_augmented)

Format

A character vector with 122806 elements

Details

A dataset containing a vector of Grady Ward's English words augmented with proper nouns (U.S. States, Countries, Mark Kantrowitz's Names List, and months) and contractions. That dataset is augmented to increase the data set size.

References

Moby Thesaurus List by Grady Ward https://www.gutenberg.org

List of names from Mark Kantrowitz http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/corpora/names/. A copy of the http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/corpora/names/readme.txt per the author's request.

Generate Random Vector of Control/Treatment Groups

Description

Generate a random vector of binary groups (e.g., control/treatment).

Usage

group(n, x = c("Control", "Treatment"), prob = NULL, name = "Group")

Arguments

Value

Returns a random factor vector of group (control/treatment) elements.

Note

If you want > 2 groups see 'r_sample_factor'.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

group(10)
100*table(group(n <- 10000))/n
100*table(group(n <- 10000, prob = c(.3, .7)))/n

Generate Random Vector of Hair Colors

Description

Generate a random vector of hair colors.

Usage

hair(
  n,
  x = c("Brown", "Black", "Blonde", "Red"),
  prob = c(0.35, 0.28, 0.26, 0.11),
  name = "Hair"
)

Arguments

Details

The hair colors and probabilities:

Value

Returns a random vector of hair color elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

hair(10)
v <- table(hair(10000))
lbs <- paste0(names(v), "\n", round(100*v/sum(v), 1), "%")
pie(v, col = replace(names(v), 3, "yellow"), labels = lbs)

Generate Random Vector of Heights

Description

height and height_in - Generate a random normal vector of heights in inches.

height_cm - Generate a random normal vector of heights in centimeters.

Usage

height(
  n,
  mean = 69,
  sd = 3.75,
  min = 1,
  max = NULL,
  digits = 0,
  name = "Height"
)

height_in(
  n,
  mean = 69,
  sd = 3.75,
  min = 1,
  max = NULL,
  digits = 1,
  name = "Height(in)"
)

height_cm(
  n,
  mean = 175.26,
  sd = 9.525,
  min = 1,
  max = NULL,
  digits = 1,
  name = "Height(cm)"
)

Arguments

Value

Returns a random normal vector of height elements.

Note

height rounds to nearest whole number. height_in & height_in round to the nearest tenths.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

height(10)
hist(height(10000))
interval(height, 5, n = 1000)

Generate a Random Sequence of H:M:S Times

Description

Generate a random vector of H:M:S times.

Usage

hour(n, x = seq(0, 23.5, by = 0.5), prob = NULL, random = FALSE, name = "Hour")

Arguments

Value

Returns a random vector of H:M:S time elements.

See Also

times

Examples

hour(20)
hour(20, random=TRUE)

Identification Numbers

Description

id - Generate a sequential character vector of zero-padded identification numbers (IDs).

id_factor - Generate a sequential factor vector of zero-padded identification numbers (IDs).

Usage

id(n, random = FALSE, name = "ID")

id_factor(n, random = FALSE, name = "ID")

Arguments

Value

Returns a (optionally random) vector of character/factor observations ID numbers.

Warning

id uses sprintf to generate the padded ID. Per sprintf's documentation: “The format string is passed down the OS's sprintf function...The behaviour on inputs not documented here is 'undefined', which means it is allowed to differ by platform.” See sprintf for details.

Note

id is faster than id_factor, as the later coerces the vector to a factor.

See Also

sprintf

Examples

id(1000)
r_data_frame(n=21, id)

Generate Random Gamma Vector of Incomes

Description

Generate a random gamma vector of incomes.

Usage

income(n, digits = 2, name = "Income")

Arguments

Details

Incomes are generated using: rgamma(n, 2) * 2000.

Value

Returns a random gamma vector of income elements.

See Also

gamma

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

income(10)
hist(income(10000))
pie(table(cut(income(10000), 10)))

Generate Random Vector of Internet Browsers

Description

Generate a random vector of Internet browser.

Usage

internet_browser(
  n,
  x = c("Chrome", "IE", "Firefox", "Safari", "Opera", "Android"),
  prob = c(0.5027, 0.175, 0.1689, 0.0994, 0.017, 0.0132),
  name = "Browser"
)

Arguments

Details

The browser use and probabilities (from https://gs.statcounter.com/):

Value

Returns a random factor vector of Internet browser elements.

References

https://gs.statcounter.com/

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

internet_browser(20)
barplot(table(internet_browser(10000)))
pie(table(internet_browser(10000)))

Cut Numeric Into Factor

Description

A wrapper for cut that cuts the vector and then adds the varname produced by the original function.

Usage

interval(
  fun,
  breaks,
  ...,
  labels = NULL,
  include.lowest = FALSE,
  right = TRUE,
  dig.lab = 3,
  ordered_result = FALSE,
  n
)

Arguments

Value

Returns a cut factor vector.

See Also

cut

Examples

interval(normal, 4, n=100)
attributes(interval(normal, 4, n=100))
interval(age, 3, n = 1000)

Generate Random Vector of Intelligence Quotients (IQs)

Description

Generate a random normal vector of intelligence quotients (IQs).

Usage

iq(n, mean = 100, sd = 10, min = 0, max = NULL, digits = 0, name = "IQ")

Arguments

Value

Returns a random normal vector of IQ elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

iq(10)
hist(iq(10000))
interval(iq, 5, n = 1000)

Generate Random Vector of Languages

Description

Generate a random vector of languages from the presidential_debates_2012.

Usage

language(
  n,
  x = wakefield::languages[["Language"]],
  prob = wakefield::languages[["Proportion"]],
  name = "Language"
)

Arguments

Value

Returns a random character vector of language elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

language(10)
pie(table(language(10000)))

lang <- wakefield::languages[sample(1:99, 6), ]
lang["prop"] <- lang[["N"]]/sum(lang[["N"]])
labs <- round(100 * lang[["prop"]], 1)
pie(lang[["prop"]], paste0(lang[["Language"]], "\n", labs, "%"))

Languages of the World

Description

A dataset containing native language use statistics taken from: https://en.wikipedia.org/wiki/List_of_languages_by_number_of_native_speakers.

Usage

data(languages)

Format

A data frame with 99 rows and 4 variables

Details

• Language. The language spoken.

• N. The number of speakers world-wide.

• Proportion. The proportion of speakers.

• Percent. The percentage of speakers.

References

https://en.wikipedia.org/wiki/List_of_languages_by_number_of_native_speakers

Generate Random Vector of Levels

Description

level - Generate a random vector of integer levels (1-4).

math - Generate a random vector of integer mathematics levels (1-4) similar to New York State grades 3-8 assessment results.

ela - Generate a random vector of integer English language arts (ELA) levels (1-4) similar to New York State grades 3-8 assessment results.

Usage

level(n, x = 1:4, prob = NULL, name = "Level")

math(n, x = 1:4, prob = c(0.29829, 0.33332, 0.22797, 0.14042), name = "Math")

ela(n, x = 1:4, prob = c(0.3161, 0.37257, 0.2233, 0.08803), name = "ELA")

Arguments

Details

Distribution of levels (used in prob) were taken from New York State' s 2014 assessment report: http://www.p12.nysed.gov/irs/

Value

Returns a random vector of integer levels (1-4) elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

level(10)
barplot(table(level(10000, prob = probs(4))))

math(10)
barplot(table(math(10000)))

ela(10)
barplot(table(ela(10000)))

Generate Random Vector of Likert-Type Responses

Description

Generate a random vector of Likert-type responses.

Usage

likert(
  n,
  x = c("Strongly Agree", "Agree", "Neutral", "Disagree", "Strongly Disagree"),
  prob = NULL,
  name = "Likert"
)

likert_5(
  n,
  x = c("Strongly Agree", "Agree", "Neutral", "Disagree", "Strongly Disagree"),
  prob = NULL,
  name = "Likert"
)

likert_7(
  n,
  x = c("Strongly Agree", "Agree", "Somewhat Agree", "Neutral", "Somewhat Disagree",
    "Disagree", "Strongly Disagree"),
  prob = NULL,
  name = "Likert"
)

Arguments

Value

Returns a random vector of Likert-type response elements.

Note

likert & likert_5 are identical outputs, sampling from a 5-point response scale. likert_7 samples from a 7-point response scale.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

dice(10)
barplot(table(dice(10000)))

Generate Random Lorem Ipsum Strings

Description

Generates (pseudo)random lorem ipsum text.

Usage

lorem_ipsum(n, ..., name = "Lorem_Ipsum")

paragraph(n, ..., name = "Paragraph")

Arguments

Value

Returns a random character vector of string elements.

Note

lorem_ipsum and paragraph produce identical strings but will produce different vector/column names when used inside of r_data_frame or r_list.

See Also

stri_rand_lipsum

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

lorem_ipsum(10)
paragraph(10)

lorem_ipsum(10, start_lipsum = FALSE)

Generate Random Vector of Marital Statuses

Description

Generate a random vector of marital statuses.

Usage

marital(
  n,
  x = c("Married", "Divorced", "Widowed", "Separated", "Never Married"),
  prob = NULL,
  name = "Marital"
)

Arguments

Value

Returns a random vector of marital status elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

marital(10)
barplot(table(marital(10000)))

Generate Random Vector of Military Branches

Description

Generate a random vector of military branches.

Usage

military(
  n,
  x = c("Army", "Air Force", "Navy", "Marine Corps", "Coast Guard"),
  prob = c(0.3785, 0.2334, 0.2218, 0.1366, 0.0296),
  name = "Military"
)

Arguments

Details

The military branches and probabilities used match approximate U.S. military make-up:

Value

Returns a random factor vector of military branch elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

military(10)
barplot(table(military(10000)))
pie(table(military(10000)))

Generate a Random Sequence of Minutes in H:M:S Format

Description

Generate a random vector of minutes in H:M:S format.

Usage

minute(
  n,
  x = seq(0, 59, by = 1)/60,
  prob = NULL,
  random = FALSE,
  name = "Minute"
)

Arguments

Value

Returns a random vector of minute time elements in H:M:S format.

See Also

times

Examples

minute(20)
minute(20, random=TRUE)
pie(table(minute(2000, x = seq(0, 59, by = 10)/60, prob = probs(6))))

Generate Random Vector of Months

Description

Generate a random factor vector of months.

Usage

month(n, x = month.name, prob = NULL, name = "Month")

Arguments

Value

Returns a random character vector of month elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

month(10)
pie(table(month(10000, prob = probs(12))))

Generate Random Vector of Names

Description

Generate a random vector of first names. This dataset includes all unique entries from the babynames package.

Usage

name(
  n,
  x = wakefield::name_neutral,
  prob = NULL,
  replace = FALSE,
  name = "Name"
)

Arguments

Value

Returns a random vector of name elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

name(10)
name(100)
name(1000, replace = TRUE)

Gender Neutral Names

Description

A dataset containing a character vector gender neutral names according to the U.S. Census.

Usage

data(name_neutral)

Format

A character vector with 662 elements

References

http://www.census.gov

Generate Random Normal Vector

Description

normal - A wrapper for rnorm that generate a random normal vector.

normal_round - A wrapper for rnorm that generate a rounded random normal vector.

Usage

normal(n, mean = 0, sd = 1, min = NULL, max = NULL, name = "Normal")

normal_round(
  n,
  mean = 0,
  sd = 1,
  min = NULL,
  max = NULL,
  digits = 2,
  name = "Normal"
)

Arguments

Value

Returns a random vector of elements.

See Also

rnorm

round

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

normal(100, name = "Var")
hist(normal(10000, 100, 10))
interval(normal, 9, n = 1000)

Data Frame Viewing

Description

Convenience function to view all the columns of the head of a truncated data.frame. peek invisibly returns x. This makes its use ideal in a dplyr/magrittr pipeline.

Usage

peek(x, n = 10, width = 10, ...)

Arguments

Details

By default dplyr does not print all columns of a data frame (tbl_df). This makes inspection of data difficult at times, particularly with text string data. peek allows the user to see a truncated head for inspection purposes.

Value

Prints a truncated head but invisibly returns x.

See Also

head

Examples

(dat1 <- r_data_frame(100, id, sentence, paragraph))
peek(dat1)
peek(dat1, n = 20)
peek(dat1, width = 40)

library(dplyr)

## Use in a dplyr/magrittr pipeline to view the data (silly example)
par(mfrow = c(2, 2))

r_data_frame(1000, id, sex, pet, employment, eye, sentence, paragraph) %>%
    peek %>%
    (function(x, ind = 2:5){ invisible(lapply(ind, function(i) pie(table(x[[i]]))))})

## A wider data set example
dat2 <- r_data_theme()

dat2
peek(dat2)

Plots a tbl_df Object

Description

Plots a tbl_df object.

Usage

## S3 method for class 'tbl_df'
plot(x, ...)

Arguments

Generate Random Vector of Political Parties

Description

Generate a random vector of political parties.

Usage

political(
  n,
  x = c("Democrat", "Republican", "Constitution", "Libertarian", "Green"),
  prob = c(0.577269133302094, 0.410800432748879, 0.00491084954793489,
    0.00372590303330866, 0.0032936813677832),
  name = "Political"
)

Arguments

Details

The political parties and probabilities used match approximate U.S. political make-up of registered voters (2014). The default make up is:

Value

Returns a random factor vector of political party elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

political(10)
barplot(table(political(10000)))

2012 U.S. Presidential Debate Dialogue

Description

A dataset containing 2911 ordered sentences used by speakers during the three 2012 presidential debates.

Usage

data(presidential_debates_2012)

Format

A character vector with 2911 elements

Prints an available Object.

Description

Prints an available object.

Usage

## S3 method for class 'available'
print(x, ...)

Arguments

Prints a variable Object

Description

Prints a variable object

Usage

## S3 method for class 'variable'
print(x, ...)

Arguments

Generate a Random Vector of Probabilities.

Description

Generate a random vector of probabilities that sum to 1.

Usage

probs(j, upper = 1e+06)

Arguments

Value

Returns a vector of probabilities summing to 1.

Examples

probs(10)
sum(probs(100))
pie(table(month(10000, prob = probs(12))))

Pre-Selected Column Data Set

Description

r_data - Generate a data set with pre-set columns selected.

r_data_theme - Generate a themed data set with pre-set columns.

Usage

r_data(n = 500, ...)

r_data_theme(n = 100, data_theme = "the_works")

Arguments

Details

The pre-selected columns include:

• ID

• Race

• Age

• Sex

• Hour

• IQ

• Height

• Died

The user may use ... to add additional columns. r_data is a convenience function to quickly produce a data set. For more specific usage use the more flexible r_data_frame function.

Value

Returns a tbl_df.

See Also

r_data_frame

Examples

r_data()
r_data(10)
r_data(10, paragraph, Attending = valid)

peek(r_data_theme())
plot(r_data_theme(), flip=TRUE)

r_data_theme(, "survey")
r_data_theme(, "survey2")

Data Frame Production (From Variable Functions)

Description

Produce a tbl_df data frame that allows the user to lazily pass unnamed wakefield variable functions (optionally, without call parenthesis).

Usage

r_data_frame(n, ..., rep.sep = "_")

Arguments

Value

Returns a tbl_df.

Author(s)

Josh O'Brien and Tyler Rinker <tyler.rinker@gmail.com>.

References

https://stackoverflow.com/a/29617983/1000343

See Also

r_list, r_series r_dummy

Examples

r_data_frame(n = 30,
    id,
    race,
    age,
    sex,
    hour,
    iq,
    height,
    died,
    Scoring = rnorm,
    Smoker = valid
)

r_data_frame(n = 30,
    id,
    race,
    age(x = 8:14),
    Gender = sex,
    Time = hour,
    iq,
    grade, grade, grade,  #repeated measures
    height(mean=50, sd = 10),
    died,
    Scoring = rnorm,
    Smoker = valid
)

r_data_frame(n = 500,
    id,
    age, age, age,
    grade, grade, grade
)

## Repeated Measures/Time Series
r_data_frame(n=100,
    id,
    age,
    sex,
    r_series(likert, 3),
    r_series(likert, 4, name = "Item", integer = TRUE)
)

## Expanded Dummy Coded Variables
r_data_frame(n=100,
    id,
    age,
    r_dummy(sex, prefix=TRUE),
    r_dummy(political)
)

## `peek` to view al columns
## `plot` (`table_heat`) for a graphic representation
library(dplyr)
r_data_frame(n=100,
    id,
    dob,
    animal,
    grade, grade,
    death,
    dummy,
    grade_letter,
    gender,
    paragraph,
    sentence
) %>%
   r_na() %>%
   peek %>%
   plot(palette = "Set1")

Generate Random Dummy Values

Description

Generate random values from a wakefield variable function.

Usage

r_dummy(fun, n, ..., prefix = FALSE, rep.sep = "_")

Arguments

Value

Returns a tbl_df.

See Also

r_list, r_data_frame, r_series

Examples

r_dummy(sex, 10)
r_dummy(race, 1000)
r_dummy(race, 1000, name = "Ethnicity")

Insert Data Frames Into r_data_frame

Description

Safely insert data.frame objects into a r_data_frame or r_list.

Usage

r_insert(x, name = "Inserted")

Arguments

Value

Returns a data.frame with a attributes(x)[["seriesname"]] assigned.

See Also

seriesname

Examples

dat <- dplyr::data_frame(
    Age_1 = age(100), Age_2 = age(100), Age_3 = age(100),
    Smokes = smokes(n=100),
    Sick = ifelse(Smokes, sample(5:10, 100, TRUE), sample(0:4, 100, TRUE)),
    Death = ifelse(Smokes, sample(0:1, 100, TRUE, prob = c(.2, .8)),
        sample(0:1, 100, TRUE, prob = c(.7, .3)))
)

r_data_frame(100,
   id,
   r_insert(dat)
)

r_list(10,
   id,
   r_insert(dat)
)

List Production (From Variable Functions)

Description

Produce a named list that allows the user to lazily pass unnamed wakefield variable functions (optionally, without call parenthesis).

Usage

r_list(n, ..., rep.sep = "_")

Arguments

Value

Returns a named list of equal length vectors.

Author(s)

Josh O'Brien and Tyler Rinker <tyler.rinker@gmail.com>.

References

https://stackoverflow.com/a/29617983/1000343

See Also

r_data_frame, r_series r_dummy

Examples

r_list(
    n = 30,
    id,
    race,
    age,
    sex,
    hour,
    iq,
    height,
    died,
    Scoring = rnorm
)

r_list(
    n = 30,
    id,
    race,
    age(x = 8:14),
    Gender = sex,
    Time = hour,
    iq,
    height(mean=50, sd = 10),
    died,
    Scoring = rnorm
)

Replace a Proportion of Values With NA

Description

Replaces a proportion of values with NA. Useful for simulating missing data.

Usage

r_na(x, cols = -1, prob = 0.05)

Arguments

Value

Returns a data.frame or list with random missing values.

Examples

r_na(mtcars)
r_na(mtcars, NULL)


library(dplyr)

r_data_frame(
    n = 30,
    id,
    race,
    age,
    sex,
    hour,
    iq,
    height,
    died,
    Scoring = rnorm,
    Smoker = valid
) %>%
    r_na(prob=.4)

Generate Random Vector

Description

Generate a random vector.

Usage

r_sample(n, x = 1:100, prob = NULL, name = "Sample")

Arguments

Value

Returns a random vector of elements.

See Also

sample

Examples

r_sample(100, name = "Var")
table(r_sample(x = c("Dog", "Cat", "Fish", "Bird"), n=1000))
r_sample(x = c("B", "W"), prob = c(.7, .3), n = 25, name = "Race")
r_sample(25, x = c(TRUE, FALSE))

Generate Random Binary Vector

Description

r_sample_binary - Generate a random binary vector.

r_sample_binary_factor - Generate a random binary vector and coerces to a factor.

Usage

r_sample_binary(n, x = 1:2, prob = NULL, name = "Binary")

r_sample_binary_factor(n, x = 1:2, prob = NULL, name = "Binary")

Arguments

Value

Returns a random binary vector of elements.

See Also

sample.int

Examples

r_sample_binary(100, name = "Var")
table(r_sample_binary(1000))
c("B", "W")[r_sample_binary(10)]

Generate Random Factor Vector

Description

Generate a random vector and coerces to a factor.

Usage

r_sample_factor(n, x = LETTERS, prob = NULL, name = "Factor")

Arguments

Value

Returns a random actor vector of elements.

See Also

sample

Examples

r_sample_factor(100, name = "Var")
table(r_sample_factor(x = c("Dog", "Cat", "Fish", "Bird"), n=1000))
r_sample_factor(x = c("B", "W"), prob = c(.7, .3), n = 25)

Generate Random Integer Vector

Description

Generate a random integer vector.

Usage

r_sample_integer(n, x = 1:100, prob = NULL, name = "Integer")

Arguments

Value

Returns a random integer vector of elements.

See Also

sample

Examples

r_sample_integer(100, name = "Var")
table(r_sample_integer(x = c("Dog", "Cat", "Fish", "Bird"), n=1000))
r_sample_integer(x = c("B", "W"), prob = c(.7, .3), n = 25, name = "Race")
r_sample_integer(25, x = c(TRUE, FALSE))

Generate Random Logical Vector

Description

Generate a random logical (TRUE/FALSE) vector.

Usage

r_sample_logical(n, prob = NULL, name = "Logical")

Arguments

Value

Returns a random logical (TRUE/FALSE) vector of elements.

See Also

sample

Examples

r_sample_logical(100, name = "Var")
table(r_sample_logical(1000))
c("B", "W")[r_sample_logical(10)]

Generate Random Ordered Factor Vector

Description

Generate a random vector and coerces to an ordered factor.

Usage

r_sample_ordered(n, x = LETTERS[1:5], prob = NULL, name = "Ordered")

Arguments

Value

Returns a random factor vector of elements.

See Also

sample, ordered

Examples

r_sample_ordered(100, name = "Var")

lvls <- c("Strongly Agree", "Agree", "Neutral", "Disagree", "Strongly Disagree")
table(r_sample_ordered(x = lvls, n=1000))

(out <- r_sample_ordered(x = c("Black", "Grey", "White"),
    prob = c(.5, .2, .3), n = 100))
slices <- c(table(out))
pie(slices, main="Pie Chart of Colors", col = tolower(names(slices)))

Generate Random Vector (Without Replacement)

Description

Generate a random vector without replacement.

Usage

r_sample_replace(n, x = 1:100, prob = NULL, replace = FALSE, name = "Sample")

Arguments

Value

Returns a random vector of elements.

See Also

sample

Examples

r_sample(100, name = "Var")
table(r_sample(x = c("Dog", "Cat", "Fish", "Bird"), n=1000))
r_sample(x = c("B", "W"), prob = c(.7, .3), n = 25, name = "Race")
r_sample(25, x = c(TRUE, FALSE))

Data Frame Series (Repeated Measures)

Description

Produce a tbl_df data frame of repeated measures from a wakefield variable function.

Usage

r_series(fun, j, n, ..., integer = FALSE, relate = NULL, rep.sep = "_")

Arguments

Value

Returns a tbl_df.

References

https://github.com/trinker/wakefield/issues/1/#issuecomment-96166910

See Also

r_list, r_data_frame r_dummy

Examples

r_series(grade, 5, 10)

## Custom name prefix
r_series(likert, 5, 10, name = "Question")

## Convert factors to integers
r_series(likert_7, 5, 10, integer = TRUE)

## Related variables
r_series(likert, 10, 200, relate = list(operation = "*", mean = 2, sd = 1))
r_series(likert, 10, 200, relate = "--3_1")
r_series(age, 10, 200, relate = "+5_0")

## Change sd to reduce/increase correlation
round(cor(r_series(grade, 10, 10, relate = "+1_2")), 2)
round(cor(r_series(grade, 10, 10, relate = "+1_0")), 2)
round(cor(r_series(grade, 10, 10, relate = "+1_.5")), 2)
round(cor(r_series(grade, 10, 10, relate = "+1_20")), 2)

## Plot Example 1
library(dplyr); library(ggplot2)

dat <- r_data_frame(12,
    name,
    r_series(likert, 10, relate = "+1_.5")
)

# Suggested use of tidyr or reshape2 package here instead
dat <- data.frame(
    ID = rep(dat[[1]], ncol(dat[-1])),
    stack(dat[-1])
)

dat[["Time"]] <- factor(sub("Variable_", "", dat[["ind"]]), levels = 1:10)
ggplot(dat, aes(x = Time, y = values, color = ID, group = ID)) +
    geom_line(size=.8)

## Plot Example 2
dat <- r_data_frame(12,
    name,
    r_series(grade, 100, relate = "+1_2")
)

# Suggested use of tidyr or reshape2 package here instead
dat <- data.frame(
    ID = rep(dat[[1]], ncol(dat[-1])),
    ind = rep(colnames(dat[-1]), each = nrow(dat)),
    values = unlist(dat[-1])
)


dat[["Time"]] <- as.numeric(sub("Grade_", "", dat[["ind"]]))
ggplot(dat, aes(x = Time, y = values, color = ID, group = ID)) +
    geom_line(size=.8) + theme_bw()

Generate Random Vector of Races

Description

Generate a random vector of races.

Usage

race(
  n,
  x = c("White", "Hispanic", "Black", "Asian", "Bi-Racial", "Native", "Other",
    "Hawaiian"),
  prob = c(0.637, 0.163, 0.122, 0.047, 0.019, 0.007, 0.002, 0.0015),
  name = "Race"
)

Arguments

Details

The races and probabilities used match approximate U.S. racial make-up. The default make up is:

Value

Returns a random factor vector of elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), religion(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

race(10)
100*table(race(n <- 10000))/n

Create Related Numeric Columns

Description

Generate columns that are related.

Usage

relate(
  x,
  j,
  name = NULL,
  operation = "+",
  mean = 5,
  sd = 1,
  rep.sep = "_",
  digits = max(nchar(sub("^[^.]*.", "", x)))
)

Arguments

Value

Returns a tbl_df.

See Also

r_series

Examples

relate(1:10, 10)

(x <- r_data_frame(10, id, relate(1:10, 10, "Time", mean = 2)))
library(ggplot2)

dat <- with(x, data.frame(ID = rep(ID, ncol(x[, -1])), stack(x[, -1])))
dat[["Time"]] <- factor(sub("Time_", "", dat[["ind"]]), levels = 1:10)
ggplot(dat, aes(x = Time, y = values, color = ID, group = ID)) +
    geom_line(size=.8)

relate(1:10, 10, name = "X", operation = "-")
relate(1:10, 10, "X", mean = 1, sd = 0)
relate(1:10, 10, "Var", "*")
relate(1:10, 10, "Var", "/")

relate(gpa(30), 5, mean = .1)
relate(likert(10), 5, mean = .1, sd = .2)
relate(date_stamp(10), 6)
relate(time_stamp(10), 6)
relate(rep(100, 10), 6, "Reaction", "-")

Generate Random Vector of Religions

Description

Generate a random vector of religion.

Usage

religion(
  n,
  x = c("Christian", "Muslim", "None", "Hindu", "Buddhist", "Folk", "Other", "Jewish"),
  prob = c(0.31477, 0.23163, 0.16323, 0.14985, 0.07083, 0.05882, 0.00859, 0.00227),
  name = "Religion"
)

Arguments

Details

The religion and probabilities used match approximate world religion make-up (from Pew Research Center). The default make up is:

Value

Returns a random factor vector of religion elements.

References

https://www.pewforum.org/2012/12/18/table-religious-composition-by-country-in-numbers/

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), sat(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

religion(10)
barplot(table(religion(10000)))
pie(table(religion(10000)))

Generate Random Vector of Scholastic Aptitude Test (SATs)

Description

grade - Generate a random normal vector of scholastic aptitude test (SATs).

Usage

sat(n, mean = 1500, sd = 100, min = 0, max = 2400, digits = 0, name = "SAT")

Arguments

Value

Returns a random normal vector of SAT elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sentence(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

sat(10)
hist(sat(10000))
interval(sat, 5, n = 1000)

Generate a Random Sequence of Seconds in H:M:S Format

Description

Generate a random vector of seconds in H:M:S format.

Usage

second(
  n,
  x = seq(0, 59, by = 1)/3600,
  prob = NULL,
  random = FALSE,
  name = "Second"
)

Arguments

Value

Returns a random vector of second time elements in H:M:S format.

See Also

times

Examples

second(20)
second(20, random=TRUE)
pie(table(second(2000, x = seq(0, 59, by = 10)/3600, prob = probs(6))))

Generate Random Vector of Sentences

Description

Generate a random vector of sentences from the presidential_debates_2012.

Usage

sentence(
  n,
  x = wakefield::presidential_debates_2012,
  prob = NULL,
  name = "Sentence"
)

Arguments

Value

Returns a random character vector of sentence elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sex_inclusive(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

sentence(10)

Add Internal Name to Data Frame

Description

Adds attributes(x)[["seriesname"]] attribute to a data.frame.

Usage

seriesname(x, name)

Arguments

Value

Returns a data.frame with a attributes(x)[["seriesname"]] assigned.

Examples

seriesname(mtcars, "Cars")
attributes(seriesname(mtcars, "Cars"))

Generate Random Vector of Genders

Description

Generate a random vector of genders.

Usage

sex(
  n,
  x = c("Male", "Female"),
  prob = c(0.51219512195122, 0.48780487804878),
  name = "Sex"
)

gender(
  n,
  x = c("Male", "Female"),
  prob = c(0.51219512195122, 0.48780487804878),
  name = "Gender"
)

Arguments

Details

The genders and probabilities used match approximate gender make-up:

Value

Returns a random factor vector of gender elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

sex(10)
100*table(sex(n <- 10000))/n

Generate Random Vector of Non-Binary Genders

Description

Generate a random vector of non-binary genders. Proportion of trans* category was taken from the Williams Institute Report (2011), and subtracted equally from the male and female categories.

Usage

sex_inclusive(
  n,
  x = c("Male", "Female", "Intersex"),
  prob = NULL,
  name = "Sex"
)

gender_inclusive(
  n,
  x = c("Male", "Female", "Trans*"),
  prob = NULL,
  name = "Gender"
)

Arguments

Details

The genders and probabilities used match approximate gender make-up:

Value

Returns a random factor vector of sex or gender elements.

Author(s)

Matthew Sigal <msigal@yorku.ca>

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

sex_inclusive(10)
barplot(table(sex_inclusive(10000)))

gender_inclusive(10)
barplot(table(gender_inclusive(10000)))

Generate Random Logical Smokes Vector

Description

Generate a random logical (TRUE/FALSE) smokes vector.

Usage

smokes(n, prob = c(0.822, 0.178), name = "Smokes")

Arguments

Details

The probabilities are non-smoker: 82.2% vs. smoker: 17.8%.

Value

Returns a random logical vector of smokes elements.

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex_inclusive(), sex(), speed(), state(), string(), upper(), valid(), year(), zip_code()