create_fake_data: Create fake data

Description

Fake data that can be used for unit-testing or demonstration

Usage

create_fake_data(
  obs = 1000,
  target_name = "target_ind",
  factorise_target = FALSE,
  target1_prob = 0.5,
  add_extreme = TRUE,
  flip_gender = FALSE,
  add_id = FALSE,
  seed = 123
)

Value

A dataframe

Arguments

obs: Number of observations
target_name: Variable name of target
factorise_target: Should target variable be factorised? (from 0/1 to facotr no/yes)?
target1_prob: Probability that buy = 1
add_extreme: Add an obervation with extreme values?
flip_gender: Should Male/Female be flipped in data?
add_id: Add an id-variable to data?
seed: Seed for randomization

Details

Variables in dataset:

id = Identifier
period = Year & Month (YYYYMM)
city_ind = Indicating if customer is residing in a city (1 = yes, 0 = no)
female_ind = Gender of customer is female (1 = yes, 0 = no)
fixedvoice_ind = Customer has a fixed voice product (1 = yes, 0 = no)
fixeddata_ind = Customer has a fixed data product (1 = yes, 0 = no)
fixedtv_ind = Customer has a fixed tv product (1 = yes, 0 = no)
mobilevoice_ind = Customer has a mobile voice product (1 = yes, 0 = no)
mobiledata_ind = Customer has a mobile data product (1 = yes, 0 = no)
bbi_speed_ind = Customer has a Broadband Internet (BBI) with speed
bbi_usg_gb = Broadband Internet (BBI) usage in Gigabyte (GB) last month
hh_single = Expected to be a Single Household (1 = yes, 0 = no)

Target in dataset:

target_ind (may be renamed) = Did customer buy a new product in next month? (1 = yes, 0 = no)