My helper module that allows you to create fake Pandas DataFrames.

For example, you can create a fake dataset with bank accounts data, marketing campaign data, customer and transaction data, etc.

Recommended library to generate fake data:

• Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you.

Install the dependencies from requirements.txt file.

$ pip install -r requirements.txt

1.List all currently available DataFrames.

from fakedatafactory import FakeDataFactory

fake_data_factory = FakeDataFactory()

fake_data_factory.list_available_dataframe_types()

Returns:

["bankaccount", "campaignevent", "customer", "cardtransactions"]

2.Create fake pandas DataFrame.

from fakedatafactory import FakeDataFactory

fake_data_factory = FakeDataFactory()

fake_data_factory.generate_fake_dataframe(
    dataframe_type="customer",
    num_of_rows=5
)

Returns:

You can easily create a new DataFrame type adding subclass of FakeRowBase to file fake_rows.py. Requirement:

• Your class name needs to end with FakeRow phrase. (example: FootballGameFakeRow)