idmd.data.generator.DatasetGenerator

class idmd.data.generator.DatasetGenerator

Bases: object

Generates sample datasets with different distributions.

Methods

generate_normal_distribution	Generate a dataset with a normal distribution.
generate_random_integers	Generate a dataset with random integers.
generate_uniform_distribution	Generate a dataset with a uniform distribution.

static generate_normal_distribution(size, mean=0, std=1)

Generate a dataset with a normal distribution.

Return type:

DataFrame

Args:

size (int): Number of samples. mean (float): Mean of the distribution. Defaults to 0. std (float): Standard deviation of the distribution. Defaults to 1.

Returns:

pd.DataFrame: A DataFrame containing the generated data.

static generate_random_integers(size, low=0, high=100)

Generate a dataset with random integers.

Return type:

DataFrame

Args:

size (int): Number of samples. low (int): Lower bound of the integers. Defaults to 0. high (int): Upper bound of the integers. Defaults to 100.

Returns:

pd.DataFrame: A DataFrame containing the generated data.

static generate_uniform_distribution(size, low=0, high=1)

Generate a dataset with a uniform distribution.

Return type:

DataFrame

Args:

size (int): Number of samples. low (float): Lower bound of the distribution. Defaults to 0. high (float): Upper bound of the distribution. Defaults to 1.

Returns:

pd.DataFrame: A DataFrame containing the generated data.