Can you help me create a dataset. They represent identity documents. If the identity number has less than 8 figures, we will replicate the first ones until we obtain exactly 8. We must avoid the digits 0 and 1, if any of the figures is less than 2, we will replace it with 2.

Example 1: 12345679 -> 22345679

Example 2: 804156 -> 804145630 -> 82425632

using sklearn.datasets.make_regression from the scikit-learn library

Using the following arguments:

- n_sample = 200 + 10 first digit ID

- n_predictors = 10 + second digit ID + third digit ID

- n_informative = 10 + second digit ID

- bias = 2

- noise = 10 * fourth digit ID

- seed = ID_number

- shuffle = False

It will have at least 220 observations and 14 predictor variables, of which at least 2 will not be related to the response variable.

I found this example

# import library

from sklearn.datasets import make_regression

# create features and targets

features, target = make_regression(n_samples=100,

n_features=10,

n_informative=5,

n_targets=1,

random_state=42)

# print features and target

print("Features:")

print(features[:5])

print("Target:")

print(target[:5])