Generate synthetic data for classification using sklearn

classification_synth_generator.py

from sklearn.datasets import make_classification
import pandas as pd

num_column = 100
num_rows = 10
X, Y = make_classification(n_features=num_column, n_redundant=0, n_informative=5, n_classes=3, n_clusters_per_class=1, n_samples=num_rows)

cols = []
for i in range(0, num_column):
    cols.append(f'{i}')
x = pd.DataFrame(X, columns=cols)
y = pd.DataFrame(Y, columns=['Class'])

x['Class'] = Y

print(x)