🌟Machine Learning code recipe - 10: How to Create simulated data for clustering in Python?

We recently launched an end-to-end solved industry project with video explanation, solution code and dataset. The project is Predict Churn for a Telecom company using Logistic Regression. Its available here. 

## How to Create simulated data for clustering in Python
def Kickstarter_Example_24():
    print()
    print(format('How to Create simulated data for clustering in Python', '*^82'))

    # Load libraries
    from sklearn.datasets import make_blobs
    import matplotlib.pyplot as plt
    import pandas as pd

    # Make the features (X) and output (y) with 200 samples,
    features, clusters = make_blobs(n_samples = 2000,
                  n_features = 10, centers = 5,
                  # with .5 cluster standard deviation,
.
.