Recipe: How to Create simulated data for clustering in Python?
DATA MUNGING SIMULATED DATA

How to Create simulated data for clustering in Python?

This recipe helps you Create simulated data for clustering in Python
In [1]:
## 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,
                  cluster_std = 0.4,
                  shuffle = True)

    # View the first five observations and their 10 features
    print()
    print("Feature Matrix: ");
    print(pd.DataFrame(features, columns=['Feature 1', 'Feature 2', 'Feature 3',
         'Feature 4', 'Feature 5', 'Feature 6', 'Feature 7', 'Feature 8',
         'Feature 9', 'Feature 10']).head())

    # Create a scatterplot of the first and second features
    plt.scatter(features[:,0], features[:,1])

    # Show the scatterplot
    plt.show()

Kickstarter_Example_24()
**************How to Create simulated data for clustering in Python***************

Feature Matrix:
   Feature 1  Feature 2  Feature 3  Feature 4  Feature 5  Feature 6  \
0  -5.301777  -0.288487   4.426895  -7.346082   0.841896   7.120860
1  -2.146525   5.418930  -8.526391  -3.028764  -4.153195   9.803507
2   1.560945   6.419495  -1.759591  -9.156973   8.489981   4.229867
3   6.243948  -6.006760  -9.065597   3.672920  -1.327192   5.638014
4   5.883899   7.947210  -6.298867  -6.715524   0.361343  -5.462168

   Feature 7  Feature 8  Feature 9  Feature 10
0   5.853593  -4.528930   5.301169    4.174106
1   3.005134  -7.790637   6.252099    5.263176
2  -5.721829   5.110951  -0.667662   -2.777335
3  -9.557726  -5.902056   6.441669    2.168129
4  -2.620218  -6.522848   6.959409    5.542048
<Figure size 640x480 with 1 Axes>


Stuck at work?
Can't find the recipe you are looking for. Let us know and we will find an expert to create the recipe for you. Click here
Companies using this Recipe
1 developer from Embicon
1 developer from MudraCircle
1 developer from YASH Technologies
1 developer from Altimetrik
1 developer from HvH
1 developer from Novabase
1 developer from ANAC
1 developer from KPMG
1 developer from Thomson Reuters
1 developer from Ekimetrics