Visualize clusters

Cluster Analysis in Python

Shaumik Daityari

Business Analyst

Why visualize clusters?

Try to make sense of the clusters formed
An additional step in validation of clusters
Spot trends in data

An introduction to seaborn

seaborn: a Python data visualization library based on matplotlib
Has better, easily modifiable aesthetics than matplotlib!
Contains functions that make data visualization tasks easy in the context of data analytics
Use case for clustering: hue parameter for plots

Visualize clusters with matplotlib

from matplotlib import pyplot as plt

df = pd.DataFrame({'x': [2, 3, 5, 6, 2],
                   'y': [1, 1, 5, 5, 2],
                   'labels': ['A', 'A', 'B', 'B', 'A']})

colors = {'A':'red', 'B':'blue'}

df.plot.scatter(x='x', 
                y='y',
                c=df['labels'].apply(lambda x: colors[x]))
plt.show()

Visualize clusters with seaborn

from matplotlib import pyplot as plt
import seaborn as sns

df = pd.DataFrame({'x': [2, 3, 5, 6, 2],
                   'y': [1, 1, 5, 5, 2],
                   'labels': ['A', 'A', 'B', 'B', 'A']})

sns.scatterplot(x='x', 
                y='y', 
                hue='labels', 
                data=df)
plt.show()

Comparison of both methods of visualization

matplotlib plot

seaborn plot

Next up: Try some visualizations

Cluster Analysis in Python

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