display_clustering.py

import matplotlib.pyplot as plt
import seaborn as sns

from mpl_toolkits.mplot3d import Axes3D

def plot2D(x, y, labels, x_label, y_label):
  fig = plt.figure(figsize=(20,7))
  ax = fig.add_subplot()
  scatter = ax.scatter(x, y, c = labels, cmap="Dark2", linewidths = 0.1);
  ax.legend(*scatter.legend_elements())
  plt.xlabel(x_label)
  plt.ylabel(y_label)
  plt.show()

from sklearn.cluster import KMeans

def kmeans(df, n_clusters):
    kmeans = KMeans(n_clusters = n_clusters)
    kmeans.fit(df)

    return model, kmeans.labels_

model, labels = kmeans(x, 2)

plot2D(x['relaxation'], x['systolic'], labels, 'relaxation', 'systolic') #
plot2D(x['relaxation'], x['fasting blood sugar'], labels, 'relaxation', 'fasting blood sugar')

plot2D(x['systolic'], x['age'], labels, 'systolic', 'age') #
plot2D(x['relaxation'], x['age'], labels, 'relaxation', 'age') #

plot2D(x['LDL'], x['HDL'], labels, 'LDL', 'HDL')

plot2D(x['fasting blood sugar'], x['hemoglobin'], labels, 'fasting blood suga', 'hemoglobin')