Merge branch 'master' of https://github.com/PerryXDeng/wheatyeeters

data_exploration/wellness_cluster_test.py

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+import sklearn.cluster as cluster
+import pandas as pd
+from matplotlib import pyplot as plt
+
+
+def find_kmeans(mat, k, first, second):
+    km = cluster.KMeans(n_clusters=k)
+    km.fit(mat)
+
+    # Plot sse against k
+    plt.figure(figsize=(6, 6))
+    plt.xlabel('Metric: ' + first)
+    plt.ylabel('Metric: ' + second)
+    plt.scatter(mat[:, 0], mat[:, 1], c=km.labels_, cmap='rainbow')
+    plt.show()
+
+
+# Read csv in
+df = pd.read_csv('../data_preparation/cleaned/time_series_normalized_wellness_menstruation.csv')
+
+# Specify what things you want
+df = df[["normFatigue", "normSleepQuality"]]
+
+# values, num clusters, axis labelsg
+find_kmeans(df.values, 2, "normFatigue", "normSleepQuality")