mlessentials/Lab05/Exercise5.03/Exercise5_3.ipynb

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   "source": [
    "import pandas as pd\n",
    "from sklearn.cluster import KMeans\n",
    "import altair as alt"
   ]
  },
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   "source": [
    "file_url = '../DataSet/taxstats2015.csv'"
   ]
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   "source": [
    "df = pd.read_csv(file_url, usecols=['Postcode', 'Average total business income', 'Average total business expenses'])"
   ]
  },
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   "source": [
    "df.head()"
   ]
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    "X = df[['Average total business income', 'Average total business expenses']]"
   ]
  },
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   "source": [
    "clusters = pd.DataFrame()\n",
    "inertia = []"
   ]
  },
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    "clusters['cluster_range'] = range(1, 15)"
   ]
  },
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    "for k in clusters['cluster_range']:\n",
    "    kmeans = KMeans(n_clusters=k).fit(X)\n",
    "    inertia.append(kmeans.inertia_)"
   ]
  },
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   "source": [
    "clusters['inertia'] = inertia\n",
    "clusters"
   ]
  },
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   "outputs": [],
   "source": [
    "alt.Chart(clusters).mark_line().encode(alt.X('cluster_range'), alt.Y('inertia'))"
   ]
  },
  {
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   "source": [
    "optim_cluster = 4"
   ]
  },
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   "source": [
    "kmeans = KMeans(random_state=42, n_clusters=optim_cluster)\n",
    "kmeans.fit(X)"
   ]
  },
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   "cell_type": "code",
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   "source": [
    "df['cluster2'] = kmeans.predict(X)"
   ]
  },
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    "df.head()"
   ]
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   "cell_type": "code",
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   "source": [
    "alt.Chart(df).mark_circle().encode(x='Average total business income', y='Average total business expenses',color='cluster2:N', tooltip=['Postcode', 'cluster2', 'Average total business income', 'Average total business expenses']).interactive()"
   ]
  },
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