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‎Customer in Mall clusterng/customer_clustering.ipynb

Lines changed: 16 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -1573,17 +1573,17 @@
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"output_type": "stream",
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"text": [
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"Average age for customers in cluster one: 40.94444444444444\n",
1576-
"Average annual income (in thousends) for customers in cluster one: 104.88888888888889\n",
1577-
"Deviation of the mean for annual income (in thousends) for customers in cluster one: 16.927587243211693\n",
1576+
"Average annual income (in thousands) for customers in cluster one: 104.88888888888889\n",
1577+
"Deviation of the mean for annual income (in thousands) for customers in cluster one: 16.927587243211693\n",
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"In cluster one we have: 18 customers\n",
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"From those customers we have 9 male and 9 female\n"
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]
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}
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],
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"source": [
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"print(\"Average age for customers in cluster one: {}\".format(np.array(cluster_2['Age']).mean()))\n",
1585-
"print(\"Average annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_2['Annual Income (k$)']).mean()))\n",
1586-
"print(\"Deviation of the mean for annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_2['Annual Income (k$)']).std()))\n",
1585+
"print(\"Average annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_2['Annual Income (k$)']).mean()))\n",
1586+
"print(\"Deviation of the mean for annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_2['Annual Income (k$)']).std()))\n",
15871587
"print(\"In cluster one we have: {} customers\".format(cluster_2.shape[0]))\n",
15881588
"print(\"From those customers we have {} male and {} female\".format(cluster_2.loc[(cluster_2['Genre'] == 1.0)].shape[0], cluster_2.loc[(cluster_2['Genre'] == 0.0)].shape[0]))"
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]
@@ -2137,17 +2137,17 @@
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"output_type": "stream",
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"text": [
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"Average age for customers in cluster one: 48.53333333333333\n",
2140-
"Average annual income (in thousends) for customers in cluster one: 52.68888888888889\n",
2141-
"Deviation of the mean for annual income (in thousends) for customers in cluster one: 18.271194356414593\n",
2140+
"Average annual income (in thousands) for customers in cluster one: 52.68888888888889\n",
2141+
"Deviation of the mean for annual income (in thousands) for customers in cluster one: 18.271194356414593\n",
21422142
"In cluster one we have: 90 customers\n",
21432143
"From those customers we have 40 male and 50 female\n"
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]
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}
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],
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"source": [
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"print(\"Average age for customers in cluster one: {}\".format(np.array(cluster_3['Age']).mean()))\n",
2149-
"print(\"Average annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_3['Annual Income (k$)']).mean()))\n",
2150-
"print(\"Deviation of the mean for annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_3['Annual Income (k$)']).std()))\n",
2149+
"print(\"Average annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_3['Annual Income (k$)']).mean()))\n",
2150+
"print(\"Deviation of the mean for annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_3['Annual Income (k$)']).std()))\n",
21512151
"print(\"In cluster one we have: {} customers\".format(cluster_3.shape[0]))\n",
21522152
"print(\"From those customers we have {} male and {} female\".format(cluster_3.loc[(cluster_3['Genre'] == 1.0)].shape[0], cluster_3.loc[(cluster_3['Genre'] == 0.0)].shape[0]))"
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]
@@ -2442,17 +2442,17 @@
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"output_type": "stream",
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"text": [
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"Average age for customers in cluster one: 32.58620689655172\n",
2445-
"Average annual income (in thousends) for customers in cluster one: 86.75862068965517\n",
2446-
"Deviation of the mean for annual income (in thousends) for customers in cluster one: 12.62907202317211\n",
2445+
"Average annual income (in thousands) for customers in cluster one: 86.75862068965517\n",
2446+
"Deviation of the mean for annual income (in thousands) for customers in cluster one: 12.62907202317211\n",
24472447
"In cluster one we have: 29 customers\n",
24482448
"From those customers we have 12 male and 17 female\n"
24492449
]
24502450
}
24512451
],
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"source": [
24532453
"print(\"Average age for customers in cluster one: {}\".format(np.array(cluster_4['Age']).mean()))\n",
2454-
"print(\"Average annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_4['Annual Income (k$)']).mean()))\n",
2455-
"print(\"Deviation of the mean for annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_4['Annual Income (k$)']).std()))\n",
2454+
"print(\"Average annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_4['Annual Income (k$)']).mean()))\n",
2455+
"print(\"Deviation of the mean for annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_4['Annual Income (k$)']).std()))\n",
24562456
"print(\"In cluster one we have: {} customers\".format(cluster_4.shape[0]))\n",
24572457
"print(\"From those customers we have {} male and {} female\".format(cluster_4.loc[(cluster_4['Genre'] == 1.0)].shape[0], cluster_4.loc[(cluster_4['Genre'] == 0.0)].shape[0]))"
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]
@@ -2803,17 +2803,17 @@
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"output_type": "stream",
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"text": [
28052805
"Average age for customers in cluster one: 28.416666666666668\n",
2806-
"Average annual income (in thousends) for customers in cluster one: 62.416666666666664\n",
2807-
"Deviation of the mean for annual income (in thousends) for customers in cluster one: 9.67923034130297\n",
2806+
"Average annual income (in thousands) for customers in cluster one: 62.416666666666664\n",
2807+
"Deviation of the mean for annual income (in thousands) for customers in cluster one: 9.67923034130297\n",
28082808
"In cluster one we have: 36 customers\n",
28092809
"From those customers we have 16 male and 20 female\n"
28102810
]
28112811
}
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],
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"source": [
28142814
"print(\"Average age for customers in cluster one: {}\".format(np.array(cluster_5['Age']).mean()))\n",
2815-
"print(\"Average annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_5['Annual Income (k$)']).mean()))\n",
2816-
"print(\"Deviation of the mean for annual income (in thousends) for customers in cluster one: {}\".format(np.array(cluster_5['Annual Income (k$)']).std()))\n",
2815+
"print(\"Average annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_5['Annual Income (k$)']).mean()))\n",
2816+
"print(\"Deviation of the mean for annual income (in thousands) for customers in cluster one: {}\".format(np.array(cluster_5['Annual Income (k$)']).std()))\n",
28172817
"print(\"In cluster one we have: {} customers\".format(cluster_5.shape[0]))\n",
28182818
"print(\"From those customers we have {} male and {} female\".format(cluster_5.loc[(cluster_5['Genre'] == 1.0)].shape[0], cluster_5.loc[(cluster_5['Genre'] == 0.0)].shape[0]))"
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]

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