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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
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"source": [
"<a href=\"https://cognitiveclass.ai\"><img src = \"https://ibm.box.com/shared/static/9gegpsmnsoo25ikkbl4qzlvlyjbgxs5x.png\" width = 400> </a>\n",
"\n",
"<h1 align=center><font size = 5><em>k</em>-means Clustering</font></h1>"
]
},
{
"cell_type": "markdown",
"metadata": {
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"source": [
"## Introduction\n",
"\n",
"There are many models for clustering out there. In this lab, we will be presenting the model that is considered the one of the simplest model among them. Despite its simplicity, *k*-means is vastly used for clustering in many data science applications, especially useful if you need to quickly discover insights from unlabeled data.\n",
"\n",
"Some real-world applications of *k*-means include:\n",
"- customer segmentation,\n",
"- understand what the visitors of a website are trying to accomplish,\n",
"- pattern recognition, and,\n",
"- data compression.\n",
"\n",
"In this lab, we will learn *k*-means clustering with 3 examples:\n",
"- *k*-means on a randomly generated dataset.\n",
"- Using *k*-means for customer segmentation."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"## Table of Contents\n",
"\n",
"1. <a href=\"#item1\"><em>k</em>-means on a Randomly Generated Dataset</a> \n",
"2. <a href=\"#item2\">Using <em>k</em> for Customer Segmentation</a> \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
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},
"source": [
"Before we start with the main lab content, let's download all the dependencies that we will need."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Libraries imported.\n"
]
}
],
"source": [
"import random # library for random number generation\n",
"import numpy as np # library for vectorized computation\n",
"import pandas as pd # library to process data as dataframes\n",
"\n",
"import matplotlib.pyplot as plt # plotting library\n",
"# backend for rendering plots within the browser\n",
"%matplotlib inline \n",
"\n",
"from sklearn.cluster import KMeans \n",
"from sklearn.datasets.samples_generator import make_blobs\n",
"\n",
"print('Libraries imported.')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<a id='item1'></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"## 1. *k*-means on a Randomly Generated Dataset"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Let's first demonstrate how *k*-means works with an example of engineered datapoints. "
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### 30 data points belonging to 2 different clusters (x1 is the first feature and x2 is the second feature)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Datapoints defined!\n",
"type of x1: <class 'list'>\n",
"len(x1): 30\n"
]
}
],
"source": [
"# data\n",
"x1 = [-4.9, -3.5, 0, -4.5, -3, -1, -1.2, -4.5, -1.5, -4.5, -1, -2, -2.5, -2, -1.5, 4, 1.8, 2, 2.5, 3, 4, 2.25, 1, 0, 1, 2.5, 5, 2.8, 2, 2]\n",
"x2 = [-3.5, -4, -3.5, -3, -2.9, -3, -2.6, -2.1, 0, -0.5, -0.8, -0.8, -1.5, -1.75, -1.75, 0, 0.8, 0.9, 1, 1, 1, 1.75, 2, 2.5, 2.5, 2.5, 2.5, 3, 6, 6.5]\n",
"\n",
"print('Datapoints defined!')\n",
"print(\"type of x1:\",type(x1))\n",
"print(\"len(x1):\",len(x1))"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Define a function that assigns each datapoint to a cluster"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"assign_members function defined!\n"
]
}
],
"source": [
"colors_map = np.array(['b', 'r'])\n",
"def assign_members(x1, x2, centers):\n",
" compare_to_first_center = np.sqrt(np.square(np.array(x1) - centers[0][0]) + np.square(np.array(x2) - centers[0][1]))\n",
" print(\"\\ntype(compare_to_first_center):\",type(compare_to_first_center))\n",
" compare_to_second_center = np.sqrt(np.square(np.array(x1) - centers[1][0]) + np.square(np.array(x2) - centers[1][1]))\n",
" print(\"\\ntype(compare_to_second_center):\",type(compare_to_second_center))\n",
" class_of_points = compare_to_first_center > compare_to_second_center\n",
" colors = colors_map[class_of_points + 1 - 1]\n",
" return colors, class_of_points\n",
"\n",
"print('assign_members function defined!')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"A) first less than second:\n",
"A: compare_to_first_centerQQQ = 10\n",
"A: compare_to_second_centerQQQ = 12\n",
"A: class_of_pointsQQQ: False\n",
"A: class_of_pointsQQQ +1 -1: 0\n",
"A: colors_mapQQQ[class_of_pointsQQQ]: []\n",
"A: colors_mapQQQ[class_of_pointsQQQ +1 -1]: b\n",
"\n",
"B) first greater than second:\n",
"B: compare_to_first_centerQQQ = 15\n",
"B: compare_to_second_centerQQQ = 12\n",
"B: class_of_pointsQQQ: True\n",
"B: class_of_pointsQQQ +1 -1: 1\n",
"B: colors_mapQQQ[class_of_pointsQQQ]: [['b' 'r']]\n",
"B: colors_mapQQQ[class_of_pointsQQQ +1 -1]: r\n"
]
}
],
"source": [
"# Trying to fully understand the logic behind why the following works (from cell above):\n",
"# class_of_points = compare_to_first_center > compare_to_second_center\n",
"# colors = colors_map[class_of_points + 1 - 1]\n",
"# Conclusion: the boolean value gets converted/typecast/treated as a numeric 0 or 1 \n",
"# when a numeric operation is included in the evaluation\n",
"# (works because in Python, bool is a subtype of int)\n",
"\n",
"colors_mapQQQ = np.array(['b', 'r'])\n",
"\n",
"print(\"\\nA) first less than second:\")\n",
"print(\"A: compare_to_first_centerQQQ = 10\")\n",
"print(\"A: compare_to_second_centerQQQ = 12\")\n",
"compare_to_first_centerQQQ = 10\n",
"compare_to_second_centerQQQ = 12\n",
"class_of_pointsQQQ = compare_to_first_centerQQQ > compare_to_second_centerQQQ\n",
"print(\"A: class_of_pointsQQQ:\", class_of_pointsQQQ)\n",
"print(\"A: class_of_pointsQQQ +1 -1:\", class_of_pointsQQQ +1 -1)\n",
"print(\"A: colors_mapQQQ[class_of_pointsQQQ]:\",colors_mapQQQ[class_of_pointsQQQ])\n",
"print(\"A: colors_mapQQQ[class_of_pointsQQQ +1 -1]:\",colors_mapQQQ[class_of_pointsQQQ +1 -1])\n",
"\n",
"print(\"\\nB) first greater than second:\")\n",
"print(\"B: compare_to_first_centerQQQ = 15\")\n",
"print(\"B: compare_to_second_centerQQQ = 12\")\n",
"compare_to_first_centerQQQ = 15\n",
"compare_to_second_centerQQQ = 12\n",
"class_of_pointsQQQ = compare_to_first_centerQQQ > compare_to_second_centerQQQ\n",
"print(\"B: class_of_pointsQQQ:\", class_of_pointsQQQ)\n",
"print(\"B: class_of_pointsQQQ +1 -1:\", class_of_pointsQQQ +1 -1)\n",
"print(\"B: colors_mapQQQ[class_of_pointsQQQ]:\",colors_mapQQQ[class_of_pointsQQQ])\n",
"print(\"B: colors_mapQQQ[class_of_pointsQQQ +1 -1]:\",colors_mapQQQ[class_of_pointsQQQ +1 -1])"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Define a function that updates the centroid of each cluster"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"assign_members function defined!\n"
]
}
],
"source": [
"# update means:\n",
"\"\"\"\n",
"QUESTION: why is bitwise complement operator used in this case? (~class_of_points)\n",
"and why used for \"center1\" and not for \"center2\" ?\n",
"\n",
"The bitwise operator would do the following for a given integer i:\n",
"i ~i \n",
"0 -1\n",
"1 -2\n",
"2 -3\n",
"3 -4 \n",
"4 -5 \n",
"5 -6\n",
"\n",
"For a given single-dimensional array A[p], A[~p] would be the negative index ( -p -1), so A[-p-1],\n",
"hence if A is of length 5:\n",
"The first element of the array A[0] would become A[-0 -1] = A[-1] ( = A[4], the last element of the array),\n",
"the 2nd element of the array A[1] would become A[-1 -1] = A[-2] ( = A[3], the 2nd from last element in array)\n",
"the 3rd element of the array A[2] would become A[-2 -1] = A[-3] ( = A[2], the 3rd from last element in array)\n",
"the 4th element of the array A[3] would become A[-3 -1] = A[-4] ( = A[1], the 4th from last element in array)\n",
"the 5th element of the array A[4] would become A[-4 -1] = A[-5] ( = A[0], the 5th from last element in array)\n",
"\n",
"class_of_points is a bool type, so either True(1) or False(0), hence:\n",
"class_of_points = True\n",
"print(\"\\nclass_of_points:\", class_of_points)\n",
"print(\"~class_of_points:\", ~class_of_points)\n",
"class_of_points: True\n",
"~class_of_points: -2\n",
"\n",
"class_of_points = False\n",
"print(\"\\nclass_of_points:\", class_of_points)\n",
"print(\"~class_of_points:\", ~class_of_points)\n",
"class_of_points: False\n",
"~class_of_points: -1\n",
"\n",
"Still not sure why we had to ~ on a boolean...\n",
"... to get either -2 if previously True, or -1 if previously False, \n",
"and then np.array(x1)[-2] or np.array(x1)[-1] return just one single value, so why take the np.mean() of it?)\n",
" \n",
"\n",
"class_of_points = True\n",
"print(\"\\nclass_of_points:\", class_of_points)\n",
"print(\"~class_of_points:\", ~class_of_points)\n",
"\n",
"#class_of_points = False\n",
"#print(\"\\nclass_of_points:\", class_of_points)\n",
"#print(\"~class_of_points:\", ~class_of_points)\n",
"\n",
"print(\"\\nA: np.array(x1):\",np.array(x1))\n",
"\n",
"print(\"\\nB: np.array(x1)[~class_of_points]:\",np.array(x1)[~class_of_points])\n",
"print(\"np.mean(np.array(x1)[~class_of_points]):\",np.mean(np.array(x1)[~class_of_points]))\n",
"\n",
"print(\"\\nC: np.array(x1)[class_of_points]:\",np.array(x1)[class_of_points])\n",
"print(\"np.mean(np.array(x1)[class_of_points]):\",np.mean(np.array(x1)[class_of_points]))\n",
"\n",
"*** !!!ANSWER!!! ***\n",
"the class_of_points is a 30-element \"True/False\" boolean array that tells us if the point has been assigned\n",
"the red \"center2\".\n",
"\n",
"The value \"True\" if the point was further away from Center1/closed to Center2\n",
"(the Euclidian distance from the point to Center1 was greater \n",
"than the Euclidian distance from the point to Center2).\n",
"This was performed when function \"assign_members(x1, x2, centers)\"\" is executed.\n",
"\n",
"If the value is \"True\", the point has been assigned (at least as of the last iteration)\n",
"to the red \"Center2\" (whose coordinates are the coordinate pair at center[1], \n",
"aka center2x at center[1][0], center2y at center[1],[1]).\n",
"If the value is \"False\", then the point has been assigned to the blue \"center1\" (coordinates center[0]).\n",
"\"\"\"\n",
"\n",
"def update_centers(x1, x2, class_of_points):\n",
" print(\"\\ntype(class_of_points):\", type(class_of_points))\n",
" print(\"class_of_points:\", class_of_points)\n",
" print(\"\\ntype(~class_of_points):\", type(~class_of_points))\n",
" print(\"~class_of_points:\", ~class_of_points)\n",
"# If class_of_points = \"True\" (aka the point is closer to Center2 and belongs to Center2), \n",
"# then ~class_of_points = \"False\" (meaning the point does NOT belong to Center1);\n",
"# this signifies that the x1,x2 coordinates will be used to recompute a better Center2 pair of coordinates,\n",
"# and WILL NOT BE USED to recompute a better Center1 pair of coordinates.\n",
"#\n",
"# If however class_of_points = \"False\", then the reverse is correct, meaning the point is closer to Center1\n",
"# and belongs to Center1 (and NOT Center2), and will be used to recomputer a better Center1 coordinate pair,\n",
"# (and NOT recomputer a better Center2 coordinate pair).\n",
" center1 = [np.mean(np.array(x1)[~class_of_points]), np.mean(np.array(x2)[~class_of_points])]\n",
" center2 = [np.mean(np.array(x1)[class_of_points]), np.mean(np.array(x2)[class_of_points])]\n",
" print(\"\\ncenter1:\",center1)\n",
" print(\"np.array(x1)[~class_of_points]:\",np.array(x1)[~class_of_points])\n",
" print(\"\\ncenter2:\",center2)\n",
" print(\"np.array(x1)[class_of_points]:\",np.array(x1)[class_of_points])\n",
" return [center1, center2]\n",
"\n",
"print('\\nassign_members function defined!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Define a function that plots the data points along with the cluster centroids"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"plot_points function defined!\n"
]
}
],
"source": [
"def plot_points(centroids=None, colors='g', figure_title=None):\n",
" # plot the figure\n",
" fig = plt.figure(figsize=(15, 10)) # create a figure object\n",
" ax = fig.add_subplot(1, 1, 1)\n",
" \n",
" centroid_colors = ['bx', 'rx']\n",
" if centroids:\n",
" for (i, centroid) in enumerate(centroids):\n",
" ax.plot(centroid[0], centroid[1], centroid_colors[i], markeredgewidth=5, markersize=20)\n",
" plt.scatter(x1, x2, s=500, c=colors)\n",
" \n",
" # define the ticks\n",
" xticks = np.linspace(-6, 8, 15, endpoint=True)\n",
" yticks = np.linspace(-6, 6, 13, endpoint=True)\n",
"\n",
" # fix the horizontal axis\n",
" ax.set_xticks(xticks)\n",
" ax.set_yticks(yticks)\n",
"\n",
" # add tick labels\n",
" xlabels = xticks\n",
" ax.set_xticklabels(xlabels)\n",
" ylabels = yticks\n",
" ax.set_yticklabels(ylabels)\n",
"\n",
" # style the ticks\n",
" ax.xaxis.set_ticks_position('bottom')\n",
" ax.yaxis.set_ticks_position('left')\n",
" ax.tick_params('both', length=2, width=1, which='major', labelsize=15)\n",
" \n",
" # add labels to axes\n",
" ax.set_xlabel('x1', fontsize=20)\n",
" ax.set_ylabel('x2', fontsize=20)\n",
" \n",
" # add title to figure\n",
" ax.set_title(figure_title, fontsize=24)\n",
"\n",
" plt.show()\n",
"\n",
"print('plot_points function defined!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Initialize *k*-means - plot data points"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot_points(figure_title='Scatter Plot of x2 vs x1')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Initialize *k*-means - randomly define clusters and add them to plot"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"centers = [[-2, 2], [2, -2]]\n",
"plot_points(centers, figure_title='k-means Initialization')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Run *k*-means (4-iterations only)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
},
"scrolled": false
},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 1 - Press Enter to update the members of each cluster \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(compare_to_first_center): <class 'numpy.ndarray'>\n",
"\n",
"type(compare_to_second_center): <class 'numpy.ndarray'>\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 1 - Press Enter to update the centers \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(class_of_points): <class 'numpy.ndarray'>\n",
"class_of_points: [False True True False False True True False False False False False\n",
" False False True True True True True True True True False False\n",
" False False True False False False]\n",
"\n",
"type(~class_of_points): <class 'numpy.ndarray'>\n",
"~class_of_points: [ True False False True True False False True True True True True\n",
" True True False False False False False False False False True True\n",
" True True False True True True]\n",
"\n",
"center1: [-1.1235294117647057, 0.47941176470588237]\n",
"np.array(x1)[~class_of_points]: [-4.9 -4.5 -3. -4.5 -1.5 -4.5 -1. -2. -2.5 -2. 1. 0. 1. 2.5\n",
" 2.8 2. 2. ]\n",
"\n",
"center2: [1.3346153846153848, -0.45384615384615373]\n",
"np.array(x1)[class_of_points]: [-3.5 0. -1. -1.2 -1.5 4. 1.8 2. 2.5 3. 4. 2.25\n",
" 5. ]\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 2 - Press Enter to update the members of each cluster \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(compare_to_first_center): <class 'numpy.ndarray'>\n",
"\n",
"type(compare_to_second_center): <class 'numpy.ndarray'>\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 2 - Press Enter to update the centers \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(class_of_points): <class 'numpy.ndarray'>\n",
"class_of_points: [False False True False False True False False False False False False\n",
" False False False True True True True True True True True False\n",
" False True True True False False]\n",
"\n",
"type(~class_of_points): <class 'numpy.ndarray'>\n",
"~class_of_points: [ True True False True True False True True True True True True\n",
" True True True False False False False False False False False True\n",
" True False False False True True]\n",
"\n",
"center1: [-1.8588235294117643, -0.4529411764705882]\n",
"np.array(x1)[~class_of_points]: [-4.9 -3.5 -4.5 -3. -1.2 -4.5 -1.5 -4.5 -1. -2. -2.5 -2. -1.5 0.\n",
" 1. 2. 2. ]\n",
"\n",
"center2: [2.2961538461538464, 0.7653846153846153]\n",
"np.array(x1)[class_of_points]: [ 0. -1. 4. 1.8 2. 2.5 3. 4. 2.25 1. 2.5 5.\n",
" 2.8 ]\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 3 - Press Enter to update the members of each cluster \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(compare_to_first_center): <class 'numpy.ndarray'>\n",
"\n",
"type(compare_to_second_center): <class 'numpy.ndarray'>\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 3 - Press Enter to update the centers \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(class_of_points): <class 'numpy.ndarray'>\n",
"class_of_points: [False False False False False False False False False False False False\n",
" False False False True True True True True True True True True\n",
" True True True True True True]\n",
"\n",
"type(~class_of_points): <class 'numpy.ndarray'>\n",
"~class_of_points: [ True True True True True True True True True True True True\n",
" True True True False False False False False False False False False\n",
" False False False False False False]\n",
"\n",
"center1: [-2.506666666666667, -2.1133333333333337]\n",
"np.array(x1)[~class_of_points]: [-4.9 -3.5 0. -4.5 -3. -1. -1.2 -4.5 -1.5 -4.5 -1. -2. -2.5 -2.\n",
" -1.5]\n",
"\n",
"center2: [2.39, 2.2633333333333336]\n",
"np.array(x1)[class_of_points]: [4. 1.8 2. 2.5 3. 4. 2.25 1. 0. 1. 2.5 5. 2.8 2.\n",
" 2. ]\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 4 - Press Enter to update the members of each cluster \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(compare_to_first_center): <class 'numpy.ndarray'>\n",
"\n",
"type(compare_to_second_center): <class 'numpy.ndarray'>\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Iteration 4 - Press Enter to update the centers \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"type(class_of_points): <class 'numpy.ndarray'>\n",
"class_of_points: [False False False False False False False False False False False False\n",
" False False False True True True True True True True True True\n",
" True True True True True True]\n",
"\n",
"type(~class_of_points): <class 'numpy.ndarray'>\n",
"~class_of_points: [ True True True True True True True True True True True True\n",
" True True True False False False False False False False False False\n",
" False False False False False False]\n",
"\n",
"center1: [-2.506666666666667, -2.1133333333333337]\n",
"np.array(x1)[~class_of_points]: [-4.9 -3.5 0. -4.5 -3. -1. -1.2 -4.5 -1.5 -4.5 -1. -2. -2.5 -2.\n",
" -1.5]\n",
"\n",
"center2: [2.39, 2.2633333333333336]\n",
"np.array(x1)[class_of_points]: [4. 1.8 2. 2.5 3. 4. 2.25 1. 0. 1. 2.5 5. 2.8 2.\n",
" 2. ]\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"number_of_iterations = 4\n",
"for i in range(number_of_iterations):\n",
" input('Iteration {} - Press Enter to update the members of each cluster'.format(i + 1))\n",
" colors, class_of_points = assign_members(x1, x2, centers)\n",
" title = 'Iteration {} - Cluster Assignment'.format(i + 1)\n",
" plot_points(centers, colors, figure_title=title)\n",
" input('Iteration {} - Press Enter to update the centers'.format(i + 1))\n",
" centers = update_centers(x1, x2, class_of_points)\n",
" title = 'Iteration {} - Centroid Update'.format(i + 1)\n",
" plot_points(centers, colors, figure_title=title)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"centers[0][0]: -2.506666666666667\n",
"centers[0][1]: -2.1133333333333337\n",
"type(compare_to_first_center): <class 'numpy.ndarray'>\n",
"compare_to_first_center: [2.76602402 2.13218719 2.86465045 2.18164057 0.92855922 1.74820543\n",
" 1.39435369 1.99337793 2.34084505 2.5644146 1.99872181 1.40767736\n",
" 0.61336956 0.62347592 1.07022843 6.84126369 5.19950852 5.42127496\n",
" 5.8957235 6.32583767 7.21315157 6.12790521 5.40520325 5.25035449\n",
" 5.79478693 6.80805079 8.81095278 7.36932079 9.2809602 9.72108819]\n",
"\n",
"centers[1][0]: 2.39\n",
"centers[1][1]: 2.2633333333333336\n",
"type(compare_to_second_center): <class 'numpy.ndarray'>\n",
"compare_to_second_center: [9.2930141 8.59775811 6.23923963 8.67033897 7.4640546 6.26057328\n",
" 6.04484169 8.15541402 4.50053083 7.42348376 4.56903831 5.3531403\n",
" 6.1704763 5.94802021 5.58918102 2.77754888 1.57779734 1.41801896\n",
" 1.26811321 1.40289383 2.04648751 0.53208187 1.41472416 2.40168922\n",
" 1.41000394 0.26098106 2.62070813 0.84307638 3.7569639 4.25457923]\n",
"\n",
"type(class_of_points): <class 'numpy.ndarray'>\n",
"class_of_points: [False False False False False False False False False False False False\n",
" False False False True True True True True True True True True\n",
" True True True True True True]\n",
"\n",
"type(colors): <class 'numpy.ndarray'>\n",
"colors: ['b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'r' 'r' 'r'\n",
" 'r' 'r' 'r' 'r' 'r' 'r' 'r' 'r' 'r' 'r' 'r' 'r']\n"
]
}
],
"source": [
"print(\"\\ncenters[0][0]:\",centers[0][0])\n",
"print(\"centers[0][1]:\",centers[0][1])\n",
"compare_to_first_center = np.sqrt(np.square(np.array(x1) - centers[0][0]) + np.square(np.array(x2) - centers[0][1]))\n",
"print(\"type(compare_to_first_center):\",type(compare_to_first_center))\n",
"print(\"compare_to_first_center:\",compare_to_first_center)\n",
"\n",
"print(\"\\ncenters[1][0]:\",centers[1][0])\n",
"print(\"centers[1][1]:\",centers[1][1])\n",
"compare_to_second_center = np.sqrt(np.square(np.array(x1) - centers[1][0]) + np.square(np.array(x2) - centers[1][1]))\n",
"print(\"type(compare_to_second_center):\",type(compare_to_second_center))\n",
"print(\"compare_to_second_center:\",compare_to_second_center)\n",
"\n",
"class_of_points = compare_to_first_center > compare_to_second_center\n",
"print(\"\\ntype(class_of_points):\",type(class_of_points))\n",
"print(\"class_of_points:\",class_of_points)\n",
"\n",
"colors = colors_map[class_of_points + 1 - 1]\n",
"print(\"\\ntype(colors):\",type(colors))\n",
"print(\"colors:\",colors)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now, we have visually observed how <em>k</em>-means works, let's look at an example with many more datapoints. For this example, we will use the <strong>random</strong> library to generate thousands of datapoints."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Generating the Data"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"First, we need to set up a random seed. We use the Numpy's **random.seed()** function, and we will set the seed to 0. In other words, **random.seed(0)**."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"button": false,
"collapsed": true,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [],
"source": [
"np.random.seed(0)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Next we will be making *random clusters* of points by using the **make_blobs** class. The **make_blobs** class can take in many inputs, but we will use these specific ones.\n",
"\n",
"<b> <u> Input </u> </b>\n",
"<ul>\n",
" <li> <b>n_samples</b>: The total number of points equally divided among clusters. </li>\n",
" <ul> <li> Value will be: 5000 </li> </ul>\n",
" <li> <b>centers</b>: The number of centers to generate, or the fixed center locations. </li>\n",
" <ul> <li> Value will be: [[4, 4], [-2, -1], [2, -3],[1,1]] </li> </ul>\n",
" <li> <b>cluster_std</b>: The standard deviation of the clusters. </li>\n",
" <ul> <li> Value will be: 0.9 </li> </ul>\n",
"</ul>\n",
"\n",
"<b> <u> Output </u> </b>\n",
"<ul>\n",
" <li> <b>X</b>: Array of shape [n_samples, n_features]. (Feature Matrix)</li>\n",
" <ul> <li> The generated samples. </li> </ul> \n",
" <li> <b>y</b>: Array of shape [n_samples]. (Response Vector)</li>\n",
" <ul> <li> The integer labels for cluster membership of each sample. </li> </ul>\n",
"</ul>\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"button": false,
"collapsed": true,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [],
"source": [
"X, y = make_blobs(n_samples=5000, centers=[[4, 4], [-2, -1], [2, -3], [1, 1]], cluster_std=0.9)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Display the scatter plot of the randomly generated data."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7fb6f468e630>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 10))\n",
"plt.scatter(X[:, 0], X[:, 1], marker='.')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Setting up *k*-means"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now that we have our random data, let's set up our *k*-means clustering."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"The KMeans class has many parameters that can be used, but we will use these three:\n",
"<ul>\n",
" <li> <strong>init</strong>: Initialization method of the centroids. </li>\n",
" <ul>\n",
" <li> Value will be: \"k-means++\". k-means++ selects initial cluster centers for <em>k</em>-means clustering in a smart way to speed up convergence.</li>\n",
" </ul>\n",
" <li> <strong>n_clusters</strong>: The number of clusters to form as well as the number of centroids to generate. </li>\n",
" <ul> <li> Value will be: 4 (since we have 4 centers)</li> </ul>\n",
" <li> <strong>n_init</strong>: Number of times the <em>k</em>-means algorithm will be run with different centroid seeds. The final results will be the best output of n_init consecutive runs in terms of inertia. </li>\n",
" <ul> <li> Value will be: 12 </li> </ul>\n",
"</ul>\n",
"\n",
"Initialize KMeans with these parameters, where the output parameter is called **k_means**."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"button": false,
"collapsed": true,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [],
"source": [
"k_means = KMeans(init=\"k-means++\", n_clusters=4, n_init=12)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now let's fit the KMeans model with the feature matrix we created above, <b> X </b>."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
" n_clusters=4, n_init=12, n_jobs=None, precompute_distances='auto',\n",
" random_state=None, tol=0.0001, verbose=0)"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means.fit(X)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now let's grab the labels for each point in the model using KMeans **.labels\\_** attribute and save it as **k_means_labels**."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 3, 3, ..., 1, 0, 0], dtype=int32)"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means_labels = k_means.labels_\n",
"k_means_labels"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"We will also get the coordinates of the cluster centers using KMeans **.cluster\\_centers\\_** and save it as **k_means_cluster_centers**."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([[-2.03743147, -0.99782524],\n",
" [ 3.97334234, 3.98758687],\n",
" [ 0.96900523, 0.98370298],\n",
" [ 1.99741008, -3.01666822]])"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means_cluster_centers = k_means.cluster_centers_\n",
"k_means_cluster_centers"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Visualizing the Resulting Clusters"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"So now that we have the random data generated and the KMeans model initialized, let's plot them and see what the clusters look like."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Please read through the code and comments to understand how to plot the model."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{0, 1, 2, 3}"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"set(k_means_labels)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 3, 3, ..., 1, 0, 0], dtype=int32)"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means_labels"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# initialize the plot with the specified dimensions.\n",
"fig = plt.figure(figsize=(15, 10))\n",
"\n",
"# colors uses a color map, which will produce an array of colors based on\n",
"# the number of labels. We use set(k_means_labels) to get the\n",
"# unique labels.\n",
"colors = plt.cm.Spectral(np.linspace(0, 1, len(set(k_means_labels))))\n",
"\n",
"# create a plot\n",
"ax = fig.add_subplot(1, 1, 1)\n",
"\n",
"# loop through the data and plot the datapoints and centroids.\n",
"# k will range from 0-3, which will match the number of clusters in the dataset.\n",
"for k, col in zip(range(len([[4,4], [-2, -1], [2, -3], [1, 1]])), colors):\n",
"\n",
" # create a list of all datapoints, where the datapoints that are \n",
" # in the cluster (ex. cluster 0) are labeled as true, else they are\n",
" # labeled as false.\n",
" my_members = (k_means_labels == k)\n",
" \n",
" # define the centroid, or cluster center.\n",
" cluster_center = k_means_cluster_centers[k]\n",
" \n",
" # plot the datapoints with color col.\n",
" ax.plot(X[my_members, 0], X[my_members, 1], 'w', markerfacecolor=col, marker='.')\n",
" \n",
" # plot the centroids with specified color, but with a darker outline\n",
" ax.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col, markeredgecolor='k', markersize=6)\n",
"\n",
"# title of the plot\n",
"ax.set_title('KMeans')\n",
"\n",
"# remove x-axis ticks\n",
"ax.set_xticks(())\n",
"\n",
"# remove y-axis ticks\n",
"ax.set_yticks(())\n",
"\n",
"# show the plot\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<a id='item2'></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"## 2. Using *k*-means for Customer Segmentation"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Imagine that you have a customer dataset, and you are interested in exploring the behavior of your customers using their historical data.\n",
"\n",
"Customer segmentation is the practice of partitioning a customer base into groups of individuals that have similar characteristics. It is a significant strategy as a business can target these specific groups of customers and effectively allocate marketing resources. For example, one group might contain customers who are high-profit and low-risk, that is, more likely to purchase products, or subscribe to a service. A business task is to retain those customers. Another group might include customers from non-profit organizations, and so on."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Downloading Data"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Let's download the data and save it as a CSV file called **customer_segmentation.csv**"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data downloaded!\n"
]
}
],
"source": [
"!wget -q -O 'customer_segmentation.csv' https://cocl.us/customer_dataset\n",
"print('Data downloaded!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now that the data is downloaded, let's read it into a *pandas* dataframe."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
" <th>Card Debt</th>\n",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
" <th>Address</th>\n",
" <th>DebtIncomeRatio</th>\n",
" </tr>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
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" <td>0.124</td>\n",
" <td>1.073</td>\n",
" <td>0.0</td>\n",
" <td>NBA001</td>\n",
" <td>6.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
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" <td>4.582</td>\n",
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" <td>0.0</td>\n",
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" <td>12.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>33</td>\n",
" <td>2</td>\n",
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" <td>6.111</td>\n",
" <td>5.802</td>\n",
" <td>1.0</td>\n",
" <td>NBA013</td>\n",
" <td>20.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>29</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>19</td>\n",
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" <td>0.516</td>\n",
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" <td>NBA009</td>\n",
" <td>6.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" <td>253</td>\n",
" <td>9.308</td>\n",
" <td>8.908</td>\n",
" <td>0.0</td>\n",
" <td>NBA008</td>\n",
" <td>7.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income Card Debt Other Debt \\\n",
"0 1 41 2 6 19 0.124 1.073 \n",
"1 2 47 1 26 100 4.582 8.218 \n",
"2 3 33 2 10 57 6.111 5.802 \n",
"3 4 29 2 4 19 0.681 0.516 \n",
"4 5 47 1 31 253 9.308 8.908 \n",
"\n",
" Defaulted Address DebtIncomeRatio \n",
"0 0.0 NBA001 6.3 \n",
"1 0.0 NBA021 12.8 \n",
"2 1.0 NBA013 20.9 \n",
"3 0.0 NBA009 6.3 \n",
"4 0.0 NBA008 7.2 "
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customers_df = pd.read_csv('customer_segmentation.csv')\n",
"customers_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Pre-processing"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"As you can see, **Address** in this dataset is a categorical variable. k-means algorithm isn't directly applicable to categorical variables because Euclidean distance function isn't really meaningful for discrete variables. So, lets drop this feature and run clustering."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
" <th>Card Debt</th>\n",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
" <th>DebtIncomeRatio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>41</td>\n",
" <td>2</td>\n",
" <td>6</td>\n",
" <td>19</td>\n",
" <td>0.124</td>\n",
" <td>1.073</td>\n",
" <td>0.0</td>\n",
" <td>6.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" <td>100</td>\n",
" <td>4.582</td>\n",
" <td>8.218</td>\n",
" <td>0.0</td>\n",
" <td>12.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>33</td>\n",
" <td>2</td>\n",
" <td>10</td>\n",
" <td>57</td>\n",
" <td>6.111</td>\n",
" <td>5.802</td>\n",
" <td>1.0</td>\n",
" <td>20.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>29</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>19</td>\n",
" <td>0.681</td>\n",
" <td>0.516</td>\n",
" <td>0.0</td>\n",
" <td>6.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" <td>253</td>\n",
" <td>9.308</td>\n",
" <td>8.908</td>\n",
" <td>0.0</td>\n",
" <td>7.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income Card Debt Other Debt \\\n",
"0 1 41 2 6 19 0.124 1.073 \n",
"1 2 47 1 26 100 4.582 8.218 \n",
"2 3 33 2 10 57 6.111 5.802 \n",
"3 4 29 2 4 19 0.681 0.516 \n",
"4 5 47 1 31 253 9.308 8.908 \n",
"\n",
" Defaulted DebtIncomeRatio \n",
"0 0.0 6.3 \n",
"1 0.0 12.8 \n",
"2 1.0 20.9 \n",
"3 0.0 6.3 \n",
"4 0.0 7.2 "
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = customers_df.drop('Address', axis=1)\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now let's normalize the dataset. But why do we need normalization in the first place? Normalization is a statistical method that helps mathematical-based algorithms interpret features with different magnitudes and distributions equally. We use **StandardScaler()** to normalize our dataset."
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Step 1: X is this:\n",
" [[41. 2. 6. ... 1.073 0. 6.3 ]\n",
" [47. 1. 26. ... 8.218 0. 12.8 ]\n",
" [33. 2. 10. ... 5.802 1. 20.9 ]\n",
" ...\n",
" [25. 4. 0. ... 3.21 1. 33.4 ]\n",
" [32. 1. 12. ... 0.696 0. 2.9 ]\n",
" [52. 1. 16. ... 3.638 0. 8.6 ]]\n",
"\n",
"Step 2: X (\"nan's\" converted to numerics) is now this:\n",
" [[41. 2. 6. ... 1.073 0. 6.3 ]\n",
" [47. 1. 26. ... 8.218 0. 12.8 ]\n",
" [33. 2. 10. ... 5.802 1. 20.9 ]\n",
" ...\n",
" [25. 4. 0. ... 3.21 1. 33.4 ]\n",
" [32. 1. 12. ... 0.696 0. 2.9 ]\n",
" [52. 1. 16. ... 3.638 0. 8.6 ]]\n",
"\n",
"Step 3: normalized \"cluster_dataset\" is this:\n",
" [[ 0.74291541 0.31212243 -0.37878978 ... -0.59048916 -0.52379654\n",
" -0.57652509]\n",
" [ 1.48949049 -0.76634938 2.5737211 ... 1.51296181 -0.52379654\n",
" 0.39138677]\n",
" [-0.25251804 0.31212243 0.2117124 ... 0.80170393 1.90913822\n",
" 1.59755385]\n",
" ...\n",
" [-1.24795149 2.46906604 -1.26454304 ... 0.03863257 1.90913822\n",
" 3.45892281]\n",
" [-0.37694723 -0.76634938 0.50696349 ... -0.70147601 -0.52379654\n",
" -1.08281745]\n",
" [ 2.1116364 -0.76634938 1.09746566 ... 0.16463355 -0.52379654\n",
" -0.2340332 ]]\n"
]
}
],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"\n",
"X = df.values[:,1:]\n",
"print(\"\\nStep 1: X is this:\\n\",X)\n",
"X = np.nan_to_num(X)\n",
"print(\"\\nStep 2: X (\\\"nan\\'s\\\" converted to numerics) is now this:\\n\",X)\n",
"cluster_dataset = StandardScaler().fit_transform(X)\n",
"print(\"\\nStep 3: normalized \\\"cluster_dataset\\\" is this:\\n\",cluster_dataset)\n",
"#cluster_dataset"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Modeling"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Let's run our model and group our customers into three clusters."
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1 2 0 1 2 2 1 1 1 2 0 1 1 1 0 1 1 1 2 1 1 1 0 2 2 1 1 1 1 1 1 2 0 1 1 1 0\n",
" 0 1 2 0 2 1 2 1 2 1 1 1 1 2 2 0 1 0 0 0 1 1 1 2 1 2 2 1 1 1 0 1 0 1 1 1 1\n",
" 1 1 1 1 2 1 1 0 2 1 2 1 1 1 0 0 1 1 0 0 1 1 1 1 0 1 0 2 1 0 0 2 1 1 1 1 1\n",
" 1 1 0 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 2 1 1 0\n",
" 1 1 1 2 0 1 1 1 1 2 0 0 1 2 1 1 1 1 1 1 1 1 2 1 1 0 1 0 1 1 0 2 0 1 1 2 0\n",
" 2 1 1 1 1 1 2 1 0 1 1 1 2 2 1 2 1 0 1 1 0 1 2 1 0 1 1 1 1 1 0 0 2 1 1 0 2\n",
" 1 1 1 1 2 1 1 0 1 1 1 1 2 1 1 0 2 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 2 0 1 0 1\n",
" 1 1 2 1 0 2 0 1 2 1 1 0 1 1 1 1 0 0 0 1 1 1 2 1 1 2 1 2 1 1 2 1 1 1 0 1 1\n",
" 0 1 0 2 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 0 1 0 2 1 0 1 1 1 0 0 1 1 1 2 0\n",
" 1 1 0 1 2 1 1 1 1 1 0 2 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 2 0 1 0 1 1 1 2 2 1\n",
" 0 1 2 0 0 1 1 1 0 1 1 1 1 1 2 1 2 1 1 1 1 0 1 0 1 1 1 2 1 1 1 1 0 1 1 0 0\n",
" 2 1 1 1 1 1 0 0 1 2 0 2 1 1 0 1 1 2 2 1 0 1 1 2 1 0 1 2 1 1 1 2 1 1 1 1 2\n",
" 1 0 1 1 1 1 2 0 1 1 2 1 0 1 1 2 1 2 1 1 1 1 1 1 1 2 2 1 1 2 1 0 1 1 1 0 1\n",
" 0 1 1 1 1 1 2 0 0 1 2 1 2 1 1 0 2 1 0 0 0 2 2 0 1 1 0 1 0 0 1 0 2 1 1 0 1\n",
" 0 2 0 1 1 0 1 1 0 0 0 1 1 1 2 2 1 1 0 1 1 0 2 1 0 1 1 1 0 1 2 1 2 2 1 2 1\n",
" 1 2 1 0 1 1 1 1 0 0 1 2 1 2 1 1 2 1 0 1 0 1 0 0 0 2 0 1 1 1 0 1 1 1 2 1 2\n",
" 1 0 0 1 1 1 1 1 1 1 0 2 1 2 1 1 0 1 1 1 0 1 1 0 0 0 0 1 2 1 0 0 1 1 1 1 2\n",
" 2 1 0 1 1 2 1 1 2 1 2 1 1 2 0 2 2 2 0 1 1 0 1 2 2 1 1 1 2 0 1 1 1 1 2 1 1\n",
" 1 1 1 0 1 1 2 1 1 2 1 1 1 1 1 1 0 2 1 1 0 1 1 1 1 0 1 2 1 1 2 1 1 0 1 0 1\n",
" 0 0 1 1 1 2 0 2 1 2 2 1 0 1 2 1 2 1 1 1 1 1 2 1 0 1 1 2 2 1 1 2 1 1 1 1 1\n",
" 1 1 1 0 1 1 2 1 1 1 1 1 1 1 0 1 1 1 2 0 2 2 1 1 1 0 1 1 1 0 0 1 0 1 1 1 2\n",
" 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 2 0 0 1 0 1 1 1 1 2 0 1 1 1 1 1 2 0 1 1 1 0\n",
" 1 1 0 1 1 1 1 1 1 0 0 2 2 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 2]\n"
]
}
],
"source": [
"num_clusters = 3\n",
"\n",
"k_means = KMeans(init=\"k-means++\", n_clusters=num_clusters, n_init=12)\n",
"k_means.fit(cluster_dataset)\n",
"labels = k_means.labels_\n",
"\n",
"print(labels)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h2 id=\"insights\">Insights</h2>"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Note that each row in our dataset represents a customer, and therefore, each row is assigned a label."
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/html": [
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
" <th>Card Debt</th>\n",
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" <tr>\n",
" <th>3</th>\n",
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" <td>29</td>\n",
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" <td>19</td>\n",
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" <td>0.516</td>\n",
" <td>0.0</td>\n",
" <td>6.3</td>\n",
" <td>1</td>\n",
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" <th>4</th>\n",
" <td>5</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" <td>253</td>\n",
" <td>9.308</td>\n",
" <td>8.908</td>\n",
" <td>0.0</td>\n",
" <td>7.2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income Card Debt Other Debt \\\n",
"0 1 41 2 6 19 0.124 1.073 \n",
"1 2 47 1 26 100 4.582 8.218 \n",
"2 3 33 2 10 57 6.111 5.802 \n",
"3 4 29 2 4 19 0.681 0.516 \n",
"4 5 47 1 31 253 9.308 8.908 \n",
"\n",
" Defaulted DebtIncomeRatio Labels \n",
"0 0.0 6.3 1 \n",
"1 0.0 12.8 2 \n",
"2 1.0 20.9 0 \n",
"3 0.0 6.3 1 \n",
"4 0.0 7.2 2 "
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[\"Labels\"] = labels\n",
"df.head(5)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"We can easily check the centroid values by averaging the features in each cluster."
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\n",
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"\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
" <th>Card Debt</th>\n",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
" <th>DebtIncomeRatio</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Labels</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <th></th>\n",
" <th></th>\n",
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" <tr>\n",
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" <td>424.451807</td>\n",
" <td>31.891566</td>\n",
" <td>1.861446</td>\n",
" <td>3.963855</td>\n",
" <td>31.789157</td>\n",
" <td>1.576675</td>\n",
" <td>2.843355</td>\n",
" <td>0.993939</td>\n",
" <td>13.994578</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>426.122905</td>\n",
" <td>33.817505</td>\n",
" <td>1.603352</td>\n",
" <td>7.625698</td>\n",
" <td>36.143389</td>\n",
" <td>0.853128</td>\n",
" <td>1.816855</td>\n",
" <td>0.000000</td>\n",
" <td>7.964991</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>424.408163</td>\n",
" <td>43.000000</td>\n",
" <td>1.931973</td>\n",
" <td>17.197279</td>\n",
" <td>101.959184</td>\n",
" <td>4.220673</td>\n",
" <td>7.954483</td>\n",
" <td>0.162393</td>\n",
" <td>13.915646</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income \\\n",
"Labels \n",
"0 424.451807 31.891566 1.861446 3.963855 31.789157 \n",
"1 426.122905 33.817505 1.603352 7.625698 36.143389 \n",
"2 424.408163 43.000000 1.931973 17.197279 101.959184 \n",
"\n",
" Card Debt Other Debt Defaulted DebtIncomeRatio \n",
"Labels \n",
"0 1.576675 2.843355 0.993939 13.994578 \n",
"1 0.853128 1.816855 0.000000 7.964991 \n",
"2 4.220673 7.954483 0.162393 13.915646 "
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('Labels').mean()"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<em>k</em>-means will partition your customers into three groups since we specified the algorithm to generate 3 clusters. The customers in each cluster are similar to each other in terms of the features included in the dataset.\n",
"\n",
"Now we can create a profile for each group, considering the common characteristics of each cluster. \n",
"For example, the 3 clusters can be:\n",
"\n",
"- OLDER, HIGH INCOME, AND INDEBTED\n",
"- MIDDLE AGED, MIDDLE INCOME, AND FINANCIALLY RESPONSIBLE\n",
"- YOUNG, LOW INCOME, AND INDEBTED"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"However, you can devise your own profiles based on the means above and come up with labels that you think best describe each cluster."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"I hope that you are able to see the power of *k*-means here. This clustering algorithm provided us with insight into the dataset and lead us to group the data into three clusters. Perhaps the same results would have been achieved but using multiple tests and experiments."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Thank you for completing this lab!\n",
"\n",
"This notebook was created by [Saeed Aghabozorgi](https://ca.linkedin.com/in/saeedaghabozorgi) and [Alex Aklson](https://www.linkedin.com/in/aklson/). We hope you found this lab interesting and educational. Feel free to contact us if you have any questions!"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"This notebook is part of a course on **Coursera** called *Applied Data Science Capstone*. If you accessed this notebook outside the course, you can take this course online by clicking [here](http://cocl.us/DP0701EN_Coursera_Week3_LAB1)."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<hr>\n",
"\n",
"Copyright &copy; 2018 [Cognitive Class](https://cognitiveclass.ai/?utm_source=bducopyrightlink&utm_medium=dswb&utm_campaign=bdu). This notebook and its source code are released under the terms of the [MIT License](https://bigdatauniversity.com/mit-license/)."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.6.8"
},
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"version": "1.1.2"
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"nbformat": 4,
"nbformat_minor": 2
}
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