AgglomerativeClusteringRatcliffObershelp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "from matplotlib import pyplot as plt\n",
    "from sklearn import metrics\n",
    "from scipy.spatial.distance import squareform\n",
    "from scipy.cluster.hierarchy import fcluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ro_matrix = np.load(\"../input/condensed_distance_matrix_ratcliffobershelp.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z = linkage(ro_matrix, 'average')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fancy_dendrogram(*args, **kwargs):\n",
    "    max_d = kwargs.pop('max_d', None)\n",
    "    if max_d and 'color_threshold' not in kwargs:\n",
    "        kwargs['color_threshold'] = max_d\n",
    "    annotate_above = kwargs.pop('annotate_above', 0)\n",
    "\n",
    "    ddata = dendrogram(*args, **kwargs)\n",
    "\n",
    "    if not kwargs.get('no_plot', False):\n",
    "        plt.title('Hierarchical Clustering Dendrogram (truncated)')\n",
    "        plt.xlabel('sample index or (cluster size)')\n",
    "        plt.ylabel('distance')\n",
    "        for i, d, c in zip(ddata['icoord'], ddata['dcoord'], ddata['color_list']):\n",
    "            x = 0.5 * sum(i[1:3])\n",
    "            y = d[1]\n",
    "            if y > annotate_above:\n",
    "                plt.plot(x, y, 'o', c=c)\n",
    "                plt.annotate(\"%.3g\" % y, (x, y), xytext=(0, -5),\n",
    "                             textcoords='offset points',\n",
    "                             va='top', ha='center')\n",
    "        if max_d:\n",
    "            plt.axhline(y=max_d, c='k')\n",
    "    return ddata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3600x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(50, 10))\n",
    "fancy_dendrogram(\n",
    "    Z,\n",
    "    leaf_rotation=90.,\n",
    "    leaf_font_size=12.,\n",
    "    show_contracted=True,\n",
    "    annotate_above=10,\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = [l[2] for l in Z]\n",
    "\n",
    "fig = plt.figure(figsize=(20, 8))\n",
    "n, bins, patches = plt.hist(X, bins=200, density=False, cumulative=False, color='#0504aa',\n",
    "                            alpha=0.7, rwidth=0.8)\n",
    "plt.xlabel('distance')\n",
    "plt.ylabel('number of merge')\n",
    "plt.xticks(np.arange(0,1+0.05,0.05))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20, 8))\n",
    "plt.hist(X, bins=200, density=False, cumulative=False, color='#0504aa',\n",
    "                            alpha=0.7, rwidth=0.8)\n",
    "plt.xlabel('distance')\n",
    "plt.ylabel('number of merge')\n",
    "plt.xticks(np.arange(0,1+0.05,0.05))\n",
    "plt.ylim(top=350)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "nums_of_cluster = []\n",
    "s_scores = []\n",
    "distance_matrix = squareform(ro_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "for k in range(2,200):\n",
    "    clusters = fcluster(Z, k, criterion='maxclust')\n",
    "    s_score = metrics.silhouette_score(distance_matrix, clusters, metric='precomputed')\n",
    "    nums_of_cluster.append(k)\n",
    "    s_scores.append(s_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "for k in range(200,500):\n",
    "    clusters = fcluster(Z, k, criterion='maxclust')\n",
    "    s_score = metrics.silhouette_score(distance_matrix, clusters, metric='precomputed')\n",
    "    nums_of_cluster.append(k)\n",
    "    s_scores.append(s_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "for k in range(500,800):\n",
    "    clusters = fcluster(Z, k, criterion='maxclust')\n",
    "    s_score = metrics.silhouette_score(distance_matrix, clusters, metric='precomputed')\n",
    "    nums_of_cluster.append(k)\n",
    "    s_scores.append(s_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(nums_of_cluster, s_scores, c=\"blue\")\n",
    "\n",
    "plt.xlabel(\"Num of Cluster\", fontsize=14)\n",
    "plt.ylabel(\"Mean Silhouette Coefficient\", fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.24923369331521744"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(s_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "732"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nums_of_cluster[s_scores.index(max(s_scores))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "k = nums_of_cluster[s_scores.index(max(s_scores))]\n",
    "clusters = fcluster(Z, k, criterion='maxclust')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "lists = []\n",
    "\n",
    "with open(\"../input/anonymous-msweb.data\", \"r\") as f:\n",
    "    for line in f:\n",
    "        if line[0] == \"C\":\n",
    "            key = int(line[-6:-1])\n",
    "            lists.append([key,[]]) #[[10001]]\n",
    "        if line[0] == \"V\" and key > 0:\n",
    "            read_value = int(line[2:6])\n",
    "            lists[-1][1].append(read_value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_segments = dict()\n",
    "for i, group_num in enumerate(clusters):\n",
    "    if group_num in dict_segments:\n",
    "        dict_segments[group_num].append(lists[i][0])\n",
    "    else:\n",
    "        dict_segments[group_num] = [lists[i][0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_segments = pd.DataFrame(list(dict_segments.items()), columns=['Group Num', 'Visitor'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Group Num</th>\n",
       "      <th>Visitor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>619</td>\n",
       "      <td>[10001, 10092, 10442, 10469, 10754, 10990, 110...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>659</td>\n",
       "      <td>[10002, 10003, 10100, 10308, 10320, 10392, 106...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>[10004, 10815, 16407, 17323, 19426, 28820, 311...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>584</td>\n",
       "      <td>[10005, 15131, 16582, 17373, 18415, 18764, 205...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>717</td>\n",
       "      <td>[10006, 10008, 10018, 10022, 10042, 10044, 100...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>576</td>\n",
       "      <td>[10007, 10048, 10062, 10079, 10088, 10094, 101...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>599</td>\n",
       "      <td>[10009, 10023, 10043, 10059, 10125, 10146, 101...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>180</td>\n",
       "      <td>[10010, 10571, 16610, 19733, 22951, 27586, 339...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>388</td>\n",
       "      <td>[10011, 13159, 15125, 16662, 17563, 17934, 201...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>122</td>\n",
       "      <td>[10012, 10456, 10638, 10999, 11473, 11896, 120...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>194</td>\n",
       "      <td>[10013, 10074, 11089, 11328, 11573, 11726, 118...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>36</td>\n",
       "      <td>[10014, 10880, 10980, 11333, 11377, 11434, 118...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>372</td>\n",
       "      <td>[10015, 10151, 11060, 11551, 12107, 12245, 122...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>225</td>\n",
       "      <td>[10016, 10046, 10047, 10061, 10069, 10119, 101...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>93</td>\n",
       "      <td>[10017, 24102, 26137, 29801, 32701, 35256, 35750]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>500</td>\n",
       "      <td>[10019, 15681, 18581, 19483, 39763]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>621</td>\n",
       "      <td>[10020, 10241, 10694, 11364, 11381, 11966, 133...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>302</td>\n",
       "      <td>[10021, 10523, 10572, 11901, 14261, 14406, 146...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>691</td>\n",
       "      <td>[10024, 10207, 10806, 11409, 11717, 12172, 122...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>560</td>\n",
       "      <td>[10025, 10164, 10613, 10795, 11063, 11155, 111...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>614</td>\n",
       "      <td>[10026, 10027, 10029, 10040, 10041, 10045, 100...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>329</td>\n",
       "      <td>[10028, 10090, 10204, 10345, 10407, 10732, 107...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>428</td>\n",
       "      <td>[10030, 10106, 10202, 10378, 10507, 10552, 106...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>527</td>\n",
       "      <td>[10031, 10036, 10133, 10196, 10306, 10327, 103...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>189</td>\n",
       "      <td>[10032, 10604, 11486, 14667, 17340, 18233, 182...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>429</td>\n",
       "      <td>[10033, 10037, 10060, 10098, 10221, 10231, 102...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>449</td>\n",
       "      <td>[10034, 10075, 10339, 10466, 10544, 10556, 107...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>595</td>\n",
       "      <td>[10035, 10437, 10601, 10881, 13830, 13866, 148...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>655</td>\n",
       "      <td>[10038, 10677, 11985, 12040, 15670, 18467, 210...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>671</td>\n",
       "      <td>[10039, 10070, 10117, 10721, 11142, 11311, 113...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>275</td>\n",
       "      <td>[37171, 42197]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>593</td>\n",
       "      <td>[37370]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>704</th>\n",
       "      <td>535</td>\n",
       "      <td>[37451, 40916]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>279</td>\n",
       "      <td>[37637]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>706</th>\n",
       "      <td>460</td>\n",
       "      <td>[37660, 41486]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>665</td>\n",
       "      <td>[37945, 40491]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>708</th>\n",
       "      <td>235</td>\n",
       "      <td>[38093]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>663</td>\n",
       "      <td>[38514]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>656</td>\n",
       "      <td>[38601, 39720]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>711</th>\n",
       "      <td>467</td>\n",
       "      <td>[38609]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>712</th>\n",
       "      <td>475</td>\n",
       "      <td>[38953]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>713</th>\n",
       "      <td>199</td>\n",
       "      <td>[39066]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>714</th>\n",
       "      <td>169</td>\n",
       "      <td>[39182]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>715</th>\n",
       "      <td>570</td>\n",
       "      <td>[39350, 40876, 42205]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>716</th>\n",
       "      <td>490</td>\n",
       "      <td>[39758, 42626]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>384</td>\n",
       "      <td>[40127]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>718</th>\n",
       "      <td>13</td>\n",
       "      <td>[40233]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>719</th>\n",
       "      <td>409</td>\n",
       "      <td>[40666]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>720</th>\n",
       "      <td>727</td>\n",
       "      <td>[40810]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721</th>\n",
       "      <td>212</td>\n",
       "      <td>[40882]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>722</th>\n",
       "      <td>732</td>\n",
       "      <td>[41033]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>723</th>\n",
       "      <td>273</td>\n",
       "      <td>[41218]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>554</td>\n",
       "      <td>[41318]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>221</td>\n",
       "      <td>[41626]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>726</th>\n",
       "      <td>339</td>\n",
       "      <td>[41866]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>95</td>\n",
       "      <td>[41897]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>322</td>\n",
       "      <td>[41916]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>315</td>\n",
       "      <td>[42198]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>730</th>\n",
       "      <td>277</td>\n",
       "      <td>[42285]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>731</th>\n",
       "      <td>623</td>\n",
       "      <td>[42333, 42344]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>732 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Group Num                                            Visitor\n",
       "0          619  [10001, 10092, 10442, 10469, 10754, 10990, 110...\n",
       "1          659  [10002, 10003, 10100, 10308, 10320, 10392, 106...\n",
       "2           38  [10004, 10815, 16407, 17323, 19426, 28820, 311...\n",
       "3          584  [10005, 15131, 16582, 17373, 18415, 18764, 205...\n",
       "4          717  [10006, 10008, 10018, 10022, 10042, 10044, 100...\n",
       "5          576  [10007, 10048, 10062, 10079, 10088, 10094, 101...\n",
       "6          599  [10009, 10023, 10043, 10059, 10125, 10146, 101...\n",
       "7          180  [10010, 10571, 16610, 19733, 22951, 27586, 339...\n",
       "8          388  [10011, 13159, 15125, 16662, 17563, 17934, 201...\n",
       "9          122  [10012, 10456, 10638, 10999, 11473, 11896, 120...\n",
       "10         194  [10013, 10074, 11089, 11328, 11573, 11726, 118...\n",
       "11          36  [10014, 10880, 10980, 11333, 11377, 11434, 118...\n",
       "12         372  [10015, 10151, 11060, 11551, 12107, 12245, 122...\n",
       "13         225  [10016, 10046, 10047, 10061, 10069, 10119, 101...\n",
       "14          93  [10017, 24102, 26137, 29801, 32701, 35256, 35750]\n",
       "15         500                [10019, 15681, 18581, 19483, 39763]\n",
       "16         621  [10020, 10241, 10694, 11364, 11381, 11966, 133...\n",
       "17         302  [10021, 10523, 10572, 11901, 14261, 14406, 146...\n",
       "18         691  [10024, 10207, 10806, 11409, 11717, 12172, 122...\n",
       "19         560  [10025, 10164, 10613, 10795, 11063, 11155, 111...\n",
       "20         614  [10026, 10027, 10029, 10040, 10041, 10045, 100...\n",
       "21         329  [10028, 10090, 10204, 10345, 10407, 10732, 107...\n",
       "22         428  [10030, 10106, 10202, 10378, 10507, 10552, 106...\n",
       "23         527  [10031, 10036, 10133, 10196, 10306, 10327, 103...\n",
       "24         189  [10032, 10604, 11486, 14667, 17340, 18233, 182...\n",
       "25         429  [10033, 10037, 10060, 10098, 10221, 10231, 102...\n",
       "26         449  [10034, 10075, 10339, 10466, 10544, 10556, 107...\n",
       "27         595  [10035, 10437, 10601, 10881, 13830, 13866, 148...\n",
       "28         655  [10038, 10677, 11985, 12040, 15670, 18467, 210...\n",
       "29         671  [10039, 10070, 10117, 10721, 11142, 11311, 113...\n",
       "..         ...                                                ...\n",
       "702        275                                     [37171, 42197]\n",
       "703        593                                            [37370]\n",
       "704        535                                     [37451, 40916]\n",
       "705        279                                            [37637]\n",
       "706        460                                     [37660, 41486]\n",
       "707        665                                     [37945, 40491]\n",
       "708        235                                            [38093]\n",
       "709        663                                            [38514]\n",
       "710        656                                     [38601, 39720]\n",
       "711        467                                            [38609]\n",
       "712        475                                            [38953]\n",
       "713        199                                            [39066]\n",
       "714        169                                            [39182]\n",
       "715        570                              [39350, 40876, 42205]\n",
       "716        490                                     [39758, 42626]\n",
       "717        384                                            [40127]\n",
       "718         13                                            [40233]\n",
       "719        409                                            [40666]\n",
       "720        727                                            [40810]\n",
       "721        212                                            [40882]\n",
       "722        732                                            [41033]\n",
       "723        273                                            [41218]\n",
       "724        554                                            [41318]\n",
       "725        221                                            [41626]\n",
       "726        339                                            [41866]\n",
       "727         95                                            [41897]\n",
       "728        322                                            [41916]\n",
       "729        315                                            [42198]\n",
       "730        277                                            [42285]\n",
       "731        623                                     [42333, 42344]\n",
       "\n",
       "[732 rows x 2 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_segments.head()"
   ]
  }
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