panama.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyzing the Panama Papers with Python & Neo4j"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 0, 1)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from py2neo import Graph\n",
    "\n",
    "graph = Graph()\n",
    "\n",
    "graph.neo4j_version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"400\"\n",
       "            src=\"figure/graph-4484d19e-a182-4ed9-9f4a-8be8dbb90730.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x10810fb70>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scripts.vis import draw\n",
    "\n",
    "options = {\n",
    "    \"Officer\": \"name\",\n",
    "    \"Entity\": \"name\",\n",
    "    \"Intermediary\": \"name\",\n",
    "    \"Address\": \"address\"\n",
    "}\n",
    "\n",
    "draw(graph, options, physics=True, limit=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext cypher\n",
    "import plotly.plotly as py\n",
    "from plotly.graph_objs import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which entities have the most beneficiaries?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>entity</th>\n",
       "      <th>beneficiaries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>T.K.B.K. International Trust</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Worldwide Com-net International Trust</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Claudius Trust</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Islands International Trust</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Friends of Assisi Trust</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  entity  beneficiaries\n",
       "0           T.K.B.K. International Trust             40\n",
       "1  Worldwide Com-net International Trust             38\n",
       "2                     The Claudius Trust             36\n",
       "3            Islands International Trust             27\n",
       "4                Friends of Assisi Trust             26"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = %cypher MATCH (e:Entity)                                                          \\\n",
    "                 RETURN e.name AS entity, size(()-[:BENEFICIARY_OF]->(e)) AS beneficiaries \\\n",
    "                 ORDER BY beneficiaries DESC                                               \\\n",
    "                 LIMIT 5\n",
    "        \n",
    "df = result.get_dataframe()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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N6n/vtttuaerUqY2114FqjKzvH0S8kNWrb/yNL1Svxsha/UGEXq0+kDeXgARGJIER7/Au\nWbIkzZ07N73hDW9I6667brrzzjvTcccdl+bMmZPWXHPNdOihh6aZM2emsWNXbZeyDlTc+Ip4IauX\nesURKKvmiPFVFgFbKwEJdIHAiHd4lyXilClT0kUXXZTWW2+9tN9++6VLL710aIZ3+PWLFi3qqx/c\n9tDv0pRPL+jrWi9qRuCKQ3dIL5kwptmPVnK1eq1WnEtVpl5xbCNqjtArop3WKYGuExg1alTXHzH0\n+XR4e/D+4Q9/qEIbfvSjH6XTTz+9+pfdd989bbjhhgnHdosttkiHHXZYGj9+/NCvdHhD+2dflUe8\nkHV4+0L/rC5Sr2eFrbUfRejV2sN4YwkUTECHd9XE0+H9I79p06ale++9N02YMCGddNJJacstt6z+\nhbheOtnixYur0Idrr702XXjhhY2pu0TeGFnfP4hYclWvvvE3vlC9GiNr9QcRerX6QN5cAhIYkQR0\neHtkZwPbz3/+83TqqaemM844I73gBS/4k06x7777pvPOOy9tsMEGjTqMDlQjXI0ujnghq1cjCRpd\nrF6NcLV+cYRerT+UDZCABEYcAR3eZUh+2mmnVVkadtlllz/5V+J7Z8+endZZZ51GnUUHqhGuRhdH\nvJDVq5EEjS5Wr0a4Wr84Qq/WH8oGSEACI47AiHd4f/vb36bHHnssTZw4sRL//vvvTyeccEIVwzt6\n9Ojq37baaqtENgcyNyxYsKDK2tC06EA1Jdb/9REvZPXqn3/TK9WrKbF2r4/Qq90n8u4SkMBIJDDi\nHd5f//rXiRndBx54oEpDRvqx/fffP+20007pkUceSaecckp6+OGH01prrZUmT56ciPUdN25c476i\nA9UYWd8/iHghq1ff+BtfqF6NkbX6gwi9Wn0gby4BCYxIAiPe4c2lug5UHOmIF7J6qVccgbJqjhhf\nZRGwtRKQQBcI6PBmUlEHKg50xAtZvdQrjkBZNUeMr7II2FoJSKALBHR4M6moAxUHOuKFrF7qFUeg\nrJojxldZBGytBCTQBQI6vJlU1IGKAx3xQlYv9YojUFbNEeOrLAK2VgIS6AIBHd5MKupAxYGOeCGr\nl3rFESir5ojxVRYBWysBCXSBgA5vJhV1oOJAR7yQ1Uu94giUVXPE+CqLgK2VgAS6QECHN5OKOlBx\noCNeyOqlXnEEyqo5YnyVRcDWSkACXSCgw5tJRR2oONARL2T1Uq84AmXVHDG+yiJgayUggS4Q0OHN\npKIOVBzoiBeyeqlXHIGyao4YX2URsLUSkEAXCOjwZlJRByoOdMQLWb3UK45AWTVHjK+yCNhaCUig\nCwR0eDOpqAMVBzrihaxe6hVHoKyaI8ZXWQRsrQQk0AUCOryZVNSBigMd8UJWL/WKI1BWzRHjqywC\ntlYCEugCAR3eTCrqQMWBjnghq5d6xREoq+aI8VUWAVsrAQl0gYAObyYVdaDiQEe8kNVLveIIlFVz\nxPgqi4CtlYAEukBAhzeTijpQcaAjXsjqpV5xBMqqOWJ8lUXA1kpAAl0goMObSUUdqDjQES9k9VKv\nOAJl1RwxvsoiYGslIIEuENDhzaSiDlQc6IgXsnqpVxyBsmqOGF9lEbC1EpBAFwjo8GZSUQcqDnTE\nC1m91CuOQFk1R4yvsgjYWglIoAsEdHgzqagDFQc64oWsXuoVR6CsmiPGV1kEbK0EJNAFAjq8mVTU\ngYoDHfFCVi/1iiNQVs0R46ssArZWAhLoAgEd3kwq6kDFgY54IauXesURKKvmiPFVFgFbKwEJdIGA\nDm8mFXWg4kBHvJDVS73iCJRVc8T4KouArZWABLpAQIc3k4o6UHGgI17I6qVecQTKqjlifJVFwNZK\nQAJdIKDDm0lFHag40BEvZPVSrzgCZdUcMb7KImBrJSCBLhDQ4c2kog5UHOiIF7J6qVccgbJqjhhf\nZRGwtRKQQBcI6PBmUlEHKg50xAtZvdQrjkBZNUeMr7II2FoJSKALBHR4M6moAxUHOuKFrF7qFUeg\nrJojxldZBGytBCTQBQI6vJlU1IGKAx3xQlYv9YojUFbNEeOrLAK2VgIS6AIBHd5MKupAxYGOeCGr\nl3rFESir5ojxVRYBWysBCXSBwIh3eJ955pl09dVXp6uuuio9+eST6XnPe1465JBD0o477ljpe8cd\nd6RZs2alxx9/PE2cODGdeOKJady4cY2114FqjKzvH0S8kNWrb/yNL1Svxsha/UGEXq0+kDeXgARG\nJIER7/AuWbIkzZ07N73hDW9I6667brrzzjvTcccdl+bMmZOe85znpAMPPDAdffTRafvtt6+c4oUL\nF6YZM2Y07iw6UI2R9f2DiBeyevWNv/GF6tUYWas/iNCr1Qfy5hKQwIgkMOId3mWpPmXKlHTRRRel\nRx55JF1wwQXp7LPPri7DOd5nn33S7Nmz0+jRo6u/LVq0qK+Oc9tDv0tTPr2gr2u9qBmBKw7dIb1k\nwphmP1rJ1eq1WnEuVZl6xbGNqDlCr4h2WqcEuk5g1KhRXX/E0OfT4e3B+4c//KGaxf3Rj36UTj/9\n9DR//vxqRvfYY48duuqoo45KRx55ZJo0aZIOb2jX7L/yiBeyDm///JteqV5NibV7fYRe7T6Rd5dA\nmQR0eFdNNx3eP/KbNm1auvfee9OECRPSSSedlLbccss0b968dNddd1UhDXWZPn16OuCAA9J2223X\niLxL5I1wNbo4YslVvRpJ0Ohi9WqEq/WLI/Rq/aFsgAQkMOII6PD2SM4Gtp///Ofp1FNPTWeccUb6\nxS9+kW6++eZ0wgknDF2FY3zMMcekrbfeulFn0YFqhKvRxREvZPVqJEGji9WrEa7WL47Qq/WHsgES\nkMCII6DDuwzJTzvttCpLw6abbprOOuusdP7551dXLV68OBHfe8kll6QxY5rFjOpAxY2tiBeyeqlX\nHIGyao4YX2URsLUSkEAXCIx4h/e3v/1teuyxx6qUY5T777+/mtElhneTTTZJBx98cDr88MOHsjTc\ndNNNaebMmY2114FqjKzvH0S8kNWrb/yNL1Svxsha/UGEXq0+kDeXgARGJIER7/D++te/TszoPvDA\nA2nNNddMY8eOTfvvv3/aaaedqg5xzz33VOENjz76aDXjizM8fvz4xp1FB6oxsr5/EPFCVq++8Te+\nUL0aI2v1BxF6tfpA3lwCEhiRBEa8w5tLdR2oONIRL2T1Uq84AmXVHDG+yiJgayUggS4Q0OHNpKIO\nVBzoiBeyeqlXHIGyao4YX2URsLUSkEAXCOjwZlJRByoOdMQLWb3UK45AWTVHjK+yCNhaCUigCwR0\neDOpqAMVBzrihaxe6hVHoKyaI8ZXWQRsrQQk0AUCOryZVNSBigMd8UJWL/WKI1BWzRHjqywCtlYC\nEugCAR3eTCrqQMWBjnghq5d6xREoq+aI8VUWAVsrAQl0gYAObyYVdaDiQEe8kNVLveIIlFVzxPgq\ni4CtlYAEukBAhzeTijpQcaAjXsjqpV5xBMqqOWJ8lUXA1kpAAl0goMObSUUdqDjQES9k9VKvOAJl\n1RwxvsoiYGslIIEuENDhzaSiDlQc6IgXsnqpVxyBsmqOGF9lEbC1EpBAFwjo8GZSUQcqDnTEC1m9\n1CuOQFk1R4yvsgjYWglIoAsEdHgzqagDFQc64oWsXuoVR6CsmiPGV1kEbK0EJNAFAjq8mVTUgYoD\nHfFCVi/1iiNQVs0R46ssArZWAhLoAgEd3kwq6kDFgY54IauXesURKKvmiPFVFgFbKwEJdIGADm8m\nFXWg4kBHvJDVS73iCJRVc8T4KouArZWABLpAQIc3k4o6UHGgI17I6qVecQTKqjlifJVFwNZKQAJd\nIKDDm0lFHag40BEvZPVSrzgCZdUcMb4e+u2i9Ov//b+yQBTS2g3WWStNGDuqkNbaTAnkI6DDm4m1\nDlQc6IgXsnqpVxyBsmp2fKlXWQRsrQSWTUCHN1PP0IGKA+0LOY5tRM3qFUE1rk71imMbUXOEXhHt\ntE4J5Cagw5uJuA5vHOgIA69e6hVHoKyaHV/qVRYBWysBZ3hb7QM6UHH4fSHHsY2oWb0iqMbVqV5x\nbCNqjtArop3WKYHcBJzhzURchzcOdISBVy/1iiNQVs2OL/Uqi4CtlYAzvK32AR2oOPy+kOPYRtSs\nXhFU4+pUrzi2ETVH6BXRTuuUQG4CzvBmIq7DGwc6wsCrl3rFESirZseXepVFwNZKwBneVvuADlQc\nfl/IcWwjalavCKpxdapXHNuImqP0+sIP/iuiuSO+zne/YtO0zcZjRzyHHACc4c1BOaWkwxsHOsrA\nv+Oc78Q1egTXrF5lia9e6uX7K64PRIyvuNaWXbMObyb9NBhxoCMMhnqpVxyBsmp2fKmX9jCuD0SM\nr7jWll2zDm8m/TQYcaAjDIZ6qVccgbJqdnypl/Ywrg9EjK+41pZdsw5vJv00GHGgIwyGeqlXHIGy\nanZ8qZf2MK4PRIyvuNaWXbMOb0rphhtuSJdddll64okn0rrrrpuOOOKItO2221bKHn/88em2225L\na6yxRvW/d9tttzR16tTGqmswGiPr+wcRBkO9+sbf+EL1aoys1R+oV6v4G99cvRoja/UHEXq1+kAD\nfHMd3pQqZ3eXXXZJG220Ubr11lvTKaecki6//PLKyT300EPTzJkz09ixq7aLUgcqbhREGAz1Uq84\nAmXV7PhSL+1hXB+IGF9xrS27Zh3eZei3++67p89//vNpnXXWSfvtt1+69NJLh2Z4h1/+1FNP9dUD\nbnvod2mvC2/u61ovakbgyvftmF4yYUyzH63kavVarTiXqky94thG1HzFoTuEjK8pn14Q0dwRX6d6\nldUFmug1atSosh5uwFqrwztMkPvuuy+dfPLJ6eKLL67+Bed3ww03TIsWLUpbbLFFOuyww9L48eOH\nfsXf+yk4UBr4fkg1v6aJwei3dvXql1Tz69SrObM2f6FebdJvfm/1as6szV800UuHd9WU0uHt4ff0\n009XMbt77713euUrX1n9y5NPPpnoZIsXL05z585N1157bbrwwgsbU3dJqDGyvn8QsSSkXn3jb3yh\nejVG1uoP1KtV/I1vrl6NkbX6gwi9Wn2gAb65Du8fxVmyZEk69dRT0+abb57e/e53L1eyfffdN513\n3nlpgw02aCSrDlQjXI0ujjAY6tVIgkYXq1cjXK1frF6tS9CoAerVCFfrF0fo1fpDDWgDdHhTSji7\ns2bNSuutt95KMzBMmTIlzZ49u4rvbVJ0oJrQanZthMFQr2YaNLlavZrQav9a9WpfgyYtUK8mtNq/\nNkKv9p9qMFugw5tSOuecc9Laa6+dDjnkkKVUeuyxxxL/bbXVVpVTPGfOnLRgwYIqa0PTogPVlFj/\n10cYDPXqn3/TK9WrKbF2r1evdvk3vbt6NSXW7vURerX7RIN79xHv8D7wwAPpoIMOSs997nOXUom/\nvfa1r61SlD388MNprbXWSpMnT07Tpk1L48aNa6yoDlRjZH3/IMJgqFff+BtfqF6NkbX6A/VqFX/j\nm6tXY2St/iBCr1YfaIBvPuId3lza6EDFkY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNg\nxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+\n4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq\n2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DE\ngY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7i\nWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ\n8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSB\njjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbdp4fjJwAACAASURBVM06vJn002DEgY4wGOqlXnEEyqrZ\n8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSB\njjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJa\nW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnx\npV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGO\nMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpb\nds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGl\nXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4w\nGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2\nzTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe\n2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8KaUbbrghXXbZ\nZemJJ55I6667bjriiCPStttuWyl7xx13pFmzZqXHH388TZw4MZ144olp3LhxjVXXYDRG1vcPIgyG\nevWNv/GF6tUYWas/UK9W8Te+uXo1RtbqDyL0avWBBvjmOrwpVc7uLrvskjbaaKN06623plNOOSVd\nfvnlacmSJenAAw9MRx99dNp+++3TVVddlRYuXJhmzJjRWFIdqMbI+v5BhMFQr77xN75QvRoja/UH\n6tUq/sY3V6/GyFr9QYRerT7QAN9ch3cZ4uy+++7p85//fHrggQfSBRdckM4+++zqKhzgffbZJ82e\nPTuNHj26+ttTTz3Vl7y3PfS7tNeFN/d1rRc1I3Dl+3ZML5kwptmPVnK1eq1WnEtVpl5xbCNqvuLQ\nHULG15RPL4ho7oivU73K6gJN9Bo1alRZDzdgrdXhHSbIfffdl04++eR08cUXp/nz51czuscee+zQ\nVUcddVQ68sgj06RJk6q/LVq0qC9JcaA08H2hanxRE4PRb+Xq1S+p5tepV3Nmbf5Cvdqk3/ze6tWc\nWZu/aKKXDu+qKaXD28Pv6aefTscff3zae++90ytf+co0b968dNddd1UhDXWZPn16OuCAA9J2223X\niLxL5I1wNbo4YklIvRpJ0Ohi9WqEq/WL1at1CRo1QL0a4Wr94gi9Wn+oAW2ADu8fhSFc4dRTT02b\nb755eve731399frrr08333xzOuGEE4bkmzZtWjrmmGPS1ltv3UhSHahGuBpdHGEw1KuRBI0uVq9G\nuFq/WL1al6BRA9SrEa7WL47Qq/WHGtAG6PD+MTaXTAzrrbdemjp16pBUd955ZzrrrLPS+eefX/1t\n8eLFacqUKemSSy5JY8Y0ixnVgYobAREGQ73UK45AWTU7vtRLexjXByLGV1xry65ZhzeldM4556S1\n1147HXLIIUupyazvwQcfnA4//PChLA033XRTmjlzZmPVNRiNkfX9gwiDoV594298oXo1RtbqD9Sr\nVfyNb65ejZG1+oMIvVp9oAG++Yh3eMnEcNBBB6XnPve5S8nE34jlveeee9IZZ5yRHn300bTppptW\n4Q3jx49vLKkOVGNkff8gwmCoV9/4G1+oXo2RtfoD9WoVf+Obq1djZK3+IEKvVh9ogG8+4h3eXNro\nQMWRjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAx\nvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTK\nqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNg\nxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+\n4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq\n2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DE\ngY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7i\nWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ\n8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSB\njjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJa\nW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnx\npV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGO\nMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpb\nds06vJn002DEgY4wGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGl\nXtrDuD4QMb7iWlt2zTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4w\nGOqlXnEEyqrZ8aVe2sO4PhAxvuJaW3bNOryZ9NNgxIGOMBjqpV5xBMqq2fGlXtrDuD4QMb7iWlt2\nzTq8mfTTYMSBjjAY6qVecQTKqtnxpV7aw7g+EDG+4lpbds06vJn002DEgY4wGOqlXnEEyqrZ8aVe\n2sO4PhAxvuJaW3bNOrx/1O/BBx9MH/rQh9Kuu+6a9txzzyFVjz/++HTbbbelNdZYo/rbbrvtlqZO\nndpYdQ1GY2R9/yDCYKhX3/gbX6hejZG1+gP1ahV/45urV2Nkrf4gQq9WH2iAb67Dm1K65ZZb0rnn\nnps222yzNHny5KUc3kMPPTTNnDkzjR07dpVk1IFaJXwr/HGEwVAv9YojUFbNji/10h7G9YGI8RXX\n2rJr1uFNKd13331p9OjRad68eWnMmDFLObz77bdfuvTSS4dmeIfL/dRTT/XVA2576Hdprwtv7uta\nL2pG4Mr37ZheMmFMsx+t5Gr1Wq04l6pMveLYRtSsXhFU4+pUrzi2ETU30WvttdeOaMKIqVOHt0fq\niy++uJrJ7Q1p2H333dOGG26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0cYTBUK9GEjS6WL0a4Wr9YvVqXYJGDVCvRrhavzhCr9Yf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\nO1lnsvnEJz5R/Q27aIxvOVr309L/DzfAOxKswhM/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = Data([Bar(x=df[\"entity\"], y=df[\"beneficiaries\"])])\n",
    "\n",
    "py.image.ishow({'data': data})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Heatmap of co-occurrence of shareholders among entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>e1.name</th>\n",
       "      <th>e2.name</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DRAGON KING INVESTMENT LTD.</td>\n",
       "      <td>LUK FOOK (CONTROL) LIMITED</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BASINGSTOKE PROPERTY LIMITED</td>\n",
       "      <td>BENBOW HOUSE LIMITED</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WEST END QUAY LIMITED</td>\n",
       "      <td>WESTMEAD PROPERTY HOLDINGS LTD.</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BASINGSTOKE PROPERTY LIMITED</td>\n",
       "      <td>BEACHLEIGH HOLDINGS LIMITED</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BENBOW HOUSE LIMITED</td>\n",
       "      <td>WESTMEAD PROPERTY HOLDINGS LTD.</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        e1.name                          e2.name  weight\n",
       "0   DRAGON KING INVESTMENT LTD.       LUK FOOK (CONTROL) LIMITED      72\n",
       "1  BASINGSTOKE PROPERTY LIMITED             BENBOW HOUSE LIMITED      11\n",
       "2         WEST END QUAY LIMITED  WESTMEAD PROPERTY HOLDINGS LTD.       8\n",
       "3  BASINGSTOKE PROPERTY LIMITED      BEACHLEIGH HOLDINGS LIMITED       7\n",
       "4          BENBOW HOUSE LIMITED  WESTMEAD PROPERTY HOLDINGS LTD.       5"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = %cypher MATCH (e:Entity)                                                 \\\n",
    "                 WITH e, size(()-[:SHAREHOLDER_OF]->(e)) AS shareholders          \\\n",
    "                 ORDER BY shareholders DESC                                       \\\n",
    "                 LIMIT 50                                                         \\\n",
    "                                                                                  \\\n",
    "                 WITH collect(e) AS top_e                                         \\\n",
    "                 UNWIND top_e AS e1                                               \\\n",
    "                 UNWIND top_e AS e2                                               \\\n",
    "                                                                                  \\\n",
    "                 MATCH (e1)<-[:SHAREHOLDER_OF]-(:Officer)-[:SHAREHOLDER_OF]->(e2) \\\n",
    "                 WHERE e1.name < e2.name                                          \\\n",
    "                 RETURn e1.name, e2.name, count(*) AS weight                      \\\n",
    "                 ORDER BY weight DESC\n",
    "            \n",
    "df = result.get_dataframe()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "names = list(set(list(df[\"e1.name\"]) + list(df[\"e2.name\"])))\n",
    "heat = [[0 for i in range(len(names))] for j in range(len(names))] \n",
    "\n",
    "for idx, row in df.iterrows():\n",
    "    i = names.index(row[\"e1.name\"])\n",
    "    j = names.index(row[\"e2.name\"])\n",
    "    heat[i][j] = row[\"weight\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AiMIbdoz4m3rs5YIE4xjaIUOGyPfffy+ZM2dWf7OPfWItWrRw+OLQXXg3bdok9+/fVxvD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XD33g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\nYiXnCgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.graph_objs as go\n",
    "\n",
    "data = [go.Heatmap(z = heat, x = names, y = names)]\n",
    "py.image.ishow({'data': data})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Graph Algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A subgraph of shareholders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<igraph.Graph at 0x10c7327c8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from igraph import Graph as IGraph\n",
    "\n",
    "query = \"\"\"\n",
    "MATCH (o:Officer)\n",
    "WITH o, size((o)-[:SHAREHOLDER_OF]->()) AS entities\n",
    "ORDER BY entities DESC\n",
    "LIMIT 100\n",
    "\n",
    "WITH collect(o) AS top_o\n",
    "UNWIND top_o AS o1\n",
    "UNWIND top_o AS o2\n",
    "\n",
    "MATCH (o1)-[:SHAREHOLDER_OF]->(:Entity)<-[:SHAREHOLDER_OF]-(o2)\n",
    "WHERE o1.name < o2.name\n",
    "RETURn o1.name, o2.name, count(*) AS weight\n",
    "ORDER BY weight DESC\n",
    "\"\"\"\n",
    "\n",
    "data = graph.run(query)\n",
    "\n",
    "ig = IGraph.TupleList(data, weights=True)\n",
    "ig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which officers have the highest betweenness?\n",
    "\n",
    "$betweenness(v) = \\sum_{s, t \\in V} \\frac{\\sigma_{st}(v)}{\\sigma_{st}}$\n",
    "\n",
    "The betweenness centrality of a node $v$ is the number of shortest paths that pass through $v$, $\\sigma_{st}(v)$,  divided by the total number of shortest paths, $\\sigma_{st}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Helm Trust Company Limited', 58.5),\n",
       " ('Minerva Services Limited', 57.0),\n",
       " ('Portcullis TrustNet (Samoa) Limited', 47.93333333333334),\n",
       " ('Trustcorp Limited', 24.0),\n",
       " ('HELM MANAGEMENT LIMITED', 19.5)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "between = [(node[\"name\"], node.betweenness()) for node in ig.vs]\n",
    "top = sorted(between, key=lambda x: x[1], reverse=True)\n",
    "top[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Community Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusters = IGraph.community_walktrap(ig, weights=\"weight\")\n",
    "clusters = clusters.as_clustering()\n",
    "len(clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'group': 0, 'id': 0, 'label': 'BOS NOMINEES (JERSEY) LIMITED'},\n",
       " {'group': 0, 'id': 1, 'label': 'BOS SECRETARIES (JERSEY) LIMITED'},\n",
       " {'group': 1, 'id': 2, 'label': 'BROCK NOMINEES LIMITED'},\n",
       " {'group': 1, 'id': 3, 'label': 'TENBY NOMINEES LIMITED'},\n",
       " {'group': 2, 'id': 4, 'label': 'INTERCON LIMITED'}]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nodes = [{\"id\": node.index, \"label\": node[\"name\"]} for node in ig.vs]\n",
    "\n",
    "for node in nodes:\n",
    "    node[\"group\"] = clusters.membership[node[\"id\"]]\n",
    "    \n",
    "nodes[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'from': 0, 'to': 1},\n",
       " {'from': 2, 'to': 3},\n",
       " {'from': 4, 'to': 5},\n",
       " {'from': 6, 'to': 7},\n",
       " {'from': 7, 'to': 8}]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges = [{\"from\": x[0], \"to\": x[1]} for x in ig.get_edgelist()]\n",
    "edges[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"400\"\n",
       "            src=\"figure/graph-726ad2a5-1e88-44d5-b13a-67f6d2684b30.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x10c7924a8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scripts.vis import vis_network\n",
    "vis_network(nodes, edges, physics=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Graph Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"graph-b4604d79-dc12-478e-8790-d63999ddd020\"></div>\n",
       "           <script type=\"text/javascript\">\n",
       "           require.config({baseUrl: '/',\n",
       "                             paths: {jgraph: ['nbextensions/jgraph.min', 'https://rawgit.com/patrickfuller/jgraph/master/js/build/jgraph.min']}});\n",
       "           require(['jgraph'], function () {\n",
       "               var $d = $('#graph-b4604d79-dc12-478e-8790-d63999ddd020');\n",
       "               $d.width(600); $d.height(400);\n",
       "               $d.jgraph = jQuery.extend({}, jgraph);\n",
       "               $d.jgraph.create($d, {nodeSize: 2.000000,\n",
       "                                     edgeSize: 0.250000,\n",
       "                                     defaultNodeColor: '0x5bc0de',\n",
       "                                     defaultEdgeColor: '0xaaaaaa',\n",
       "                                     shader: 'basic',\n",
       "                                     z: 100,\n",
       "                                     runOptimization: true,\n",
       "                                     directed: true,\n",
       "                                     showSave: false});\n",
       "               $d.jgraph.draw({\n",
       "    \"edges\": [\n",
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       "        { \"source\": 688794, \"target\": 360228 },\n",
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       "        { \"source\": 692617, \"target\": 199722 },\n",
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       "        { \"source\": 688798, \"target\": 199722 },\n",
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       "        { \"source\": 688794, \"target\": 199722 },\n",
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       "        { \"source\": 673757, \"target\": 199722 },\n",
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       "        \"708475\": { \"location\": [ 2.000, 2.000, 2.000 ] },\n",
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       "        \"709716\": { \"location\": [ 2.000, 2.000, 2.000 ] },\n",
       "        \"709717\": { \"location\": [ 2.000, 2.000, 2.000 ] },\n",
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       "        \"709721\": { \"location\": [ 2.000, 2.000, 2.000 ] },\n",
       "        \"709722\": { \"location\": [ -2.000, -2.000, -2.000 ] },\n",
       "        \"709723\": { \"location\": [ -2.000, -2.000, -2.000 ] },\n",
       "        \"709724\": { \"location\": [ 2.000, 2.000, 2.000 ] },\n",
       "        \"709729\": { \"location\": [ -2.000, -2.000, -2.000 ] },\n",
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       "        \"731489\": { \"location\": [ -2.000, -2.000, -2.000 ] }\n",
       "    }\n",
       "});\n",
       "\n",
       "               $d.resizable({\n",
       "                   aspectRatio: 600 / 400,\n",
       "                   resize: function (evt, ui) {\n",
       "                       $d.jgraph.renderer.setSize(ui.size.width,\n",
       "                                                  ui.size.height);\n",
       "                   }\n",
       "               });\n",
       "           });\n",
       "           </script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import jgraph\n",
    "\n",
    "query = \"\"\"\n",
    "MATCH (off:Officer)-[:REGISTERED_ADDRESS]->(:Address)<-[:REGISTERED_ADDRESS]-(ent:Entity)\n",
    "RETURN id(off), id(ent)\n",
    "LIMIT 100\n",
    "\"\"\"\n",
    "\n",
    "data = graph.run(query)\n",
    "tup = [tuple(x) for x in data]\n",
    "\n",
    "jgraph.draw(tup)"
   ]
  }
 ],
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