R dataframe | SO 4734581 #notebook #transient #inactive

Untitled1.ipynb

{
 "metadata": {
  "name": "R dataframe | SO 4734581",
  "notebook_path": "https://gist.github.com/4734581"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import pandas.rpy.common as com\n",
      "import rpy2\n",
      "r = rpy2.robjects.r"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C':[7,8,9]},\n",
      "                 index=[\"one\", \"two\", \"three\"])\n",
      "rdf = com.convert_to_r_dataframe(df)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "r.assign('bob', rdf)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "<DataFrame - Python:0x10b9159e0 / R:0x1083aa038>\n",
        "[IntVector, IntVector, IntVector]\n",
        "  A: <class 'rpy2.robjects.vectors.IntVector'>\n",
        "  <IntVector - Python:0x10b915d40 / R:0x1086d84e8>\n",
        "[       1,        2,        3]\n",
        "  B: <class 'rpy2.robjects.vectors.IntVector'>\n",
        "  <IntVector - Python:0x10b915cb0 / R:0x1086d84b0>\n",
        "[       4,        5,        6]\n",
        "  C: <class 'rpy2.robjects.vectors.IntVector'>\n",
        "  <IntVector - Python:0x10b915ef0 / R:0x1086d8478>\n",
        "[       7,        8,        9]"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R plot(bob$$A, bob$$B)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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BEyCAgzdmtBgBBBBAIAQCBHAIBpEuIIAAAggET4AADt6Y0WIEEEAAgRAIEMAh\nGES6gAACCCAQPAECOHhjRosRQAABBEIgQACHYBDpAgIIIIBA8AQI4OCNGS1GAAEEEAiBAAEcgkGk\nCwgggAACwRMggIM3ZrQYAQQQQCAEAgRwCAaRLiCAAAIIBE+AAA7emNFiBBBAAIEQCBDAIRhEuoAA\nAgggEDwBAjh4Y0aLEUAAAQRCIEAAh2AQ6QICCCCAQPAECODgjRktRgABBBAIgQABHIJBpAsIIIAA\nAsETIICDN2a0GAEEEEAgBAIEcAgGkS4ggAACCARPgAAO3pjRYgQQQACBEAgQwCEYRLqAAAIIIBA8\nAQI4eGNGixFAAAEEQiBAAIdgEOkCAggggEDwBAjg4I0ZLUYAAQQQCIEAARyCQaQLCCCAAALBEyCA\ngzdmtBgBBBBAIAQCBHAIBpEuIIAAAggET4AADt6Y0WIEEEAAgRAIEMAhGES6gAACCCAQPAECOHhj\nRosRQAABBEIgQACHYBDpAgIIIIBA8AQI4OCNGS1GAAEEEAiBAAEcgkGkCwgggAACwRMggIM3ZrQY\nAQQQQCAEAgRwCAaRLiCAAAIIBE+AAA7emNFiBBBAAIEQCBDAIRhEuoAAAgggEDwBAjh4Y0aLEUAA\nAQRCIEAAh2AQ6QICCCCAQPAErA3gvXv3yvHjx4MnSosRQAABBBBwIWBFAPft21c2b95smrtlyxbp\n1q2bNG/eXJo2bSqDBg2SY8eOuegKiyCAAAIIIBAcASsCeMOGDZKfn2/Uxo0bJ23btpWdO3fKqlWr\nJDs7W7SMCQEEEEAAgTAJWBHARUGXLFkio0aNkgYNGkibNm1k7NixsmLFiqKLMI8AAggggEDgBawJ\nYN3b3bVrl3Ts2FH279+fgF2/fr1kZWUlXjODAAIIIIBAGASq2tCJ3r17y/z582XMmDGSm5srNWrU\nkFmzZpk94UmTJsmyZctsaCZtQAABBBBAwDMBKwL4gQceEP3RaceOHZKXl2fmr7nmGhk2bJjUrl3b\nvOY/CCCAAAIIhEXAigAuipmRkSH6o5Mejtaroo8cOeLqMPTBgwfl0KFDRatLzOueNVdTJziYQQAB\nBBBIs4B1AVzSY86cOZKTkyNTpkwp+VbSaz1UvWjRoqRyLfjwww+lSZMmKd+jEAEEEEAAgYoWsD6A\nR4wY4dqkR48eoj+ppiFDhsju3btTvUUZAggggAACFS5gzVXQJXteUFCQOBdc8j1eI4AAAgggEHQB\nawN47ty5MnTo0KD70n4EEEAAAQRSClhxCDozM1P27dtXrIFHjx41z4LWIO7evbvMmDGj2Pu8QAAB\nBBBAIMgCVgSwhuuAAQOkT58+0q9fP+M5b948Wb16tTz55JNSq1atIBvTdgQQQAABBJIErDgE3blz\nZ1mzZo1s27bNHHbWwG3YsKG5/7dly5ZmPqnlFCCAAAIIIBBgASv2gNWvbt26MnPmTJk9e7Z06dJF\nOnToIFWqVAkwLU1HAAEEEEDAWcCKPeCizevZs6csXbrUnBPWryNkQgABBBBAIIwC1uwBF8Vt1qyZ\neTZ00TLmEUAAAQQQCJOAdXvAYcKlLwgggAACCDgJEMBOMpQjgAACCCDgowAB7CMuVSOAAAIIIOAk\nQAA7yVCOAAIIIICAjwIEsI+4VI0AAggggICTAAHsJEM5AggggAACPgoQwD7iUjUCCCCAAAJOAgSw\nkwzlCCCAAAII+ChAAPuIS9UIIIAAAgg4CRDATjKUI4AAAggg4KMAAewjLlUjgAACCCDgJEAAO8lQ\njgACCCCAgI8CBLCPuFSNAAIIIICAkwAB7CRDOQIIIIAAAj4KEMA+4lI1AggggAACTgIEsJMM5Qgg\ngAACCPgoQAD7iEvVCCCAAAIIOAkQwE4ylCOAAAIIIOCjAAHsIy5VI4AAAggg4CRAADvJUI4AAggg\ngICPAgSwj7hUjQACCCCAgJMAAewkQzkCCCCAAAI+ChDAPuJSNQIIIIAAAk4CBLCTDOUIIIAAAgj4\nKEAA+4hL1QgggAACCDgJEMBOMpQjgAACCCDgowAB7CMuVSOAAAIIIOAkQAA7yVCOAAIIIICAjwIE\nsI+4VI0AAggggICTAAHsJEM5AggggAACPgoQwD7iUjUCCCCAAAJOAgSwkwzlCCCAAAII+ChAAPuI\nS9UIIIAAAgg4CRDATjKUI4AAAggg4KMAAewjLlUjgAACCCDgJEAAO8lQjgACCCCAgI8CBLCPuFSN\nAAIIIICAkwAB7CRDOQIIIIAAAj4KEMA+4lI1AggggAACTgIEsJMM5QgggAACCPgoQAD7iEvVCCCA\nAAIIOAkQwE4ylCOAAAIIIOCjAAHsIy5VI4AAAggg4CRAADvJUI4AAggggICPAgSwj7hUjQACCCCA\ngJMAAewkQzkCCCCAAAI+ChDAPuJSNQIIIIAAAk4CBLCTDOUIIIAAAgj4KEAA+4hL1QgggAACCDgJ\nEMBOMpQjgAACCCDgowAB7CMuVSOAAAIIIOAkQAA7yVCOAAIIIICAjwIEsI+4VI0AAggggICTAAHs\nJEM5AggggAACPgoQwD7iUjUCCCCAAAJOAgSwkwzlCCCAAAII+ChAAPuIS9UIIIAAAgg4CRDATjKU\nI4AAAggg4KMAAewjLlUjgAACCCDgJEAAO8lQjgACCCCAgI8CBLCPuFSNAAIIIICAkwAB7CRDOQII\nIIAAAj4KEMA+4lI1AggggAACTgLWBfDx48fl4MGDTu2lHAEEEEAAgVAIWBHAR48eleHDh0vz5s2l\nevXq0qBBA6lVq5acd955MmPGjFBA0wkEEEAAAQSKClQt+iJd84MHD5bdu3fLwoULpVWrViZ88/Ly\nZOPGjXL//fdLQUGB3H333elqHutFAAEEEEDAcwEr9oCXLl0qkydPlvbt20vt2rWlUqVKUq9ePenU\nqZNMmDBB5s2b53nHqRABBBBAAIF0ClgRwHqoefny5SkdFixYII0aNUr5XkUULlmyxBwGX7x4cUWs\njnUggAACCEREwIpD0KNHj5ZevXrJ+PHjpXXr1lK3bl3Jzc2VTZs2iV6UtWjRorQMR79+/cw56csu\nu0yeeuopmTZtmrz11ltSubIVf7ekxYSVIoAAAgh4I2BFAGdlZcnatWtl9erVkp2dbc4H616vnvft\n0qWLOSTtTXfd1zJr1ixzDvrjjz82H+rTp48MHDhQXnvtNenbt6/7ilgSAQQQQACBFAJWBLC2q0aN\nGtK1a9ekJm7ZskWOHDkiGtI/NL366qvy9ttvp1xs3bp10qxZs5TvpSr87LPPzB550ffuvPNOswdc\ntIx5BBBAAAEEyiJgTQA7NX7OnDmSk5MjU6ZMcVokUX7zzTfL9ddfn3hddEbryc/PL1p00nk9DK7h\n37lz58Ryupeu5UwIIIAAAgiUV8D6AB4xYoTrPupetP6kmjQ4v//++1RvpSy74447pEePHtK0aVP5\n2c9+Ju+//77cddddcujQoZTLU4gAAggggEBpBKwNYL33Vx/Qka49zsaNG5vbnx588EGZOXOm6Ovt\n27eb26NKA8yyCCCAAAIIpBKwNoDnzp1rbk2aOnVqqnZXSJk+kUuvfGZCAAEEEEDAawErAjgzM1P2\n7dtXrG+696u3IGkQd+/enUdSFtPhBQIIIIBA0AWsCGB93vOAAQNEb/XRe2910qdf6W1JTz75pHk0\nZdChaT8CCCCAAAJFBax4ooReabxmzRrZtm2bDB061ARuw4YNzWMpW7ZsKTrPhAACCCCAQJgErNgD\nVlC92Eovdpo9e7Z5+EaHDh2kSpUqYbKmLwgggAACCCQErNgDTrQmPtOzZ0/RL2fQc8J6CxATAggg\ngAACYRSwZg+4KK4+sWr+/PlFi5hHAAEEEEAgVALW7QGHSpfOIIAAAggg4CBAADvAUIwAAggggICf\nApVi8cnPFdhSt365Qrdu3Vx9qUPJNut3FTs94rLksrwuu4De+12pUiWpVq1a2Svhk64E9LnotWrV\ncrUsC5VdQJ/op9szF5SW3dDNJwtj7JJLLnGzeLFlvvjiC3n33XclIyOjWHlFvIhMAJcH8/LLL5cV\nK1aUpwo+60Jg0qRJ0qRJE/MMbheLs0g5BNimy4FXio8+8sgj8pvf/EY6duxYik+xaGkF9uzZI4MH\nDw7ct9VxCLq0I83yCCCAAAIIeCBAAHuASBUIIIAAAgiUVoAALq0YyyOAAAIIIOCBAAHsASJVIIAA\nAgggUFoBAri0YiyPAAIIIICABwIEsAeIVIEAAggggEBpBbgNyYXYrl275Mc//rGLJVmkPAJ5eXnm\nfknuTy2PorvPsk27cyrvUgcOHDD3W//oRz8qb1V8/iQCJ06cMN8f0Lhx45MsZd9bBLB9Y0KLEEAA\nAQQiIMAh6AgMMl1EAAEEELBPgAC2b0xoEQIIIIBABAQI4AgMMl1EAAEEELBPgAC2b0xoEQIIIIBA\nBAQI4AgMMl1EAAEEELBPgAC2b0xoEQIIIIBABAQI4AgMMl1EAAEEELBPgAAuMSb6xc7ff/99iVJe\n+iFw7NgxP6qlTgQQQCAQAgRwkWHSp6n07NlTnn766SKlxWdXrFghnTt3ljPPPFNuuOEGOXjwYPEF\neOVKYNasWdKpUyfHZdesWSMtWrQo9rNjxw7H5XkjWUCNr7jiCrngggukT58+smnTpuSF4iVs0ylZ\nXBdu3LhRbr31VuP8i1/8wvFL4dmmXZOmXFB3jIYMGSJZWVly7rnnyvjx41Mup4Xjxo2T9u3bm9/T\nOm/tFN/jY4oLxP/niMWDNVa/fv1YfMBSmuzduzcWfyRl7J///Gfs6NGjsfjGEOvfv3/KZSlMLRB/\nNF/s3nvvjTVq1Ch20UUXpV4oXvriiy/GBgwYEMvPz0/8xP9AclyeN4oLxB81GWvSpEls9+7d5o3p\n06fHrr766uILxV+xTSeRlLrgqquuir3yyivmc/E/EmPxxyEm3ItWxjZdVKP08xMmTIjdeOONsXgQ\nx7755pvY6aefHlu9enVSRbNnz45deumlsUOHDsX0/4P4H6CxRYsWJS1nQwF7wP//p1H8fyC57777\nzF+yTn8t6V+w55xzjvnLqlq1ajJ48GB5++23nRanPIXAsmXL5JRTThH1Ptn02WefSYcOHWTPnj0S\nDwnzmUqVKp3sI7xXRECP5sR/EUk8hE2p7gWvWrWqyBL/nWWbTiIpVYE633PPPYnfG/FQkDp16sin\nn36aVA/bdBJJqQruvPNOefnll6Vy5crmJ74TlPJ04eLFi80Rn3r16knTpk3N2LzzzjulWldFLUwA\n/7/0xIkT5eabbz6p+/bt24t9KYP+csvNzZXvvvvupJ/jzf8J9OjRQ5566impWbPm/wpTzOkvq2ee\neUbie21yxhlnyB/+8IcUS1HkJKBB0KVLl8TbL730knTr1i3xunCGbbpQomz/ahh0795d9A9ynfQP\nTD0tler0Ctt02YwLP6VfaKF/3Lz55pvy85//3GzPqZxLbtMawl9//XVhNVb9SwCXYjj2799vvtmk\n8COFIXLkyJHCIv71SOAnP/mJTJs2TT7//HOzN/Hcc8+ZPWGPqo9UNVOnTpX58+ebP2hKdpxtuqRI\n2V/rtvq73/1Onn/+eTn11FOTKmKbTiIpU4EeCdNzwHr0JtV1DSW3aT3iFj+VVaZ1+f0hArgUwg0b\nNhT9yrzC6fDhw1KjRg2JnzcuLOJfjwQmTZpk/srV6vSii/g5HQ73l8F28uTJMmLECPnrX/8qzZo1\nS6qBbTqJpEwFmzdvlssvv1xGjhyZOBxdsiK26ZIiZXt9yy23yMyZM83vBP1jp+RUcpvW39l6RMjG\niQAuxajoL7Ds7OzEJ3S+efPmidfMeCNQUFAgjz/+uOi/hZMeZYhfuFX4kn9dCOh59lGjRpnw1WsX\nUk1s06lUSlf2xRdfyJVXXimPPvqo3HXXXSk/zDadkqVUhfELCeXDDz9MfKZdu3aydevWxOvCGd2m\nc3JyCl+a39m2/p4mgBPDlHpGz+fo3oNOekuH/s+m53n0vO+zzz4rN910U+oPUlpqAb0dZt++feao\nwt/+9jdzCFor0f/p1q5da84Hl7rSiH7gyy+/lPjV5uZ8mf71r18Mrz86sU17u1HoYefevXubPd9C\nZ71ASCe2ae+s1VSPMBw/flziVzibvWA96qCTHoresGGDmddbSfVirZ07d5rw1XPGesuolZMNl2Lb\n1Ib4FY3FbkN67733YvFzCIkm6iXutWvXjmVkZMS6du0aix+GTrzHjHuB5cuXJ92GpLfNLFy40FSy\ncuXK2CWXXBLLzMyMxc+nxd544w33lbNkbNiwYbH4L5ykH72ti23auw3ko48+SjJW93gAmJWwTXtn\nrdtur169YmeddZb5eeihh2LffvutWcGgQYNit912m5nX2xX19lD9vRG/ACv22GOPedcIj2uqpPVZ\n+ZeBxY3Sv8D0/C/nfv0fJN2j0Ata9GpTJv8E2Kb9sy1ZM9t0SZHSvdYLqvSK6KpVq570g3ruV5fT\nH1snAtjWkaFdCCCAAAKhFmC3ItTDS+cQQAABBGwVIIBtHRnahQACCCAQagECONTDS+cQQAABBGwV\nIIBtHRnahQACCCAQagECONTDS+cQQAABBGwVIIBtHRnahQACCCAQagECONTDS+cQQAABBGwVIIBt\nHRnahQACCCAQagECONTDS+cQQAABBGwVIIBtHRnahQACCCAQagECONTDS+cQQAABBGwVIIBtHRna\nhQACCCAQagECONTDS+cQQAABBGwVIIBtHRnahQACCCAQagECONTDS+cQQAABBGwVIIBtHRnahQAC\nCCAQagECONTDS+cQQAABBGwVIIBtHRnahUAFC+zcuVMef/xxOXbsWAWvmdUhEE0BAjia406vAyzw\n0UcfybnnnlvqHrRs2VI2bNiQ8nN33HGH3HDDDTJjxgw5++yz5cMPPyy23D/+8Q+pUqWKzJw5s1g5\nLxBAoOwCBHDZ7fgkAqEQWLt2rXz88ceyatUqueqqq2TixImyYMGCYn3T4L3vvvtk6tSpxcp5gQAC\nZRcggMtuxycRSJvA0aNHpX///lK/fn0Tmjt27DBtOXHihEyaNEmysrIkIyPDHFLWssLplVdekdNP\nP13atGmTCNlDhw6J/hQUFJjFrrvuOhkzZkzhR0z5/PnzZfTo0bJr1y75/PPPE+8xgwACZRcggMtu\nxycRSJvAv//9bznttNPkX//6lwnU22+/3bTlhRdekBdffFEmT54sc+bMkddff12mT5+eaKceSn7v\nvffksccek1tuuUX27t0rl156qZxxxhly4YUXytatW+XLL79MLK8zGr6dOnWSOnXqmM+wF1yMhxcI\nlF0gxoQAAoESiJ+fjVWrVi12+PBh0+6NGzfG4r8BzOt4UMbGjx+f6M8TTzwR69Kli3ndokWL2Kuv\nvpp4r127drF4OJvX8T3q2KxZs2LxPWpT97Rp0xLLxfeIzXtasG7duljjxo1jujwTAgiUT4A94LL/\n7cInEUibQDw8pXbt2mb955xzjtSqVUv0KuacnByzt1rYMN1z1fLCqWPHjoWzcvHFFyfeiwe69OzZ\nU2666SZ57bXXZMiQIaKHrvfs2SOLFy+Whx9+WDIzM+XGG280ZbpXzIQAAuUTIIDL58enEUiLQNFQ\nzc7Olvz8fGnatKk0bNjQHJYubNT69eulVatWhS8TgasF8T1n85m5c+fKuHHjEstce+218u2335qf\n+F6xXHnllbJw4UKZN2+e+Rk6dCgXYyW0mEGg7AIEcNnt+CQCaRPQPdOVK1dK/ACYuXWoc+fOUrdu\nXfnlL38pGpq5ubly4MABcx5Yz/EWTm+//baZ1Suf9ZYkDVc9t/vcc8/JV199Zd576623TLnuVevV\nz3369BHd4y78ueeee2Tp0qXyn//8p7Ba/kUAgTIIVC3DZ/gIAgikWUDvAx42bJh8/fXXUrVqVXnn\nnXdMi4YPH24C88wzzzTlV199tWhZ4aQXXbVt29aErd5upPcGx88NS/fu3c1FWHrYWS/sip9HNnvI\nupf861//uvDj5t/WrVubw9d6z/DIkSOLvccLBBBwL1BJTyG7X5wlEUDAJgEN1EaNGiU1KS8vT/S8\nbs2aNZPe071jLa9evXqx93SPWe/11XPATAgg4L8AAey/MWtAIDAC27Ztk7POOisw7aWhCARZgAAO\n8ujRdgQQQACBwApwEVZgh46GI4AAAggEWYAADvLo0XYEEEAAgcAKEMCBHToajgACCCAQZAECOMij\nR9sRQAABBAIrQAAHduhoOAIIIIBAkAUI4CCPHm1HAAEEEAisAAEc2KGj4QgggAACQRYggIM8erQd\nAQQQQCCwAgRwYIeOhiOAAAIIBFmAAA7y6NF2BBBAAIHAChDAgR06Go4AAgggEGQBAjjIo0fbEUAA\nAQQCK0AAB3boaDgCCCCAQJAFCOAgjx5tRwABBBAIrAABHNiho+EIIIAAAkEW+D/9QvtikE7TPAAA\nAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "r.assign('testX', df.A)\n",
      "r.assign('testY', df.B)\n",
      "%R plot(testX, testY)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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aIkCAAAECuQUEcG4qFQkQIECAQHECArg4Sy0RIECAAIHcAgI4N5WKBAgQIECg\nOAEBXJyllggQIECAQG4BAZybSkUCBAgQIFCcgAAuzlJLBAgQIEAgt4AAzk2lIgECBAgQKE5AABdn\nqSUCBAgQIJBbQADnplKRAAECBAgUJyCAi7PUEgECBAgQyC0ggHNTqUiAAAECBIoTEMDFWWqJAAEC\nBAjkFhDAualUJECAAAECxQkI4OIstUSAAAECBHILCODcVCoSIECAAIHiBARwcZZaIkCAAAECuQUE\ncG4qFQkQIECAQHECArg4Sy0RIECAAIHcAgI4N5WKBAgQIECgOIHSBvCqVatiy5YtxS2plggQIECA\nQIkEShHAo0ePjldeeSVjWbx4cYwYMSIGDx4cAwYMiEsuuSQ2b95cIjJdIUCAAAECOy9QigBetGhR\nrF+/Pluam2++OY444ohYsWJFzJs3L5YsWRKpzESAAAECBDqTQCkCuDXok08+Gddff3307ds3Dj/8\n8Ljpppti7ty5rat4ToAAAQIEdnuB0gRw2tp9/fXX48QTT4y33nqrBfbFF1+MoUOHtrz2hAABAgQI\ndAaBbmVYiFGjRsWMGTPixhtvjLVr10aPHj1i+vTp2Zbw5MmTY86cOWXopj4QIECAAIHCBEoRwFdc\ncUWkR5qWL18e69aty56fddZZMXHixOjVq1f22j8ECBAgQKCzCJQigFtjDhw4MNIjTWl3dDoresOG\nDbl2Q69evTrWrFnTurmW52nL2tnULRyeECBAgECdBUoXwDt6PPTQQ7F06dKYMmXKjm+1eZ12Vc+a\nNatNeSp4/vnno3///hXfU0iAAAECBHa1QOkDeNKkSblNRo4cGelRaZowYUKsXLmy0lvKCBAgQIDA\nLhcozVnQOy75xo0bW44F7/ie1wQIECBAYHcXKG0AP/LII3H55Zfv7r76T4AAAQIEKgqUYhf0kCFD\n4s0339yug5s2bcruBZ2C+Oyzz45p06Zt974XBAgQIEBgdxYoRQCncB0zZkycf/75ccEFF2Sejz/+\neMyfPz9uueWW6Nmz5+5srO8ECBAgQKCNQCl2QZ988smxYMGC+NWvfpXtdk6B269fv+z634MOOih7\n3qbnCggQIECAwG4sUIot4OTXu3fvuO++++LBBx+M4cOHxwknnBBdu3bdjWl1nQABAgQIVBcoxRZw\n6+6de+65MXv27OyYcPo6QhMBAgQIEOiMAqXZAm6NO2jQoOze0K3LPCdAgAABAp1JoHRbwJ0J17IQ\nIECAAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAAgWoCAriajHICBAgQIFBDAQFcQ1xNEyBAgACB\nagICuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAAgWoCAria\njHICBAgQIFBDAQFcQ1xNEyBAgACBagICuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQI\nECBQQwEBXENcTRMgQIAAgWoCAriajHICBAgQIFBDAQFcQ1xNEyBAgACBagICuJqMcgIECBAgUEMB\nAVxDXE0TIECAAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAAgWoCAriajHICBAgQIFBDAQFcQ1xN\nEyBAgACBagICuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAA\ngWoCAriajHICBAgQIFBDAQFcQ1xNEyBAgACBagICuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4\nmoxyAgQIECBQQwEBXENcTRMgQIAAgWoCAriajHICBAgQIFBDAQFcQ1xNEyBAgACBagICuJqMcgIE\nCBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAAgWoCAriajHICBAgQIFBD\nAQFcQ1xNEyBAgACBagICuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQIECBQQwEBXENc\nTRMgQIAAgWoCAriajHICBAgQIFBDAQFcQ1xNEyBAgACBagICuJqMcgIECBAgUEMBAVxDXE0TIECA\nAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAAgWoCAriajHICBAgQIFBDAQFcQ1xNEyBAgACBagIC\nuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQIECBQQwEBXENcTRMgQIAAgWoCAriajHIC\nBAgQIFBDAQFcQ1xNEyBAgACBagICuJqMcgIECBAgUEMBAVxDXE0TIECAAIFqAgK4moxyAgQIECBQ\nQwEBXENcTRMgQIAAgWoCpQvgLVu2xOrVq6v1VzkBAgQIEOgUAqUI4E2bNsU111wTgwcPjj333DP6\n9u0bPXv2jKOPPjqmTZvWKaAtBAECBAgQaC3QrfWLej0fP358rFy5MmbOnBmHHnpoFr7r1q2Ll156\nKS677LLYuHFjXHzxxfXqnvkSIECAAIHCBUqxBTx79uy466674phjjolevXpFly5dYp999olhw4bF\n7bffHo8//njhC65BAgQIECBQT4FSBHDa1fzMM89UdHjiiSdiv/32q/jerih88skns93gP/jBD3bF\n7MyDAAECBBpEoBS7oG+44YY477zz4rbbbovDDjssevfuHWvXro2XX3450klZs2bNqstwXHDBBdkx\n6VNOOSW+/vWvxz333BPf+973Yo89SvF3S11MzJQAAQIEihEoRQAPHTo0Fi5cGPPnz48lS5Zkx4PT\nVm867jt8+PBsl3Qxi5u/lenTp2fHoH/2s59lHzr//PNj7Nix8cADD8To0aPzN6QmAQIECBCoIFCK\nAE796tGjR5x22mlturh48eLYsGFDpJD+XdP9998fjz76aMVqP//5z2PQoEEV36tU+MILL2Rb5K3f\nu+iii7It4NZlnhMgQIAAgY4IlCaAq3X+oYceiqVLl8aUKVOqVWkp/9znPhef+tSnWl63fpLaWb9+\nfeui93yedoOn8D/55JNb6qWt9FRuIkCAAAECOytQ+gCeNGlS7mVMW9HpUWlKwfnuu+9Weqti2V/8\nxV/EyJEjY8CAAfGxj30snn322Rg3blysWbOmYn2FBAgQIECgPQKlDeB07W+6QUe9tjj333//7PKn\nK6+8Mu67775Ir5ctW5ZdHtUeYHUJECBAgEAlgdIG8COPPJJdmjR16tRK/d4lZemOXOnMZxMBAgQI\nEChaoBQBPGTIkHjzzTe3W7a09ZsuQUpBfPbZZ7sl5XY6XhAgQIDA7i5QigBO93seM2ZMpEt90rW3\naUp3v0qXJd1yyy3ZrSl3d2j9J0CAAAECrQVKcUeJdKbxggUL4le/+lVcfvnlWeD269cvuy3lQQcd\nFOm5iQABAgQIdCaBUmwBJ9B0slU62enBBx/Mbr5xwgknRNeuXTuTtWUhQIAAAQItAqXYAm7pTfOT\nc889N9KXM6RjwukSIBMBAgQIEOiMAqXZAm6Nm+5YNWPGjNZFnhMgQIAAgU4lULot4E6la2EIECBA\ngEAVAQFcBUYxAQIECBCopUCXpuapljMoS9vpyxVGjBiR60sdduxz+q7iare43LGu1x0XSNd+d+nS\nJbp3797xRnwyl0C6L3rPnj1z1VWp4wLpjn5pfXZCaccN83xyW4yddNJJeapvV+e1116Lp556KgYO\nHLhd+a540TABvDOYp556asydO3dnmvDZHAKTJ0+O/v37Z/fgzlFdlZ0QsE7vBF47Pnr11VfHpz/9\n6TjxxBPb8SlV2yvwxhtvxPjx43e7b6uzC7q9I60+AQIECBAoQEAAF4CoCQIECBAg0F4BAdxeMfUJ\nECBAgEABAgK4AERNECBAgACB9goI4PaKqU+AAAECBAoQEMAFIGqCAAECBAi0V8BlSDnEXn/99Tjg\ngANy1FRlZwTWrVuXXS/p+tSdUcz3Wet0PqedrfX2229n11u/733v29mmfP49BLZu3Zp9f8D+++//\nHrXK95YALt+Y6BEBAgQINICAXdANMMgWkQABAgTKJyCAyzcmekSAAAECDSAggBtgkC0iAQIECJRP\nQACXb0z0iAABAgQaQEAAN8AgW0QCBAgQKJ+AAC7fmOgRAQIECDSAgABugEG2iAQIECBQPgEBvMOY\npC92fvfdd3co9bIWAps3b65Fs9okQIDAbiEggFsNU7qbyrnnnhvf+MY3WpVu/3Tu3Llx8sknxyGH\nHBLnnHNOrF69evsKXuUSmD59egwbNqxq3QULFsSBBx643WP58uVV63ujrUAyPv300+PYY4+N888/\nP15++eW2lZpLrNMVWXIXvvTSS/GFL3whc/7EJz5R9UvhrdO5SStWTBtGEyZMiKFDh8bv//7vx223\n3VaxXiq8+eab45hjjsl+T6fnpZ2at/hMzQLN/zmamoO1qU+fPk3NA1bRZNWqVU3Nt6Rs+vd///em\nTZs2NTWvDE1//ud/XrGuwsoCzbfma/ryl7/ctN9++zUdd9xxlSs1l377299uGjNmTNP69etbHs1/\nIFWt743tBZpvNdnUv3//ppUrV2Zv3HvvvU1nnnnm9pWaX1mn25C0u+CTn/xk03e+853sc81/JDY1\n3w6xxb11Y9bp1hrtf3777bc3feYzn2lqDuKm//mf/2n64Ac/2DR//vw2DT344INNf/iHf9i0Zs2a\npvT/oPkP0KZZs2a1qVeGAlvA//unUfN/oLj00kuzv2Sr/bWU/oI98sgjs7+sunfvHuPHj49HH320\nWnXlFQTmzJkT73//+yN5v9f0wgsvxAknnBBvvPFGNIdE9pkuXbq810e810og7c1p/kUUzSGclaat\n4Hnz5rWq8f+fWqfbkLSrIDl/6Utfavm90RwKsffee8e//du/tWnHOt2GpF0FF110UfzDP/xD7LHH\nHtmjeSOo4uHCH/zgB9ken3322ScGDBiQjc1jjz3WrnntqsoC+H+l77jjjvjc5z73nu7Lli3b7ksZ\n0i+3tWvXxm9/+9v3/Jw3/09g5MiR8fWvfz322muv/yus8Cz9svq7v/u7aN5qi4MPPji+8pWvVKil\nqJpACoLhw4e3vH333XfHiBEjWl5ve2Kd3ibRsZ8pDM4+++xIf5CnKf2BmQ5LVTq8Yp3umPG2T6Uv\ntEh/3Hz3u9+Nj3/849n6XMl5x3U6hfB///d/b2umVD8FcDuG46233sq+2WTbR7aFyIYNG7YV+VmQ\nwB/8wR/EPffcE6+++mq2NXHnnXdmW8IFNd9QzUydOjVmzJiR/UGz44Jbp3cU6fjrtK7+2Z/9WXzz\nm9+MD3zgA20ask63IelQQdoTlo4Bp703lc5r2HGdTnvcmg9ldWhetf6QAG6HcL9+/SJ9Zd626Z13\n3okePXpE83HjbUV+FiQwefLk7K/c1Fw66aL5mI7d/R2wveuuu2LSpEnxwx/+MAYNGtSmBet0G5IO\nFbzyyitx6qmnxnXXXdeyO3rHhqzTO4p07PXnP//5uO+++7LfCemPnR2nHdfp9Ds77REq4ySA2zEq\n6RfYkiVLWj6Rng8ePLjltSfFCGzcuDH++q//OtLPbVPay9B84ta2l37mEEjH2a+//vosfNO5C5Um\n63QllfaVvfbaa3HGGWfEtddeG+PGjav4Yet0RZZ2FTafSBjPP/98y2eOOuqo+OUvf9nyetuTtE4v\nXbp028vsd3ZZf08L4JZhqvwkHc9JWw9pSpd0pP9s6ThPOu576623xmc/+9nKH1TaboF0Ocybb76Z\n7VV4+umns13QqZH0n27hwoXZ8eB2N9qgH/j1r38dzWebZ8fL0l//6Yvh0yNN1uliV4q023nUqFHZ\nlu8253SCUJqs08VZJ9O0h2HLli3RfIZzthWc9jqkKe2KXrRoUfY8XUqaTtZasWJFFr7pmHG6ZLSU\nUxlOxS5TH5rPaNzuMqQf/ehHTc3HEFq6mE5x79WrV9PAgQObTjvttKbm3dAt73mSX+CZZ55pcxlS\numxm5syZWSPPPfdc00knndQ0ZMiQpubjaU3/9E//lL9xNZsmTpzY1PwLp80jXdZlnS5uBfnpT3/a\nxji5NwdANhPrdHHWad0977zzmj70oQ9lj6uuuqrpN7/5TTaDSy65pOnCCy/MnqfLFdPloen3RvMJ\nWE1f+9rXiutEwS11Se2V8i+DEncq/QWWjv869lv7QUpbFOmElnS2qal2Atbp2tnu2LJ1ekeR9r1O\nJ1SlM6K7dev2nh9Mx35TvfQo6ySAyzoy+kWAAAECnVrAZkWnHl4LR4AAAQJlFRDAZR0Z/SJAgACB\nTi0ggDv18Fo4AgQIECirgAAu68joFwECBAh0agEB3KmH18IRIECAQFkFBHBZR0a/CBAgQKBTCwjg\nTj28Fo4AAQIEyioggMs6MvpFgAABAp1aQAB36uG1cAQIECBQVgEBXNaR0S8CBAgQ6NQCArhTD6+F\nI0CAAIGyCgjgso6MfhEgQIBApxYQwJ16eC0cAQIECJRVQACXdWT0iwABAgQ6tYAA7tTDa+EIECBA\noKwCArisI6NfBAgQINCpBQRwpx5eC0eAAAECZRUQwGUdGf0iQIAAgU4tIIA79fBauEYQ+K//+q+4\n8847O7yorT//05/+NHr16hXPP/98S3tvvPFGHHLIIfHYY4+1lHlCgMDOCwjgnTfUAoG6Cjz77LMx\ne/bsDveh9ec/9rGPxdVXXx2f/exnIwXvb3/72zjnnHPiT/7kT7KfHZ6JDxIg0EagS1Pz1KZUAQEC\nu4XAihUr4qMf/Wi888478elPfzoeeOCB+NGPfhSXXnppLF26NE4//fS4++67o1+/fvHqq6/G6NGj\n4xe/+EUMGTIkJk+eHAcddFCbz2/dujVOO+206N+/fxx44IHx4x//OH7yk5/EnnvuuVuY6CSB3UVA\nAO8uI6WfBCoIpLC899574+GHH84ev/nNb+Kwww6Lb33rW/GJT3wirrnmmujbt2/ceuutMXLkyDju\nuONiwoQJMXXq1Jg2bVosWLBgu8+n3c9p+s///M849thjY4899oif/exn2S7oCrNXRIDATgjYBb0T\neD5KoN4CKSB79uwZ3bt3z47dPvroo3HUUUdlu4xT+bXXXhuzZs3KutmtW7f413/911i8eHF8+ctf\nzo7z7vj5bcuz7777Rp8+faJr167Ru3fvbcV+EiBQoIAALhBTUwTqLZBOqHrxxRfj937v97LHxz/+\n8VizZk0sX748/v7v/z42b94c6TjvkUceGQ8++GDV7l511VVZnbQV/Fd/9VdV63mDAIGOC3Tr+Ed9\nkgCBsgmkcD3ppJO2OykrHSc+4IADYtWqVfHII49kx4u/853vZMeDzzrrrDaL8PTTT8f999+fBfmW\nLVviwx/+cMycOTNGjBjRpq4CAgQ6LmALuON2PkmgFAJpV/PatWuzvpxxxhnZruWFCxdmr9NJWSlk\n07HiCy+8MDv2m44Jjxo1Kt73vvdFOgez9efTyVxjxoyJW265JTsB69BDD40bb7wxxo0bF+vWrSvF\n8uoEgc4i4CSszjKSlqNhBZYsWZKdyTxo0KB44YUXsrObv/KVr8TAgQNjr732yk7ISlvF6fjv2LFj\ns0uL0iVGX/3qV+PKK6+M1p8//vjj4z/+4z9izpw50aVLl8z03XffjWHDhsXQoUPjrrvualhnC06g\naAEBXLSo9gjUQSBt4aZrdlPgpimFZjr2m06m2nFavXp17L333pFOyto27fj5beV+EiBQOwEBXDtb\nLRMgQIAAgaoCjgFXpfEGAQIECBConYAArp2tlgkQIECAQFUBAVyVxhsECBAgQKB2AgK4drZaJkCA\nAAECVQUEcFUabxAgQIAAgdoJCODa2WqZAAECBAhUFRDAVWm8QYAAAQIEaicggGtnq2UCBAgQIFBV\nQABXpfEGAQIECBConYAArp2tlgkQIECAQFUBAVyVxhsECBAgQKB2AgK4drZaJkCAAAECVQUEcFUa\nbxAgQIAAgdoJCODa2WqZAAECBAhUFRDAVWm8QYAAAQIEaicggGtnq2UCBAgQIFBV4P8BuSM6JoXy\ngrEAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R hist(bob$$A)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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V5zy2OPcPi3Mo3/T49QiEfgjRK7avueYa46TbzszMNMu5+9EPQu4y06ZNM5Od0wrmtwaw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\nnm06Co4AAggg4GWB/wVEblsTYSbe7wAAAABJRU5ErkJggg==\n"
      },
      {
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "array([<rpy2.rinterface.SexpVector - Python:0x10acbb210 / R:0x1083c6028>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb1e0 / R:0x10868d608>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb240 / R:0x1085d40c8>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb258 / R:0x1085d3fa8>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb270 / R:0x1085d3e88>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb288 / R:0x10791fca8>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb2a0 / R:0x107910d48>], dtype=object)"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%R hist(testX)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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33XabtGnTRpo1aybDhg2TgwcPVqAqLIIAAggggEDsCFgRwA8//LAcf/zxcuqp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\nrkJggg==\n"
      },
      {
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "array([<rpy2.rinterface.SexpVector - Python:0x10acbb318 / R:0x108020f10>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb2e8 / R:0x10851c740>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb348 / R:0x10860c560>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb360 / R:0x10860c3b0>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb378 / R:0x10860c320>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb390 / R:0x108718988>,\n",
        "       <rpy2.rinterface.SexpVector - Python:0x10acbb3a8 / R:0x108718958>], dtype=object)"
       ]
      }
     ],
     "prompt_number": 7
    }
   ],
   "metadata": {}
  }
 ]
}