0.2 Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "cannot import name certs",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-4b66ad388e97>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mgraphlab\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/mshokry/anaconda2/envs/gl-env/lib/python2.7/site-packages/graphlab/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     48\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mgraphlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutil\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mset_runtime_config\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 50\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mgraphlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0m_mt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     51\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mgraphlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maws\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0maws\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     52\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mvisualization\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/mshokry/anaconda2/envs/gl-env/lib/python2.7/site-packages/graphlab/connect/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[0;34m\"\"\" The module usage metric tracking object \"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mgraphlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mDEFAULT_CONFIG\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0m_default_local_conf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mgraphlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetric_tracker\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mMetricTracker\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0m_MetricTracker\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     32\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     33\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/mshokry/anaconda2/envs/gl-env/lib/python2.7/site-packages/graphlab/util/metric_tracker.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mthreading\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mcopy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0m_copy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mrequests\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0m_requests\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     18\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0msys\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0m_sys\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/mshokry/anaconda2/envs/gl-env/lib/python2.7/site-packages/requests/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     61\u001b[0m \u001b[0mwarnings\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msimplefilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ignore'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mDependencyWarning\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     62\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 63\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mutils\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     64\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mmodels\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mRequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mResponse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mPreparedRequest\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     65\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mapi\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhead\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpost\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdelete\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/mshokry/anaconda2/envs/gl-env/lib/python2.7/site-packages/requests/utils.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0m__version__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mcerts\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     23\u001b[0m \u001b[0;31m# to_native_string is unused here, but imported here for backwards compatibility\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0m_internal_utils\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mto_native_string\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mImportError\u001b[0m: cannot import name certs"
     ]
    }
   ],
   "source": [
    "import graphlab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[INFO] graphlab.cython.cy_server: GraphLab Create v2.1 started. Logging: /tmp/graphlab_server_1489177903.log\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This non-commercial license of GraphLab Create for academic use is assigned to msn4eg@gmail.com and will expire on December 12, 2017.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>Finished parsing file /home/mshokry/anaconda2/ml-reg/Philadelphia_Crime_Rate_noNA.csv</pre>"
      ],
      "text/plain": [
       "Finished parsing file /home/mshokry/anaconda2/ml-reg/Philadelphia_Crime_Rate_noNA.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Parsing completed. Parsed 99 lines in 0.02602 secs.</pre>"
      ],
      "text/plain": [
       "Parsing completed. Parsed 99 lines in 0.02602 secs."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------------------\n",
      "Inferred types from first 100 line(s) of file as \n",
      "column_type_hints=[int,float,float,float,float,str,str]\n",
      "If parsing fails due to incorrect types, you can correct\n",
      "the inferred type list above and pass it to read_csv in\n",
      "the column_type_hints argument\n",
      "------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>Finished parsing file /home/mshokry/anaconda2/ml-reg/Philadelphia_Crime_Rate_noNA.csv</pre>"
      ],
      "text/plain": [
       "Finished parsing file /home/mshokry/anaconda2/ml-reg/Philadelphia_Crime_Rate_noNA.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Parsing completed. Parsed 99 lines in 0.009043 secs.</pre>"
      ],
      "text/plain": [
       "Parsing completed. Parsed 99 lines in 0.009043 secs."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sales = graphlab.SFrame.read_csv('Philadelphia_Crime_Rate_noNA.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">HousePrice</th>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Brookhaven</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.8</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">20.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">-3.5</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Bryn Athyn</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Montgome</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">20.2</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">14.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.6</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Bryn Mawr</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Montgome</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">264298</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">26.4298</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">20.4</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">26.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">6.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Buckingham</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Bucks</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[99 rows x 7 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tHousePrice\tint\n",
       "\tHsPrc ($10,000)\tfloat\n",
       "\tCrimeRate\tfloat\n",
       "\tMilesPhila\tfloat\n",
       "\tPopChg\tfloat\n",
       "\tName\tstr\n",
       "\tCounty\tstr\n",
       "\n",
       "Rows: 99\n",
       "\n",
       "Data:\n",
       "+------------+-----------------+-----------+------------+--------+------------+\n",
       "| HousePrice | HsPrc ($10,000) | CrimeRate | MilesPhila | PopChg |    Name    |\n",
       "+------------+-----------------+-----------+------------+--------+------------+\n",
       "|   140463   |     14.0463     |    29.7   |    10.0    |  -1.0  |  Abington  |\n",
       "|   113033   |     11.3033     |    24.1   |    18.0    |  4.0   |   Ambler   |\n",
       "|   124186   |     12.4186     |    19.5   |    25.0    |  8.0   |   Aston    |\n",
       "|   110490   |      11.049     |    49.4   |    25.0    |  2.7   |  Bensalem  |\n",
       "|   79124    |      7.9124     |    54.1   |    19.0    |  3.9   | Bristol B. |\n",
       "|   92634    |      9.2634     |    48.6   |    20.0    |  0.6   | Bristol T. |\n",
       "|   89246    |      8.9246     |    30.8   |    15.0    |  -2.6  | Brookhaven |\n",
       "|   195145   |     19.5145     |    10.8   |    20.0    |  -3.5  | Bryn Athyn |\n",
       "|   297342   |     29.7342     |    20.2   |    14.0    |  0.6   | Bryn Mawr  |\n",
       "|   264298   |     26.4298     |    20.4   |    26.0    |  6.0   | Buckingham |\n",
       "+------------+-----------------+-----------+------------+--------+------------+\n",
       "+----------+\n",
       "|  County  |\n",
       "+----------+\n",
       "| Montgome |\n",
       "| Montgome |\n",
       "| Delaware |\n",
       "|  Bucks   |\n",
       "|  Bucks   |\n",
       "|  Bucks   |\n",
       "| Delaware |\n",
       "| Montgome |\n",
       "| Montgome |\n",
       "|  Bucks   |\n",
       "+----------+\n",
       "[99 rows x 7 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
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       "                if (typeof requirejs !== 'undefined') {\n",
       "                    // disable load timeout; ipython_app.js is large and can take a while to load.\n",
       "                    requirejs.config({waitSeconds: 0});\n",
       "                }\n",
       "\n",
       "                require(['https://static.turi.com/products/graphlab-create/2.1/canvas/js/ipython_app.js'], function(IPythonApp){\n",
       "                    var app = new IPythonApp();\n",
       "                    app.attachView('sframe','Plots', {\"selected_variable\": {\"name\": [\"sales\"], \"descriptives\": {\"rows\": 99, \"columns\": 7}, \"view_component\": \"Plots\", \"view_file\": \"sframe\", \"view_params\": {\"y\": \"HousePrice\", \"x\": \"CrimeRate\", \"columns\": [\"HousePrice\", \"HsPrc ($10,000)\", \"CrimeRate\", \"MilesPhila\", \"PopChg\", \"Name\", \"County\"], \"view\": \"Scatter Plot\"}, \"view_components\": [\"Summary\", \"Table\", \"Bar Chart\", \"BoxWhisker Plot\", \"Line Chart\", \"Scatter Plot\", \"Heat Map\", \"Plots\"], \"type\": \"SFrame\", \"columns\": [{\"dtype\": \"int\", \"name\": \"HousePrice\"}, {\"dtype\": \"float\", \"name\": \"HsPrc ($10,000)\"}, {\"dtype\": \"float\", \"name\": \"CrimeRate\"}, {\"dtype\": \"float\", \"name\": \"MilesPhila\"}, {\"dtype\": \"float\", \"name\": \"PopChg\"}, {\"dtype\": \"str\", \"name\": \"Name\"}, {\"dtype\": \"str\", \"name\": \"County\"}], \"column_identifiers\": [\"Name\", \"PopChg\", \"County\", \"HousePrice\", \"MilesPhila\", \"HsPrc ($10,000)\", \"CrimeRate\"]}, \"complete\": 1, \"ipython\": true, \"progress\": 1.0, \"data\": [[29.7, 140463], [24.1, 113033], [19.5, 124186], [49.4, 110490], [54.1, 79124], [48.6, 92634], [30.8, 89246], [10.8, 195145], [20.2, 297342], [20.4, 264298], [17.3, 134342], [50.3, 147600], [34.2, 77370], [33.7, 170822], [45.7, 40642], [22.3, 71359], [48.1, 104923], [19.4, 190317], [71.9, 215512], [45.1, 178105], [31.3, 131025], [24.9, 149844], [27.2, 170556], [17.7, 280969], [29.0, 114233], [21.4, 74502], [28.6, 475112], [29.3, 97167], [17.5, 114572], [16.5, 436348], [17.8, 389302], [17.3, 122392], [31.2, 130436], [14.5, 272790], [15.7, 194435], [28.6, 299621], [20.8, 210884], [29.3, 112471], [19.3, 93738], [39.5, 121024], [13.0, 156035], [24.1, 185404], [38.0, 126160], [40.1, 143072], [36.1, 96769], [26.6, 94014], [25.1, 118214], [14.6, 157446], [18.2, 150283], [15.3, 153842], [15.2, 197214], [17.4, 206127], [73.3, 71981], [7.1, 169401], [12.5, 99843], [45.8, 60000], [44.9, 28000], [65.0, 60000], [49.9, 61800], [54.8, 38000], [53.5, 38000], [69.9, 42000], [366.1, 96200], [24.6, 103087], [58.6, 147720], [53.2, 78175], [17.4, 92215], [15.5, 271804], [14.5, 119566], [24.1, 100231], [21.2, 95831], [9.8, 229711], [29.9, 74308], [7.2, 259506], [19.4, 159573], [41.1, 147176], [11.2, 205732], [21.2, 215783], [42.8, 116710], [9.4, 359112], [61.7, 189959], [19.4, 133198], [6.6, 242821], [15.9, 142811], [18.8, 200498], [13.2, 199065], [34.5, 93648], [22.1, 163001], [22.1, 436348], [71.9, 124478], [31.9, 168276], [44.6, 114157], [28.6, 130088], [24.0, 152624], [13.8, 174232], [29.9, 196515], [9.9, 232714], [22.6, 245920], [13.0, 130953]], \"columns\": [{\"dtype\": \"int\", \"name\": \"HousePrice\"}, {\"dtype\": \"float\", \"name\": \"HsPrc ($10,000)\"}, {\"dtype\": \"float\", \"name\": \"CrimeRate\"}, {\"dtype\": \"float\", \"name\": \"MilesPhila\"}, {\"dtype\": \"float\", \"name\": \"PopChg\"}, {\"dtype\": \"str\", \"name\": \"Name\"}, {\"dtype\": \"str\", \"name\": \"County\"}]}, e);\n",
       "                });\n",
       "            })();\n",
       "        "
      ]
     },
     "metadata": {},
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   "source": [
    "graphlab.canvas.set_target('ipynb')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "$(\"head\").append($(\"<link/>\").attr({\n",
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       "\n",
       "                if (typeof requirejs !== 'undefined') {\n",
       "                    // disable load timeout; ipython_app.js is large and can take a while to load.\n",
       "                    requirejs.config({waitSeconds: 0});\n",
       "                }\n",
       "\n",
       "                require(['https://static.turi.com/products/graphlab-create/2.1/canvas/js/ipython_app.js'], function(IPythonApp){\n",
       "                    var app = new IPythonApp();\n",
       "                    app.attachView('sframe','Plots', {\"selected_variable\": {\"name\": [\"sales\"], \"descriptives\": {\"rows\": 99, \"columns\": 7}, \"view_component\": \"Plots\", \"view_file\": \"sframe\", \"view_params\": {\"y\": \"HousePrice\", \"x\": \"CrimeRate\", \"columns\": [\"HousePrice\", \"HsPrc ($10,000)\", \"CrimeRate\", \"MilesPhila\", \"PopChg\", \"Name\", \"County\"], \"view\": \"Scatter Plot\"}, \"view_components\": [\"Summary\", \"Table\", \"Bar Chart\", \"BoxWhisker Plot\", \"Line Chart\", \"Scatter Plot\", \"Heat Map\", \"Plots\"], \"type\": \"SFrame\", \"columns\": [{\"dtype\": \"int\", \"name\": \"HousePrice\"}, {\"dtype\": \"float\", \"name\": \"HsPrc ($10,000)\"}, {\"dtype\": \"float\", \"name\": \"CrimeRate\"}, {\"dtype\": \"float\", \"name\": \"MilesPhila\"}, {\"dtype\": \"float\", \"name\": \"PopChg\"}, {\"dtype\": \"str\", \"name\": \"Name\"}, {\"dtype\": \"str\", \"name\": \"County\"}], \"column_identifiers\": [\"Name\", \"PopChg\", \"County\", \"HousePrice\", \"MilesPhila\", \"HsPrc ($10,000)\", \"CrimeRate\"]}, \"complete\": 1, \"ipython\": true, \"progress\": 1.0, \"data\": [[29.7, 140463], [24.1, 113033], [19.5, 124186], [49.4, 110490], [54.1, 79124], [48.6, 92634], [30.8, 89246], [10.8, 195145], [20.2, 297342], [20.4, 264298], [17.3, 134342], [50.3, 147600], [34.2, 77370], [33.7, 170822], [45.7, 40642], [22.3, 71359], [48.1, 104923], [19.4, 190317], [71.9, 215512], [45.1, 178105], [31.3, 131025], [24.9, 149844], [27.2, 170556], [17.7, 280969], [29.0, 114233], [21.4, 74502], [28.6, 475112], [29.3, 97167], [17.5, 114572], [16.5, 436348], [17.8, 389302], [17.3, 122392], [31.2, 130436], [14.5, 272790], [15.7, 194435], [28.6, 299621], [20.8, 210884], [29.3, 112471], [19.3, 93738], [39.5, 121024], [13.0, 156035], [24.1, 185404], [38.0, 126160], [40.1, 143072], [36.1, 96769], [26.6, 94014], [25.1, 118214], [14.6, 157446], [18.2, 150283], [15.3, 153842], [15.2, 197214], [17.4, 206127], [73.3, 71981], [7.1, 169401], [12.5, 99843], [45.8, 60000], [44.9, 28000], [65.0, 60000], [49.9, 61800], [54.8, 38000], [53.5, 38000], [69.9, 42000], [366.1, 96200], [24.6, 103087], [58.6, 147720], [53.2, 78175], [17.4, 92215], [15.5, 271804], [14.5, 119566], [24.1, 100231], [21.2, 95831], [9.8, 229711], [29.9, 74308], [7.2, 259506], [19.4, 159573], [41.1, 147176], [11.2, 205732], [21.2, 215783], [42.8, 116710], [9.4, 359112], [61.7, 189959], [19.4, 133198], [6.6, 242821], [15.9, 142811], [18.8, 200498], [13.2, 199065], [34.5, 93648], [22.1, 163001], [22.1, 436348], [71.9, 124478], [31.9, 168276], [44.6, 114157], [28.6, 130088], [24.0, 152624], [13.8, 174232], [29.9, 196515], [9.9, 232714], [22.6, 245920], [13.0, 130953]], \"columns\": [{\"dtype\": \"int\", \"name\": \"HousePrice\"}, {\"dtype\": \"float\", \"name\": \"HsPrc ($10,000)\"}, {\"dtype\": \"float\", \"name\": \"CrimeRate\"}, {\"dtype\": \"float\", \"name\": \"MilesPhila\"}, {\"dtype\": \"float\", \"name\": \"PopChg\"}, {\"dtype\": \"str\", \"name\": \"Name\"}, {\"dtype\": \"str\", \"name\": \"County\"}]}, e);\n",
       "                });\n",
       "            })();\n",
       "        "
      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "sales.show(view=\"Scatter Plot\", x=\"CrimeRate\", y=\"HousePrice\")"
   ]
  },
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