dice.ipynb

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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Dice API Interface"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "More info in the [documentation](http://www.dice.com/common/content/util/apidoc/jobsearch.html).\n",
      "\n",
      "Supported parameters:\n",
      "* *direct* - (optional) if the value of this parameter is \"1\" then jobs returned will be direct hire\n",
      "* *areacode* - (optional) specify the jobs area code\n",
      "* *country* - (optional) specify the jobs ISO 3166 country code\n",
      "* *state* - (optional) specify the jobs United States Post Office state code\n",
      "* *skill* - (optional) specify search text for the jobs skill property\n",
      "* *city* - (optional) specify the jobs United States Post Office ZipCode as the center of 40 mile radius\n",
      "* *text* - (optional) specify search text for the jobs entire body\n",
      "* *ip* - (optional) specify an IP address that will be used to look up a geocode which will be used in the search\n",
      "* *age* - (optional) specify a posting age (a.k.a. days back)\n",
      "* *diceid* - (optional) specify a Dice customer ID to find only jobs from that company\n",
      "* *page* - (optional) specify a page number of the results to be displayed (1 based)\n",
      "* *pgcnt* - (optional) specify the number of results per page\n",
      "* *sort* - (optional) specify a sort paremeter; sort=1 sorts by posted age, sort=2 sorts by job title, sort=3 sorts by company, sort=4 sorts by location\n",
      "* *sd* - (optional) sort direction; sd=a sort order is ASCENDING sd=d sort order is DESCENDING"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sys\n",
      "import requests\n",
      "import pandas as pd\n",
      "import numpy as np\n",
      "from datetime import datetime, date\n",
      "import time"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "domain = 'http://service.dice.com'\n",
      "path = '/api/rest/jobsearch/v1/simple.json'\n",
      "parameters = {'text': 'data', 'page': 1, 'pgcnt': 5}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "response = requests.get(domain + path, params = parameters)\n",
      "data = response.json()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "{u'count': 31232,\n",
        " u'firstDocument': 1,\n",
        " u'lastDocument': 5,\n",
        " u'nextUrl': u'/api/rest/jobsearch/v1/simple.json?areacode=&country=&state=&skill=&city=&text=data&pgcnt=5&ip=&diceid=&page=2',\n",
        " u'resultItemList': [{u'company': u'DCM Data Systems',\n",
        "   u'date': u'2017-02-10',\n",
        "   u'detailUrl': u'http://www.dice.com/job/result/10109811/DPCMSDBDLMI?src=19',\n",
        "   u'jobTitle': u'Syncsort DMX : Big Data',\n",
        "   u'location': u'Lansing, MI'},\n",
        "  {u'company': u'Data Resource Group',\n",
        "   u'date': u'2017-02-06',\n",
        "   u'detailUrl': u'http://www.dice.com/job/result/10354693/827902?src=19',\n",
        "   u'jobTitle': u'Data Analyst',\n",
        "   u'location': u'Beaverton, OR'},\n",
        "  {u'company': u'Data Resource Technologies',\n",
        "   u'date': u'2017-02-07',\n",
        "   u'detailUrl': u'http://www.dice.com/job/result/10124769/SASE-GA-JM?src=19',\n",
        "   u'jobTitle': u'Secure Assets Data Analyst',\n",
        "   u'location': u'Atlanta, GA'},\n",
        "  {u'company': u'DCM Data Systems',\n",
        "   u'date': u'2017-02-08',\n",
        "   u'detailUrl': u'http://www.dice.com/job/result/10109811/DGCESESRCA?src=19',\n",
        "   u'jobTitle': u'Software Engineer  - Big Data',\n",
        "   u'location': u'San Ramon, CA'},\n",
        "  {u'company': u'Projas Technologies, LLC',\n",
        "   u'date': u'2017-02-11',\n",
        "   u'detailUrl': u'http://www.dice.com/job/result/10126850/DATA-ENGINEER?src=19',\n",
        "   u'jobTitle': u'Senior Data Engineer *** 200K or contract to hire ***',\n",
        "   u'location': u'San Francisco, CA'}]}"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Example empty list (no results):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "requests.get(domain + path, params = {'text': 'janitor', 'city': '10001'}).json()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "{u'count': 0, u'firstDocument': 0, u'lastDocument': 0}"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Example overflown list (i.e., over the page limit):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "requests.get(domain + path, params = {'text': 'sql', 'city': '10001', 'page': 100}).json()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "{u'count': 2306, u'firstDocument': 0, u'lastDocument': 0}"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.DataFrame(data['resultItemList'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>company</th>\n",
        "      <th>date</th>\n",
        "      <th>detailUrl</th>\n",
        "      <th>jobTitle</th>\n",
        "      <th>location</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>DCM Data Systems</td>\n",
        "      <td>2017-02-10</td>\n",
        "      <td>http://www.dice.com/job/result/10109811/DPCMSD...</td>\n",
        "      <td>Syncsort DMX : Big Data</td>\n",
        "      <td>Lansing, MI</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Data Resource Group</td>\n",
        "      <td>2017-02-06</td>\n",
        "      <td>http://www.dice.com/job/result/10354693/827902...</td>\n",
        "      <td>Data Analyst</td>\n",
        "      <td>Beaverton, OR</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Data Resource Technologies</td>\n",
        "      <td>2017-02-07</td>\n",
        "      <td>http://www.dice.com/job/result/10124769/SASE-G...</td>\n",
        "      <td>Secure Assets Data Analyst</td>\n",
        "      <td>Atlanta, GA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>DCM Data Systems</td>\n",
        "      <td>2017-02-08</td>\n",
        "      <td>http://www.dice.com/job/result/10109811/DGCESE...</td>\n",
        "      <td>Software Engineer  - Big Data</td>\n",
        "      <td>San Ramon, CA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Projas Technologies, LLC</td>\n",
        "      <td>2017-02-11</td>\n",
        "      <td>http://www.dice.com/job/result/10126850/DATA-E...</td>\n",
        "      <td>Senior Data Engineer *** 200K or contract to h...</td>\n",
        "      <td>San Francisco, CA</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "                      company        date  \\\n",
        "0            DCM Data Systems  2017-02-10   \n",
        "1         Data Resource Group  2017-02-06   \n",
        "2  Data Resource Technologies  2017-02-07   \n",
        "3            DCM Data Systems  2017-02-08   \n",
        "4    Projas Technologies, LLC  2017-02-11   \n",
        "\n",
        "                                           detailUrl  \\\n",
        "0  http://www.dice.com/job/result/10109811/DPCMSD...   \n",
        "1  http://www.dice.com/job/result/10354693/827902...   \n",
        "2  http://www.dice.com/job/result/10124769/SASE-G...   \n",
        "3  http://www.dice.com/job/result/10109811/DGCESE...   \n",
        "4  http://www.dice.com/job/result/10126850/DATA-E...   \n",
        "\n",
        "                                            jobTitle           location  \n",
        "0                            Syncsort DMX : Big Data        Lansing, MI  \n",
        "1                                       Data Analyst      Beaverton, OR  \n",
        "2                         Secure Assets Data Analyst        Atlanta, GA  \n",
        "3                      Software Engineer  - Big Data      San Ramon, CA  \n",
        "4  Senior Data Engineer *** 200K or contract to h...  San Francisco, CA  "
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def get_job_listing(**kwargs):\n",
      "    parameters = kwargs\n",
      "    all_pages = False\n",
      "    if not parameters.has_key('pgcnt'):\n",
      "        parameters['pgcnt'] = 50\n",
      "    elif parameters['pgcnt'] > 50:\n",
      "        # That seems to be as much as they'll give\n",
      "        parameters['pgcnt'] = 50\n",
      "    if not parameters.has_key('page'):\n",
      "        parameters['page'] = 1\n",
      "        all_pages = True\n",
      "    df = pd.DataFrame()\n",
      "    df_, totalResults = _get_sub_listing(parameters)\n",
      "    resultsPerPage = parameters['pgcnt']\n",
      "    if len(df_) == 0:\n",
      "        return df\n",
      "    df = df.append(df_)\n",
      "    if all_pages:\n",
      "        percent = 0\n",
      "        max_page = (totalResults-1)/resultsPerPage + 1\n",
      "        print 'Total pages:', max_page\n",
      "        sys.stdout.flush()\n",
      "        for page in xrange(2, max_page + 1):\n",
      "            time.sleep(2)\n",
      "            parameters['page'] = page\n",
      "            df_ = _get_sub_listing(parameters)[0]\n",
      "            while(percent < page*100/max_page):\n",
      "                percent += 1\n",
      "                if percent % 10 == 0:\n",
      "                    sys.stdout.write(str(percent) + '%')\n",
      "                else:\n",
      "                    sys.stdout.write('.')\n",
      "                sys.stdout.flush()\n",
      "            if len(df_) > 0:\n",
      "                df = df.append(df_)\n",
      "            else:\n",
      "                return df.reset_index(drop = True)\n",
      "    return df.reset_index(drop = True)\n",
      "\n",
      "def _get_sub_listing(parameters):\n",
      "    root = 'http://service.dice.com'\n",
      "    path = '/api/rest/jobsearch/v1/simple.json'\n",
      "    response = requests.get(root + path, params=parameters)\n",
      "    data = response.json()\n",
      "    totalResults = data['count']\n",
      "    if data.has_key('resultItemList'):\n",
      "        df = pd.DataFrame(data['resultItemList'])\n",
      "        if 'date' in df.columns:\n",
      "            #df['date'] = df['date'].apply(lambda l: datetime.strptime(l, \"%Y-%m-%d\").date())\n",
      "            df['date'] = pd.to_datetime(df['date'])\n",
      "        return df, totalResults\n",
      "    return pd.DataFrame(), totalResults"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "listing = get_job_listing(text = 'data', city = '10001', sort = 1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Total pages: 75\n"
       ]
      },
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       "text": [
        "80%"
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        "."
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        "."
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        "."
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        "."
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        "."
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        "."
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        "."
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        "."
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        "."
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       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "90%"
       ]
      },
      {
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       "stream": "stdout",
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        "."
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      },
      {
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        "."
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        "."
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       "stream": "stdout",
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        "."
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        "."
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      },
      {
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        "."
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      {
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        "."
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      {
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        "."
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      },
      {
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       "stream": "stdout",
       "text": [
        "."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "100%"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "listing.dtypes"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "company              object\n",
        "date         datetime64[ns]\n",
        "detailUrl            object\n",
        "jobTitle             object\n",
        "location             object\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "listing.describe()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>company</th>\n",
        "      <th>date</th>\n",
        "      <th>detailUrl</th>\n",
        "      <th>jobTitle</th>\n",
        "      <th>location</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
        "      <td>3709</td>\n",
        "      <td>3709</td>\n",
        "      <td>3709</td>\n",
        "      <td>3709</td>\n",
        "      <td>3709</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>unique</th>\n",
        "      <td>1046</td>\n",
        "      <td>28</td>\n",
        "      <td>3639</td>\n",
        "      <td>3049</td>\n",
        "      <td>253</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>top</th>\n",
        "      <td>CyberCoders</td>\n",
        "      <td>2017-02-11 00:00:00</td>\n",
        "      <td>http://www.dice.com/job/result/10225460/855344...</td>\n",
        "      <td>Business Analyst</td>\n",
        "      <td>New York, NY</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>freq</th>\n",
        "      <td>153</td>\n",
        "      <td>1211</td>\n",
        "      <td>2</td>\n",
        "      <td>26</td>\n",
        "      <td>1451</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>first</th>\n",
        "      <td>NaN</td>\n",
        "      <td>2017-01-12 00:00:00</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>last</th>\n",
        "      <td>NaN</td>\n",
        "      <td>2017-02-11 00:00:00</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "            company                 date  \\\n",
        "count          3709                 3709   \n",
        "unique         1046                   28   \n",
        "top     CyberCoders  2017-02-11 00:00:00   \n",
        "freq            153                 1211   \n",
        "first           NaN  2017-01-12 00:00:00   \n",
        "last            NaN  2017-02-11 00:00:00   \n",
        "\n",
        "                                                detailUrl          jobTitle  \\\n",
        "count                                                3709              3709   \n",
        "unique                                               3639              3049   \n",
        "top     http://www.dice.com/job/result/10225460/855344...  Business Analyst   \n",
        "freq                                                    2                26   \n",
        "first                                                 NaN               NaN   \n",
        "last                                                  NaN               NaN   \n",
        "\n",
        "            location  \n",
        "count           3709  \n",
        "unique           253  \n",
        "top     New York, NY  \n",
        "freq            1451  \n",
        "first            NaN  \n",
        "last             NaN  "
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "byCompany = listing.groupby('company')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "byCompany['company'].agg('count').sort_values(ascending=False)[0:20]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "company\n",
        "CyberCoders                       153\n",
        "Robert Half Technology             76\n",
        "Kforce Inc.                        68\n",
        "Verizon                            56\n",
        "Deloitte                           54\n",
        "Gambit Technologies                51\n",
        "Software Guidance & Assistance     41\n",
        "Bloomberg L.P.                     35\n",
        "Princeton Information Ltd          33\n",
        "Mitchell Martin, Inc.              31\n",
        "UBS                                31\n",
        "TEKsystems, Inc.                   31\n",
        "eclaro                             31\n",
        "The Judge Group                    29\n",
        "U.S. Tech Solutions Inc.           29\n",
        "Cognizant Technology Solutions     28\n",
        "Synechron Inc.                     26\n",
        "Net2Source Inc.                    25\n",
        "Hyatt Leader                       24\n",
        "Collabera                          23\n",
        "Name: company, dtype: int64"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.hist(listing['date'].apply(lambda l: l.toordinal()) - date(1970, 1, 1).toordinal() - time.time()/24/60/60, bins=35)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "(array([  4.00000000e+01,   2.40000000e+01,   0.00000000e+00,\n",
        "          1.00000000e+00,   2.10000000e+01,   2.00000000e+01,\n",
        "          0.00000000e+00,   3.30000000e+01,   2.70000000e+01,\n",
        "          4.80000000e+01,   0.00000000e+00,   6.00000000e+00,\n",
        "          4.50000000e+01,   0.00000000e+00,   4.80000000e+01,\n",
        "          4.60000000e+01,   5.60000000e+01,   6.80000000e+01,\n",
        "          0.00000000e+00,   4.00000000e+00,   0.00000000e+00,\n",
        "          6.90000000e+01,   6.50000000e+01,   1.20000000e+02,\n",
        "          7.80000000e+01,   9.50000000e+01,   8.00000000e+00,\n",
        "          0.00000000e+00,   1.00000000e+01,   1.47000000e+02,\n",
        "          1.47000000e+02,   2.40000000e+02,   2.91000000e+02,\n",
        "          7.41000000e+02,   1.21100000e+03]),\n",
        " array([-31.21126356, -30.3541207 , -29.49697784, -28.63983498,\n",
        "        -27.78269213, -26.92554927, -26.06840641, -25.21126356,\n",
        "        -24.3541207 , -23.49697784, -22.63983498, -21.78269213,\n",
        "        -20.92554927, -20.06840641, -19.21126356, -18.3541207 ,\n",
        "        -17.49697784, -16.63983498, -15.78269213, -14.92554927,\n",
        "        -14.06840641, -13.21126356, -12.3541207 , -11.49697784,\n",
        "        -10.63983498,  -9.78269213,  -8.92554927,  -8.06840641,\n",
        "         -7.21126356,  -6.3541207 ,  -5.49697784,  -4.63983498,\n",
        "         -3.78269213,  -2.92554927,  -2.06840641,  -1.21126356]),\n",
        " <a list of 35 Patch objects>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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aQ9+vYZCkFjH0JalFDH1JahFDX9KqM+wbMpNwxBEvWJXfojmMF3IlrTrDL8LC4b8Q64Vc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\nUAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f7101266bd0>"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dates = listing.groupby('date')['date'].count()\n",
      "plt.bar(dates.index, dates)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "<Container object of 28 artists>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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YG1gFnBIRG/M2XwZmAS8AZ0fE4pr9esRgZl1lvI0Y/AM3M7MBjLfA4D+JYWZmBQcGMzMr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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f7101087b90>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for s in listing.loc[listing.duplicated([col for col in listing.columns if col != 'detailUrl'], keep=False),:].sort_values('company')['detailUrl']:\n",
      "    print s"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "http://www.dice.com/job/result/10123488/16-01014?src=19\n",
        "http://www.dice.com/job/result/10123488/16-01303?src=19\n",
        "http://www.dice.com/job/result/10123488/17-00178?src=19\n",
        "http://www.dice.com/job/result/10123488/16-01303?src=19\n",
        "http://www.dice.com/job/result/10123488/16-01014?src=19\n",
        "http://www.dice.com/job/result/10123488/17-00178?src=19\n",
        "http://www.dice.com/job/result/10201176/PM_Warehouse?src=19\n",
        "http://www.dice.com/job/result/10201176/PMIAM?src=19\n",
        "http://www.dice.com/job/result/analytic/TV517-22399?src=19\n",
        "http://www.dice.com/job/result/analytic/TV517-22399?src=19\n",
        "http://www.dice.com/job/result/10441603/861407?src=19\n",
        "http://www.dice.com/job/result/10441603/861407?src=19\n",
        "http://www.dice.com/job/result/10340096/-2-417BM?src=19\n",
        "http://www.dice.com/job/result/10340096/763258?src=19\n",
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     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Looks like some results are duplicates, while others are not. Can only tell by actually visiting the pages."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}