bogus_check_counts.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5LBBUqGyJQ8Q"
   },
   "source": [
    "### Set up environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 213
    },
    "colab_type": "code",
    "id": "bpG2zPdyJNtf",
    "outputId": "bc9f2919-8c18-4b9a-95eb-fa50eb13d21b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting oscn==0.0.0.25\n",
      "  Downloading https://files.pythonhosted.org/packages/91/2b/362a3d8533b83b72dbd5201686baba4515c0b62041c429dc0dafb24933ba/oscn-0.0.0.25-py3-none-any.whl\n",
      "Requirement already satisfied: beautifulsoup4 in /Users/owner/projects/python_envs/oscn/lib/python3.6/site-packages (from oscn==0.0.0.25) (4.6.0)\n",
      "Requirement already satisfied: requests in /Users/owner/projects/python_envs/oscn/lib/python3.6/site-packages (from oscn==0.0.0.25) (2.20.0)\n",
      "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /Users/owner/projects/python_envs/oscn/lib/python3.6/site-packages (from requests->oscn==0.0.0.25) (1.23)\n",
      "Requirement already satisfied: idna<2.8,>=2.5 in /Users/owner/projects/python_envs/oscn/lib/python3.6/site-packages (from requests->oscn==0.0.0.25) (2.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/owner/projects/python_envs/oscn/lib/python3.6/site-packages (from requests->oscn==0.0.0.25) (2018.4.16)\n",
      "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /Users/owner/projects/python_envs/oscn/lib/python3.6/site-packages (from requests->oscn==0.0.0.25) (3.0.4)\n",
      "Installing collected packages: oscn\n",
      "  Found existing installation: oscn 0.0.0.31\n",
      "    Uninstalling oscn-0.0.0.31:\n",
      "      Successfully uninstalled oscn-0.0.0.31\n",
      "Successfully installed oscn-0.0.0.25\n"
     ]
    }
   ],
   "source": [
    "!pip install oscn==0.0.0.25\n",
    "\n",
    "import oscn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<oscn.parse.docket.DocketMinute at 0x10fcb9c50>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcb9cf8>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcb9860>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcb9d68>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcb9da0>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcb9f98>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2048>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2080>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc20f0>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2160>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc21d0>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2240>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc22b0>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2358>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2390>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2400>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc24a8>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2518>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2550>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc25f8>,\n",
       " <oscn.parse.docket.DocketMinute at 0x10fcc2668>]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oscn.request.Case().docket"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SpYkP0g316dT"
   },
   "source": [
    "### Set up the OSCN information needed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ePxYAgknPIYw"
   },
   "outputs": [],
   "source": [
    "\n",
    "years = ['2017','2018']\n",
    "counties = ['tulsa', 'mayes', 'delaware']\n",
    "types =['CM','CF']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Request the cases from OSCN and save as files\n",
    "This takes a couple hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 623
    },
    "colab_type": "code",
    "id": "901XB5X2PLMQ",
    "outputId": "0a055488-40dd-4cd3-ce7e-6fbc8f3925e6"
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "\n",
    "# for county in counties:\n",
    "#   for year in years:\n",
    "#     for type in types:      \n",
    "#       cases=oscn.request.CaseList(type=type, year=year,county=county)\n",
    "#       all_cases = [c for c in cases]\n",
    "#       file_name = f'data/{type}.{county}.{year}.oscn'\n",
    "#       f = open(file_name, 'wb')\n",
    "#       z(all_cases, f)\n",
    "#       f.close()\n",
    "#       print(f'{file_name}: {len(all_cases)}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Retrieve the saved files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 237
    },
    "colab_type": "code",
    "id": "qVsbnkB-1v6T",
    "outputId": "80d17652-1b74-4cc6-b8a6-6b611e3a1bfe",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data/tulsa.2017.CM.cases added 6050\n",
      "data/tulsa.2017.CF.cases added 6587\n",
      "data/tulsa.2018.CM.cases added 5024\n",
      "data/tulsa.2018.CF.cases added 4834\n",
      "data/mayes.2017.CM.cases added 629\n",
      "data/mayes.2017.CF.cases added 425\n",
      "data/mayes.2018.CM.cases added 451\n",
      "data/mayes.2018.CF.cases added 332\n",
      "data/delaware.2017.CM.cases added 930\n",
      "data/delaware.2017.CF.cases added 440\n",
      "data/delaware.2018.CM.cases added 861\n",
      "data/delaware.2018.CF.cases added 433\n",
      "counted case: 26996 length saved 26996\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "import zlib\n",
    "\n",
    "case_count =0 \n",
    "saved_cases =[]\n",
    "\n",
    "\n",
    "# restore_cases = lambda compressed_case: pickle.loads(zlib.decompress(compressed_case) )\n",
    "\n",
    "for county in counties:\n",
    "  for year in years:\n",
    "    for type in types:      \n",
    "      file_name = f'data/{county}.{year}.{type}.cases'\n",
    "      pickled_cases = zlib.decompress(open(file_name, 'rb').read(), zlib.MAX_WBITS)  \n",
    "      new_cases =  [case for case in pickle.loads(pickled_cases)]\n",
    "    \n",
    "      new_case_count = len(new_cases)\n",
    "      case_count += new_case_count\n",
    "      print(f'{file_name} added {new_case_count}')\n",
    "      saved_cases += new_cases\n",
    "        \n",
    "print(f'counted case: {case_count} length saved {len(saved_cases)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "gbDCRWzhxVSh",
    "outputId": "a61c3a75-95c9-4c5f-d15f-94a051809a45"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Filed', 'County', 'Type', 'CaseNumber', 'Counts', 'Source']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "columns = ['Filed','County','Type', 'CaseNumber', 'Counts','Source']\n",
    "case_data = lambda c: [c.filed, c.county, c.type, c.case_number, c.counts, c.source]\n",
    "%time all_cases = pd.DataFrame([case_data(c) for c in saved_cases], columns = columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "all_cases.groupby(['County']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filed</th>\n",
       "      <th>County</th>\n",
       "      <th>Type</th>\n",
       "      <th>CaseNumber</th>\n",
       "      <th>Counts</th>\n",
       "      <th>Source</th>\n",
       "      <th>Charge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-1</td>\n",
       "      <td>[{'description': 'POSSESSION OF CONTROLLED DAN...</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-2</td>\n",
       "      <td>[{'description': 'PUBLIC INTOXICATION'}]</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-3</td>\n",
       "      <td>[{'description': 'PETIT LARCENY'}, {'descripti...</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-4</td>\n",
       "      <td>[{'description': 'DOMESTIC ABUSE - ASSAULT AND...</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-5</td>\n",
       "      <td>[{'description': 'POSSESSION OF CONTROLLED DAN...</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Filed County Type CaseNumber  \\\n",
       "0 2017-01-03  mayes   CM  CM-2017-1   \n",
       "1 2017-01-03  mayes   CM  CM-2017-2   \n",
       "2 2017-01-04  mayes   CM  CM-2017-3   \n",
       "3 2017-01-04  mayes   CM  CM-2017-4   \n",
       "4 2017-01-04  mayes   CM  CM-2017-5   \n",
       "\n",
       "                                              Counts  \\\n",
       "0  [{'description': 'POSSESSION OF CONTROLLED DAN...   \n",
       "1           [{'description': 'PUBLIC INTOXICATION'}]   \n",
       "2  [{'description': 'PETIT LARCENY'}, {'descripti...   \n",
       "3  [{'description': 'DOMESTIC ABUSE - ASSAULT AND...   \n",
       "4  [{'description': 'POSSESSION OF CONTROLLED DAN...   \n",
       "\n",
       "                                              Source Charge  \n",
       "0  https://www.oscn.net/dockets/GetCaseInformatio...         \n",
       "1  https://www.oscn.net/dockets/GetCaseInformatio...         \n",
       "2  https://www.oscn.net/dockets/GetCaseInformatio...         \n",
       "3  https://www.oscn.net/dockets/GetCaseInformatio...         \n",
       "4  https://www.oscn.net/dockets/GetCaseInformatio...         "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_cases.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# charge_list = lambda charges:[charge['description'] for charge in charges ] if charges else []\n",
    "\n",
    "# all_cases['Charge'] = [charge_list(counts) for counts in all_cases['Counts'] ] \n",
    "\n",
    "# all_cases.drop(columns=['Charge'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Expand Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# convert the date from a string to a python DateTime type\n",
    "all_cases['FiledDate'] = pd.to_datetime(all_cases['Filed'])\n",
    "\n",
    "# create a map to all the existing non Count data\n",
    "\n",
    "safe_len = lambda counts: len(counts) if counts else 0\n",
    "lens = all_cases['Counts'].apply(safe_len)\n",
    "vals = range(all_cases.shape[0])\n",
    "ilocations = np.repeat(vals, lens)\n",
    "\n",
    "# get the index of all non Count columns\n",
    "cols = [i for i,c in enumerate(all_cases.columns) if c != 'Counts']\n",
    "# create a new expanded data frame and copy the old data\n",
    "count_frame = all_cases.iloc[ilocations, cols].copy()\n",
    "\n",
    "# Create a new column with the exanded data\n",
    "\n",
    "description = lambda count: count['description'] if count else \"\"\n",
    "safe_counts = lambda counts: counts if counts else {}\n",
    "count_frame['Charge'] = [description(item) for items in all_cases['Counts'] for item in items]\n",
    "count_frame.reset_index( inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Count of counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filed</th>\n",
       "      <th>County</th>\n",
       "      <th>Type</th>\n",
       "      <th>CaseNumber</th>\n",
       "      <th>Source</th>\n",
       "      <th>Charge</th>\n",
       "      <th>FiledDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-1</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>POSSESSION OF CONTROLLED DANGEROUS SUBSTANCE</td>\n",
       "      <td>2017-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-1</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>UNLAWFUL POSSESSION OF DRUG PARAPHERNALIA</td>\n",
       "      <td>2017-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-2</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>PUBLIC INTOXICATION</td>\n",
       "      <td>2017-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-3</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>PETIT LARCENY</td>\n",
       "      <td>2017-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-3</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>OBSTRUCTING OFFICER</td>\n",
       "      <td>2017-01-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Filed County Type CaseNumber  \\\n",
       "0 2017-01-03  mayes   CM  CM-2017-1   \n",
       "0 2017-01-03  mayes   CM  CM-2017-1   \n",
       "1 2017-01-03  mayes   CM  CM-2017-2   \n",
       "2 2017-01-04  mayes   CM  CM-2017-3   \n",
       "2 2017-01-04  mayes   CM  CM-2017-3   \n",
       "\n",
       "                                              Source  \\\n",
       "0  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "0  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "1  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "2  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "2  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "\n",
       "                                         Charge  FiledDate  \n",
       "0  POSSESSION OF CONTROLLED DANGEROUS SUBSTANCE 2017-01-03  \n",
       "0     UNLAWFUL POSSESSION OF DRUG PARAPHERNALIA 2017-01-03  \n",
       "1                           PUBLIC INTOXICATION 2017-01-03  \n",
       "2                                 PETIT LARCENY 2017-01-04  \n",
       "2                           OBSTRUCTING OFFICER 2017-01-04  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_frame.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    ## Filter for bugus check counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filed</th>\n",
       "      <th>County</th>\n",
       "      <th>Type</th>\n",
       "      <th>CaseNumber</th>\n",
       "      <th>Source</th>\n",
       "      <th>Charge</th>\n",
       "      <th>FiledDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6937</td>\n",
       "      <td>6938</td>\n",
       "      <td>6938</td>\n",
       "      <td>6938</td>\n",
       "      <td>6938</td>\n",
       "      <td>6938</td>\n",
       "      <td>6937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>418</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2617</td>\n",
       "      <td>4191</td>\n",
       "      <td>918</td>\n",
       "      <td>418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>2017-02-14 00:00:00</td>\n",
       "      <td>delaware</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-53</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>UNLAWFUL POSSESSION OF DRUG PARAPHERNALIA, A M...</td>\n",
       "      <td>2017-02-14 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>69</td>\n",
       "      <td>3841</td>\n",
       "      <td>3815</td>\n",
       "      <td>52</td>\n",
       "      <td>51</td>\n",
       "      <td>257</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>first</th>\n",
       "      <td>2017-01-03 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-03 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last</th>\n",
       "      <td>2018-09-10 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-09-10 00:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Filed    County  Type  CaseNumber  \\\n",
       "count                  6937      6938  6938        6938   \n",
       "unique                  418         2     2        2617   \n",
       "top     2017-02-14 00:00:00  delaware    CM  CM-2017-53   \n",
       "freq                     69      3841  3815          52   \n",
       "first   2017-01-03 00:00:00       NaN   NaN         NaN   \n",
       "last    2018-09-10 00:00:00       NaN   NaN         NaN   \n",
       "\n",
       "                                                   Source  \\\n",
       "count                                                6938   \n",
       "unique                                               4191   \n",
       "top     https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "freq                                                   51   \n",
       "first                                                 NaN   \n",
       "last                                                  NaN   \n",
       "\n",
       "                                                   Charge            FiledDate  \n",
       "count                                                6938                 6937  \n",
       "unique                                                918                  418  \n",
       "top     UNLAWFUL POSSESSION OF DRUG PARAPHERNALIA, A M...  2017-02-14 00:00:00  \n",
       "freq                                                  257                   69  \n",
       "first                                                 NaN  2017-01-03 00:00:00  \n",
       "last                                                  NaN  2018-09-10 00:00:00  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_frame.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "bogus_count = re.compile(r'(utter.*forged|bogus)', re.I | re.M)\n",
    "\n",
    "is_check_case= lambda row: True if bogus_count.search(row['Charge']) else False\n",
    "    \n",
    "\n",
    "count_frame['Bogus_Check'] = count_frame.apply(is_check_case, axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Filed</th>\n",
       "      <th>County</th>\n",
       "      <th>Type</th>\n",
       "      <th>CaseNumber</th>\n",
       "      <th>Source</th>\n",
       "      <th>Charge</th>\n",
       "      <th>FiledDate</th>\n",
       "      <th>Bogus_Check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-1</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>POSSESSION OF CONTROLLED DANGEROUS SUBSTANCE</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-1</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>UNLAWFUL POSSESSION OF DRUG PARAPHERNALIA</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-2</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>PUBLIC INTOXICATION</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-3</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>PETIT LARCENY</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>mayes</td>\n",
       "      <td>CM</td>\n",
       "      <td>CM-2017-3</td>\n",
       "      <td>https://www.oscn.net/dockets/GetCaseInformatio...</td>\n",
       "      <td>OBSTRUCTING OFFICER</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index      Filed County Type CaseNumber  \\\n",
       "0      0 2017-01-03  mayes   CM  CM-2017-1   \n",
       "1      0 2017-01-03  mayes   CM  CM-2017-1   \n",
       "2      1 2017-01-03  mayes   CM  CM-2017-2   \n",
       "3      2 2017-01-04  mayes   CM  CM-2017-3   \n",
       "4      2 2017-01-04  mayes   CM  CM-2017-3   \n",
       "\n",
       "                                              Source  \\\n",
       "0  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "1  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "2  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "3  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "4  https://www.oscn.net/dockets/GetCaseInformatio...   \n",
       "\n",
       "                                         Charge  FiledDate  Bogus_Check  \n",
       "0  POSSESSION OF CONTROLLED DANGEROUS SUBSTANCE 2017-01-03        False  \n",
       "1     UNLAWFUL POSSESSION OF DRUG PARAPHERNALIA 2017-01-03        False  \n",
       "2                           PUBLIC INTOXICATION 2017-01-03        False  \n",
       "3                                 PETIT LARCENY 2017-01-04        False  \n",
       "4                           OBSTRUCTING OFFICER 2017-01-04        False  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_frame.reset_index( inplace=True)\n",
    "count_frame.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "County    Bogus_Check\n",
       "delaware  False          3670\n",
       "          True            171\n",
       "mayes     False          3061\n",
       "          True             36\n",
       "Name: Bogus_Check, dtype: int64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_frame.groupby(['County'])['Bogus_Check'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x134a56278>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "month = count_frame.FiledDate.dt.to_period(\"M\")\n",
    "\n",
    "counts_with_bogus = count_frame.query(\"Bogus_Check == True\")\n",
    "groups = [month]\n",
    "by_month=round(counts_with_bogus.groupby(groups).size()/count_frame.groupby(groups).size()*100,2)\n",
    "by_month.plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      2017-01\n",
       "0      2017-01\n",
       "1      2017-01\n",
       "2      2017-01\n",
       "2      2017-01\n",
       "2      2017-01\n",
       "3      2017-01\n",
       "4      2017-01\n",
       "4      2017-01\n",
       "5      2017-01\n",
       "5      2017-01\n",
       "6      2017-01\n",
       "7      2017-01\n",
       "8      2017-01\n",
       "8      2017-01\n",
       "8      2017-01\n",
       "8      2017-01\n",
       "9      2017-01\n",
       "10     2017-01\n",
       "11     2017-01\n",
       "12     2017-01\n",
       "13     2017-01\n",
       "14     2017-01\n",
       "14     2017-01\n",
       "15     2017-01\n",
       "15     2017-01\n",
       "15     2017-01\n",
       "16     2017-01\n",
       "17     2017-01\n",
       "17     2017-01\n",
       "         ...  \n",
       "4185   2018-09\n",
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       "Name: FiledDate, Length: 6938, dtype: object"
      ]
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     "execution_count": 74,
     "metadata": {},
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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