{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "22edc8c3",
   "metadata": {},
   "source": [
    "# Analysis of Seattle PD bicycle-related Field Contacts\n",
    "\n",
    "##### Ethan C. Campbell, for Central Seattle Greenways / Helmet Law Working Group\n",
    "\n",
    "For questions, contact me at ethanchenbell@gmail.com."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "feb63b0f",
   "metadata": {},
   "source": [
    "#### Import packages and set file system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a74f338",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from numpy import *\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_columns',100)\n",
    "pd.set_option('display.max_colwidth',50)\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.ticker as mtick\n",
    "import matplotlib.colors as mcolors\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['figure.dpi'] = 300     # turn on for higher-quality figure export\n",
    "from datetime import datetime, timedelta\n",
    "import platform\n",
    "import warnings\n",
    "import sys\n",
    "\n",
    "from IPython.core.display import display, HTML\n",
    "# display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n",
    "\n",
    "# choose root directory for data files\n",
    "if platform.system() == 'Darwin':\n",
    "    data_dir = '/Users/Ethan/Documents/Finances and records/2020-06-30 - Helmet Law Working Group/Data/'\n",
    "    results_dir = '/Users/Ethan/Documents/Finances and records/2020-06-30 - Helmet Law Working Group/Figures/'\n",
    "elif platform.system() == 'Linux':\n",
    "    data_dir = '/dat1/ethancc/CSG/'\n",
    "    results_dir = data_dir\n",
    "    \n",
    "# set directory paths\n",
    "current_results_dir = results_dir + '2021-12-03 - Seattle PD Field Contact analyses/'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57fc43c7",
   "metadata": {},
   "source": [
    "#### Load compiled bike citation records\n",
    "\n",
    "Note: file created previously in Jupyter notebook [***csg_compile_king_county_bike_citations.ipynb***](https://github.com/ethan-campbell/Miscellaneous/blob/master/csg_compile_king_county_bike_citations.ipynb), which is available on my GitHub."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4104e6a1",
   "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>Court Name</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>Case Key (KCDC) or Token (MCs)</th>\n",
       "      <th>Case Type</th>\n",
       "      <th>Case File Date</th>\n",
       "      <th>Law Enforcement Agency</th>\n",
       "      <th>Violation Date</th>\n",
       "      <th>Law Code</th>\n",
       "      <th>Law Description</th>\n",
       "      <th>Disposition</th>\n",
       "      <th>Disposition Date</th>\n",
       "      <th>Defendant Gender</th>\n",
       "      <th>Defendant Race</th>\n",
       "      <th>Defendant Ethnicity</th>\n",
       "      <th>Officer Badge Number</th>\n",
       "      <th>AR Ordered Amount</th>\n",
       "      <th>AR Adjustment Amount</th>\n",
       "      <th>AR Paid Amount</th>\n",
       "      <th>AR Due Amount</th>\n",
       "      <th>Originating Query</th>\n",
       "      <th>City</th>\n",
       "      <th>Violation Datetime</th>\n",
       "      <th>Officer First Name</th>\n",
       "      <th>Officer Middle Name</th>\n",
       "      <th>Officer Last Name</th>\n",
       "      <th>AR Adjusted Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1658</th>\n",
       "      <td>King County District Court</td>\n",
       "      <td>8Z0505330</td>\n",
       "      <td>37573291</td>\n",
       "      <td>Infraction</td>\n",
       "      <td>2018-08-27</td>\n",
       "      <td>Seattle Police Department</td>\n",
       "      <td>2018-08-25</td>\n",
       "      <td>RCW 46.61.755</td>\n",
       "      <td>Violating Laws While Riding Bicycle</td>\n",
       "      <td>Committed</td>\n",
       "      <td>2018-10-15</td>\n",
       "      <td>Male</td>\n",
       "      <td>White</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All bike violations (requested KCHC 9.10.010 a...</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1756</th>\n",
       "      <td>King County District Court</td>\n",
       "      <td>I10974250</td>\n",
       "      <td>38502744</td>\n",
       "      <td>Infraction</td>\n",
       "      <td>2007-08-20</td>\n",
       "      <td>Seattle Police Department</td>\n",
       "      <td>2007-08-17</td>\n",
       "      <td>King County Health Code 9.10.010A or 9.15.010</td>\n",
       "      <td>Bicycle Helmet Required</td>\n",
       "      <td>Committed</td>\n",
       "      <td>2009-11-03</td>\n",
       "      <td>Male</td>\n",
       "      <td>Black</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All bike violations (requested KCHC 9.10.010 a...</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1757</th>\n",
       "      <td>King County District Court</td>\n",
       "      <td>I11111192</td>\n",
       "      <td>38621778</td>\n",
       "      <td>Infraction</td>\n",
       "      <td>2008-09-29</td>\n",
       "      <td>Seattle Police Department</td>\n",
       "      <td>2008-09-19</td>\n",
       "      <td>King County Health Code 9.10.010A or 9.15.010</td>\n",
       "      <td>Bicycle Helmet Required</td>\n",
       "      <td>Committed</td>\n",
       "      <td>2009-10-30</td>\n",
       "      <td>Male</td>\n",
       "      <td>White</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All bike violations (requested KCHC 9.10.010 a...</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Court Name Case Number Case Key (KCDC) or Token (MCs)  \\\n",
       "1658  King County District Court   8Z0505330                       37573291   \n",
       "1756  King County District Court   I10974250                       38502744   \n",
       "1757  King County District Court   I11111192                       38621778   \n",
       "\n",
       "       Case Type Case File Date     Law Enforcement Agency Violation Date  \\\n",
       "1658  Infraction     2018-08-27  Seattle Police Department     2018-08-25   \n",
       "1756  Infraction     2007-08-20  Seattle Police Department     2007-08-17   \n",
       "1757  Infraction     2008-09-29  Seattle Police Department     2008-09-19   \n",
       "\n",
       "                                           Law Code  \\\n",
       "1658                                  RCW 46.61.755   \n",
       "1756  King County Health Code 9.10.010A or 9.15.010   \n",
       "1757  King County Health Code 9.10.010A or 9.15.010   \n",
       "\n",
       "                          Law Description Disposition Disposition Date  \\\n",
       "1658  Violating Laws While Riding Bicycle   Committed       2018-10-15   \n",
       "1756              Bicycle Helmet Required   Committed       2009-11-03   \n",
       "1757              Bicycle Helmet Required   Committed       2009-10-30   \n",
       "\n",
       "     Defendant Gender Defendant Race Defendant Ethnicity  \\\n",
       "1658             Male          White             Unknown   \n",
       "1756             Male          Black             Unknown   \n",
       "1757             Male          White             Unknown   \n",
       "\n",
       "      Officer Badge Number  AR Ordered Amount  AR Adjustment Amount  \\\n",
       "1658                   NaN                NaN                   NaN   \n",
       "1756                   NaN                NaN                   NaN   \n",
       "1757                   NaN                NaN                   NaN   \n",
       "\n",
       "      AR Paid Amount  AR Due Amount  \\\n",
       "1658             NaN            NaN   \n",
       "1756             NaN            NaN   \n",
       "1757             NaN            NaN   \n",
       "\n",
       "                                      Originating Query     City  \\\n",
       "1658  All bike violations (requested KCHC 9.10.010 a...  Seattle   \n",
       "1756  All bike violations (requested KCHC 9.10.010 a...  Seattle   \n",
       "1757  All bike violations (requested KCHC 9.10.010 a...  Seattle   \n",
       "\n",
       "     Violation Datetime Officer First Name Officer Middle Name  \\\n",
       "1658                NaT                NaN                 NaN   \n",
       "1756                NaT                NaN                 NaN   \n",
       "1757                NaT                NaN                 NaN   \n",
       "\n",
       "     Officer Last Name  AR Adjusted Amount  \n",
       "1658               NaN                 NaN  \n",
       "1756               NaN                 NaN  \n",
       "1757               NaN                 NaN  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kc_citations = pd.read_excel(data_dir + '2021-10-18 - compiled King County bike citation records.xlsx').drop(columns=['Unnamed: 0'])\n",
    "spd_citations = kc_citations[kc_citations['Law Enforcement Agency'] == 'Seattle Police Department']\n",
    "spd_citations.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb5fabd7",
   "metadata": {},
   "source": [
    "#### Load compiled King County jurisdiction citation statistics\n",
    "\n",
    "Note: file created previously in Jupyter notebook [***csg_analyze_king_county_bike_citations.ipynb***](https://github.com/ethan-campbell/Miscellaneous/blob/master/csg_analyze_king_county_bike_citations.ipynb), which is available on my GitHub."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "23c470f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Population (OFM, April 2021)                                                                                       769500\n",
       "Years with citation records                                             2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010...\n",
       "Total helmet citations in records                                                                                    1694\n",
       "Recent helmet citations (2015-2019 only)                                                                              215\n",
       "Average annual citations (over all years that citations were issued)                                                 94.1\n",
       "Average annual citations (2015-2019 only)                                                                              43\n",
       "Annual citation rate per 100k people (all years)                                                                     12.2\n",
       "Annual citation rate per 100k people (2015-2019 only)                                                                 5.6\n",
       "King County helmet law citations (%)                                                                                 99.9\n",
       "Municipal helmet law citations (%)                                                                                    0.1\n",
       "Citations - White (%)                                                                                                72.8\n",
       "Citations - Black (%)                                                                                                17.4\n",
       "Citations - Asian or Pacific Islander (%)                                                                             1.6\n",
       "Citations - Native American or Alaskan Native (%)                                                                       1\n",
       "Citations - Unknown/other (%)                                                                                         7.1\n",
       "Census (2015-2019) - White (%)                                                                                       67.3\n",
       "Census (2015-2019) - Black (%)                                                                                        8.6\n",
       "Census (2015-2019) - Asian or Pacific Islander (%)                                                                   18.9\n",
       "Census (2015-2019) - Native American or Alaskan Native (%)                                                            1.3\n",
       "Census (2015-2019) - Other (%)                                                                                        3.9\n",
       "Fines charged - number of data points                                                                                 176\n",
       "Fines charged - average ($)                                                                                        103.14\n",
       "Fines charged - standard deviation ($)                                                                              18.33\n",
       "Fines charged - median ($)                                                                                            102\n",
       "Fines charged - IQR25% ($)                                                                                            102\n",
       "Fines charged - IQR75% ($)                                                                                            102\n",
       "Fines charged - most common value (mode) ($)                                                                          102\n",
       "Fines assessed after adjustments - number of data points                                                              176\n",
       "Fines assessed after adjustments - average ($)                                                                      88.18\n",
       "Fines assessed after adjustments - standard deviation ($)                                                           38.14\n",
       "Fines assessed after adjustments - median ($)                                                                         102\n",
       "Fines assessed after adjustments - IQR25% ($)                                                                         102\n",
       "Fines assessed after adjustments - IQR75% ($)                                                                         102\n",
       "Fines assessed after adjustments - most common value (mode) ($)                                                       102\n",
       "Fraction of citations unpaid                                                                                         76.7\n",
       "Name: Seattle, dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load compiled statistics by city\n",
    "cities = pd.read_excel(data_dir + '2021-10-18 - King County helmet citation statistics.xlsx',index_col='Jurisdiction')\n",
    "cities.loc['Seattle']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6742467",
   "metadata": {},
   "source": [
    "#### Load summaries of Seattle PD bicycle-related Field Contact narrative reports\n",
    "\n",
    "Note: records span May 7, 2019 to March 26, 2021; some narrative reports were redacted prior to release to public."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f71df464",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Additional Information Origin</th>\n",
       "      <th>FCC Type (redundant)</th>\n",
       "      <th>Homelessness</th>\n",
       "      <th>Officer on Bike Patrol</th>\n",
       "      <th>Type of Bike Violation</th>\n",
       "      <th>Riding Location</th>\n",
       "      <th>Subject Asked to Produce Identification</th>\n",
       "      <th>Subject Produced Identification</th>\n",
       "      <th>Subject Identified Verbally</th>\n",
       "      <th>Warrant Check</th>\n",
       "      <th>Warrant Check Result</th>\n",
       "      <th>Outcome</th>\n",
       "      <th>Reason for Suspicion/Other Circumstances</th>\n",
       "      <th>Other notes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Report Number</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-163273</th>\n",
       "      <td>FCs (Installment 2)</td>\n",
       "      <td>Bike/infraction warning-no cite</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Helmet violation</td>\n",
       "      <td>Street (presumed)</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Verbal warning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-163288</th>\n",
       "      <td>FCs (Installment 2)</td>\n",
       "      <td>Bike/infraction warning-no cite</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Helmet violation</td>\n",
       "      <td>Street (presumed)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Verbal warning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-163496</th>\n",
       "      <td>FCs (Installment 2)</td>\n",
       "      <td>Bike/infraction warning-no cite</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Helmet violation</td>\n",
       "      <td>Street (presumed)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Verbal warning</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Additional Information Origin             FCC Type (redundant)  \\\n",
       "Report Number                                                                  \n",
       "2019-163273             FCs (Installment 2)  Bike/infraction warning-no cite   \n",
       "2019-163288             FCs (Installment 2)  Bike/infraction warning-no cite   \n",
       "2019-163496             FCs (Installment 2)  Bike/infraction warning-no cite   \n",
       "\n",
       "              Homelessness Officer on Bike Patrol Type of Bike Violation  \\\n",
       "Report Number                                                              \n",
       "2019-163273            Yes                    Yes       Helmet violation   \n",
       "2019-163288            Yes                    Yes       Helmet violation   \n",
       "2019-163496            Yes                    Yes       Helmet violation   \n",
       "\n",
       "                 Riding Location Subject Asked to Produce Identification  \\\n",
       "Report Number                                                              \n",
       "2019-163273    Street (presumed)                                     Yes   \n",
       "2019-163288    Street (presumed)                                     NaN   \n",
       "2019-163496    Street (presumed)                                     NaN   \n",
       "\n",
       "              Subject Produced Identification Subject Identified Verbally  \\\n",
       "Report Number                                                               \n",
       "2019-163273                               NaN                         NaN   \n",
       "2019-163288                               NaN                         Yes   \n",
       "2019-163496                               Yes                         NaN   \n",
       "\n",
       "              Warrant Check Warrant Check Result         Outcome  \\\n",
       "Report Number                                                      \n",
       "2019-163273             Yes                Clear  Verbal warning   \n",
       "2019-163288             Yes                Clear  Verbal warning   \n",
       "2019-163496             Yes                Clear  Verbal warning   \n",
       "\n",
       "              Reason for Suspicion/Other Circumstances Other notes  \n",
       "Report Number                                                       \n",
       "2019-163273                                        NaN         NaN  \n",
       "2019-163288                                        NaN         NaN  \n",
       "2019-163496                                        NaN         NaN  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load SPD Field Contact report summaries\n",
    "spd_fc_summaries = pd.read_excel(data_dir + '2021-12-03 - Seattle PD Field Contact Report summaries - Installments 2-3.xlsx',index_col='Report Number')\n",
    "spd_fc_summaries.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c9014a0",
   "metadata": {},
   "source": [
    "#### Load Seattle PD bicycle-related Field Contact fields from Records Management System (RMS) data\n",
    "\n",
    "Note: records span May 7, 2019 to March 26, 2021, after Seattle PD began using Mark43 exclusively as their RMS."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "id": "3a917e8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Keyword</th>\n",
       "      <th>Report ID</th>\n",
       "      <th>Primary Agency</th>\n",
       "      <th>Report Type</th>\n",
       "      <th>Report Writer</th>\n",
       "      <th>Participating Officer</th>\n",
       "      <th>All Assisting Officers and Assist Types</th>\n",
       "      <th>Report Date / Time</th>\n",
       "      <th>Event Statistics</th>\n",
       "      <th>Event Location Location Alias</th>\n",
       "      <th>Event Location Street Address</th>\n",
       "      <th>Event Location Cross Street 1</th>\n",
       "      <th>Event Location Cross Street 2</th>\n",
       "      <th>Event Location City</th>\n",
       "      <th>Event Location State</th>\n",
       "      <th>Event Location Location Category</th>\n",
       "      <th>Event Location Lat</th>\n",
       "      <th>Event Location Long</th>\n",
       "      <th>Event Location Neighborhood</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Hour Group</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "      <th>Event District</th>\n",
       "      <th>Event Sector</th>\n",
       "      <th>Event Grid</th>\n",
       "      <th>Event Neighborhood</th>\n",
       "      <th>FCC Type</th>\n",
       "      <th>FCC Disposition</th>\n",
       "      <th>FCC Subject 1 Involvement Type</th>\n",
       "      <th>FCC Subject 1 Home Address Location Alias</th>\n",
       "      <th>FCC Subject 1 Home Address Cross Street 1</th>\n",
       "      <th>FCC Subject 1 Home Address Cross Street 2</th>\n",
       "      <th>FCC Subject 1 Home Address City</th>\n",
       "      <th>FCC Subject 1 Home Address State</th>\n",
       "      <th>FCC Subject 1 Home Address Location Category</th>\n",
       "      <th>FCC Subject 1 Home Address Neighborhood</th>\n",
       "      <th>FCC Subject 1 Sex</th>\n",
       "      <th>FCC Subject 1 Race</th>\n",
       "      <th>FCC Subject 1 Ethnicity</th>\n",
       "      <th>Year of Manufacture</th>\n",
       "      <th>Make</th>\n",
       "      <th>Model</th>\n",
       "      <th>Registration State</th>\n",
       "      <th>Vehicle Color</th>\n",
       "      <th>Vehicle Property Status</th>\n",
       "      <th>Vehicle Property Status Date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Report Number</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-163273</th>\n",
       "      <td>Bicycle</td>\n",
       "      <td>8198880844</td>\n",
       "      <td>Seattle Police Department</td>\n",
       "      <td>Field Contact</td>\n",
       "      <td>EDUARDO FRANCISCO LOPEZ #8343</td>\n",
       "      <td>BERNARD THOMAS MAHONEY #6296</td>\n",
       "      <td>BERNARD THOMAS MAHONEY #6296 (Backing Officer)...</td>\n",
       "      <td>2019-05-07 16:59:00</td>\n",
       "      <td>Body Worn Video, Homelessness</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NW LEARY WY</td>\n",
       "      <td>15 AV NW</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.663660</td>\n",
       "      <td>-122.376134</td>\n",
       "      <td>WEST WOODLAND</td>\n",
       "      <td>2019-05-07</td>\n",
       "      <td>11:47:00</td>\n",
       "      <td>1100</td>\n",
       "      <td>May</td>\n",
       "      <td>Tue</td>\n",
       "      <td>N</td>\n",
       "      <td>B</td>\n",
       "      <td>B1</td>\n",
       "      <td>WEST WOODLAND</td>\n",
       "      <td>Bike/infraction warning-no cite</td>\n",
       "      <td>Identify/release, Oral/Verbal Warning, Stop Ex...</td>\n",
       "      <td>suspect</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-163288</th>\n",
       "      <td>Bicycle</td>\n",
       "      <td>8198893317</td>\n",
       "      <td>Seattle Police Department</td>\n",
       "      <td>Field Contact</td>\n",
       "      <td>EDUARDO FRANCISCO LOPEZ #8343</td>\n",
       "      <td>BERNARD THOMAS MAHONEY #6296</td>\n",
       "      <td>BERNARD THOMAS MAHONEY #6296 (Backing Officer)...</td>\n",
       "      <td>2019-05-07 17:17:00</td>\n",
       "      <td>Body Worn Video, Homelessness</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NW BALLARD WY</td>\n",
       "      <td>11 AV NW</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.662927</td>\n",
       "      <td>-122.370779</td>\n",
       "      <td>WEST WOODLAND</td>\n",
       "      <td>2019-05-07</td>\n",
       "      <td>11:53:00</td>\n",
       "      <td>1100</td>\n",
       "      <td>May</td>\n",
       "      <td>Tue</td>\n",
       "      <td>N</td>\n",
       "      <td>B</td>\n",
       "      <td>B2</td>\n",
       "      <td>WEST WOODLAND</td>\n",
       "      <td>Bike/infraction warning-no cite</td>\n",
       "      <td>Identify/release, Oral/Verbal Warning, Stop Ex...</td>\n",
       "      <td>suspect</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>White</td>\n",
       "      <td>Not Hispanic Or Latino</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-163496</th>\n",
       "      <td>Bicycle</td>\n",
       "      <td>8198924485</td>\n",
       "      <td>Seattle Police Department</td>\n",
       "      <td>Field Contact</td>\n",
       "      <td>EDUARDO FRANCISCO LOPEZ #8343</td>\n",
       "      <td>BERNARD THOMAS MAHONEY #6296</td>\n",
       "      <td>BERNARD THOMAS MAHONEY #6296 (Backing Officer)...</td>\n",
       "      <td>2019-05-07 17:32:00</td>\n",
       "      <td>Body Worn Video, Homelessness</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NW 46 ST</td>\n",
       "      <td>9 AV NW</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.662193</td>\n",
       "      <td>-122.368626</td>\n",
       "      <td>WEST WOODLAND</td>\n",
       "      <td>2019-05-07</td>\n",
       "      <td>14:26:00</td>\n",
       "      <td>1400</td>\n",
       "      <td>May</td>\n",
       "      <td>Tue</td>\n",
       "      <td>N</td>\n",
       "      <td>B</td>\n",
       "      <td>B2</td>\n",
       "      <td>WEST WOODLAND</td>\n",
       "      <td>Bike/infraction warning-no cite</td>\n",
       "      <td>Identify/release, Oral/Verbal Warning, Stop Ex...</td>\n",
       "      <td>suspect</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>Not Hispanic Or Latino</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Keyword   Report ID             Primary Agency    Report Type  \\\n",
       "Report Number                                                                  \n",
       "2019-163273    Bicycle  8198880844  Seattle Police Department  Field Contact   \n",
       "2019-163288    Bicycle  8198893317  Seattle Police Department  Field Contact   \n",
       "2019-163496    Bicycle  8198924485  Seattle Police Department  Field Contact   \n",
       "\n",
       "                               Report Writer         Participating Officer  \\\n",
       "Report Number                                                                \n",
       "2019-163273    EDUARDO FRANCISCO LOPEZ #8343  BERNARD THOMAS MAHONEY #6296   \n",
       "2019-163288    EDUARDO FRANCISCO LOPEZ #8343  BERNARD THOMAS MAHONEY #6296   \n",
       "2019-163496    EDUARDO FRANCISCO LOPEZ #8343  BERNARD THOMAS MAHONEY #6296   \n",
       "\n",
       "                         All Assisting Officers and Assist Types  \\\n",
       "Report Number                                                      \n",
       "2019-163273    BERNARD THOMAS MAHONEY #6296 (Backing Officer)...   \n",
       "2019-163288    BERNARD THOMAS MAHONEY #6296 (Backing Officer)...   \n",
       "2019-163496    BERNARD THOMAS MAHONEY #6296 (Backing Officer)...   \n",
       "\n",
       "                Report Date / Time               Event Statistics  \\\n",
       "Report Number                                                       \n",
       "2019-163273    2019-05-07 16:59:00  Body Worn Video, Homelessness   \n",
       "2019-163288    2019-05-07 17:17:00  Body Worn Video, Homelessness   \n",
       "2019-163496    2019-05-07 17:32:00  Body Worn Video, Homelessness   \n",
       "\n",
       "              Event Location Location Alias Event Location Street Address  \\\n",
       "Report Number                                                               \n",
       "2019-163273                             NaN                           NaN   \n",
       "2019-163288                             NaN                           NaN   \n",
       "2019-163496                             NaN                           NaN   \n",
       "\n",
       "              Event Location Cross Street 1 Event Location Cross Street 2  \\\n",
       "Report Number                                                               \n",
       "2019-163273                     NW LEARY WY                      15 AV NW   \n",
       "2019-163288                   NW BALLARD WY                      11 AV NW   \n",
       "2019-163496                        NW 46 ST                       9 AV NW   \n",
       "\n",
       "              Event Location City Event Location State  \\\n",
       "Report Number                                            \n",
       "2019-163273               SEATTLE                   WA   \n",
       "2019-163288               SEATTLE                   WA   \n",
       "2019-163496               SEATTLE                   WA   \n",
       "\n",
       "              Event Location Location Category  Event Location Lat   \\\n",
       "Report Number                                                         \n",
       "2019-163273                                NaN            47.663660   \n",
       "2019-163288                                NaN            47.662927   \n",
       "2019-163496                                NaN            47.662193   \n",
       "\n",
       "               Event Location Long Event Location Neighborhood       Date  \\\n",
       "Report Number                                                               \n",
       "2019-163273            -122.376134               WEST WOODLAND 2019-05-07   \n",
       "2019-163288            -122.370779               WEST WOODLAND 2019-05-07   \n",
       "2019-163496            -122.368626               WEST WOODLAND 2019-05-07   \n",
       "\n",
       "                   Time  Hour Group Month Day of Week Event District  \\\n",
       "Report Number                                                          \n",
       "2019-163273    11:47:00        1100   May         Tue              N   \n",
       "2019-163288    11:53:00        1100   May         Tue              N   \n",
       "2019-163496    14:26:00        1400   May         Tue              N   \n",
       "\n",
       "              Event Sector Event Grid Event Neighborhood  \\\n",
       "Report Number                                              \n",
       "2019-163273              B         B1      WEST WOODLAND   \n",
       "2019-163288              B         B2      WEST WOODLAND   \n",
       "2019-163496              B         B2      WEST WOODLAND   \n",
       "\n",
       "                                      FCC Type  \\\n",
       "Report Number                                    \n",
       "2019-163273    Bike/infraction warning-no cite   \n",
       "2019-163288    Bike/infraction warning-no cite   \n",
       "2019-163496    Bike/infraction warning-no cite   \n",
       "\n",
       "                                                 FCC Disposition  \\\n",
       "Report Number                                                      \n",
       "2019-163273    Identify/release, Oral/Verbal Warning, Stop Ex...   \n",
       "2019-163288    Identify/release, Oral/Verbal Warning, Stop Ex...   \n",
       "2019-163496    Identify/release, Oral/Verbal Warning, Stop Ex...   \n",
       "\n",
       "              FCC Subject 1 Involvement Type  \\\n",
       "Report Number                                  \n",
       "2019-163273                          suspect   \n",
       "2019-163288                          suspect   \n",
       "2019-163496                          suspect   \n",
       "\n",
       "              FCC Subject 1 Home Address Location Alias  \\\n",
       "Report Number                                             \n",
       "2019-163273                                         NaN   \n",
       "2019-163288                                         NaN   \n",
       "2019-163496                                         NaN   \n",
       "\n",
       "              FCC Subject 1 Home Address Cross Street 1  \\\n",
       "Report Number                                             \n",
       "2019-163273                                         NaN   \n",
       "2019-163288                                         NaN   \n",
       "2019-163496                                         NaN   \n",
       "\n",
       "              FCC Subject 1 Home Address Cross Street 2  \\\n",
       "Report Number                                             \n",
       "2019-163273                                         NaN   \n",
       "2019-163288                                         NaN   \n",
       "2019-163496                                         NaN   \n",
       "\n",
       "              FCC Subject 1 Home Address City  \\\n",
       "Report Number                                   \n",
       "2019-163273                           SEATTLE   \n",
       "2019-163288                           SEATTLE   \n",
       "2019-163496                           SEATTLE   \n",
       "\n",
       "              FCC Subject 1 Home Address State  \\\n",
       "Report Number                                    \n",
       "2019-163273                                 WA   \n",
       "2019-163288                                 WA   \n",
       "2019-163496                                 WA   \n",
       "\n",
       "              FCC Subject 1 Home Address Location Category  \\\n",
       "Report Number                                                \n",
       "2019-163273                                            NaN   \n",
       "2019-163288                                            NaN   \n",
       "2019-163496                                            NaN   \n",
       "\n",
       "              FCC Subject 1 Home Address Neighborhood FCC Subject 1 Sex  \\\n",
       "Report Number                                                             \n",
       "2019-163273                                       NaN              Male   \n",
       "2019-163288                                       NaN              Male   \n",
       "2019-163496                                       NaN              Male   \n",
       "\n",
       "                      FCC Subject 1 Race FCC Subject 1 Ethnicity  \\\n",
       "Report Number                                                      \n",
       "2019-163273                          NaN                     NaN   \n",
       "2019-163288                        White  Not Hispanic Or Latino   \n",
       "2019-163496    Black or African American  Not Hispanic Or Latino   \n",
       "\n",
       "               Year of Manufacture Make Model Registration State  \\\n",
       "Report Number                                                      \n",
       "2019-163273                    NaN  NaN   NaN                NaN   \n",
       "2019-163288                    NaN  NaN   NaN                NaN   \n",
       "2019-163496                    NaN  NaN   NaN                NaN   \n",
       "\n",
       "              Vehicle Color Vehicle Property Status  \\\n",
       "Report Number                                         \n",
       "2019-163273             NaN                     NaN   \n",
       "2019-163288             NaN                     NaN   \n",
       "2019-163496             NaN                     NaN   \n",
       "\n",
       "              Vehicle Property Status Date  \n",
       "Report Number                               \n",
       "2019-163273                            NaT  \n",
       "2019-163288                            NaT  \n",
       "2019-163496                            NaT  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# load SPD Field Contact report entries\n",
    "spd_fc_data = pd.read_excel(data_dir + '2021-06-16 - Seattle PD Records Management System (RMS) Field Contacts (2019-05-07 to 2021-03-26) - all bike-related.xlsx',\n",
    "                            index_col='Report Number')\n",
    "\n",
    "# redact identifying information; display\n",
    "spd_fc_data.drop(columns=['Report Subtype','FCC Subject 1','FCC Subject 1 DOB','FCC Subject 1 Home Address Street Address',\n",
    "                          'FCC Subject 1 Home Address Lat ','FCC Subject 1 Home Address Long','License Plate / Registration #','VIN #'],\n",
    "                 inplace=True)\n",
    "display(spd_fc_data.head(3))\n",
    "\n",
    "# merge subject types into narrative summary entries\n",
    "subject_types = spd_fc_data.loc[spd_fc_summaries.index]['FCC Subject 1 Involvement Type']\n",
    "subject_types = subject_types[~subject_types.index.duplicated()]\n",
    "spd_fc_summaries['Subject Types'] = subject_types\n",
    "\n",
    "# merge dates into narrative summary entries\n",
    "fc_dates = spd_fc_data.loc[spd_fc_summaries.index]['Date']\n",
    "fc_dates = fc_dates[~fc_dates.index.duplicated()]\n",
    "spd_fc_summaries['Date'] = fc_dates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aafefeb4",
   "metadata": {},
   "source": [
    "#### Field Contact narrative reports: summary statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "id": "2539d13f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Number of reports reviewed: 40\n",
      "\n",
      "Breakdown of types of Field Contacts:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Bike/infraction warning-no cite         30\n",
       "Terry Stop                               7\n",
       "Pedestrian violation/warning-no cite     1\n",
       "Other infraction                         1\n",
       "Trespass Warning (to suspect)            1\n",
       "Name: FCC Type (redundant), dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Breakdown of types of Field Contacts (%):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Bike/infraction warning-no cite         75.0\n",
       "Terry Stop                              17.5\n",
       "Pedestrian violation/warning-no cite     2.5\n",
       "Other infraction                         2.5\n",
       "Trespass Warning (to suspect)            2.5\n",
       "Name: FCC Type (redundant), dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Fraction of Field Contacts involving a homeless subject, either noted by officer or inferred from clear narrative elements: 47.5%\n",
      "\n",
      "Fraction of Field Contacts in which officer(s) were on mounted bike patrol: 57.5%\n",
      "\n",
      "Fraction of Field Contacts originating from a bike helmet violation: 85.0%\n",
      "\n",
      "Fraction of Field Contacts in which a warrant check was conducted: 55.0%\n",
      "\n",
      "Fraction of Field Contacts in which a warrant check was conducted (suspicion-related stops only): 37.5%\n",
      "\n",
      "Results of warrant checks (yes indicates an open warrant was identified):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Clear                                      11\n",
       "Yes, non-extraditable / no action taken     6\n",
       "Clear (presumed)                            4\n",
       "Yes                                         1\n",
       "Name: Warrant Check Result, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Results of warrant checks (yes indicates an open warrant was identified) (%):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Clear                                      50.000000\n",
       "Yes, non-extraditable / no action taken    27.272727\n",
       "Clear (presumed)                           18.181818\n",
       "Yes                                         4.545455\n",
       "Name: Warrant Check Result, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Outcomes of Field Contacts:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Verbal warning                             32\n",
       "Subject released                            6\n",
       "Referred for charging/prosecution           1\n",
       "Arrest / later released (wrong suspect)     1\n",
       "Name: Outcome, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Outcomes of Field Contacts (%):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Verbal warning                             80.0\n",
       "Subject released                           15.0\n",
       "Referred for charging/prosecution           2.5\n",
       "Arrest / later released (wrong suspect)     2.5\n",
       "Name: Outcome, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Suspicion articulated for Terry Stops:\n",
      "['Theft in progress suspected (appeared to be tampering with Lime Bike)'\n",
      " 'Stolen bike suspected (riding Lime Bike with a trailer attached)' nan\n",
      " 'Theft suspected (attempting to remove bike from rack while riding another bike)'\n",
      " 'Theft in progress suspected (attempted to steal marked police bike)'\n",
      " 'Subject was loading a second bike onto the Lime Bike he was riding, but gave plausible explanation, showing that brake lines of second bike were broken'\n",
      " 'Subject riding a Lime Bike with a broken rear light and rear wheel lock']\n",
      "\n",
      "Fraction of Terry Stops in which a bike violation (e.g., helmet violation) was the sole rationale originally articulated for the stop; \n",
      "i.e., cases in which suspicion developed after the stop was initiated: 29% (2 of 7)\n",
      "\n",
      "NOTE: no suspicion was articulated in narrative reports for the remainder of Field Contacts that were not Terry Stops\n"
     ]
    }
   ],
   "source": [
    "print('\\nNumber of reports reviewed:',len(spd_fc_summaries))\n",
    "\n",
    "print('\\nBreakdown of types of Field Contacts:')\n",
    "display(spd_fc_summaries['FCC Type (redundant)'].value_counts())\n",
    "\n",
    "print('\\nBreakdown of types of Field Contacts (%):')\n",
    "display(100 * spd_fc_summaries['FCC Type (redundant)'].value_counts() / len(spd_fc_summaries))\n",
    "\n",
    "print('\\nFraction of Field Contacts involving a homeless subject, either noted by officer or inferred from clear narrative elements: {0:.1f}%'\\\n",
    "      .format(100 * sum(spd_fc_summaries['Homelessness'].str.contains('Yes')) / len(spd_fc_summaries)))\n",
    "\n",
    "print('\\nFraction of Field Contacts in which officer(s) were on mounted bike patrol: {0:.1f}%'\\\n",
    "      .format(100 * sum(spd_fc_summaries['Officer on Bike Patrol'].str.contains('Yes')) / len(spd_fc_summaries)))\n",
    "\n",
    "print('\\nFraction of Field Contacts originating from a bike helmet violation: {0:.1f}%'\\\n",
    "      .format(100 * sum(spd_fc_summaries['Type of Bike Violation'].str.contains('Helmet violation')) / len(spd_fc_summaries)))\n",
    "\n",
    "print('\\nFraction of Field Contacts in which a warrant check was conducted: {0:.1f}%'\\\n",
    "      .format(100 * sum(spd_fc_summaries['Warrant Check'].str.contains('Yes')) / len(spd_fc_summaries)))\n",
    "\n",
    "print('\\nResults of warrant checks (yes indicates an open warrant was identified):')\n",
    "display(spd_fc_summaries['Warrant Check Result'].value_counts())\n",
    "\n",
    "print('\\nResults of warrant checks (yes indicates an open warrant was identified) (%):')\n",
    "display(100 * spd_fc_summaries['Warrant Check Result'].value_counts() / sum(spd_fc_summaries['Warrant Check'].str.contains('Yes')))\n",
    "\n",
    "print('\\nOutcomes of Field Contacts:')\n",
    "display(spd_fc_summaries['Outcome'].value_counts())\n",
    "\n",
    "print('\\nOutcomes of Field Contacts (%):')\n",
    "display(100 * spd_fc_summaries['Outcome'].value_counts() / len(spd_fc_summaries))\n",
    "\n",
    "print('\\nSuspicion articulated for Terry Stops:')\n",
    "print(spd_fc_summaries[spd_fc_summaries['FCC Type (redundant)'] == 'Terry Stop']['Reason for Suspicion/Other Circumstances'].values)\n",
    "\n",
    "print('\\nFraction of Terry Stops in which a bike violation (e.g., helmet violation) was the sole rationale originally articulated for the stop; \\n' + \\\n",
    "      'i.e., cases in which suspicion developed after the stop was initiated: {0:.0f}% ({1} of {2})'\n",
    "      .format(100 * 2 / spd_fc_summaries['FCC Type (redundant)'].value_counts()['Terry Stop'],\n",
    "              2,spd_fc_summaries['FCC Type (redundant)'].value_counts()['Terry Stop']))\n",
    "\n",
    "print('\\nNOTE: no suspicion was articulated in narrative reports for the remainder of Field Contacts that were not Terry Stops')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "id": "b8cdf955",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Time period of Field Contact data availability: 22.6 months, from 2019-05-07 to 2021-03-26\n",
      "\n",
      "Search keywords used for public records request (plus \"Biker\" and \"Bicycler\", which returned no Field Contacts during this period):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Bicycle      908\n",
       "Bike         591\n",
       "Bicyclist     24\n",
       "Cyclist        4\n",
       "Name: Keyword, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "From here on, we are specifically analyzing two largest types of Field Contacts for which subjects were reliably bicyclists\n",
      "  in the narrative reports reviewed: \n",
      "944 Terry Stops and 201 \"Bike/infraction warning-no cite\" entries (ignoring less common categories - \n",
      "  campsite clearances, other infractions, tresspass warnings, park violations, pedestrian violations/warnings, citizen tips, etc.)\n",
      "\n",
      "Fraction of bike infraction warning entries involving suspicion of subject unrelated to infraction (i.e., pretextual stops):\n",
      "  57.7%\n",
      "\n",
      "Annual rate of police contacts based on these records:\n",
      "- Terry Stops only: 501 per year (some may not be stops of bicyclists, but most likely are)\n",
      "- Bike infraction warnings only: 107 per year\n",
      "- Both combined: 608 per year\n",
      "- ** Estimated Terry Stops that develop solely from a bike infraction, based on 2-in-7 statistic from above: 143 per year\n",
      "- ** Bike infraction warnings involving suspicion (pretextual stops): 62 per year\n",
      "\n",
      "      ** = suspicion-related stops enabled by existing bicycle infractions\n",
      "\n",
      "Compare sum of two final annual rates to annual rate of bike-related citations (to bicyclists) based on Seattle Municipal Court records:\n",
      "- 132 per year\n",
      "\n",
      "Frequency of arrests resulting from Terry stops of bicyclists: 30.7%\n",
      "\n",
      "\n",
      "-- DEMOGRAPHICS --\n",
      "\n",
      "\n",
      "Fraction of Field Contacts involving a homeless subject, as noted by officer in a check box RMS field:\n",
      "- Terry Stops only: 30.0%\n",
      "- Bike infraction warnings only: 17.4%\n",
      "- Both combined: 27.8%\n",
      "\n",
      "      NOTE: the details in the narrative reports reviewed above indicate these percentages are likely an undercount\n",
      "\n",
      "\n",
      "All recorded bike infraction stops resulting in warnings (n = 125):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "White                        76.8\n",
       "Black or African American    20.0\n",
       "Unknown                       2.4\n",
       "Asian                         0.8\n",
       "Name: FCC Subject 1 Race, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Not Hispanic Or Latino    79.166667\n",
       "Hispanic Or Latino        20.833333\n",
       "Name: FCC Subject 1 Ethnicity, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Pretextual stops (bike infraction stops resulting in warnings in which suspicion was a factor in the stop) (n = 78):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "White                        76.923077\n",
       "Black or African American    21.794872\n",
       "Unknown                       1.282051\n",
       "Name: FCC Subject 1 Race, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Not Hispanic Or Latino    81.25\n",
       "Hispanic Or Latino        18.75\n",
       "Name: FCC Subject 1 Ethnicity, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Terry stops of bicyclists (n = 834):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "White                                        58.033573\n",
       "Black or African American                    30.575540\n",
       "Unknown                                       5.635492\n",
       "American Indian or Alaska Native              3.117506\n",
       "Asian                                         2.398082\n",
       "Native Hawaiian or Other Pacific Islander     0.239808\n",
       "Name: FCC Subject 1 Race, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Not Hispanic Or Latino    74.166667\n",
       "Hispanic Or Latino        25.833333\n",
       "Name: FCC Subject 1 Ethnicity, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# subset Field Contacts into (1) Terry Stops, and (2) 'Bike/infraction warning-no cite'\n",
    "spd_fc_terry_stops = spd_fc_data[spd_fc_data['FCC Type'] == 'Terry Stop']\n",
    "spd_fc_bike_warning = spd_fc_data[spd_fc_data['FCC Type'] == 'Bike/infraction warning-no cite']\n",
    "spd_fc_combined = spd_fc_data[logical_or(spd_fc_data['FCC Type'] == 'Terry Stop',\n",
    "                                         spd_fc_data['FCC Type'] == 'Bike/infraction warning-no cite')]\n",
    "\n",
    "# summarize\n",
    "data_avail_in_months = (datetime(2021,3,26)-datetime(2019,5,7)) / timedelta(days=30.5)\n",
    "print('\\nTime period of Field Contact data availability: {0:.1f} months, from {1} to {2}'\\\n",
    "      .format(data_avail_in_months, datetime(2019,5,7).date(), datetime(2021,3,26).date()))\n",
    "\n",
    "print('\\nSearch keywords used for public records request (plus \"Biker\" and \"Bicycler\", which returned no Field Contacts during this period):')\n",
    "display(spd_fc_data['Keyword'].value_counts())\n",
    "\n",
    "print('\\nFrom here on, we are specifically analyzing two largest types of Field Contacts for which subjects were reliably bicyclists\\n  in the narrative reports reviewed: \\n' + \\\n",
    "      '{0} Terry Stops and {1} \"Bike/infraction warning-no cite\" entries (ignoring less common categories - \\n'\\\n",
    "      .format(*spd_fc_data['FCC Type'].value_counts()[['Terry Stop','Bike/infraction warning-no cite']].values) + \\\n",
    "      '  campsite clearances, other infractions, tresspass warnings, park violations, pedestrian violations/warnings, citizen tips, etc.)')\n",
    "\n",
    "susp_frac = spd_fc_bike_warning['FCC Subject 1 Involvement Type'].value_counts()[['suspect','Suspicious']].sum() \\\n",
    "            / len(spd_fc_bike_warning)\n",
    "print('\\nFraction of bike infraction warning entries involving suspicion of subject unrelated to infraction (i.e., pretextual stops):\\n  {0:.1f}%'\n",
    "      .format(100 * susp_frac))\n",
    "\n",
    "print('\\nAnnual rate of police contacts based on these records:\\n' + \\\n",
    "      '- Terry Stops only: {0:.0f} per year (some may not be stops of bicyclists, but most likely are)\\n'\n",
    "      .format(12 * len(spd_fc_terry_stops) / data_avail_in_months) + \\\n",
    "      '- Bike infraction warnings only: {0:.0f} per year\\n'\n",
    "      .format(12 * len(spd_fc_bike_warning) / data_avail_in_months) + \\\n",
    "      '- Both combined: {0:.0f} per year\\n'\n",
    "      .format(12 * len(spd_fc_combined) / data_avail_in_months) + \\\n",
    "      '- ** Estimated Terry Stops that develop solely from a bike infraction, based on 2-in-7 statistic from above: {0:.0f} per year\\n'\n",
    "      .format((2/7) * 12 * len(spd_fc_terry_stops) / data_avail_in_months) + \\\n",
    "      '- ** Bike infraction warnings involving suspicion (pretextual stops): {0:.0f} per year\\n'\n",
    "      .format(susp_frac * 12 * len(spd_fc_bike_warning) / data_avail_in_months) + \\\n",
    "      '\\n      ** = suspicion-related stops enabled by existing bicycle infractions')\n",
    "\n",
    "annual_citation_rate = len(spd_citations[logical_and(spd_citations['Violation Date'].dt.year >= 2015,\n",
    "                                                     spd_citations['Violation Date'].dt.year <= 2019)]) / 5\n",
    "print('\\nCompare sum of two final annual rates to annual rate of bike-related citations (to bicyclists) based on Seattle Municipal Court records:\\n' + \\\n",
    "      '- {0:.0f} per year'.format(annual_citation_rate))\n",
    "\n",
    "print('\\nFrequency of arrests resulting from Terry stops of bicyclists: {0:.1f}%'\\\n",
    "      .format(100 * sum(spd_fc_terry_stops['FCC Disposition'].str.contains('Arrest',case=False)) \\\n",
    "              / len(spd_fc_terry_stops)))\n",
    "      \n",
    "\n",
    "print('\\n\\n-- DEMOGRAPHICS --')\n",
    "\n",
    "print('\\n\\nFraction of Field Contacts involving a homeless subject, as noted by officer in a check box RMS field:\\n' + \\\n",
    "      '- Terry Stops only: {0:.1f}%\\n- Bike infraction warnings only: {1:.1f}%\\n- Both combined: {2:.1f}%\\n'\n",
    "      .format(100 * sum(spd_fc_terry_stops['Event Statistics'].str.contains('Homelessness')) / len(spd_fc_terry_stops),\n",
    "              100 * sum(spd_fc_bike_warning['Event Statistics'].str.contains('Homelessness')) / len(spd_fc_bike_warning),\n",
    "              100 * sum(spd_fc_combined['Event Statistics'].str.contains('Homelessness')) / len(spd_fc_combined)) + \\\n",
    "      '\\n      NOTE: the details in the narrative reports reviewed above indicate these percentages are likely an undercount')\n",
    "\n",
    "susp_mask = logical_or(spd_fc_bike_warning['FCC Subject 1 Involvement Type'] == 'suspect',\n",
    "                       spd_fc_bike_warning['FCC Subject 1 Involvement Type'] == 'Suspicious')\n",
    "spd_fc_bike_warning_susp = spd_fc_bike_warning[susp_mask]\n",
    "spd_fc_bike_warning_non_susp = spd_fc_bike_warning[~susp_mask]\n",
    "\n",
    "def ethnicity_disp(input_data):\n",
    "    ethnicity_counts = input_data[input_data['FCC Subject 1 Race'] == 'White']['FCC Subject 1 Ethnicity'].value_counts().drop('Unknown')\n",
    "    print()\n",
    "    eth_summary = 100 * ethnicity_counts / ethnicity_counts.sum()\n",
    "    display(eth_summary)\n",
    "    return eth_summary\n",
    "\n",
    "print('\\n\\nAll recorded bike infraction stops resulting in warnings (n = {0}):'\\\n",
    "      .format(spd_fc_bike_warning['FCC Subject 1 Race'].value_counts().sum()))\n",
    "demos_spd_fc_bike_warning = 100 * spd_fc_bike_warning['FCC Subject 1 Race'].value_counts(normalize=True)\n",
    "display(demos_spd_fc_bike_warning)\n",
    "eth_spd_fc_bike_warning = ethnicity_disp(spd_fc_bike_warning)\n",
    "\n",
    "print('\\n\\nPretextual stops (bike infraction stops resulting in warnings in which suspicion was a factor in the stop) (n = {0}):'\\\n",
    "      .format(spd_fc_bike_warning_susp['FCC Subject 1 Race'].value_counts().sum()))\n",
    "demos_spd_fc_bike_warning_susp = 100 * spd_fc_bike_warning_susp['FCC Subject 1 Race'].value_counts(normalize=True)\n",
    "display(demos_spd_fc_bike_warning_susp)\n",
    "eth_spd_fc_bike_warning_susp = ethnicity_disp(spd_fc_bike_warning_susp)\n",
    "\n",
    "print('\\n\\nTerry stops of bicyclists (n = {0}):'\\\n",
    "      .format(spd_fc_terry_stops['FCC Subject 1 Race'].value_counts().sum()))\n",
    "demos_spd_fc_terry_stops = 100 * spd_fc_terry_stops['FCC Subject 1 Race'].value_counts(normalize=True)\n",
    "display(demos_spd_fc_terry_stops)\n",
    "eth_spd_fc_terry_stops = ethnicity_disp(spd_fc_terry_stops)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "c309fa84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3000x1650 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5.5),facecolor='w')\n",
    "\n",
    "labels = ['White','Hispanic/Latino','Asian/Pacific Islander','Black','Other/Unknown']\n",
    "colors = ['cornflowerblue','cornflowerblue','indianred','olivedrab','0.7']\n",
    "bump_label = [0,0,0,-0.4,0]\n",
    "bump_label_v = [0,0,0,0,0]\n",
    "label_star = [0,0,0,0,0]\n",
    "y_baseline = 4.2\n",
    "widths = array([demos_spd_fc_bike_warning['White'] * eth_spd_fc_bike_warning['Not Hispanic Or Latino']/100,\n",
    "                demos_spd_fc_bike_warning['White'] * eth_spd_fc_bike_warning['Hispanic Or Latino']/100,\n",
    "                demos_spd_fc_bike_warning['Asian'],\n",
    "                demos_spd_fc_bike_warning['Black or African American'],\n",
    "                demos_spd_fc_bike_warning['Unknown']])\n",
    "h1 = plt.barh(y_baseline,widths,height=0.5,left=array([0,*cumsum(widths)[:-1]]),color=colors,edgecolor='w',linewidth=2.0)\n",
    "h1[1].set_hatch('/////')   # for Hispanic/Latino category\n",
    "for w_idx, w in enumerate(widths):\n",
    "    plt.text(array([0,*cumsum(widths)[:-1]])[w_idx] + w/2 + bump_label[w_idx], y_baseline - 0.4 + bump_label_v[w_idx],\n",
    "             '{0:.1f}%{1}'.format(w,'$^*$'*label_star[w_idx]),\n",
    "             horizontalalignment='center',fontstyle='italic',color='0.3',fontsize=9)\n",
    "plt.text(2,y_baseline+0.3,r'$\\bf{Recorded~bicycle~infraction~stops~resulting~in~warnings}$ (Seattle PD, 2019-2021)')\n",
    "plt.text(86,y_baseline+0.34,'(n = {0})'.format(spd_fc_bike_warning['FCC Subject 1 Race'].value_counts().sum()),\n",
    "         style='italic',color='0.3',verticalalignment='center',fontsize=9)\n",
    "\n",
    "labels = ['White','Hispanic/Latino','Black','Other/Unknown']\n",
    "colors = ['cornflowerblue','cornflowerblue','olivedrab','0.7']\n",
    "bump_label = [0,0,-0.4,0]\n",
    "bump_label_v = [0,0,0,0]\n",
    "label_star = [0,0,0,0]\n",
    "y_baseline = 3.0\n",
    "widths = array([demos_spd_fc_bike_warning_susp['White'] * eth_spd_fc_bike_warning_susp['Not Hispanic Or Latino']/100,\n",
    "                demos_spd_fc_bike_warning_susp['White'] * eth_spd_fc_bike_warning_susp['Hispanic Or Latino']/100,\n",
    "                demos_spd_fc_bike_warning_susp['Black or African American'],\n",
    "                demos_spd_fc_bike_warning_susp['Unknown']])\n",
    "h2 = plt.barh(y_baseline,widths,height=0.5,left=array([0,*cumsum(widths)[:-1]]),color=colors,edgecolor='w',linewidth=2.0)\n",
    "h2[1].set_hatch('/////')   # for Hispanic/Latino category\n",
    "for w_idx, w in enumerate(widths):\n",
    "    plt.text(array([0,*cumsum(widths)[:-1]])[w_idx] + w/2 + bump_label[w_idx], y_baseline - 0.4 + bump_label_v[w_idx],\n",
    "             '{0:.1f}%{1}'.format(w,'$^*$'*label_star[w_idx]),\n",
    "             horizontalalignment='center',fontstyle='italic',color='0.3',fontsize=9)\n",
    "plt.text(2,y_baseline+0.3,r'$\\bf{Recorded~pretextual~stops~of~cyclists}$$^\\ddag$ (Seattle PD, 2019-2021)')\n",
    "plt.text(68,y_baseline+0.34,'(n = {0})'.format(spd_fc_bike_warning_susp['FCC Subject 1 Race'].value_counts().sum()),\n",
    "         style='italic',color='0.3',verticalalignment='center',fontsize=9)\n",
    "plt.text(100,y_baseline-0.67,'$^\\ddag$These represent bicycle infraction stops resulting in warnings in which ' + \\\n",
    "                             'some unrelated suspicion was recorded as a factor in the stop',\n",
    "         fontstyle='italic',horizontalalignment='right',color='0.5',fontsize=7)\n",
    "\n",
    "labels = ['White','Hispanic/Latino','Asian/Pacific Islander','Black',\n",
    "          'Native American/Alaska Native','Other/Unknown']\n",
    "colors = ['cornflowerblue','cornflowerblue','indianred','olivedrab','gold','0.7']\n",
    "bump_label = [0,0,0,-0.4,0.0,1.2]\n",
    "bump_label_v = [0,0,0,0,0,0]   # if needed, drop by -0.17\n",
    "label_star = [0,0,0,0,0,0]\n",
    "y_baseline = 1.6\n",
    "widths = array([demos_spd_fc_terry_stops['White'] * eth_spd_fc_terry_stops['Not Hispanic Or Latino']/100,\n",
    "                demos_spd_fc_terry_stops['White'] * eth_spd_fc_terry_stops['Hispanic Or Latino']/100,\n",
    "                demos_spd_fc_terry_stops['Asian'] + demos_spd_fc_terry_stops['Native Hawaiian or Other Pacific Islander'],\n",
    "                demos_spd_fc_terry_stops['Black or African American'],\n",
    "                demos_spd_fc_terry_stops['American Indian or Alaska Native'],\n",
    "                demos_spd_fc_terry_stops['Unknown']])\n",
    "h3 = plt.barh(y_baseline,widths,height=0.5,left=array([0,*cumsum(widths)[:-1]]),color=colors,edgecolor='w',linewidth=2.0)\n",
    "h3[1].set_hatch('/////')   # for Hispanic/Latino category\n",
    "for w_idx, w in enumerate(widths):\n",
    "    plt.text(array([0,*cumsum(widths)[:-1]])[w_idx] + w/2 + bump_label[w_idx], y_baseline - 0.4 + bump_label_v[w_idx],\n",
    "             '{0:.1f}%{1}'.format(w,'$^*$'*label_star[w_idx]),\n",
    "             horizontalalignment='center',fontstyle='italic',color='0.3',fontsize=9)\n",
    "plt.text(2,y_baseline+0.3,r'$\\bf{Inferred~Terry~stops~of~cyclists}$$^\\S$ (Seattle PD, 2019-2021)')\n",
    "plt.text(62,y_baseline+0.34,'(n = {0})'.format(spd_fc_terry_stops['FCC Subject 1 Race'].value_counts().sum()),\n",
    "         style='italic',color='0.3',verticalalignment='center',fontsize=9)\n",
    "plt.text(100,y_baseline-0.80,'$^\\S$These were identified as containing one of the keywords \"bicycle,\" \"bike,\" \"bicyclist,\" or \"cyclist\" ' + \\\n",
    "                             'in the associated Field Contact report;\\na small fraction (< ~15%) may represent stops by ' + \\\n",
    "                             'officers on bicycle patrol or stops involving a bicycle, rather than stops of cyclists',\n",
    "         fontstyle='italic',horizontalalignment='right',color='0.5',fontsize=7)\n",
    "\n",
    "plt.ylim([0,4.7])\n",
    "\n",
    "plt.legend(h3,labels,ncol=3,frameon=False,loc='lower left',prop={'size':9.5});\n",
    "plt.xticks([]); plt.yticks([])\n",
    "plt.gca().spines['top'].set_visible(False); plt.gca().spines['bottom'].set_visible(False)\n",
    "plt.gca().spines['left'].set_visible(False); plt.gca().spines['right'].set_visible(False)\n",
    "\n",
    "plt.savefig(current_results_dir + 'spd_field_contact_racial_demographics.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "id": "75449fda",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# housing status demographics from review of 40 narrative Field Contact reports\n",
    "\n",
    "fc_report_housing = 100 * spd_fc_summaries['Homelessness'].value_counts(normalize=True,dropna=False)\n",
    "presume_homeless_ratio = (fc_report_housing['Yes'] + fc_report_housing['Yes (presumed)']) / fc_report_housing['Yes']\n",
    "fc_data_homeless_recorded = 100 * sum(spd_fc_combined['Event Statistics'].str.contains('Homelessness')) / len(spd_fc_combined)\n",
    "fc_data_homeless_inferred = fc_data_homeless_recorded * presume_homeless_ratio\n",
    "\n",
    "def autopct(percent): return ('%.0f%%' % percent)\n",
    "\n",
    "plt.figure(figsize=(6,4),facecolor='w')\n",
    "wedges, labels, autopct = plt.pie([(100-fc_data_homeless_inferred),fc_data_homeless_inferred],\n",
    "                                  explode=tile(0.01,2),startangle=90,\n",
    "                                  labels=['Not\\nindicated','Homeless'],\n",
    "                                  colors=['0.4','0.7'],\n",
    "                                  labeldistance=1.10,autopct=autopct,pctdistance=0.75)\n",
    "autopct[0].set_color('w')\n",
    "for lab in labels: lab.set_fontsize(11)\n",
    "for pct in autopct: pct.set_fontsize(10)\n",
    "plt.title('Housing status in bicyclist Field Contact reports\\n(2019-2021)');\n",
    "# RE: text below... see updated version in Keynote presentation for OIG, 12/14/21\n",
    "# plt.text(0.5,0.05,\"Note: the 'homelessness' box was selected by officers in {0:.0f}% of $n$ = {1} reports; however,\\nthe frequency of homelessness mentioned in a sample of Field Contact narratives ($n$ = {2})\\nsuggests a scaling factor of ~{3:.1f}x to account for underreporting.\".format(fc_data_homeless_recorded,len(spd_fc_combined),len(spd_fc_summaries),presume_homeless_ratio),\n",
    "#          fontsize=7,fontstyle='italic',horizontalalignment='center',transform=plt.gcf().transFigure);\n",
    "plt.tight_layout()\n",
    "plt.savefig(current_results_dir + 'spd_field_contact_homelessness.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "id": "556870fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bicycle Helmet Required                                   0.550082\n",
       "Bicycle Rider Rights/Duties Violation                     0.305057\n",
       "Bicycle No/Improper Lamps/Reflectors                      0.069494\n",
       "Bicycle Yield Right of Way in Crosswalk                   0.022838\n",
       "Bicycle Riding on Roadways Rules Violation                0.019250\n",
       "Bicycle Unsafe Pass on Right                              0.008809\n",
       "Bicycle Riding on Sidewalk/Public Path Rules Violation    0.006852\n",
       "Bicycle No/Improper Hand Signals                          0.006525\n",
       "Bicycle No/Improper Brakes                                0.003915\n",
       "Bicycle Control One Hand Minimum Required                 0.002610\n",
       "Bicycle Clinging to Vehicle                               0.001305\n",
       "Bicycle Failure to Ride on Seat                           0.000979\n",
       "Bicycle Excess Passengers                                 0.000979\n",
       "Bicycle Parent of Child Responsibility                    0.000653\n",
       "Bicycle Riding More Than 2 Abreast                        0.000326\n",
       "Violating Laws While Riding Bicycle                       0.000326\n",
       "Name: Law Description, dtype: float64"
      ]
     },
     "execution_count": 404,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# frequency distribution of all Seattle bicycle citations\n",
    "spd_citations['Law Description'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd0bf75c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "PyCharm (Miscellaneous)",
   "language": "python",
   "name": "pycharm-bf1ba4a2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}