From 90117c61c54c15356889d48cbe2a0c7b0cde9ee4 Mon Sep 17 00:00:00 2001 From: Aristotel Fani Date: Fri, 22 Mar 2024 11:38:04 -0400 Subject: [PATCH 01/24] Add arrests percentage stops by contraband type graph (#286) * Add arrests by percentage view + component * add arrests percentage of searches graph * add graph for stop counts with or without driver arrested * Add graph for percentage of stops with arrests per stop purpose group * Add percentage of stops with arrests per stop purpose * Add percentage of searches for stop purpose groups graph * add arrests percentage of searches per stop purpose graph * add percentage of stops per contraband type * Update counts of stops w/o arrests graph --- .../src/Components/AgencyData/AgencyData.js | 8 +- .../src/Components/Charts/Arrest/Arrests.js | 136 +++++ .../Charts/Arrest/Arrests.styles.js | 32 ++ .../Arrest/Charts/CountOfStopsAndArrests.js | 150 ++++++ .../Arrest/Charts/PercentageOfSearches.js | 144 ++++++ .../PercentageOfSearchesForPurposeGroup.js | 151 ++++++ .../PercentageOfSearchesPerStopPurpose.js | 147 ++++++ .../Charts/Arrest/Charts/PercentageOfStops.js | 144 ++++++ .../PercentageOfStopsForPurposeGroup.js | 151 ++++++ .../PercentageOfStopsPerContrabandType.js | 147 ++++++ .../Charts/PercentageOfStopsPerStopPurpose.js | 146 ++++++ frontend/src/Components/Charts/ChartRoutes.js | 7 + .../NewCharts/HorizontalBarChart.js | 16 +- frontend/src/Components/Sidebar/Sidebar.js | 7 + frontend/src/Routes/slugs.js | 1 + nc/models.py | 8 +- nc/prime_cache.py | 8 + nc/urls.py | 40 ++ nc/views.py | 474 +++++++++++++++++- 19 files changed, 1909 insertions(+), 8 deletions(-) create mode 100644 frontend/src/Components/Charts/Arrest/Arrests.js create mode 100644 frontend/src/Components/Charts/Arrest/Arrests.styles.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js create mode 100644 frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js diff --git a/frontend/src/Components/AgencyData/AgencyData.js b/frontend/src/Components/AgencyData/AgencyData.js index f06e5dca..a8bdef2a 100644 --- a/frontend/src/Components/AgencyData/AgencyData.js +++ b/frontend/src/Components/AgencyData/AgencyData.js @@ -67,7 +67,13 @@ function AgencyData(props) { )} - {chartsOpen && } + {chartsOpen && ( + + )} ); diff --git a/frontend/src/Components/Charts/Arrest/Arrests.js b/frontend/src/Components/Charts/Arrest/Arrests.js new file mode 100644 index 00000000..1cb96b48 --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Arrests.js @@ -0,0 +1,136 @@ +import React, { useEffect, useState } from 'react'; +import ArrestsStyled from './Arrests.styles'; + +// Util +import { YEARS_DEFAULT } from '../chartUtils'; + +// Hooks +import useMetaTags from '../../../Hooks/useMetaTags'; +import useTableModal from '../../../Hooks/useTableModal'; + +// Children +import DataSubsetPicker from '../ChartSections/DataSubsetPicker/DataSubsetPicker'; +import PercentageOfStops from './Charts/PercentageOfStops'; +import useYearSet from '../../../Hooks/useYearSet'; +import PercentageOfSearches from './Charts/PercentageOfSearches'; +import CountOfStopsAndArrests from './Charts/CountOfStopsAndArrests'; +import PercentageOfStopsForStopPurposeGroup from './Charts/PercentageOfStopsForPurposeGroup'; +import PercentageOfStopsForStopPurpose from './Charts/PercentageOfStopsPerStopPurpose'; +import PercentageOfSearchesForStopPurposeGroup from './Charts/PercentageOfSearchesForPurposeGroup'; +import PercentageOfSearchesPerStopPurpose from './Charts/PercentageOfSearchesPerStopPurpose'; +import PercentageOfStopsPerContrabandType from './Charts/PercentageOfStopsPerContrabandType'; +import Switch from 'react-switch'; +import { SwitchContainer } from '../TrafficStops/TrafficStops.styled'; + +function Arrests(props) { + const [year, setYear] = useState(YEARS_DEFAULT); + const [yearRange] = useYearSet(); + const [togglePercentageOfStops, setTogglePercentageOfStops] = useState(true); + const [togglePercentageOfSearches, setTogglePercentageOfSearches] = useState(true); + + const renderMetaTags = useMetaTags(); + const [renderTableModal] = useTableModal(); + + useEffect(() => { + if (window.location.hash) { + document.querySelector(`${window.location.hash}`).scrollIntoView(); + } + }, []); + + const handleYearSelect = (y) => { + if (y === year) return; + setYear(y); + }; + + return ( + + {renderMetaTags()} + {renderTableModal()} +
+ +
+ + + + + + + Switch to view {togglePercentageOfStops ? 'all stop purposes' : 'grouped stop purposes '} + + setTogglePercentageOfStops(!togglePercentageOfStops)} + checked={togglePercentageOfStops} + className="react-switch" + /> + + {togglePercentageOfStops ? ( + + ) : ( + + )} + + + + Switch to view{' '} + {togglePercentageOfSearches ? 'all stop purposes' : 'grouped stop purposes '} + + setTogglePercentageOfSearches(!togglePercentageOfSearches)} + checked={togglePercentageOfSearches} + className="react-switch" + /> + + + {togglePercentageOfSearches ? ( + + ) : ( + + )} + + + + ); +} + +export default Arrests; + +export const ARRESTS_TABLE_COLUMNS = [ + { + Header: 'Year', + accessor: 'year', // accessor is the "key" in the data + }, + { + Header: 'White*', + accessor: 'white', + }, + { + Header: 'Black*', + accessor: 'black', + }, + { + Header: 'Native American*', + accessor: 'native_american', + }, + { + Header: 'Asian*', + accessor: 'asian', + }, + { + Header: 'Other*', + accessor: 'other', + }, + { + Header: 'Hispanic', + accessor: 'hispanic', + }, + { + Header: 'Total', + accessor: 'total', + }, +]; diff --git a/frontend/src/Components/Charts/Arrest/Arrests.styles.js b/frontend/src/Components/Charts/Arrest/Arrests.styles.js new file mode 100644 index 00000000..a29c47ce --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Arrests.styles.js @@ -0,0 +1,32 @@ +import styled from 'styled-components'; +import ChartPageBase from '../ChartSections/ChartPageBase'; +import { smallerThanDesktop, smallerThanTabletLandscape } from '../../../styles/breakpoints'; + +export default styled(ChartPageBase)``; + +export const ChartWrapper = styled.div` + width: 100%; + height: auto; +`; + +export const HorizontalBarWrapper = styled.div` + display: flex; + flex-direction: row; + flex-wrap: no-wrap; + width: 100%; + margin: 0 auto; + justify-content: space-evenly; + + @media (${smallerThanDesktop}) { + flex-wrap: wrap; + } +`; + +export const BarContainer = styled.div` + width: 100%; + height: 500px; + @media (${smallerThanTabletLandscape}) { + width: 100%; + } + display: ${(props) => (props.visible ? 'block' : 'none')}; +`; diff --git a/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js b/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js new file mode 100644 index 00000000..f53441b5 --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js @@ -0,0 +1,150 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function CountOfStopsAndArrests(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-stops-driver-arrested/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + const labels = ['Stops With Arrests', 'Stops Without Arrests']; + const colors = ['#96a0fa', '#5364f4']; + + const datasets = res.data.arrest_counts.map((dataset, i) => ({ + axis: 'y', + label: labels[i], + data: dataset.data, + fill: false, + backgroundColor: colors[i], + borderColor: colors[i], + hoverBackgroundColor: colors[i], + borderWidth: 1, + })); + const data = { + labels: ['White', 'Black', 'Hispanic', 'Asian', 'Native American', 'Other'], + datasets, + isModalOpen: false, + tableData, + csvData: tableData, + }; + + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => ctx.raw; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of stops that led to an arrest for a given race / ethnic group.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default CountOfStopsAndArrests; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js new file mode 100644 index 00000000..7f35db85 --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js @@ -0,0 +1,144 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfSearches(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-searches/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + const colors = ['#02bcbb', '#8879fc', '#9c0f2e', '#ffe066', '#0c3a66', '#9e7b9b']; + const data = { + labels: ['White', 'Black', 'Hispanic', 'Asian', 'Native American', 'Other'], + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages, + fill: false, + backgroundColor: colors, + borderColor: colors, + hoverBackgroundColor: colors, + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of searches that led to an arrest for a given race / ethnic group.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfSearches; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js new file mode 100644 index 00000000..2c4fc577 --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js @@ -0,0 +1,151 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfSearchesForStopPurposeGroup(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-searches-by-purpose-group/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + + const colors = { + 'Safety Violation': '#5F0F40', + 'Regulatory Equipment': '#E36414', + Other: '#0F4C5C', + }; + const data = { + labels: Object.keys(colors), + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages.map((d) => d.data), + fill: false, + backgroundColor: Object.values(colors), + borderColor: Object.values(colors), + hoverBackgroundColor: Object.values(colors), + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of stops that led to an arrest for a given stop purpose group.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfSearchesForStopPurposeGroup; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js new file mode 100644 index 00000000..5093e025 --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js @@ -0,0 +1,147 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfStopsForStopPurpose(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-searches-per-stop-purpose/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + + const data = { + labels: res.data.labels, + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages.map((d) => d.data), + fill: false, + // backgroundColor: Object.values(colors), + // borderColor: Object.values(colors), + // hoverBackgroundColor: Object.values(colors), + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of searches that led to an arrest for a given stop purpose.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfStopsForStopPurpose; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js new file mode 100644 index 00000000..2a6ad5ba --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js @@ -0,0 +1,144 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfStops(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-stops/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + const colors = ['#02bcbb', '#8879fc', '#9c0f2e', '#ffe066', '#0c3a66', '#9e7b9b']; + const data = { + labels: ['White', 'Black', 'Hispanic', 'Asian', 'Native American', 'Other'], + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages, + fill: false, + backgroundColor: colors, + borderColor: colors, + hoverBackgroundColor: colors, + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of stops that led to an arrest for a given race / ethnic group.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfStops; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js new file mode 100644 index 00000000..2f5fd55d --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js @@ -0,0 +1,151 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfStopsForStopPurposeGroup(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-stops-by-purpose-group/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + + const colors = { + 'Safety Violation': '#5F0F40', + 'Regulatory Equipment': '#E36414', + Other: '#0F4C5C', + }; + const data = { + labels: Object.keys(colors), + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages.map((d) => d.data), + fill: false, + backgroundColor: Object.values(colors), + borderColor: Object.values(colors), + hoverBackgroundColor: Object.values(colors), + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of stops that led to an arrest for a given stop purpose group.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfStopsForStopPurposeGroup; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js new file mode 100644 index 00000000..ce5a51a9 --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js @@ -0,0 +1,147 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfStopsPerContrabandType(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-stops-per-contraband-type/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + + const colors = ['#9FD356', '#3C91E6', '#EFCEFA', '#2F4858', '#A653F4']; + const data = { + labels: ['Alcohol', 'Drugs', 'Money', 'Other', 'Weapons'], + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages, + fill: false, + backgroundColor: colors, + borderColor: colors, + hoverBackgroundColor: colors, + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of stops that led to an arrest for a given contraband type.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfStopsPerContrabandType; diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js new file mode 100644 index 00000000..87d1e4bd --- /dev/null +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js @@ -0,0 +1,146 @@ +import React, { useEffect, useState } from 'react'; +import * as S from '../../ChartSections/ChartsCommon.styled'; + +// Children +import { P } from '../../../../styles/StyledComponents/Typography'; +import ChartHeader from '../../ChartSections/ChartHeader'; +import HorizontalBarChart from '../../../NewCharts/HorizontalBarChart'; +import axios from '../../../../Services/Axios'; +import useOfficerId from '../../../../Hooks/useOfficerId'; +import { ChartWrapper } from '../Arrests.styles'; +import NewModal from '../../../NewCharts/NewModal'; +import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; + +function PercentageOfStopsForStopPurpose(props) { + const { agencyId, agencyName, showCompare, year } = props; + + const officerId = useOfficerId(); + + const initArrestData = { + labels: [], + datasets: [], + isModalOpen: false, + tableData: [], + csvData: [], + loading: true, + }; + const [arrestData, setArrestData] = useState(initArrestData); + + useEffect(() => { + const params = []; + if (year && year !== 'All') { + params.push({ param: 'year', val: year }); + } + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${p.val}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-stops-per-stop-purpose/?${urlParams}`; + axios + .get(url) + .then((res) => { + const tableData = []; + const resTableData = res.data.table_data.length + ? JSON.parse(res.data.table_data) + : { data: [] }; + resTableData.data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + + const data = { + labels: res.data.labels, + datasets: [ + { + axis: 'y', + label: 'All', + data: res.data.arrest_percentages.map((d) => d.data), + fill: false, + // backgroundColor: Object.values(colors), + // borderColor: Object.values(colors), + // hoverBackgroundColor: Object.values(colors), + borderWidth: 1, + }, + ], + isModalOpen: false, + tableData, + csvData: tableData, + }; + setArrestData(data); + }) + .catch((err) => console.log(err)); + }, [year]); + + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; + + const subjectObserving = () => { + if (officerId) { + return 'by this officer'; + } + if (agencyId === '-1') { + return 'for the entire state'; + } + return 'by this department'; + }; + + const getYearPhrase = () => (year && year !== 'All' ? ` in ${year}` : ''); + + const getBarChartModalSubHeading = (title) => `${title} ${subjectObserving()}${getYearPhrase()}`; + + return ( + + setArrestData((state) => ({ ...state, isOpen: true }))} + /> + +

Percentage of stops that led to an arrest for a given stop purpose group.

+ setArrestData((state) => ({ ...state, isOpen: false }))} + /> + + + + + + + + ); +} + +export default PercentageOfStopsForStopPurpose; diff --git a/frontend/src/Components/Charts/ChartRoutes.js b/frontend/src/Components/Charts/ChartRoutes.js index 8fec035b..045d442f 100644 --- a/frontend/src/Components/Charts/ChartRoutes.js +++ b/frontend/src/Components/Charts/ChartRoutes.js @@ -15,6 +15,7 @@ import SearchRate from './SearchRate/SearchRate'; import Contraband from './Contraband/Contraband'; import UseOfForce from './UseOfForce/UseOfForce'; import FJRoute from '../Containers/FJRoute'; +import Arrests from './Arrest/Arrests'; function Charts(props) { const match = useRouteMatch(); @@ -63,6 +64,12 @@ function Charts(props) { renderLoading={() => } renderError={() => } /> + } + renderLoading={() => } + renderError={() => } + /> ); } diff --git a/frontend/src/Components/NewCharts/HorizontalBarChart.js b/frontend/src/Components/NewCharts/HorizontalBarChart.js index 2873e976..d3fd101b 100644 --- a/frontend/src/Components/NewCharts/HorizontalBarChart.js +++ b/frontend/src/Components/NewCharts/HorizontalBarChart.js @@ -35,8 +35,16 @@ export default function HorizontalBarChart({ displayStopPurposeTooltips = false, redraw = false, pinMaxValue = true, // Some graph percentages go beyond 100% + tickStyle = 'percent', + stepSize = 0.5, modalConfig = {}, }) { + const tickCallback = function tickCallback(val) { + if (tickStyle === 'percent') { + return `${val * 100}%`; + } + return val.toLocaleString(); + }; const options = { responsive: true, maintainAspectRatio, @@ -46,10 +54,8 @@ export default function HorizontalBarChart({ stacked: xStacked, max: pinMaxValue ? 1 : null, ticks: { - stepSize: pinMaxValue ? 0.1 : 0.5, - format: { - style: 'percent', - }, + stepSize: pinMaxValue ? 0.1 : stepSize, + callback: tickCallback, }, }, y: { @@ -152,12 +158,14 @@ export default function HorizontalBarChart({ position: 'top', }; modalOptions.plugins.tooltip.enabled = true; + modalOptions.plugins.tooltip.callbacks.label = tooltipLabelCallback; modalOptions.plugins.title = { display: true, text: modalConfig.chartTitle, }; modalOptions.scales.y.max = null; modalOptions.scales.y.ticks.display = true; + modalOptions.scales.x.ticks.callback = tickCallback; return modalOptions; }; diff --git a/frontend/src/Components/Sidebar/Sidebar.js b/frontend/src/Components/Sidebar/Sidebar.js index 97835c6b..d1caba5e 100644 --- a/frontend/src/Components/Sidebar/Sidebar.js +++ b/frontend/src/Components/Sidebar/Sidebar.js @@ -70,6 +70,13 @@ function Sidebar(props) { > Use of Force + + Arrests + ); diff --git a/frontend/src/Routes/slugs.js b/frontend/src/Routes/slugs.js index df6910ff..c04ba368 100644 --- a/frontend/src/Routes/slugs.js +++ b/frontend/src/Routes/slugs.js @@ -17,3 +17,4 @@ export const SEARCHES_SLUG = '/searches'; export const SEARCH_RATE_SLUG = '/search-rate'; export const CONTRABAND_SLUG = '/contraband'; export const USE_OF_FORCE_SLUG = '/use-of-force'; +export const ARREST_SLUG = '/arrests'; diff --git a/nc/models.py b/nc/models.py index 7bce1e8a..4987111d 100755 --- a/nc/models.py +++ b/nc/models.py @@ -235,7 +235,9 @@ def census_profile(self): WHEN nc_stop.purpose IN ({",".join(map(str, StopPurposeGroup.regulatory_purposes()))}) THEN 'Regulatory and Equipment' ELSE 'Other' END) as stop_purpose_group + , "nc_stop"."driver_arrest" , "nc_stop"."engage_force" + , (nc_search.search_id IS NOT NULL) AS driver_searched , "nc_search"."type" AS "search_type" , (CASE WHEN nc_contraband.contraband_id IS NULL THEN false @@ -260,7 +262,7 @@ def census_profile(self): LEFT OUTER JOIN "nc_contraband" ON ("nc_stop"."stop_id" = "nc_contraband"."stop_id") GROUP BY - 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 + 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 ORDER BY "agency_id", "date" ASC; """ # noqa @@ -277,7 +279,9 @@ class StopSummary(pg.ReadOnlyMaterializedView): agency = models.ForeignKey("Agency", on_delete=models.DO_NOTHING) stop_purpose = models.PositiveSmallIntegerField(choices=StopPurpose.choices) stop_purpose_group = models.CharField(choices=StopPurposeGroup.choices, max_length=32) + driver_arrest = models.BooleanField() engage_force = models.BooleanField() + driver_searched = models.BooleanField() search_type = models.PositiveSmallIntegerField(choices=SEARCH_TYPE_CHOICES) contraband_found = models.BooleanField() officer_id = models.CharField(max_length=15) @@ -356,6 +360,7 @@ class Meta: WHEN nc_person.gender = 'F' THEN 'Female' END) as driver_gender , (nc_search.search_id IS NOT NULL) AS driver_searched + , nc_stop.driver_arrest AS driver_arrest , nc_search.search_id , contraband_found , contraband_id @@ -388,6 +393,7 @@ class ContrabandSummary(pg.ReadOnlyMaterializedView): ) driver_gender = models.CharField(max_length=8, choices=GENDER_CHOICES) driver_searched = models.BooleanField() + driver_arrest = models.BooleanField() search = models.ForeignKey("Search", on_delete=models.DO_NOTHING) contraband_found = models.BooleanField() contraband = models.ForeignKey("Contraband", on_delete=models.DO_NOTHING) diff --git a/nc/prime_cache.py b/nc/prime_cache.py index 06008bd6..407f4215 100755 --- a/nc/prime_cache.py +++ b/nc/prime_cache.py @@ -30,6 +30,14 @@ "nc:contraband-percentages-grouped-stop-purpose", "nc:contraband-percentages-grouped-stop-purpose-modal", "nc:use-of-force", + "nc:arrests-percentage-of-stops", + "nc:arrests-percentage-of-searches", + "nc:arrests-stops-driver-arrested", + "nc:arrests-percentage-of-stops-by-purpose-group", + "nc:arrests-percentage-of-stops-per-stop-purpose", + "nc:arrests-percentage-of-searches-by-purpose-group", + "nc:arrests-percentage-of-searches-per-stop-purpose", + "nc:arrests-percentage-of-stops-per-contraband-type", ) DEFAULT_CUTOFF_SECS = 4 diff --git a/nc/urls.py b/nc/urls.py index 6a9a23ad..24b1b97e 100755 --- a/nc/urls.py +++ b/nc/urls.py @@ -80,4 +80,44 @@ views.AgencyUseOfForceView.as_view(), name="use-of-force", ), + path( + "api/agency//arrests-percentage-of-stops/", + views.AgencyArrestsPercentageOfStopsView.as_view(), + name="arrests-percentage-of-stops", + ), + path( + "api/agency//arrests-percentage-of-searches/", + views.AgencyArrestsPercentageOfSearchesView.as_view(), + name="arrests-percentage-of-searches", + ), + path( + "api/agency//arrests-stops-driver-arrested/", + views.AgencyCountOfStopsAndArrests.as_view(), + name="arrests-stops-driver-arrested", + ), + path( + "api/agency//arrests-percentage-of-stops-by-purpose-group/", + views.AgencyArrestsPercentageOfStopsByGroupPurposeView.as_view(), + name="arrests-percentage-of-stops-by-purpose-group", + ), + path( + "api/agency//arrests-percentage-of-stops-per-stop-purpose/", + views.AgencyArrestsPercentageOfStopsPerStopPurposeView.as_view(), + name="arrests-percentage-of-stops-per-stop-purpose", + ), + path( + "api/agency//arrests-percentage-of-searches-by-purpose-group/", + views.AgencyArrestsPercentageOfSearchesByGroupPurposeView.as_view(), + name="arrests-percentage-of-searches-by-purpose-group", + ), + path( + "api/agency//arrests-percentage-of-searches-per-stop-purpose/", + views.AgencyArrestsPercentageOfSearchesPerStopPurposeView.as_view(), + name="arrests-percentage-of-searches-per-stop-purpose", + ), + path( + "api/agency//arrests-percentage-of-stops-per-contraband-type/", + views.AgencyArrestsPercentageOfStopsPerContrabandTypeView.as_view(), + name="arrests-percentage-of-stops-per-contraband-type", + ), ] diff --git a/nc/views.py b/nc/views.py index 50c929e6..d353fab9 100644 --- a/nc/views.py +++ b/nc/views.py @@ -4,7 +4,7 @@ from functools import reduce from operator import concat -import numpy +import numpy as np import pandas as pd from dateutil import relativedelta @@ -1535,7 +1535,7 @@ def get(self, request, agency_id): def get_val(df, column, purpose): if column in df and purpose in df[column]: val = df[column][purpose] - return float(0) if numpy.isnan(val) else float(val) + return float(0) if np.isnan(val) else float(val) return float(0) for col in columns: @@ -1640,3 +1640,473 @@ def get(self, request, agency_id): df = pd.DataFrame(pivot_df) data = self.build_response(df, unique_x_range) return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfStopsView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrest_qs = qs + if year: + arrest_qs = arrest_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrest_qs = arrest_qs.values("driver_race_comb", "driver_arrest", "count") + + # Build charts data + df = pd.DataFrame(arrest_qs) + columns = ["White", "Black", "Hispanic", "Asian", "Native American", "Other"] + percentages = [0] * len(columns) + + if arrest_qs.count() > 0: + for i, c in enumerate(columns): + driver_arrest_cond = (df["driver_race_comb"] == c) & df["driver_arrest"] + filtered_df = df[driver_arrest_cond] + + arrests_count = filtered_df["count"].sum() + stops_count = df[df["driver_race_comb"] == c]["count"].sum() + percentages[i] = np.nan_to_num(arrests_count / stops_count) + + # Build modal table data + table_data_qs = ( + qs.filter(driver_arrest=True) + .values("driver_race_comb") + .annotate(stop_count=Sum("count")) + .annotate(year=ExtractYear("date")) + ) + + table_data = [] + if table_data_qs.count() > 0: + pivot_df = ( + pd.DataFrame(table_data_qs) + .pivot(index="year", columns=["driver_race_comb"], values="stop_count") + .fillna(value=0) + ) + + pivot_df = pd.DataFrame(pivot_df).rename( + columns={ + "White": "white", + "Black": "black", + "Hispanic": "hispanic", + "Asian": "asian", + "Native American": "native_american", + "Other": "other", + } + ) + table_data = pivot_df.to_json(orient="table") + + data = {"arrest_percentages": percentages, "table_data": table_data} + + return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfSearchesView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrest_qs = qs + if year: + arrest_qs = arrest_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrest_qs = arrest_qs.values( + "driver_race_comb", "driver_arrest", "driver_searched", "count" + ) + + # Build charts data + df = pd.DataFrame(arrest_qs) + columns = ["White", "Black", "Hispanic", "Asian", "Native American", "Other"] + percentages = [0] * len(columns) + + if arrest_qs.count() > 0: + for i, c in enumerate(columns): + arrest_cond = (df["driver_race_comb"] == c) & df["driver_arrest"] + arrests_count = df[arrest_cond]["count"].sum() + + searched_cond = (df["driver_race_comb"] == c) & df["driver_searched"] + searches_count = df[searched_cond]["count"].sum() + percentages[i] = np.nan_to_num(arrests_count / searches_count) + + # Build modal table data + table_data_qs = ( + qs.filter(driver_arrest=True) + .values("driver_race_comb") + .annotate( + stop_count=Sum("count"), + year=ExtractYear("date"), + ) + ) + + table_data = [] + if table_data_qs.count() > 0: + pivot_df = ( + pd.DataFrame(table_data_qs) + .pivot(index="year", columns=["driver_race_comb"], values="stop_count") + .fillna(value=0) + ) + + pivot_df = pd.DataFrame(pivot_df).rename( + columns={ + "White": "white", + "Black": "black", + "Hispanic": "hispanic", + "Asian": "asian", + "Native American": "native_american", + "Other": "other", + } + ) + table_data = pivot_df.to_json(orient="table") + + data = {"arrest_percentages": percentages, "table_data": table_data} + + return Response(data=data, status=200) + + +class AgencyCountOfStopsAndArrests(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrest_qs = qs + if year: + arrest_qs = arrest_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrest_qs = arrest_qs.values( + "driver_race_comb", "driver_arrest", "driver_searched", "count" + ) + + # Build charts data + df = pd.DataFrame(arrest_qs) + columns = ["White", "Black", "Hispanic", "Asian", "Native American", "Other"] + not_arrested_group = {"data": [0] * len(columns)} + arrested_group = {"data": [0] * len(columns)} + + if arrest_qs.count() > 0: + for i, c in enumerate(columns): + not_arrest_cond = (df["driver_race_comb"] == c) & ~df["driver_arrest"] + not_arrested_group["data"][i] = df[not_arrest_cond]["count"].sum() + + for i, c in enumerate(columns): + arrest_cond = (df["driver_race_comb"] == c) & df["driver_arrest"] + arrested_group["data"][i] = df[arrest_cond]["count"].sum() + + chart_data = [arrested_group, not_arrested_group] + + # Build modal table data + table_data_qs = ( + qs.filter(driver_arrest=True) + .values("driver_race_comb") + .annotate( + stop_count=Sum("count"), + year=ExtractYear("date"), + ) + ) + + table_data = [] + if table_data_qs.count() > 0: + pivot_df = ( + pd.DataFrame(table_data_qs) + .pivot(index="year", columns=["driver_race_comb"], values="stop_count") + .fillna(value=0) + ) + + pivot_df = pd.DataFrame(pivot_df).rename( + columns={ + "White": "white", + "Black": "black", + "Hispanic": "hispanic", + "Asian": "asian", + "Native American": "native_american", + "Other": "other", + } + ) + table_data = pivot_df.to_json(orient="table") + + data = {"arrest_counts": chart_data, "table_data": table_data} + + return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfStopsByGroupPurposeView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrests_qs = qs + if year: + arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrests_qs = arrests_qs.values("stop_purpose_group", "driver_arrest", "count") + + # Build charts data + arrest_percentages_df = pd.DataFrame(arrests_qs).fillna(value=0) + arrest_percentages = [] + stop_purpose_types = [ + StopPurposeGroup.SAFETY_VIOLATION, + StopPurposeGroup.REGULATORY_EQUIPMENT, + StopPurposeGroup.OTHER, + ] + + if arrests_qs.count() > 0: + for stop_purpose in stop_purpose_types: + group = { + "stop_purpose": " ".join( + [name.title() for name in stop_purpose.name.split("_")] + ), + "data": 0, + } + filtered_df = arrest_percentages_df[ + arrest_percentages_df["stop_purpose_group"] == stop_purpose.value + ] + stop_count = filtered_df["count"].sum() + arrest_found_count = filtered_df["driver_arrest"].sum() + group["data"] = np.nan_to_num(arrest_found_count / stop_count) + + arrest_percentages.append(group) + + data = { + "arrest_percentages": arrest_percentages, + "table_data": [], + } + return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfStopsPerStopPurposeView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrests_qs = qs + if year: + arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrests_qs = arrests_qs.values("stop_purpose", "driver_arrest", "count") + + # Build charts data + arrest_percentages_df = pd.DataFrame(arrests_qs).fillna(value=0) + arrest_percentages = [] + stop_purpose_types = StopPurpose.choices + + if arrests_qs.count() > 0: + for stop_purpose in stop_purpose_types: + group = { + "stop_purpose": " ".join([name.title() for name in stop_purpose[1].split("_")]), + "data": 0, + } + filtered_df = arrest_percentages_df[ + arrest_percentages_df["stop_purpose"] == stop_purpose[0] + ] + + stop_count = filtered_df["count"].sum() + arrest_found_count = filtered_df["driver_arrest"].sum() + group["data"] = np.nan_to_num(arrest_found_count / stop_count) + + arrest_percentages.append(group) + + data = { + "labels": [sp[1] for sp in stop_purpose_types], + "arrest_percentages": arrest_percentages, + "table_data": [], + } + + return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfSearchesByGroupPurposeView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrests_qs = qs + if year: + arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrests_qs = arrests_qs.values( + "stop_purpose_group", "driver_arrest", "driver_searched", "count" + ) + + # Build charts data + arrest_percentages_df = pd.DataFrame(arrests_qs).fillna(value=0) + arrest_percentages = [] + stop_purpose_types = [ + StopPurposeGroup.SAFETY_VIOLATION, + StopPurposeGroup.REGULATORY_EQUIPMENT, + StopPurposeGroup.OTHER, + ] + + if arrests_qs.count() > 0: + for stop_purpose in stop_purpose_types: + group = { + "stop_purpose": " ".join( + [name.title() for name in stop_purpose.name.split("_")] + ), + "data": 0, + } + filtered_df = arrest_percentages_df[ + arrest_percentages_df["stop_purpose_group"] == stop_purpose.value + ] + arrest_found_count = filtered_df[filtered_df["driver_arrest"]]["count"].sum() + search_count = filtered_df[filtered_df["driver_searched"]]["count"].sum() + + group["data"] = np.nan_to_num(arrest_found_count / search_count) + + arrest_percentages.append(group) + + data = { + "arrest_percentages": arrest_percentages, + "table_data": [], + } + return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfSearchesPerStopPurposeView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = StopSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrests_qs = qs + if year: + arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrests_qs = arrests_qs.values("stop_purpose", "driver_arrest", "driver_searched", "count") + + # Build charts data + arrest_percentages_df = pd.DataFrame(arrests_qs).fillna(value=0) + arrest_percentages = [] + stop_purpose_types = StopPurpose.choices + + if arrests_qs.count() > 0: + for stop_purpose in stop_purpose_types: + group = { + "stop_purpose": " ".join([name.title() for name in stop_purpose[1].split("_")]), + "data": 0, + } + filtered_df = arrest_percentages_df[ + arrest_percentages_df["stop_purpose"] == stop_purpose[0] + ] + + arrest_found_count = filtered_df[filtered_df["driver_arrest"]]["count"].sum() + search_count = filtered_df[filtered_df["driver_searched"]]["count"].sum() + group["data"] = np.nan_to_num(arrest_found_count / search_count) + + arrest_percentages.append(group) + + data = { + "labels": [sp[1] for sp in stop_purpose_types], + "arrest_percentages": arrest_percentages, + "table_data": [], + } + + return Response(data=data, status=200) + + +class AgencyArrestsPercentageOfStopsPerContrabandTypeView(APIView): + @method_decorator(cache_page(CACHE_TIMEOUT)) + def get(self, request, agency_id): + year = request.GET.get("year", None) + + qs = ContrabandSummary.objects.all() + + agency_id = int(agency_id) + if agency_id != -1: + qs = qs.filter(agency_id=agency_id) + officer = request.query_params.get("officer", None) + if officer: + qs = qs.filter(officer_id=officer) + + arrests_qs = qs + if year: + arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) + + arrests_qs = arrests_qs.values("contraband_type", "driver_arrest").annotate( + contraband_found_count=Count( + "contraband_id", distinct=True, filter=Q(contraband_found=True) + ) + ) + + # Build charts data + arrest_percentages_df = pd.DataFrame(arrests_qs).fillna(value=0) + columns = ["Alcohol", "Drugs", "Money", "Other", "Weapons"] + arrest_percentages = [0] * len(columns) + + if arrests_qs.count() > 0: + for i, contraband in enumerate(columns): + filtered_df = arrest_percentages_df[ + arrest_percentages_df["contraband_type"] == contraband + ] + + arrest_found_count = filtered_df[filtered_df["driver_arrest"]][ + "contraband_found_count" + ].sum() + stop_count = filtered_df["contraband_found_count"].sum() + arrest_percentages[i] = np.nan_to_num(arrest_found_count / stop_count) + + data = { + "arrest_percentages": arrest_percentages, + "table_data": [], + } + + return Response(data=data, status=200) From 93eacc9764e9b07d239df4f963d55fa331c0abc3 Mon Sep 17 00:00:00 2001 From: Colin Copeland Date: Sat, 30 Mar 2024 11:03:40 -0400 Subject: [PATCH 02/24] Arrest data review (#253) --- .gitignore | 1 + .../2023-10-contraband-type/django.ipynb | 1653 +++ .../2024-01-arrest-data/arrest-v7.ipynb | 10582 ++++++++++++++++ nc/notebooks/2024-01-arrest-data/arrest.ipynb | 9285 ++++++++++++++ nc/notebooks/requirements.txt | 4 +- 5 files changed, 21523 insertions(+), 2 deletions(-) create mode 100644 nc/notebooks/2023-10-contraband-type/django.ipynb create mode 100644 nc/notebooks/2024-01-arrest-data/arrest-v7.ipynb create mode 100644 nc/notebooks/2024-01-arrest-data/arrest.ipynb diff --git a/.gitignore b/.gitignore index f5a196ad..06ad5bcf 100644 --- a/.gitignore +++ b/.gitignore @@ -16,6 +16,7 @@ traffic_stops.log.1 reports env venv +bin jmeter.log npm-debug.log .transifexrc diff --git a/nc/notebooks/2023-10-contraband-type/django.ipynb b/nc/notebooks/2023-10-contraband-type/django.ipynb new file mode 100644 index 00000000..eae3f90b --- /dev/null +++ b/nc/notebooks/2023-10-contraband-type/django.ipynb @@ -0,0 +1,1653 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "641a3449-6579-42d1-b43b-5f62c4000248", + "metadata": {}, + "outputs": [], + "source": [ + "#Setup Notebook to load Django code\n", + "# From project root, run: jupyter-lab\",\n", + "\n", + "import os\n", + "import sys\n", + "import io\n", + "from pathlib import Path\n", + "\n", + "django_project_dir = Path('../../..')\n", + "sys.path.insert(0, str(django_project_dir))\n", + "os.environ.setdefault(\"DJANGO_SETTINGS_MODULE\", \"traffic_stops.settings.dev\")\n", + "os.environ[\"DJANGO_ALLOW_ASYNC_UNSAFE\"] = \"true\"\n", + "\n", + "import django\n", + "django.setup()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "8889dce8-f479-41be-b578-99d6e7cc5eba", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "from django.db import connections\n", + "from django.db.models import Count, F, ExpressionWrapper, FloatField, Value, Q\n", + "from django.db.models.functions import ExtractYear, NullIf\n", + "from nc.models import ContrabandSummary \n", + "from nc import query\n", + "import pprint\n", + "\n", + "from pygments import highlight\n", + "from pygments.formatters import TerminalFormatter\n", + "from pygments.lexers import PostgresLexer\n", + "from sqlparse import format\n", + "from django.db.models import QuerySet\n", + "\n", + "\n", + "def print_sql(queryset: QuerySet):\n", + " formatted = format(str(queryset.query), reindent=True)\n", + " print(highlight(formatted, PostgresLexer(), TerminalFormatter()))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "b79b62ac-e622-4a55-b5cb-3e6b00f6255e", + "metadata": {}, + "outputs": [], + "source": [ + "# ContrabandSummary.refresh()" + ] + }, + { + "cell_type": "markdown", + "id": "9ca0c739-86f9-495c-b123-9cb53ecf1019", + "metadata": {}, + "source": [ + "## 1. CONTRABAND \"HIT RATE\"" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "2d54f9ea-b602-417d-bb77-37327da784ef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'Asian': [20.24],\n", + " 'Black': [27.66],\n", + " 'Hispanic': [17.13],\n", + " 'Native American': [23.33],\n", + " 'Other': [24.49],\n", + " 'White': [21.39]}" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "group_by = [\"driver_race\"]\n", + "df = query.contraband_query(agency_id=80, group_by=group_by)\n", + "chart = query.hit_rate_chart(df, group_by=group_by)\n", + "table = query.hit_rate_table(df, group_by=group_by)\n", + "chart\n", + "\n", + "# pprint.pprint(table, width=200, sort_dicts=False)\n", + "\n", + "# Total across race for each yearb" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "dbee6030-b115-46b6-903a-fc9ac012db4f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'Asian': [20.24],\n", + " 'Black': [27.66],\n", + " 'Hispanic': [17.13],\n", + " 'Native American': [23.33],\n", + " 'Other': [24.49],\n", + " 'White': [21.39]}" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "group_by = [\"driver_race\"]\n", + "df = query.contraband_query(agency_id=80, group_by=group_by)\n", + "chart = query.hit_rate_chart(df, group_by=group_by)\n", + "table = query.hit_rate_table(df, group_by=group_by)\n", + "chart\n", + "\n", + "# pprint.pprint(table, width=200, sort_dicts=False)\n", + "\n", + "# Total across race for each yearb" + ] + }, + { + "cell_type": "markdown", + "id": "8897df6b-5688-40d4-b39b-d4329544fc48", + "metadata": {}, + "source": [ + "## 2. CONTRABAND \"HIT RATE\" BY STOP PURPOSE" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "2f1a2188-cf3e-4ccf-a256-3c5787ae5ce1", + "metadata": {}, + "outputs": [], + "source": [ + "group_by = [\"driver_race\", \"stop_purpose_group\"]\n", + "df = query.contraband_query(agency_id=80, group_by=group_by)\n", + "chart = query.hit_rate_chart(df, group_by=group_by)\n", + "table = query.hit_rate_table(df, group_by=group_by)\n", + "# pprint.pprint(chart, sort_dicts=False)\n", + "\n", + "# pprint.pprint(table, width=200, sort_dicts=False)\n", + "\n", + "# response = {\"datasets\": {\n", + "# \"Regulatory and Equipment\": [\n", + "# {'label': 'Asian', 'data': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]},\n", + "# ],\n", + "# \"Safety Violation\": {},\n", + "# \"Other\": {},\n", + "# }}\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "fa7d9187-b688-445e-87c9-828b8869e16d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Other', 'Other', 'Other', 'Other', 'Other', 'Other',\n", + " 'Regulatory and Equipment', 'Regulatory and Equipment',\n", + " 'Regulatory and Equipment', 'Regulatory and Equipment',\n", + " 'Regulatory and Equipment', 'Regulatory and Equipment',\n", + " 'Safety Violation', 'Safety Violation', 'Safety Violation',\n", + " 'Safety Violation', 'Safety Violation', 'Safety Violation'],\n", + " dtype='object', name='stop_purpose_group')" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1 = df.pivot_table(\n", + " index=\"year\", columns=[\"stop_purpose_group\", \"driver_race\", ], values=\"contraband_found_count\", fill_value=0\n", + " ).astype(\"Int64\")\n", + "df1.columns.get_level_values(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "9875b806-6243-4f26-9761-fbeb86c736c5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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.....................
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" + ], + "text/plain": [ + " stop_purpose_group driver_race contraband_type year search_count \\\n", + "0 Other Asian Alcohol 2020 1 \n", + "1 Other Asian Drugs 2020 1 \n", + "2 Other Asian Money 2020 1 \n", + "3 Other Asian Other 2020 1 \n", + "4 Other Asian Weapons 2020 1 \n", + "... ... ... ... ... ... \n", + "1405 Safety Violation White None 2019 15 \n", + "1406 Safety Violation White None 2020 10 \n", + "1407 Safety Violation White None 2021 8 \n", + "1408 Safety Violation White None 2022 11 \n", + "1409 Safety Violation White None 2023 3 \n", + "\n", + " contraband_found_count \n", + "0 0 \n", + "1 0 \n", + "2 0 \n", + "3 1 \n", + "4 0 \n", + "... ... \n", + "1405 0 \n", + "1406 0 \n", + "1407 0 \n", + "1408 0 \n", + "1409 0 \n", + "\n", + "[1410 rows x 6 columns]" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "group_by = [\"stop_purpose_group\", \"driver_race\", \"contraband_type\"]\n", + "df = query.contraband_query(agency_id=80, group_by=group_by)\n", + "chart = query.hit_rate_chart(df, group_by=group_by)\n", + "table = query.hit_rate_table(df, group_by=group_by)\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "bbc2f500-061d-494e-98e0-4cbea3b64eda", + "metadata": {}, + "source": [ + "## 4. Contraband \"Hit rate\" by type" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2f40a244-b3bb-4eca-8ec9-e12f89d8048b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'Alcohol': [7.14],\n", + " 'Drugs': [63.04],\n", + " 'Money': [10.16],\n", + " 'Other': [5.78],\n", + " 'Weapons': [15.71]}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "group_by = [\"contraband_type\"]\n", + "df = query.contraband_query(agency_id=80, group_by=group_by)\n", + "chart = query.hit_rate_chart(df, group_by=group_by)\n", + "table = query.hit_rate_table(df, group_by=group_by)\n", + "chart" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "94f322cd-752f-438a-876d-00eeef6b3b84", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "03408451-3bf4-4871-b077-23edfc20b7b9", + "metadata": {}, + "outputs": [], + "source": [] + 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+ " 1,\n", + " 0,\n", + " 0,\n", + " 2,\n", + " 1,\n", + " 1,\n", + " 1,\n", + " 1,\n", + " 1],\n", + " 'Black': [0,\n", + " 224,\n", + " 107,\n", + " 95,\n", + " 86,\n", + " 150,\n", + " 259,\n", + " 415,\n", + " 148,\n", + " 319,\n", + " 392,\n", + " 343,\n", + " 303,\n", + " 294,\n", + " 388,\n", + " 227,\n", + " 150,\n", + " 203,\n", + " 349,\n", + " 254,\n", + " 344,\n", + " 572,\n", + " 352],\n", + " 'Hispanic': [0,\n", + " 43,\n", + " 17,\n", + " 11,\n", + " 13,\n", + " 17,\n", + " 31,\n", + " 38,\n", + " 12,\n", + " 22,\n", + " 25,\n", + " 28,\n", + " 22,\n", + " 25,\n", + " 20,\n", + " 18,\n", + " 14,\n", + " 28,\n", + " 25,\n", + " 18,\n", + " 25,\n", + " 51,\n", + " 42],\n", + " 'Native American': [0,\n", + " 0,\n", + " 0,\n", + " 1,\n", + " 0,\n", + " 0,\n", + " 1,\n", + " 2,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 2,\n", + " 1,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 1,\n", + " 1,\n", + " 0,\n", + " 0],\n", + " 'Other': [0,\n", + " 3,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 1,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 0,\n", + " 1,\n", + " 1,\n", + " 0,\n", + " 0,\n", + " 1,\n", + " 0,\n", + " 1,\n", + " 1,\n", + " 1,\n", + " 0,\n", + " 1,\n", + " 0,\n", + " 1],\n", + " 'White': [0,\n", + " 43,\n", + " 29,\n", + " 25,\n", + " 14,\n", + " 30,\n", + " 54,\n", + " 57,\n", + " 28,\n", + " 47,\n", + " 41,\n", + " 40,\n", + " 35,\n", + " 32,\n", + " 34,\n", + " 26,\n", + " 21,\n", + " 16,\n", + " 30,\n", + " 24,\n", + " 25,\n", + " 20,\n", + " 14]}" + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "table = df.pivot_table(index=\"year\", columns=[\"driver_race\"], values=\"contraband_found_count\", fill_value=0).astype(\"Int64\")\n", + "table = {\"labels\": list(table.index), \"datasets\": []}\n", + "for dataset in table.to_dict(\"list\"):\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cd55e470-2f24-4700-8dbb-181591832df7", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a84f8529-6b87-4739-a0a4-ec098ad89236", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "7a8e243f-00af-410a-a9e0-0c1624883d5d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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driver_racesearch_countcontraband_found_counthit_rate
0Asian841821.428571
1Black18253597432.728866
2Hispanic256954521.214480
3Native American30930.000000
4Other491224.489796
5White249268527.487961
\n", + "
" + ], + "text/plain": [ + " driver_race search_count contraband_found_count hit_rate\n", + "0 Asian 84 18 21.428571\n", + "1 Black 18253 5974 32.728866\n", + "2 Hispanic 2569 545 21.214480\n", + "3 Native American 30 9 30.000000\n", + "4 Other 49 12 24.489796\n", + "5 White 2492 685 27.487961" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1 = df.groupby(['driver_race'])[['search_count', 'contraband_found_count']].agg('sum').reset_index()\n", + "df1[\"hit_rate\"] = df1.contraband_found_count / df1.search_count * 100\n", + "df1" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "5199f04d-1548-4296-ac91-db4333065708", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'Asian': [21.428571428571427],\n", + " 'Black': [32.72886648770065],\n", + " 'Hispanic': [21.214480342545738],\n", + " 'Native American': [30.0],\n", + " 'Other': [24.489795918367346],\n", + " 'White': [27.48796147672552]}" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "table = df1.pivot_table(columns=\"driver_race\", values=[\"hit_rate\"])\n", + "table.to_dict(\"list\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e765c888-2101-470a-8841-333ca6f2dbe5", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "df1a9388-e206-4896-8300-217cdfc2771b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "f2b19095-ff62-42f1-9a1a-42b068376f44", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "GroupAggregate (cost=388782.24..409052.15 rows=413639 width=87) (actual time=391.816..487.000 rows=1528 loops=1)\n", + " Output: driver_race, stop_purpose_group, contraband_type, (date_part('year'::text, stop_date)), count(DISTINCT search_id), count(DISTINCT contraband_id), (((count(DISTINCT contraband_id))::numeric * 1.0) / (NULLIF(count(DISTINCT search_id), 0))::numeric)\n", + " Group Key: (date_part('year'::text, nc_contrabandsummary.stop_date)), nc_contrabandsummary.driver_race, nc_contrabandsummary.stop_purpose_group, nc_contrabandsummary.contraband_type\n", + " -> Sort (cost=388782.24..389885.45 rows=441286 width=47) (actual time=391.724..425.388 rows=399617 loops=1)\n", + " Output: driver_race, stop_purpose_group, contraband_type, (date_part('year'::text, stop_date)), search_id, contraband_id\n", + " Sort Key: (date_part('year'::text, nc_contrabandsummary.stop_date)), nc_contrabandsummary.driver_race, nc_contrabandsummary.stop_purpose_group, nc_contrabandsummary.contraband_type\n", + " Sort Method: external merge Disk: 18472kB\n", + " -> Index Scan using nc_contraba_agency__a29b5e_idx on public.nc_contrabandsummary (cost=0.56..339456.74 rows=441286 width=47) (actual time=28.272..230.930 rows=399617 loops=1)\n", + " Output: driver_race, stop_purpose_group, contraband_type, date_part('year'::text, stop_date), search_id, contraband_id\n", + " Index Cond: (nc_contrabandsummary.agency_id = 80)\n", + "Planning Time: 1.370 ms\n", + "JIT:\n", + " Functions: 9\n", + " Options: Inlining false, Optimization false, Expressions true, Deforming true\n", + " Timing: Generation 17.508 ms, Inlining 0.000 ms, Optimization 3.375 ms, Emission 24.632 ms, Total 45.515 ms\n", + "Execution Time: 508.383 ms\n", + "CPU times: user 24.7 ms, sys: 10.9 ms, total: 35.6 ms\n", + "Wall time: 846 ms\n" + ] + }, + { + "data": { + "text/html": [ + "
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driver_race_combstop_purpose_groupcontraband_typeyearsearch_countcontraband_found_counthit_rate
0BlackOtherNone200100NaN
1AsianOtherNone2002100.0
2AsianRegulatory and EquipmentNone2002400.0
3AsianSafety ViolationNone2002300.0
4BlackOtherAlcohol200234341.0
........................
1523WhiteSafety ViolationDrugs2023881.0
1524WhiteSafety ViolationMoney2023881.0
1525WhiteSafety ViolationOther2023881.0
1526WhiteSafety ViolationWeapons2023881.0
1527WhiteSafety ViolationNone2023300.0
\n", + "

1528 rows × 7 columns

\n", + "
" + ], + "text/plain": [ + " driver_race_comb stop_purpose_group contraband_type year \\\n", + "0 Black Other None 2001 \n", + "1 Asian Other None 2002 \n", + "2 Asian Regulatory and Equipment None 2002 \n", + "3 Asian Safety Violation None 2002 \n", + "4 Black Other Alcohol 2002 \n", + "... ... ... ... ... \n", + "1523 White Safety Violation Drugs 2023 \n", + "1524 White Safety Violation Money 2023 \n", + "1525 White Safety Violation Other 2023 \n", + "1526 White Safety Violation Weapons 2023 \n", + "1527 White Safety Violation None 2023 \n", + "\n", + " search_count contraband_found_count hit_rate \n", + "0 0 0 NaN \n", + "1 1 0 0.0 \n", + "2 4 0 0.0 \n", + "3 3 0 0.0 \n", + "4 34 34 1.0 \n", + "... ... ... ... \n", + "1523 8 8 1.0 \n", + "1524 8 8 1.0 \n", + "1525 8 8 1.0 \n", + "1526 8 8 1.0 \n", + "1527 3 0 0.0 \n", + "\n", + "[1528 rows x 7 columns]" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "\n", + "qs = (\n", + " \n", + " .annotate(year=ExtractYear(\"date\"))\n", + " .values(\"year\", \"driver_race_comb\", \"stop_purpose_group\", \"contraband_type\")\n", + " .annotate(\n", + " search_count=Count(\"search_id\", distinct=True),\n", + " contraband_found_count=Count(\"contraband_id\", distinct=True),\n", + " )\n", + " .annotate(\n", + " hit_rate=ExpressionWrapper(\n", + " F(\"contraband_found_count\") * 1.0 / NullIf('search_count', Value(0)), output_field=FloatField()\n", + " )\n", + " )\n", + " .order_by(\"year\")\n", + ")\n", + "print(qs.explain(analyze=True, verbose=True))\n", + "pd.DataFrame(qs)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "d0087b90-f373-4714-9007-591280f3e148", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[34mSELECT\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mdriver_race\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mstop_purpose_group\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mcontraband_type\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[34mEXTRACT\u001b[39;49;00m(\u001b[33m'\u001b[39;49;00m\u001b[33myear\u001b[39;49;00m\u001b[33m'\u001b[39;49;00m\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[34mFROM\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mstop_date\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m)\u001b[37m \u001b[39;49;00m\u001b[34mAS\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33myear\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00mCOUNT(\u001b[34mDISTINCT\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33msearch_id\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m)\u001b[37m \u001b[39;49;00m\u001b[34mAS\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33msearch_count\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00mCOUNT(\u001b[34mDISTINCT\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mcontraband_id\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m)\u001b[37m \u001b[39;49;00m\u001b[34mAS\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mcontraband_found_count\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m((COUNT(\u001b[34mDISTINCT\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mcontraband_id\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m)\u001b[37m \u001b[39;49;00m*\u001b[37m \u001b[39;49;00m\u001b[34m1.0\u001b[39;49;00m)\u001b[37m \u001b[39;49;00m/\u001b[37m \u001b[39;49;00m\u001b[34mNULLIF\u001b[39;49;00m(COUNT(\u001b[34mDISTINCT\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33msearch_id\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m),\u001b[37m \u001b[39;49;00m\u001b[34m0\u001b[39;49;00m))\u001b[37m \u001b[39;49;00m\u001b[34mAS\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mhit_rate\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[37m\u001b[39;49;00m\n", + "\u001b[34mFROM\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[37m\u001b[39;49;00m\n", + "\u001b[34mWHERE\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33magency_id\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[37m \u001b[39;49;00m=\u001b[37m \u001b[39;49;00m\u001b[34m80\u001b[39;49;00m\u001b[37m\u001b[39;49;00m\n", + "\u001b[34mGROUP\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[34mBY\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mdriver_race\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mstop_purpose_group\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mcontraband_type\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m,\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[34mEXTRACT\u001b[39;49;00m(\u001b[33m'\u001b[39;49;00m\u001b[33myear\u001b[39;49;00m\u001b[33m'\u001b[39;49;00m\u001b[37m\u001b[39;49;00m\n", + "\u001b[37m \u001b[39;49;00m\u001b[34mFROM\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mnc_contrabandsummary\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[34m.\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33mstop_date\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m)\u001b[37m\u001b[39;49;00m\n", + "\u001b[34mORDER\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[34mBY\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[33myear\u001b[39;49;00m\u001b[33m\"\u001b[39;49;00m\u001b[37m \u001b[39;49;00m\u001b[34mASC\u001b[39;49;00m\u001b[37m\u001b[39;49;00m\n", + "\n" + ] + } + ], + "source": [ + "print_sql(qs)" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "id": "cb538ef7-2762-4307-be3b-da821cfb61ce", + "metadata": {}, + "outputs": [], + "source": [ + "from enum import Enum\n", + "\n", + "class StopPurpose(Enum):\n", + " SPEED_LIMIT_VIOLATION = 1 # Safety Violation\n", + " STOP_LIGHT_SIGN_VIOLATION = 2 # Safety Violation\n", + " DRIVING_WHILE_IMPAIRED = 3 # Safety Violation\n", + " SAFE_MOVEMENT_VIOLATION = 4 # Safety Violation\n", + " VEHICLE_EQUIPMENT_VIOLATION = 5 # Regulatory and Equipment\n", + " VEHICLE_REGULATORY_VIOLATION = 6 # Regulatory and Equipment\n", + " OTHER_MOTOR_VEHICLE_VIOLATION = 9 # Regulatory and Equipment\n", + " SEAT_BELT_VIOLATION = 7 # Regulatory and Equipment\n", + " INVESTIGATION = 8 # Investigatory\n", + " CHECKPOINT = 10 # Investigatory\n", + " \n", + " @classmethod\n", + " def safety_violation(cls):\n", + " return [cls.SPEED_LIMIT_VIOLATION.value, cls.STOP_LIGHT_SIGN_VIOLATION.value, cls.DRIVING_WHILE_IMPAIRED.value, cls.SAFE_MOVEMENT_VIOLATION.value]\n", + " \n", + " @classmethod\n", + " def regulatory_equipment(cls):\n", + " return [cls.VEHICLE_EQUIPMENT_VIOLATION.value, cls.VEHICLE_REGULATORY_VIOLATION.value, cls.OTHER_MOTOR_VEHICLE_VIOLATION.value, cls.SEAT_BELT_VIOLATION.value]\n", + " \n", + " @classmethod\n", + " def investigatory(cls):\n", + " return [cls.INVESTIGATION.value, cls.CHECKPOINT.value]\n", + "\n", + "contraband_summary_sql = f\"\"\"\n", + " WITH \n", + " contraband_groups AS (\n", + " SELECT\n", + " *\n", + " , (CASE WHEN nc_contraband.pints > 0 OR nc_contraband.gallons > 0 THEN true\n", + " ELSE false\n", + " END) AS alcohol_found\n", + " , (CASE WHEN nc_contraband.ounces > 0 OR nc_contraband.pounds > 0 OR nc_contraband.dosages > 0 OR nc_contraband.grams > 0 OR nc_contraband.kilos > 0 THEN true\n", + " ELSE false\n", + " END) AS drugs_found\n", + " , (CASE WHEN nc_contraband.money > 0 THEN true\n", + " ELSE false\n", + " END) AS money_found\n", + " , (CASE WHEN nc_contraband.dollar_amount > 0 THEN true\n", + " ELSE false\n", + " END) AS other_found\n", + " , (CASE WHEN nc_contraband.weapons > 0 THEN true\n", + " ELSE false\n", + " END) AS weapons_found\n", + " FROM nc_contraband\n", + " ),\n", + " contraband_types_without_id AS (\n", + " SELECT\n", + " contraband_id\n", + " , person_id\n", + " , search_id\n", + " , stop_id\n", + " , unnest(ARRAY['Alcohol', 'Drugs', 'Money', 'Other', 'Weapons']) AS contraband_type\n", + " , unnest(ARRAY[alcohol_found, drugs_found, money_found, other_found, weapons_found]) AS contraband_found\n", + " FROM contraband_groups\n", + " ), \n", + " contraband_types AS (\n", + " SELECT\n", + " ROW_NUMBER() OVER () AS contraband_type_id\n", + " , *\n", + " FROM contraband_types_without_id\n", + " ),\n", + " contraband_summary AS (\n", + " SELECT\n", + " nc_stop.stop_id\n", + " , date AT TIME ZONE 'America/New_York' AS stop_date\n", + " , nc_stop.agency_id\n", + " , (CASE WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.safety_violation()))}) THEN 'Safety Violation'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.investigatory()))}) THEN 'Investigatory'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.regulatory_equipment()))}) THEN 'Regulatory and Equipment'\n", + " ELSE 'Other'\n", + " END) as stop_purpose_group\n", + " , (CASE WHEN nc_person.ethnicity = 'H' THEN 'Hispanic'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'A' THEN 'Asian'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'B' THEN 'Black'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'I' THEN 'Native American'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'U' THEN 'Other'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'W' THEN 'White'\n", + " END) as driver_race\n", + " , (CASE WHEN nc_person.gender = 'M' THEN 'Male'\n", + " WHEN nc_person.gender = 'F' THEN 'Female'\n", + " END) as driver_gender\n", + " , (nc_search.search_id IS NOT NULL) AS driver_searched\n", + " , nc_search.search_id\n", + " , (contraband_id IS NOT NULL) AS contraband_id_found\n", + " , contraband_found\n", + " , contraband_id\n", + " , contraband_type_id\n", + " , contraband_type AS contraband_type_found\n", + " FROM \"nc_stop\"\n", + " INNER JOIN \"nc_person\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_person\".\"stop_id\" AND \"nc_person\".\"type\" = 'D')\n", + " LEFT OUTER JOIN \"nc_search\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_search\".\"stop_id\")\n", + " LEFT OUTER JOIN \"contraband_types\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"contraband_types\".\"stop_id\")\n", + " )\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ba4d751-becc-4a93-805d-e7a54690639d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 162, + "id": "69ca858b-d290-49dc-808c-338444dcc671", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 162, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 163, + "id": "d3b388cb-b357-41da-9163-7d733ccb130e", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/xj/05km0jzj6zv0nnrw6x4f4j8h0000gn/T/ipykernel_37974/562806849.py:2: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", + " df = pd.read_sql(\n" + ] + }, + { + "data": { + "text/html": [ + "
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contraband_type_foundstop_countsearch_countcountraband_found_countcontraband_hit_rate
0Alcohol724372435170.071379
1Drugs7243724345660.630402
2Money724372437360.101615
3Other724372434190.057849
4Weapons7243724311380.157117
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" + ], + "text/plain": [ + " contraband_type_found stop_count search_count countraband_found_count \\\n", + "0 Alcohol 7243 7243 517 \n", + "1 Drugs 7243 7243 4566 \n", + "2 Money 7243 7243 736 \n", + "3 Other 7243 7243 419 \n", + "4 Weapons 7243 7243 1138 \n", + "\n", + " contraband_hit_rate \n", + "0 0.071379 \n", + "1 0.630402 \n", + "2 0.101615 \n", + "3 0.057849 \n", + "4 0.157117 " + ] + }, + "execution_count": 163, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def contraband_hit_rate_by_type():\n", + " df = pd.read_sql(\n", + " f\"\"\"\n", + " {contraband_summary_sql}\n", + " SELECT\n", + " contraband_type_found\n", + " , count(stop_id) AS stop_count\n", + " , count(search_id) FILTER (WHERE driver_searched = true) AS search_count\n", + " , count(contraband_type_id) FILTER (WHERE contraband_found = true) AS countraband_found_count\n", + " FROM contraband_summary\n", + " WHERE agency_id IN (80)\n", + " AND driver_searched = true\n", + " AND contraband_type_found <> 'None'\n", + " GROUP BY 1\n", + " ORDER BY 1\n", + " \"\"\",\n", + " connections['traffic_stops_nc'],\n", + " )\n", + " df[\"contraband_hit_rate\"] = df.countraband_found_count / df.search_count\n", + " return df\n", + "contraband_hit_rate_by_type()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "be49a72c-e5a4-4468-9753-3c007349962e", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/nc/notebooks/2024-01-arrest-data/arrest-v7.ipynb b/nc/notebooks/2024-01-arrest-data/arrest-v7.ipynb new file mode 100644 index 00000000..b6ac7db3 --- /dev/null +++ b/nc/notebooks/2024-01-arrest-data/arrest-v7.ipynb @@ -0,0 +1,10582 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ae95c93d-6ad9-4d15-a75a-8d8932fd40ad", + "metadata": {}, + "source": [ + "# Arrest data v7 (prep for development)\n", + "\n", + "Date: February 28, 2024" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "55672bb9-b1e1-4f36-bbac-a131b14c8d19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + " \n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# jupyter nbconvert arrest-v7.ipynb --to html --no-input --output=arrest-data-preview-v7.html\n", + "# inv deploy-html-notebooks --dir-name 2024-01-arrest-data\n", + "\n", + "import os\n", + "\n", + "from sqlalchemy import create_engine\n", + "\n", + "from dash import Dash, html, dcc\n", + "import plotly.express as px\n", + "import pandas as pd\n", + "\n", + "import plotly\n", + "plotly.offline.init_notebook_mode()\n", + "\n", + "pg_engine = create_engine(\"postgresql://copelco@127.0.0.1:5432/traffic_stops_nc\")\n", + "pg_conn = pg_engine.connect()" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "58efb8b8-a90f-4122-ba1c-05be7969d070", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
idname
080Durham Police Department
\n", + "
" + ], + "text/plain": [ + " id name\n", + "0 80 Durham Police Department" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def lookup_agencies(agency_names):\n", + " return pd.read_sql(\n", + " f\"\"\"\n", + " SELECT\n", + " id\n", + " , name\n", + " FROM nc_agency\n", + " WHERE name ~ '{\"|\".join(agency_names)}'\n", + " ORDER BY 2\n", + " \"\"\",\n", + " pg_conn,\n", + " )\n", + "df = lookup_agencies({\n", + " \"Durham Police\",\n", + "})\n", + "agency_ids = df['id'].tolist()\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "19e0d5b4-9fb3-47bb-b5f7-75f3595d27a8", + "metadata": {}, + "outputs": [], + "source": [ + "from enum import Enum\n", + "\n", + "class StopPurpose(Enum):\n", + " SPEED_LIMIT_VIOLATION = 1 # Safety Violation\n", + " STOP_LIGHT_SIGN_VIOLATION = 2 # Safety Violation\n", + " DRIVING_WHILE_IMPAIRED = 3 # Safety Violation\n", + " SAFE_MOVEMENT_VIOLATION = 4 # Safety Violation\n", + " VEHICLE_EQUIPMENT_VIOLATION = 5 # Regulatory and Equipment\n", + " VEHICLE_REGULATORY_VIOLATION = 6 # Regulatory and Equipment\n", + " OTHER_MOTOR_VEHICLE_VIOLATION = 9 # Regulatory and Equipment\n", + " SEAT_BELT_VIOLATION = 7 # Regulatory and Equipment\n", + " INVESTIGATION = 8 # Investigatory\n", + " CHECKPOINT = 10 # Investigatory\n", + " \n", + " @classmethod\n", + " def safety_violation(cls):\n", + " return [cls.SPEED_LIMIT_VIOLATION.value, cls.STOP_LIGHT_SIGN_VIOLATION.value, cls.DRIVING_WHILE_IMPAIRED.value, cls.SAFE_MOVEMENT_VIOLATION.value]\n", + " \n", + " @classmethod\n", + " def regulatory_equipment(cls):\n", + " return [cls.VEHICLE_EQUIPMENT_VIOLATION.value, cls.VEHICLE_REGULATORY_VIOLATION.value, cls.OTHER_MOTOR_VEHICLE_VIOLATION.value, cls.SEAT_BELT_VIOLATION.value]\n", + " \n", + " @classmethod\n", + " def investigatory(cls):\n", + " return [cls.INVESTIGATION.value, cls.CHECKPOINT.value]" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "73b47c73-9ba7-4aae-80e7-83017396e58f", + "metadata": {}, + "outputs": [], + "source": [ + "colors = (\n", + " px.colors.qualitative.Pastel2[5], # Asian\n", + " px.colors.qualitative.Pastel[9], # Black\n", + " px.colors.qualitative.Antique[2], # Hispanic\n", + " px.colors.qualitative.Set2[2], # Native American\n", + " px.colors.qualitative.Set3[2], # Other\n", + " px.colors.qualitative.Pastel[0], # White\n", + ")\n", + "color_map = {\n", + " \"Asian\": px.colors.qualitative.Pastel2[5],\n", + " \"Black\": px.colors.qualitative.Pastel[9],\n", + " \"Hispanic\": px.colors.qualitative.Antique[2],\n", + " \"Native American\": px.colors.qualitative.Set2[2],\n", + " \"Other\": px.colors.qualitative.Set3[2],\n", + " \"White\": px.colors.qualitative.Pastel[0],\n", + "}\n", + "pd.set_option('display.max_rows', 500)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "a011c202-0aa8-4c2c-8bfd-6a6196fee3a3", + "metadata": {}, + "outputs": [], + "source": [ + "stops_summary_sql = f\"\"\"\n", + "SELECT\n", + " nc_stop.stop_id\n", + " , date AT TIME ZONE 'America/New_York' AS stop_date\n", + " , EXTRACT(year FROM date AT TIME ZONE 'America/New_York') AS \"year\"\n", + " , nc_stop.agency_id\n", + " , nc_stop.agency_description AS agency\n", + " , nc_stop.officer_id\n", + " , (CASE WHEN nc_stop.purpose = 1 THEN 'Speed Limit Violation'\n", + " WHEN nc_stop.purpose = 2 THEN 'Stop Light/Sign Violation'\n", + " WHEN nc_stop.purpose = 3 THEN 'Driving While Impaired'\n", + " WHEN nc_stop.purpose = 4 THEN 'Safe Movement Violation'\n", + " WHEN nc_stop.purpose = 5 THEN 'Vehicle Equipment Violation'\n", + " WHEN nc_stop.purpose = 6 THEN 'Vehicle Regulatory Violation'\n", + " WHEN nc_stop.purpose = 7 THEN 'Seat Belt Violation'\n", + " WHEN nc_stop.purpose = 8 THEN 'Investigation'\n", + " WHEN nc_stop.purpose = 9 THEN 'Other Motor Vehicle Violation'\n", + " WHEN nc_stop.purpose = 10 THEN 'Checkpoint'\n", + " END) as stop_purpose\n", + " , (CASE WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.safety_violation()))}) THEN 'Safety Violation'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.investigatory()))}) THEN 'Investigatory'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.regulatory_equipment()))}) THEN 'Regulatory and Equipment'\n", + " ELSE 'Other'\n", + " END) as stop_purpose_group\n", + " , (CASE WHEN nc_person.ethnicity = 'H' THEN 'Hispanic'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'A' THEN 'Asian'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'B' THEN 'Black'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'I' THEN 'Native American'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'U' THEN 'Other'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'W' THEN 'White'\n", + " END) as driver_race\n", + " , (CASE WHEN nc_person.gender = 'M' THEN 'male'\n", + " WHEN nc_person.gender = 'F' THEN 'female'\n", + " END) as driver_gender\n", + " , (nc_search.search_id IS NOT NULL) AS driver_searched\n", + " , driver_arrest\n", + "FROM \"nc_stop\"\n", + "INNER JOIN \"nc_person\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_person\".\"stop_id\" AND \"nc_person\".\"type\" = 'D')\n", + "LEFT OUTER JOIN \"nc_search\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_search\".\"stop_id\")\n", + "WHERE nc_stop.agency_id IN ({\",\".join(map(str, agency_ids))})\n", + "\"\"\"" + ] + }, + { + "cell_type": "markdown", + "id": "1cc18a79-4449-4702-b70a-4162655e90d1", + "metadata": {}, + "source": [ + "# 1. 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agencydriver_racestop_countsearch_countarrest_countsearch_arrest_ratestop_arrest_rate
0Durham Police DepartmentAsian658485320.3764710.004860
1Durham Police DepartmentBlack2194201852758360.3150000.026597
2Durham Police DepartmentHispanic45796260714950.5734560.032645
3Durham Police DepartmentNative American165430120.4000000.007255
4Durham Police DepartmentOther200149180.3673470.008996
5Durham Police DepartmentWhite101977251110020.3990440.009826
\n", + "
" + ], + "text/plain": [ + " agency driver_race stop_count search_count \\\n", + "0 Durham Police Department Asian 6584 85 \n", + "1 Durham Police Department Black 219420 18527 \n", + "2 Durham Police Department Hispanic 45796 2607 \n", + "3 Durham Police Department Native American 1654 30 \n", + "4 Durham Police Department Other 2001 49 \n", + "5 Durham Police Department White 101977 2511 \n", + "\n", + " arrest_count search_arrest_rate stop_arrest_rate \n", + "0 32 0.376471 0.004860 \n", + "1 5836 0.315000 0.026597 \n", + "2 1495 0.573456 0.032645 \n", + "3 12 0.400000 0.007255 \n", + "4 18 0.367347 0.008996 \n", + "5 1002 0.399044 0.009826 " + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "markdown", + "id": "d6d08bce-4ec1-419b-b45e-2e665fab3a21", + "metadata": {}, + "source": [ + "# 2. Percentage of searches that led to an arrest for a given race / ethnic group" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "a91e3266-f3b9-44d5-be70-d12c4fc6dd8a", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "Driver race=%{y}
agency=Durham Police Department
Arrest rate by searches=%{text}", + "legendgroup": "Asian", + "marker": { + "color": "rgb(255,242,174)", + "pattern": { + "shape": "" + } + }, + "name": "Asian", + "offsetgroup": "Asian", + "orientation": "h", + "showlegend": true, + "text": [ + 0.3764705882352941 + ], + "textposition": "auto", + "texttemplate": "%{x:,.1%}", + "type": "bar", + "x": [ + 0.3764705882352941 + ], + "xaxis": "x", + "y": [ + "Asian" + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "Driver race=%{y}
agency=Durham Police Department
Arrest rate by searches=%{text}", + "legendgroup": "Black", + "marker": { + "color": "rgb(180, 151, 231)", + "pattern": { + "shape": "" + } + }, + "name": "Black", + "offsetgroup": "Black", + "orientation": "h", + "showlegend": true, + "text": [ + 0.3149997301236034 + ], + "textposition": "auto", + "texttemplate": "%{x:,.1%}", + "type": "bar", + "x": [ + 0.3149997301236034 + ], + "xaxis": "x", + "y": [ + "Black" + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "Driver race=%{y}
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agencydriver_racestop_countsearch_countarrest_countsearch_arrest_ratestop_arrest_rate
0Durham Police DepartmentAsian658485320.3764710.004860
1Durham Police DepartmentBlack2194201852758360.3150000.026597
2Durham Police DepartmentHispanic45796260714950.5734560.032645
3Durham Police DepartmentNative American165430120.4000000.007255
4Durham Police DepartmentOther200149180.3673470.008996
5Durham Police DepartmentWhite101977251110020.3990440.009826
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kQAIkQAIkQAIkQAIkENkIOKxQkz3S3D2Gm5wS9NnXD5Ub91byQWSE9jIuIsij32QVfTR77K9qfi0RahKB0Ma9mhIB8tJUyb23evH5e88CJVMs2UNNBJOIJhFjEpEkEWnyktax7yS1X9oyby8V/SAlT5kW6gVeXuRDK9MXrMPsxRsxrFcr1KlaSlWXkwrlRUsiHCRaKqT0qN7DZ0PEjaRiSUqWFInSqdlyoPrzvjWTlSzUhJq8TA/r3UoXLSabf8sLrCZkhJOkBoq82L50HKJHd1XtyAvkxp2H0ca9aohDEoGZImmiIJFNEvUjkSSDezTXiUXtpVlecPt1aYJUyROriJp2PSeoqB+Np3ytdisvJZH0I2Tk61WbBL7QhibUZJ4ePHqmE4YyAJF31Zr2xafPfmpfPymaUJM/S7+a1a2oIgLl4AN52dZe3uXlu3vbusibM7OKQEmZLJEa34oNe5XElEg+SQeWvtVtO1hJywPrpqr5bOQxXIkP/XUv/Vu5ca+Sn3KqYXApn9rG8NV+LoaxA9rr5kGiniQCLDSZY2xd3vz3AX5pMUAJuoWT++gE3qQ5q1QknMhGEYJSQhq/tk4MF4c848JChJRWpL/12w9R0Y6hRYVqQk4k1+j+7RDjf+tRpK3I25CEmsbLUDZK1M7UeWtVJNvPpQrpNqwXBrLvYcIEgVGB2r1l30LZv1BbHyLSBnk2Q9XyxdTngHbYg/7nVnAPib7YlmdJomdFPPv6+atoRFPWqSaIRbjKLwE0Sf3w8XNMW7BOCRMRiSIU5QTcvp0aqedYnpmhE3+HRJxNH9nNpNM6NeHfvml1FdkWWhk+ebFJz4EpKZ+hfTbor8nQPvONCTXtFwfd2tRBuybVdZ+9G3b8pcRhSM+T9ouDXh4N0aJ+JR0WkceybgyFmrHPlJTJE9v056BIwSZ1flYRafL53bDjUPUzd/uycUiXOnloU8nvkwAJkAAJkAAJkAAJkEC4EnBYoaa9vLVuVEVFTYVWJIpEoh4kFa5/18ZBqmtRJkc3e6toLXOFmggdTZBoDfcYMhM79p/E/rVTVGqeJUKtXa8JKrJGEyNa29rLtP7YzRFqmjyRF9aOzWvq0g/1oQT38ikvyPnLtTYaGSipqTMX/amLAtJe5EUEyEu2VkRuFqzQVkVD7Vg+XkkgEWoSrbR0ppeKsrCkPHryQqWWSoqiRFGJnJGID3nJkxLcxuPL/9yDEVP+wKQhnVSk0LWb91C7tZfRMZq7h5rIr3/+faAinF6+eavS4UTUaRuta8IkODGiCaWzO+fqRKOMRQRovrItFUOJrIuG//bW8/79TyVMF07uiyJuOdG0y6jAFC+9yEpDvsEJNRGNrTzHqkjE8YM6mr05vLF1qQlVTS5pfdFYiGRaM3eo+nJw4zdlfYjAFHknaXISASRzLFFrEo0aUukyYKpK+9u9cqJOHEn9XQdPqdTtkISaRLf93PBXJRG0w1BkrkTmSx+ObJyhZMOiVdtVuqhI6Up6Kc3vP/qgePVOOjmuMTEUgRINVqRKRyRLkgBbl4wNcTzacxhSBFRo63TBiq2YOHsVRvcXeRsYgWpYOvadrKLT5JlOlTwwKlSKfF7JZ1mnlrVURFxoRQ7HkPW4afFoFY0XUjHnOTBFqBme8mn42aCtSVM+8w2FmvbZqT2zItBMLfrjlPnWT+eWVOKl63Z9I9SMfaaE989BLQpzvFdHVClX1NThsh4JkAAJkAAJkAAJkAAJhAsBhxVqp/++jmZdR6nf6JuSTiL7T8mpcZKCKdEj+kV7IVk7bxhyZk1vFaGmSbldKyYgdcqkFgm1svU81XWG0VAijErX7hYklcgcoSbperVaBUaTBe4N9p3au0n2QpIIOynBvXxKJFqFhj2NcteEw4BuTeFeq5wuQs1QqEn7cn/px4W9C1XEjaQkSmqiFEmxdMuTVd1DS48N6WkSadJn5G9B0tm0+lqkj/w9OKG2dc9x9Bo+S0VgSSSWNg5jstZUoSZiZc6STerkTGPl8IYZKiopOGGiXSNCydjLu+zLVr5+jxA/ZLTxrN1yEIPGL1B1JepN9g38qYQbfipeQLfPV3BCTVI3y9btrktFlZf0/Hmyok6V0kEiwILriLF1KXtjScSSfsScdr22L6KWQhnc+EMauIg0iYoS6W5YTBFqFRv1UuM1lOSmCDW5nxaNpqVjnrlwQ6V8S3SYZ7t6qkva50Nw49BSnUNaH9JPP3//UFOigxPbcm9T16k2Z5JeL9GSxor0R0s/NPZ92T9Q9gUMqUh/ytTphrSpk2O5t1eIdeWb5jwHlgg1w88GuWdwa9LwM99QqGmfnZYctKCNs3LZopgwqGMQLsEJNWPRmOH9c1D2COzUf0qQqNNQJ5UVSIAESIAESIAESIAESCCcCDisUJN0kp/qdjcp4kTmQjZAHzJhkZJvhmk1EikiESPyAicyR3sx2r1qkkoL1Epwe6gZEx5aGlJYhJpEbcnm/IZ7iIkwkCgW/QgEc4SajEdStSSaTDbplwgxKRIhtnhaf5UOG9zLp0RX/dK8v9H9s/YdOYvO/afq9gIK6UVeE2oX9y1UUkeiNyTFVf7T3+dJP8LM2DP1+s17lKjRWX1L5Jns7ZQ2dTK8ffcB9doNUV+T1DkpwQk1LdrRUECN6NNabfCvX0wVajMWrMesxRuUfJDDGmTjcEm/lL3DJF02rEJNmwdJp61XvYzRjxuJTtMO25BURNknTSLOtCLXLpk5UEUohnTKpxzsIZJo655jKvJKK5OHdtZtRh/c552xdamlDMv+bWlSJg1yqeG6sESoaRGnZYoXUIdAZEybEokTxVfptjIHoUWolazZRQm183vmB9m/y1ShpskPOahD0iPlc0c+f/QFosagS6vaqk+GRUS3RPTYWqiZuk7ltORte4+r6DOJsDJW5PNKPkuCk2YZ06XUHcgS3Ho5dvoyWv86Lkg6ekg/S815DiwRaoafDdKX4Nak4We+oVDTUp1D2nswuLFqKbfy+TZrjGeQauYItfD+OSiRnhLxKZ/B8lnMQgIkQAIkQAIkQAIkQAKRiYDDCjVJeSpVq6t68ZWXVnl5NVZE1Ehqjba3kbzA6p+4Jtdo6ZnaRuDDJi/Gyg17v4mgsYZQM2XPI20c2t5XZ3bO1e3jJN/TUhIlCkyiwaSYK9S0ewhHEYKSmiP78Gj7Fmkvn/r7Wck12kuiJgv0mf+XHuWh9qoKTqhJ1F3xXzojbaqkRuWG2qPs+N8qRU+lyW2aGWyqoZzU2WXgNCWtZI8xrWgvoJYINa3f+vscae2aKtREOuqndmrXa/sghVWoSYre9xXbqYMYlswYYPJnkkScyX5qIhcl/UvbI04Tavr78hlrVKIjN+8+qtIVRT6HFkVkbF1qe/j9PrVfEMEi0Uk/VPMIksZorlDTDisRWbhyzuAgQxBRZopQ04ScFrGqNWKqUJP6WvrjuvnDVfqw4f6GWnr0/Im98cP3uYOdP1sLNVPXqZaGKfu9aSecGnZa43ZymxyAEcPkNalfUaKIJYoqpGdev745z0Fwn2nSnqmyXepaKtS0z05zn1m5pzZOEa3Ht8wKcriDOUItvH8OysEj8ksEU/fPs2jR8CISIAESIAESIAESIAESsJCAwwo14SUb1vcbNVelsc0a00P9X79IWqgIDIlIEUkjaZKSSiWbN2sbjT9+9hLl6vVQX9+zapKKlpLIIonckNQaSbGRIi9DQyctUi97hqd8mhKhJm2IXJA+hrbnkTYG2bNI9i6SiA+JtNHKqGlLsHTd7iDRduYINRFG+XJm1m2ELu1KVJhsZl+2hJt6+bn6z111kqe+tNPuL/Wkvn76l4jLem0HqzRObQPq4ISaJt606DORZrJpvMhG/dLVaxr2HDqj9tMKLvVTk5ydWtSER4uausslmkaiaiwRalpqlkSXyb21ze+1gxdixnAN9VACLVrn2GZv3ab7EunVvvdEJbTCKtRkoJpwnT22h0rb1S8iyyQ6LUmi+JC0tZ9LFwqyV56sH1lHsp+g7Cu4bP0ejJwq+8gFylCtyLzIeLNkDDyNVYpIOYmQlGdKS80M7vPL2LrUDgIxPOhAoiU9B88IEv1orlDTooAMpYUc0iAy1JSUT00eNa5dHv26NFafCXIC54gpi9WehiHtoaZx0ESvRHNJGqT+AR5SR9qRfcWknwun9A0yN8L1/KWbSlzZWqiZuk611D15RmeO8gyyh5dEIcnnxrT5azHnj00wliotEbESWRtSCrccxCFC1XBdhPaz0dTnIKTPtPAQajIOLQJTJLjMvVbkIBs5HEIkdXBFE5b6z6gcTiOHEsgaMzyUwFjKp7ZdQHj8HJS1+0uL/iqqVdtLNLS55PdJgARIgARIgARIgARIIDwJOLRQk42aZX8W2QhbipyGmTVjGjx9/goXrtzSpbdpm4NrL3zy0tKwRlm1P5ls4C7/4Dd8SWnRfYzaX6xVo8rw8fmsonK0dDdLhVqbnuNVpJyk/OTOngEPH79Qe8sEV+QlS6LwpIgwypIxNY6duYJVG/epVMJ1C4brUtLMEWoimkRq1K9eRr3gfvjogz93HFaiR4uYCRSQ3ZU06dyqljqswdnZWXHTZICkiMpG43FixVTRbZJOKN/38mym+qwJNaknqZPyEnf5+h38uf0vxVbSYWUfMU2CFHXLhdLFC6gTLK/cuKtSFCWyRyKZZJ81Y0WL1pP2alYqgZTJk+DkuSs4dPyCqm6JUJPrtKhFeektXSy/Eiqy75cUGU9op3zKaYeSLibXy35lKrJr1xHdXmTWEGrayZXSJ+GeN2cmtQH/qfPX1BxpIlI78KFm5R/VJu8iBiUiUU4b3bZ0rIra0vb5kjlq2aAy5OCIPNkz4t6jZxg6cZFKk/7+u+yIGT06Dhw7r9L/ZIN5mf+QirF1KVGR7p1GqPUm7Zb+Ib8SAlPmrlFN6aeCmivU5JmWvQdF0speVblzZMSNW/fVmpNiilCTKDeJ3JI2ZF1J2rV+qqspQk2LwpTnR9o4uH6abn9CjZd2+IE8yyLM48SOhav/3MH2fSfgli8bpg3vanOhZuo6lTlr3WOcesblOa1crqjaf23L7mPqwAsRqyJQtMMXJDVR1r1wuHD1lvpFRP+uTSCSMriinXAaUhScsWtNfQ5C+kwLL6EmAkx+tkiR50ek97Vb97Bywz71d/klQ3BF/1p5Tt+999Gl68s1pgg1qWern4MXr92GpFkXzp9TRdTJfMpzLT8/OjYL/TCKED9I+E0SIAESIAESIAESIAESsAEBhxZqwlOk2qZdRyApVIYbYsvJhLK/VPmS3+v26fptyeYgG8XLy65smm+4r5r2gqXNmUSLZMuUFotX74B+RFBwL/wS7SNRP/r7sIk4kn3L5PRPKXJvw43PDdeIRHz1GTFbRX5pRaJERvRpE2TvJREXxtIwja05ebmdsXB9EF7Sl+5t66hoJa2IdBOpJdFOUvQ305b0t/6j5wV5oZOXwa6tausiujShpkXpaO2KZBrVr41ufy/ZB23YZNlEPpCLPvPBPZojXeqQT/1csWEvZP8ircjLZt1qZdQ8t6hfCb08GqpvibCR8WxYOBJZM/0XcaXtk6R/Et2btx9UtJT+nmMSeSNi1dhBEYacZY8/ESbykqkV4SdiTdo8snEmEsSPgw8fP6FIlQ4qKkykrmEJTShJ+2OmL9PNkf69+nR2VxFqEukojLS98qSOREp6dW8WJH1PJJvU056jIT1bKOFqrP161cqgX9fGQVKRja214Nal8JWIT/05l3UyYbAH8uXMpGsqtPEbu6fIwW5e03TyUuqIkF64cnuwacbG5m/OHxtx8eptNU8idpMkjq/2Q5s5qrsSB1K0qCFjkXraemtatwL6dnb/pqsiHRau3IYFy7d9MzeSli6naYa0PiTiTqSW7GsWUtEEuDxL8ksH/WLqOpVrJMJsxoJ16nNNK/K5Uavyj0qWSZH2Js5ZqTtgRKsnEk5SskOLwLpz/zH2rZ0SZO+6EAdLcXa4AAAgAElEQVT3v2+a8hxI1eA+08z5bDD1M19L8fy5VCHIibZakfmQnw8SNakVSVHu28U9SNSasXGfv3wTS9fuUqcYp0uTHD8Vd1PRjLI3mpYmG9pnikQT2+LnoMyByGFJdZcia0MkYfP6lYL9hYgpc8s6JEACJEACJEACJEACJGArAg4v1PTByguMpM04OzupSCXtxEpD+CJEZI8tFxcXtcG21DdWJFLl8dOXSJ0iqXqptlaR1D/ZND9F0kRwdXUxqVkRMRJ9lCZVMhUtZo0iL8gSeRMndkwkl764OBttVl6SJUIlWZKEQV6MRGaKfBExIIJGS6PVGtFP+ZQItSfPXyFh/Li6FEjDm8mLnvRHXghFiiWIZzpzYXr/4VPEihkDGdKmtNoLnIxd1oFsqG44vtDmQPjce/hUyRJrryHDe8scPHzyArFiREeypAm/ERIyfxLxKP9JhF2SRAmMMpJ6Mqdx48RCogTxdLeRZ+vx0xfq7yE9W6ExMfy+RDUJI+lP8qQJzb082PoSYacJCxGywX0WmHNDTbrIvmg5sqQz59IQ6wpzeb5FMsq6j2el59vUDpq7TrXnVGJGkydLZFR+SZ1HT16oX3jImGLGCDw9OLiipeRKJJNENFlaQnsOtHaD+0yz9L6WXCefvy9fvUWSxAnC9JluiXSW/lrz56B+H+TzUj7D5TMvuMhiS3jxGhIgARIgARIgARIgARKwNgEKNWsTZXtWIxDSKZ9WuwkbIgEbEJCN1Au75VRy1tnJSUUVSuqrpIyumTssWAlvg644RJPaIQ36J6E6xMDNGKSI5407DqNQgZxInSIJPvp8xobtf0E2/g8uCtKM5sNU1VKpF6ab8mISIAESIAESIAESIAESCCMBCrUwAuTltiNAoWY7tmzZtgQkVdWwSDSrpO6FtLG+bXtlv63LflsiiELaY81+R2/ayC5cvY2GHYZ+U1m2I5g4yMOqUdSm9ei/WhRq5hJjfRIgARIgARIgARIggchAgEItMswC+2CUgJygeuTkReTPk1XtrcNCAlGFgJxiK/sWvnr9TqWLpk2dPPBQhlBSF6PK+NjPqEfA19cPItVu3X0IORFVUrIzZ0iN/CGcDBpeo5STXj988PlmL9Lwuj/vQwIkQAIkQAIkQAIkQAKWEKBQs4QaryEBEiABEiABEiABEiABEiABEiABEiABEnBYAhRqDjv1HDgJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkIAlBCjULKHGa0iABEiABEiABEiABEiABEiABEiABEiABByWAIWaw049B04CJEACJEACJEACJEACJEACJEACJEACJGAJAQo1S6jxGhIgARIgARIgARIgARIgARIgARIgARIgAYclQKHmsFPPgZMACZAACZAACZAACZAACZAACZAACZAACVhCgELNEmq8hgRIgARIgARIgARIgARIgARIgARIgARIwGEJUKg57NRz4CRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAApYQoFCzhBqvIQESIAESIAESIAESIAESIAESIAESIAEScFgCFGoOO/UcOAmQAAmQAAmQAAmQAAmQAAmQAAmQAAmQgCUEKNQsocZrSIAESIAESIAESIAESIAESIAESIAESIAEHJYAhZrDTj0HTgIkQAIkQAIkQAIkQAIkQAIkQAIkQAIkYAkBCjVLqPEaEiABEiABEiABEiABEiABEiABEiABEiABhyVAoeawU8+BkwAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJWEKAQs0SaryGBEiABEiABEiABEiABEiABEiABEiABEjAYQlQqDns1HPgJEACJEACJEACJEACJEACJEACJEACJEAClhCgULOEGq8hARIgARIgARIgARIgARIgARIgARIgARJwWAIUag479Rw4CZAACZAACZAACZAACZAACZAACZAACZCAJQQo1CyhxmtIgARIgARIgARIgARIgARIgARIgARIgAQclgCFmsNOPQdOAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRgCQEKNUuo8RoSIAESIAESIAESIAESIAESIAESIAESIAGHJUCh5rBTz4GTAAmQAAmQAAmQAAmQAAmQAAmQAAmQAAlYQoBCzRJqvIYESIAESIAESIAESIAESIAESIAESIAESMBhCVCoOezUc+AkQAIkQAIkQAIkQAIkQAIkQAIkQAIkQAKWEKBQs4QaryEBEiABEiABEiABEiABEiABEiABEiABEnBYAhRqDjv1HDgJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkIAlBCjULKHGa0iABEiABEiABEiABEiABEiABEiABEiABByWAIWaw049B04CJEACJEACJEACJEACJEACJEACJEACJGAJAQo1S6jxGhIgARIgARIgARIgARIgARIgARIgARIgAYclQKHmsFPPgZMACZAACZAACZAACZAACZAACZAACZAACVhCgELNEmq8hgRIgARIgARIgARIgARIgARIgARIgARIwGEJUKg57NRz4CRAAiRAAiQQOQncuvsIz1+8QRG3nJGzg0Z6dfvuIzx98RpF3XLhy5ev+Ozrh9ixYkSZ/rOjJEACJEACJEACJEAC5hGgUDOPF2uTAAmQAAmQAAn8j8CmnUfQd9RvOh4pkiVCxTJF0KJ+JcifLS2LVm7HXycvYN6EXpY2YfF1XuMWYN3Wg7rrS/2QH709GiJT+lQhtrl49Q7sP3IOCyb3wdFTl9Cm53gc3jADCRPEtbgv+hfef/QMFRv9xyNtqmTIkyMTWjaohHy5MlvlHuY0Iv2ZNGcVxnl1gIuzszmXWqVun5Fz0Ma9KrJlSmuV9tgICZAACZAACZAACZhLgELNXGKsTwIkQAIkQAIkoAiIUBvnvRyr5gzBh4+fcPveI8xbugWv377H0pkDkTRxAotIRbRQ+/DRBz07NMCLV28xdf5a3LrzELtXToKTU7Rgx6Mv1N5/8MGd+0+QI2s6q8kmTagtntYfiRPGw5Pnr7Buy0Fs2XMMf0wfgIL5slnE2tKLrty4g7ptB+PcrnlwdXWxtBmLr8tTpgUWTu4bpaIYLR4sLyQBEiABEiABEoiUBCjUIuW0sFMkQAIkQAL2SECiao6cvIiXr98hS4bU6NSyFiqWKayG+u79R4zzXoHt+06ov7vlzYrsWdIpsSPl1PlrGO+9ApIO+XOp79GoVnnky5kJ/9x+oKLEqv1cDMvX71F1Wzeqgvq//KT+HBAQgLVbDmLpul24/+g5cmZNjx7t62Hput0oUiBnkHqdB0xFjYo/okLpQibh14TaoT+n6+qLWGvebTSyZEyNsQPa4+K12xg7Yzn+mN5fV6dDn4lo27g6vv8uu5Jy5y79g/x5smDzrqMq4ihZkoTYvPso8ufOgo07j6g+d25VS6VTSvljzU4sXLkNT569UnKpUc1y6Ni8BqJFi4YxM5bB2ckJN+88wKHjF1CsUB707eSOucs2Y+9fZ5WA6dq6DnJkSWd0jBKhJsxG9Gmtvi/9b9B+KHYsH494cWNj3Mzl2HngFOLFjYW61cqgXZNqSprpC7Wbdx6i/6i5WObtBWdnJzx68gLjZ63EyXNXlHwqX/J79O/aBD6ffDF13hps2X0UiRLEQ4MaP6F2ldKIFTP6N33ThNr2ZeOQLnVy3dwOm7wYuw+ewsH109T4Hz5+jtHTl+LYmSuKab1qZXRrrJHHcJQolBd7/jqN67fuo3qF4hjk2Vylpsr6Gjbpdzx6+lK1/VPxAhjQvSkSxIuj1tiAMfPQt4u7Yv/0+Wt8+uwLkWq5smVQvPt3a4K795/gwLHzipPMZarkiTGkZwsVsbdiw14lWDu3rI1yJQuqe4Q0flkX0pbc33ANSGTc/OVbIVF6CePHRa0qJdGwRlmT1iwrkQAJkAAJkAAJkIC1CFCoWYsk2yEBEiABEiCBUAiI1MqaKS2SJIyP/UfPYfJvq3Fk40wkiB8H/UfPxem/r6Nzy1rIkDYFvH//E9Gju2La8K64++ApKjfujV871EfJot9hx76TWLftIPasmoSLV2+jYcdhKFvCTcmxew+fYeTUP3Bk00wlI7S0TJFIxb7PjSOnLiF+vDjw9fNTEmjXiolK+si9m3Udhb82TFdyR+Tfs+evjY5oSM+WSJ8muS5CTV+oyQXL/9wD70V/Qr5+/OwVtPIci0v7F+naKlmzC4b3bo0yxQtAotHGz1qB73JnUaIpVfIkePr8lfpay4aV8WORfNi29zguXfsXa+YOVW2I0HJxcUa61Mlw78FTdBk4Dd6jPVG6WH507DtZySGRhpnSpcLgCQshMqpt42pKrsmYRfiM6d/OJKG2Y/8J9BjijWObvTF88mJc/ecuerSvj5ev32L09GXo3rYuGtcuH0SoSV/rtx+C83vmI+BrAGq0HIDkSRMp0fn1awDmLt2MJTMGYMiERUpKebavp2TY0ImL0LFZDSW6DIsxoSZ1rt28h9qtvbBt6VikSpEUNVr0R4E8WdG0bgXcvvsYvYbPws4VE5AmZVJIVFfeHJnQ2r0qnr14jSlz16B/18aoVbmkEoc3bt1Xgszn02cMHr9QzY+M9cKVW2qNSRpvnSqlEDNmDCUyB46dr9JyZS5E/q7fekjNm4yzRJF8SuLuOXRGpQHXqVoKp/++htWb9uvkX0jj19aFsTVw4/Z91Gw5EL07NULubBmQMnlinWTkhxAJkAAJkAAJkAAJhBcBCrXwIs37kAAJkAAJODwB2az+2s27SspIlM/0Beuwcs5gZM2YBt9XbIdR/dqiRsUSipP37xtw9Z87SqiJnJKIrYmDPdT3/P2/KMGxdt4w+Pn5qz9f3LdQSRkpIqyG9W6Fn4q7oUnnkUibOtk3AunVm3f4sUYXzB77K0oWzacEmquLiy4yS6KKPvn6Gp2zQt/lUFLKWISaXCCRYRKFdnzLLFy6/m+oQm3HgZNYOmOgLqXSMOVTNvyv1qyfTj7KPW7++wCXr9/Bs5evsXDFNrRpXA3N61VUQk3SH0WgSRFpJAJm5qju6u/7jpzFoHELlOwzViRC7frNe6ha/gcV0SdSSPaE69SyJgpX7oDxXh1RpVxRdalEwx0/cxnrF4wIVqidPHtV7ae2dclYJUq1ItFZhSq1w4BuTVU0ohTZu01SOWXODUtwQu2jz2cUrtwes8f2UNFvrXuMw+9T+yFO7JiqCZFWNSr9CPda5ZRQE5HnljcwPVTE67sPPrq1IZLtzIUbSmiKtIwfL7bipgm1E1tn69o1lvJpOG+HT15Eu14TdDL1zdsPKP5LJ8VCBGNI4w9tDTDl0+E/TgmABEiABEiABCKcAIVahE8BO0ACJEACJOAIBCQVskOfSUqmlf3RTUViSaTScm8vJEoYD5Xce2Pz4tG6ze/1hZqkdEqkj2GaoqQ5xo8b+xuhVqVJH5VaJ+JHJFDfzu4qQsiwSFTc+48+Ku2vdO1uSu5JBJMUESa+fv5GpyZ75nQqLTE4obZyw17MWbIJe1dPNilCzfAAAkOZIvLxp7rdsWf1JKRMlliJLEk9lKi8DOlSYuueY2hap4KKaDMUar8t2YTzl2/qhNqxM5eVdNKPmNMfpAi1wycvoECebCoiS+ShpChqUk9fjEla49BJv+PkttnBCrUN2w+r/kod/aK1JxFhMWP8l+KZPGlCTBrSyWShpkVrSRSayD3pvybMtEZ+KuGmosYMhZqkYYqMlHRWiQLsOWwWCubLjlzZ0quU0JgxXJVw1YSavrQ1RaiduXAdTbuM0rGWk08LVmiLdfOHI7qri5KkwY0/tDVAoeYIn5ocIwmQAAmQAAlEbgIUapF7ftg7EiABEiABOyEgQqyr1zRdKqYMS6SACLW8OTOjaNWOmDCoo0pblKIv1CbOXoV/7z3C9JHdvqFhTHboC7VarQaiaMHcSqoZlrMXb6gINtl/SlJHRahpRSKLJCrKWJGoJTn10phQk4gpSR0VUTK8dytdKmlIKZ/mCDWJoitVq6s6TVPbU02i4Yq65TYq1ERayh5tWoSaKUJNfw81bfxadJW0I6mQUmYsWI+te4+piCv9PdT0Uz7/On4BnfpPwYF1U4Mc0vDm3QcUr94Jq38bgtzZM4a6yoOLUBOhd+DoOSUvDxw9r6TY0c0zjR6GYCjURL7de/gUi6b0xS/N+6NS2aLwaF5D9WXBiq04cfZKsEJNxHCdNoNwZudcxIjuqq4xlGAS7da0y0ijQk3SNEMavylCbf6k3vihYO5Q2bECCZAACZAACZAACdiCAIWaLaiyTRIgARIgARIwIHDs9GW0/nWcis6RKCs5nVFS7kSoyf5hsum7CC5JVfzo8wmzF2+EW75sKv1Pi/SRfb8qlysKkTu7Dp5S0VOy35Vhyqe+UJu5cL3aEF7SSWUPsVPnrqmoNNmvTIoIN4lGkgME5GADc4om1FbOHowPPp/w773HWLBiG968fY/l3oPU3nAyFomSExElm+Rv23tCjVsTU8ZO9AxJpsSOFRPFqnmo1NQKpQur/dJEIokIMhahZi2hJlxEPsaNExODe7SApMx6Dp6p+iB72wUn1OSwiQoNeym2sj+a7DcmdWXvNdlbzs//C8Z5dVCyTdKBZS87SV01LJpQk3TOJIniq9TQ9dsOqc3/tchCkXTl6/+q9kTr3raOauLkuWvw8/dX8y1CTQ4JqFruB5WWK3ugSd9FqMrYsmVOix7t6imRKqmiiRLGDVaoaSmrIja/y5VFHeSwauM+6MvRkISaRFuGNP7QhJpcW9gtJ9q4V8PHj5/UWmMhARIgARIgARIggfAkQKEWnrR5LxIgARIgAYclIJvR9xgyU4kwKZKuuPfwWayYNQj5cmXG42cv1QmSEvkjKZVfA74iZvToSrZIkf21ZBN8EVRSZD8u2TfrzbuPaNhhaJA91ESodWlVG5XLFlUnKY6Yshh/bv9LXSdCauzA9ur+UuS0RJF3chiBFmlk6iRpBx5o7SZLkgBlihVAiwaVIamLWpE94GYu+lP9VaK79h85pztEYNGq7erk09/G99TVN/ya7O1Vpk53FYUlaZjSZznpUYqcliqphHLSZ4sGlVTKp5we2sa9qvq+oVCTQxI695/6TQqmdnPDUz71WUiaZjev6ZBTPLWxiOSU/eQkBXXf4bMqcu7y9X9Rr13goQRyAqjsRzdg7Dx1KqkUSauUU0/l70MmLsLBY+d1t2nftLo6hdSwaEJN+7pwkHZaNqiMPDn+i3ATKSty9s79J7r5lj5K2qoINTlMQE6ZlSL7qvXp7K76KPud9R05R31P1ogILxnXrDGeuCAHXxisMbleIvRmLd6g2pLDCa7duhdkLg2Fmq+vH9z+l/Ip7Yc0/tDWgER8Dpm4UPVXRKWcAstCAiRAAiRAAiRAAuFJgEItPGnzXiRAAiRAAg5P4PnLN+pUTTlJU7/4f/miS9MT+SZpjAXyZtOl4EldiQJ68eqt2nxeTvA0p4jMeP32g4pukvtrRfa4KuKWUwk4WxbZQ04OU7BWJJG09/b9R6RKntiW3TbatuzpFiOGq9lzIHMn+6VpBwZojX/67KuiDpMkjm80VdOSAUq0mhxYIfOtHVahpXxmTp9a9V9/7za5h6zBR09eIGXyJHB1cTbptiJs5cRYc9ejfuOWjl8O+ZBIQf0xmtRpViIBEiABEiABEiABKxCgULMCRDZBAiRAAiRAAmElMG/ZFmzZfVTtTSaRUCLeJD00WZL/Ir3Ceg/D6y9eu40G7Ydi98qJSJUiibWbZ3uRjIDhHmqRrHvsDgmQAAmQAAmQAAlEKQIUalFquthZEiABEiABeyUgKZ8nz17Fuw8+kNTJYt/nQdw4sWw6XDmp8eHjFyodkMX+CWzYcRglCucNcjiC/Y+aIyQBEiABEiABEiAB2xCgULMNV7ZKAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRgpwQo1Ox0YjksEiABEiABEiABEiABEiABEiABEiABEiAB2xCgULMNV7tr9eELH7sbEwdEAqYSSJ0kFvgMmEqL9eyRQJyYLnBxjoY3H/zscXgcEwmYRCBl4lh4+soHXwNMqs5KJGB3BGLHcEZ0V2e8fu9rd2PjgAIJyL95WUiABEwnQKFmOiuHrkmZ4NDT7/CDp1Bz+CXg8AAo1Bx+CRAAAAo1LgNHJ0ChZv8rgELN/ueYI7QuAQo16/K029Yo1Ox2ajkwEwhQqJkAiVXsmgCFml1PLwdnIgEKNRNBsZrdEqBQs9up1Q2MQs3+55gjtC4BCjXr8rTb1ijU7HZqOTATCFComQCJVeyaAIWaXU8vB2ciAQo1E0Gxmt0SoFCz26mlULP/qeUIbUSAQs1GYO2tWQo1e5tRjsccAhRq5tBiXXskQKFmj7PKMZlLgELNXGKsb28EKNTsbUa/HQ8j1Ox/jjlC6xKgULMuT7ttjULNbqeWAzOBAIWaCZBYxa4JUKjZ9fRycCYSoFAzERSr2S0BCjW7nVrdwCjU7H+OOULrEqBQsy5Pu2zN1/8rXrz9bJdj46BIwBQCSeLH4DNgCijWsVsCMaM7w9kpGj588ldjlEMOo+mNNkD+FsCjD+12AXBgigCFGheCoxOgULP/FUChZv9zzBFalwCFmnV52mVr85f54vETuxwaB0UCJEACJGABgbJuT5Ht7Hw4vQj84eBXvDL8i5YPItksaJaXkECkJkChFqmnh50LBwIUauEAOYJvYUuh9vL1O1y4cgu37z1CzBjRkSFNChR2ywkXZ+cIHjVvTwKWE6BQs5ydw1w5YpIv/r2jH4vgMEPnQEmABEiABIwQaFThCQrs7A3nR3fVd33rdYRf2doUalwtdk2AQs2up5eDM4EAhZoJkKJ4FVsJtTWbD2DwhIWKToa0KfDsxRt89PmExAnj4bfxPZErW4ZwIffZ1w8FK7TFqH5tUaNiiRDv6f37BixfvxuH/pweLn3jTaImAQq1qDlv4dprCrVwxc2bkQAJkECkJ0ChFumniB20AQEKNRtAZZNRigCFWpSaLos6awuhduj43+jQZxKqlvsBAz2bIX7c2AgICMCVG3cwfMof8GheEyWL5rOov+Ze9OmzL76v2A4j+rRGrcolQ7x85sL1WLFhL4WauZAdrD6FmoNNuCXDpVCzhBqvIQESIAH7JUChZr9zy5EFT4BCjavD0QlQqNn/CrCFUKvYqBecnZ2wYdEouLoETe/88uUr/Pz9VQro85dvMG7mchw9fQmfPvuh7I9u6NWxIZImTqDAL1q5Hf/8+0DJMK2s33YIuw+dxsxR3dWXvMYtQJJE8fH161ds3n0Uri4uaFSzHNxrlUP06K7o1H8K9h85h7SpkiFZkoTqmrkTeiFWzOhBJlckYP/RcyFpqm55s6nv/VKhOK78cxcBXwMwpGcLXX0//y/oMmAKShbNj8a1y6s+JIwfFxINt/vQKbx774N61UrDs3193fjfvf+IafPXYs9fZ/Dk2SsUdcuF3p0aIWfW9Pa/yOxshBRqdjahthgOhZotqLJNEiABEoi6BCjUou7cseeWE6BQs5wdr7QPAhRq9jGPIY3C2kJNhFTJml2UGGvRoFKwtxYpVaNFf5UK2rJhZVVv4YptSJYkgU7EDZu8GH9fvok1c4fq2pm9eCPmL9+Kk9tmq6/VbTtYRb6JBKtQuhDuPXyKZev3YPbYX1UU3OrN+zFkwiIVLeeWL1CU1a1W5hvRd/POQ4ydsQyHT17EwO5NVT2RXddv3oP0Y9Pi0cicPpX6ugi9bl7TVb8kdVXrQ7FCefBjkXzYc+gMzly4ju5t66Jt42oQiejuMRyv376He+3ySJwgHpas3YVbdx9h7+pJiBc3tv0vNDsaIYWaHU2mrYZCoWYrsmyXBEiABKImAQq1qDlv7HXYCFCohY0fr476BCjUov4chjYCawu185dvKnk0fURXlP2xYLC337H/JHoMmQnv0Z4oXSy/qieRZBJRNnloZyXHTBVqEn02eWgnRIsWuAf4L837o2jBXBjQrSnCmvL5/oMPilbtiGb1KqJPp0aq/VaeY+Hr548lMwYECrq2g5ExXUpMGNRRN95GHsPx5NlL7F09GfuOnEXn/lOxzNsL+XNnUXWu37qPWq0GYurwLihf8vvQponfj0QEKNQi0WRE1q5QqEXWmWG/SIAESCBiCFCoRQx33jViCVCoRSx/3j3iCVCoRfwc2LoH1hZq127eQ+3WXhjTvx2qVygebPflAADZs+zoZm+1x5qUN+8+oHj1TujUshY8mtcwWajly5UZg3s0192rY9/J6s+zxniGWahJO6OmLYWkmh5YNwWPnrzALy0GYNIQD1QsU0Qn1Az7MGnOKhVJd37PfMxbugXTF6wLchDDly9flFQTSSeyjiXqEKBQizpzFWE9pVCLMPS8MQmQAAlESgIUapFyWtgpGxOgULMxYDYf6QlQqEX6KQpzB60t1Hw++aJQpXZoUb8Senk0DLZ/U+auwdylm3Fm51zEiO6q6mnRZB2a/YIurWoroXb2wnWsXzBC146xlE9DmdVlwFT4f/lqNaF2898HSqIN69UKIgy37T2GvWum6NJGJULNsA8TZq9UKax/71mgZJqMdfbYHt/wyJA2JdKnSR7meWQD4UeAQi38WEfZO1GoRdmpY8dJgARIwCYEKNRsgpWNRnICFGqRfILYPZsToFCzOeIIv4G1hZoMqE3P8Th66hJ2rZiA1CmTBhnj3QdP4OTkhJPnrmLg2PlYNKUvChfIqeqcOHsVLT3H6E7kFBG1auO+IKduSmSbiCr9PdRCEmr+X74gf7nWGOTZDA1qlA2R97xlWzDnj026tvUrS5rng8fPcf/RM93eaNr3jQm1Kk36KFEoMnDDjsPqwIMNC0cia6Y0Qfogp59qqaoRvhjYAZMIUKiZhMmxK1GoOfb8c/QkQAIkYEiAQo1rwhEJUKg54qxzzPoEKNTsfz3YQqjdvvsI1Zr1Q+xYMdG3s4lEHQsAACAASURBVDtyZ8+gTs8UiRYYqfUr8ufJgnL1eiBD2hTo3LKWkkoi0O7cf4I9qyepNNCzF2+gSeeRqo28OTPh6OnLKk1U2jVVqMkMdugzEe8/fMKAbk1UWmmh/Dng4hz09FGpJwcgyN5ncqpo7uwZVZ+yZ06rFoEcNNDVa5r684F1U3UnkcrfRahJ+bV9fTg5O2H1pv3Ytvc4xg5oj2o/F8OHj59QvXk/dbJpn07uar+1f+89xoYdf6m02J+Ku9n/QrOjEVKo2dFk2mooFGq2Ist2SYAESCBqEqBQi5rzxl6HjQCFWtj48eqoT4BCLerPYWgjsIVQk3uKVBs7cxkOHb+g64KIsJqVSqB901+UkJIDDDwHz8CTZ69UnRTJEmHK0M747n8b90t0mZzQKfuXSRG5JRFvEsmmCbUG7Ycid46MQfZQE/ElJ2vOHNVdXSfRcqOnL4Wc5ClFrpW+GBa5ZsDYedi084j6lpZ6Kn/+7OuHghXaomalHzGyb5sgl4pQExH40eeT7uu/dqiPlg0q66LP5ETPEZMX4/jZK7o6ckKotJUjS7rQponfj0QEKNQi0WRE1q5QqEXWmWG/SIAESCBiCFCoRQx33jViCVCoRSx/3j3iCVCoRfwc2LoHthJqWr9Fij1++hIuLs5IniQRnJwCT+LUiqQ8Pv6fUEuZLJHR9Me37z/Cx+ezEm5hKU+fv0a8uLERK2b0EJsRMfbR5zOSJIqv6492UueK2YORL2emb4SapJ3279JYReIlSRzfaAScXCT7xD1/+QaJEsRDnNjfSr2wjI/Xhg8BCrXw4Ryl70KhFqWnj50nARIgAasToFCzOlI2GAUIUKhFgUliF21KgELNpngjReO2FmqRYpBW6ETTLqMgcnC5t9c3rRnbQ80Kt2QTkZQAhVoknZjI1C0Ktcg0G+wLCZAACUQ8AQq1iJ8D9iD8CVCohT9z3jFyEaBQi1zzYYveUKiFTvXh4+fwHDwT7ZtWR9kfC35zgRw4IPuitWtSPfTGWCPKE6BQi/JTaPsBUKjZnjHvQAIkQAJRiQCFWlSaLfbVWgQo1KxFku1EVQIUalF15kzvN4Wa6axYkwSEAIUa10GoBCjUQkXECiRAAiTgUAQo1BxqujnY/xGgUONScHQCFGr2vwIo1Ox/jjlC6xKgULMuT7tsjULNLqeVgyIBEiABiwlQqFmMjhdGYQIUalF48th1qxCgULMKxkjdCIVapJ4edi4SEqBQi4STEtm6RKEW2WaE/SEBEiCBiCVAoRax/Hn3iCFAoRYx3HnXyEOAQi3yzIWtekKhZiuybNdeCVCo2evMWnFcFGpWhMmmSIAESMAOCFCo2cEkcghmE6BQMxsZL7AzAhRqdjahRoZDoWb/c8wRWpcAhZp1edplaxRqdjmtHBQJkAAJWEyAQs1idLwwChOgUIvCk8euW4UAhZpVMEbqRiJSqPl8Bu4+9JNt3k1i5OoSDRnTOsEpmmn1TWqUlUjATAIUamYCc8TqFGqOOOscMwmQAAkET4BCjavDEQlQqDnirHPM+gQo1Ox/PUSkUHv28gt+W/wFz56ZJsjy5/uKJnVd4eriFKaJ8fX1w+u3H5A4UTy4ODuHqa3wuvjLl6/47OuH2LFiBHvLHftPoIhbLiRKEC+8uuWQ96FQc8hpN2/QFGrm8WJtEiABErB3AhRq9j7DHJ8xAhRqXBeOToBCzf5XQEQLtamzv+DxE9OEWuGCX9GqseVC7fzlm/h91Q6IeNJKwXzZMW5ge6RKkQR9Rs5BG/eqyJYpbaSb+KOnLqFNz/E4vGEGEiaIi/nLtyJtqqSoWKaIrq95yrTAkhkD4JY3m1X7b+xeVr1BGBsL7/5RqIVxwiLL5afOX0OiBHGRJWOab7pkisEOaRwUapFlltkPEiABEogcBCjUIsc8sBfhS4BCLXx5826RjwCFWuSbE2v3yFGEms8nX5Sq1RVlf3RDpxY1kThhfNy881AJtjbuVZA7e0aIkFo4uS+KuOW0NuYwt/f+gw/u3H+CHFnTqai6rl7TkDNrBng0r2FzoWbsXmEekBUbCO/+UahZcfKs1dStu49QvVk/bF48GpnSp1LNTpqzSpnnc7vnw9UlMBS1Xa8J+C5XFnRuVQsd+05GwXzZ0LZxtW+6YWiwzbXtFGrWmlm2QwIkQAKAfIR/+QoEBHxLI1ECIHp04Mkz46RSp4qGt28D8P5D6CRlS5H0aaPhxUvT6ofe4n81zBFq/l++wCmaE5ycQv+N89evAXj+6rX6h62xtIv3Hz7iy5cvSBD/2/SFT5988ebtOyRLmtike5kzXtYlASFAocZ14OgEKNTsfwU4ilC7ffcRqjXrh2XeXsifO8s3E6u9e6dNlQwJ48dFrSol0bBGWew7chaT56xW8k2i2bw8myF75sAItkYew1GiUF7s+es0rt+6j+oVimOQZ3OVlnnv4VOMmbEMJ85eRcwYrij2fR6M6NMa0aO7Brn3pp1HcPjURYzp3059fcLslUiaKAFaNKik/t6i+xh0a1MH8ePFQf9Rc1X/dx86hYFjF6h2U6dIimyZ06q2RQhKhN3hkxeVfJP+e7SoiVgxo0MCbhas2Irlf+7Bu/c+KFeyIPp1bowE8ePg4rXbGDtjOf6Y3l/Xtw59JqJt4+p4/vK10XsZAvxjzU4sXLkNT569QuKE8dCoZjl0bF4D0aJFg4zx3KV/kD9PFmzedVRFANaqXBIDxsxD3y7ukGufPn+touskaGi89wqIH/m51PdoVKs88uXMpG63bP0eLFm7E89evEGGtCnQuWUtfPb1Ndo/Y3XLFC9glQeaQs0qGK3bSEBAgDLmnu3qoXaVUqrxum0H48qNO1gxe7BaRH5+/ijwcxvMm9ALxQrlCVGoGRpsc207hZp155etkQAJOC6BuHGACcNccejoVyxd80UHQvzQ4N6uSBA/8EufPwMjJ/vj4aNA65YzWzR07+iiZJyUJ0+BoeP84Ct79xoplcs7oXY1Z2j79N5/GICh4/yVxBs9yBXJknx70bFTXzHvjy/quio/f7sfSZc+fvD5FHidqUJNJFfnPmPQqE4llCv1XxqCsT4fO3UBoyYvgM+nwJt0a++OahVKqj/7+HzCmKkLceTk34E8smfC0N7tkVgMJIDBY2bpvpcwQTxUKFMMbZvVctyFxpHbhACFmk2wstEoRIBCLQpNloVddRShJu/bldx7I0Z0V7RsWBn5cmZGxvQpdb/Mu3H7Pmq2HIjenRohd7YMSJk8MT5/9kONlgNUAEupH77DkrW7cPLcVexYPkFJM3nHzpsjE1q7V8WzF68xZe4a9O/aWMkiCYRxdnZG97Z18fbdB6zZckDJtjixYwaZqTMXrqNpl1E4tf039cvBghXaIkWyRNizahLuP3qm+ixpng8eP0f99kNwfs98vHj5Fr8O9Ub6NMnVveLGiYVc2TKo/mTJkBodmtVQ/es1fDYmDfFAyaLfYfXm/Rg3cwV6eTREquSJMXXeWqROmQTThnfF8bNX0MpzLC7tX6TrW8maXTC8d2vVrrF7GS63nQdOwcXFGelSJ8O9B0/RZeA0eI/2ROli+bFo5XaMn7UC3+XOgvIlv0eq5ElUvYYdh6mx1qlSCjFjxsDPpQqhcuPe+LVDfdXnHftOYt22g4qFCLkmnUeq8WTOkBpnL/4Df/8vKPdjwW/69+mzr9G67rXKWfiUBL2MQs0qGK3fSN9Rv6lGxU6/ff8Rxap5QCxqUbdcaFavIv6+fFNZ8JPbZiN2rJhKqMWPFxtv331UJven4gXQpXVtpEudXBl0zWBPnbfmfznWQW17SPaXQs3688sWSYAEHI/AgF9dkCl9YJTWvkNBhVr3Di7IlT0aRk70x7v3ARg+wBVv3gADRgYasymjXOHnDwwd64cM6aJB6u8//BVLV/8n5TSiEsU2rK8L/rkdAO/5/siSMRo6tXFREu/3FV8g39ffnzZObKBDSxfs2PsVqzcECjURcpO8/YNM0tUbAbqoOlOE2m+L12H1hl2qjb7dWoYo1ES81W/dB80aVkPNKmUgcm3ouDlY7D0cqVIkxYr1O7B111+YNKKn+g3swFHeSJcmJX71aKLa/33FZpQs5obUKZPh3N9X4TVmFqaP6YOc2TI63kLjiG1GgELNZmjZcBQhQKEWRSYqDN10FKEmiCRqa84fG7Fhx2FFTN6pJfOrce3ySqwZBqFMm78WW3Yfw47l41X9F6/eqiCYGaO64afibqq+/p5lI6f+gXcffNT7vMifpIkToH/XJkieNGGwMyQHJLhVaIs/pg/Ah4+fVP+u3byHxdP64e6DJ5i9eCPWLxiBS9f+1Qk1U1M+JUtNot1EoolHyJk1PQb3aK76svvQaXTzmo4jG2fi6s27wQo18RGmplTe/PcBLl+/g2cvX2Phim1o07gamterqITajgMnsXTGQF1GwYUrt5RQO7F1tk4yei/6E5t3H8XEwR6qjyLMpM7aecPw6vU7tYfc7LG/olih3EGyGgz7p2XrGasbhkdFdymFmjUo2qANebAnzFqBQ39OV2Ga8vBI2OihY+cxfWQ3tRBl4ctDK0WEmkix7m3rIGumtJg0exWKFsyFHu3rB3ngJLzV0LZLxEJw9lfCMinUbDDBbJIESMDhCCRPCsSKFQ39e7jgoMgwvQg17/GuuH4zAFNmB0qsejWcUbGsE9p290OSRMCYwa5YvPILDh75qr4/pI8L4sWNhl+9vg1Rq1nVGdUqOKHvUD88fxmIeVAvFyRMEA09Bn5bv0s7F+TNGQ2devvB3x86oSb3Dq6YItTevn2PT35+6NZvHNo0qRWiUBOB5jXaG1uWT9OlP7ToPFjJtZpVfkLHXqNRqpgbGtUOTHk4cOQ0Rkych51rvFX6gGFp1K4fqlcsBfc6lR1unXHAtiNAoWY7tmw5ahCgUIsa8xSWXjqSUNM4icSSlMLdB09j1uIN+G18T5QonPcboaYf8KJdW7aep4pYk5RGQ6G2YsNeJZJEwEmqZ99Rc1QKpKSRtmlcFfWqlTE6VRLNJimhdx8+RY4s6VT6aNJE8SFZZxLlJhFblgg1EXz+X74qiSYRZ+IJJKJNyqMnL1C+wa9YN384Xr99H2ahJumtkrpZtoQbMqRLia17jqFpnQoqGlA8xl8nL6hMO61oQu3ivoW6f9cJ7z2HzigG+kVSR4sUyInRM5Zh5Ya96ltyGEOP9vUUW0OhJpl9wdUNy7OiXUuhZg2KNmhDQjorNuqFrUvGYsOOv5R1rVimMBp2HI5jm73RecBU5MuVWbfxoOEeamu3HFQ5xcYMtqFtD8n+irmmULPBBLNJEiABhyUwZ5KrEmP6Qm3uFFfs3BcYISalSEEntGvujD5D/ZA6ZTR0a++CIWP9IambUjxaB0owj17fSi9J15Qos16D/PDqTSDmDi2cUSCfEzr8GrR+0sSBKaC793/Fyj8D762lfD57Ib8NBK5c+4pVG76oP2vFFKGm1W3m4YXmDauHKNQ27zyENRt3Y9GMobp7SBpn2tQpVermL4098WunpihdvKD6/o2bd+DRewzW/j4B8SWPVq/cf/gULbsMxvB+HvihUD6HXWccuPUJUKhZnylbjFoEKNSi1nxZ0ltHEWqSBujq4gJn56BbXIhocq9dHh2b1VCCbP6k3vihYG6FUvbyOnLqonq/liIRZEWqdFBphyJ0DIWa17gFau+0RVP6qvqyb5kEt+w6dAozFqwPsl+6/lyJhDtx7qoKlpE91W/deYjhUxYjXpzYKoJO0h+NCrUs6dUeaVoxFjGnCbVarQaiRJF86NmhgaquRXHtWzNF9blZ11FGUz51EWoG99Lvvxa5t2ByH5VdJ0X2YCvqltssoTZx9ir8e++RCiYKrrx5+wF/X7mp9pvPkTW9igZUQs1I/4zVteQZMbyGQs0aFG3UhhjvLq1qY9Wm/ejaqjaKFsyNolU7YuGUPmjQfqh6OAsXCDx1xFCoyfG/k+asVkbc8IEzFGoh2V+x8xRqNppgNksCJOCQBAyFmgRYiVDbsO0LNm0PjEDLlztQoo2c5I+0qaOhecNAufbifxFnrZs4o8j3Tmjv+a1QS5IYGDPIFR99gCPHvyJuXKBQASe1n5qhUOvX3UUdXCBiTjskoVhhJ5Qt5YQPH4AkiaMhVQookSdCTyvWFmqS0nngyBnMGt9Pd4+Rk+cjTsyY6NbBHRXqegQRZHfuPUSb7sOxdPZIJE+WWHfNR59P8BwwAbFjx8KEoZ7f/EPZIRccB201AhRqVkPJhqIoAQq1KDpxZnTbUYSa7BMmgkzetSVIRdIJdx08iVHTlupO9pR9xAq75UQb92r4+PETLl//V6UZikArXigvFq/eAe/fN2D/2ilIliShEmpDerZA1XI/4NDxCxg4dr6KJpPDAEQO1a1WWu1zdvWfu2p/9DVzh6o9yQzLhau30bDDULXH2HJvL/j5f0Hx6p0g/8Y5utkb8ePG/ub9/rclm5SAE/kkok8OAghJqInQk/3IpgztjBTJEmPElMV49PQlVv82BD6fPqNw5Q6YOaq7Ojhg294TkOg2+bsINWP30h+Dtl2VHIxQoXRh1a+ew2apQCBzItS0/eREklUuVxQixHYdPIVC3+XAo6cv1LZYZUsUhLNTNMU6btzYGOTZ7Jv+Xbp2O9i6ZjwawValULMGRRu1MWzyYjx7/gp7D5/V5RP3GOINV1dndSLG6R2/IWaM6BYJNX3bHpr9pVCz0QSzWRIgAYckEFyEmuxhtmZj8BFqg8b8d0hBSBFqAlX2Y2tS3wVy2IGIsYQJoASbfsqn7MXm1dMFG7Z+waYdgSLPWGnh7owfiwZGt2lRatYWaqZEqPXs3EylfUoxFqEm+7ANHT9H/dycNLwH4seP65Dri4O2HQEKNduxZctRgwCFWtSYp7D00lGEmmSDjZ6+FPuPnNPhkj3U+nVx1x0KKOmGQyYuxMvX71TEmkSHSUqoyCgpUl9kj5yQKUUElogsqS9FNr3v09ldZZp1GTBVvdNLkY333WuVVydwGityOnqxap3QtXVtNK1bQVWRaLfrN+9h5ZzB6u8i9+q1CzyUQNqXyLceQ2aq9FC3vNnUtlDGhNqXrwFKOomc6z96nhJUUuSUzOkjuiJLxjTq75LBNnPRn+rPItGEk3aogLF7GY5j/vKtKmpMihyM8NnXT6XFymmli1Ztx5GTF1VqrVY0iaif8infW7f1IEZPX6b6q/Vz9tgeePj4hTroQPu6BAEN+bUFUqdM+g0LOf0zuLpheVa0aynUrEHRRm3s2H9SPRhyWoj28KzauA9DJ/2uwicljFIr5kSoGdr2m3ceqNNEjNnfrJnSMELNRvPLZkmABByTgDGhZriHWoOazvj5p6B7qMmBAnKwgJShfV0QN47xPdQMqYpUmzTCFWf+DjykQCvD+7sicUKovdNCKloKade+fkrKSbG2UNP2UNu6YjpcXV3UPSRVtHa1sro91CTds2Gtiup7hnuovfvwEUPHzsGnT58xamBnyjTHfLRsPmoKNZsj5g0iOQEKtUg+QVbonqMINQ2VyCvZ4N7JyQlJEv3vqHU9jpKm+erNO/U9bc9WSRd9/vKNOvlTZJZWNIGVOX1qxIjhqgt80b4v18kBgiEdShDWKZR0y/jx4sBVOxY+lAbfvPsA+YWkSD7DIpFuErmXIH7QrTW0eqHdS66XKDI5RTQsRU5klXvJvw8TxPuvL9rXRWzKKaaGRb9/odUNS/8o1MJCz8bXyoNaunY3tG5URW0aKEU7wleO3JUNELUiQu3777LrTLfIOLHCkvJpaLCN2fbg7G/6NCko1Gw8z2yeBEjAMQjIv23k313TxrjiyImvWLHuCz77Bo5dO+VzxP9O+RxhcMrn1NGu+PwZGDou8JRPz44uOHDkK5asCoxoGzXQFU5OQN9hgXJM0jQlPTRVymho39wFyZJCHWDwNvCXpsibK/CkUOnD7gNBo9Nkv7VrNwNw4vRXJE0SDT07u+DrV6Bbv//EmylCTf6RGvA1AK27DUXjupVRtmQRnSyTf7x5ek1ExZ+KqYMHfHw+45cm3dGhRV3UMHLK5/J127Ft92F1ymesmNExYORM3Smfcm2XvmMh9/Pq2RZxYsdSY5R/HCdP+u0/EB1jtXGUtiBAoWYLqmwzKhGgUItKs2VZXyNSqL16+xUnzvrBz/fbw4aMjUZ+YVi8sCtcnE2rbxkR068yjAgz/UrWjMoEKNSi8uyFoe/GbHtw9pcpn2EAzUtJgARI4H8Exg1xRWIDvzPJ2x+XrwUgQXxgcG9XlaIpRUTbmCn+uPcg8BCC3DkC91TTfhH69FmgXJN6WgTa0ZNfMX9JoGDr290FWTMF/gPz/Qdg8ix/3LkX2JaU8cNcEd01qCTTvienkGbO8N8/TkXkTZ7tj39u/Xe9KUJt+MR5OHjkdJD5XzBtsBJhZ/++it5Dp2Le1EHIkDaVqnPk5N+Qgwi00qVtQ/xSqbT6q4T0j5y8ACdOX1B/z5ElA4b07aiOoH/24jXc2/2395p2fcIE8bB6wTiuPxKwGgEKNauhZENRlACFWhSdODO6HZFCTbopKYmmFvmXipNT5JBp0ucNOw6r00Hl3yYsjkOAQs1x5trikVKoWYyOF5IACZCAWQTk1M3oMaLh4SPj/6CU6LTXbwLw5u1/zVYq54Q61Z3hOcBPyTMpcvBlqhTRlETzDTmj02j/JMgrTapoePM2AE+ff1vFFKEW0sAXLt+I6//cwWivLkGqyS97nr14hSSJEuii2fQrvH3/Af5+/kiciP9YNWthsbJVCFCoWQUjG4nCBCjUovDkmdj1iBZqJnaT1Ugg0hCgUIs0UxF5O0KhFnnnhj0jARIgAYkokzJq0n/7o9maSliFWsdeo9G8QTX8UCifrbvK9knAagQo1KyGkg1FUQIUalF04szoNoWaGbBYlQT+f19jCjUug1AJUKiFiogVSIAESCDCCKRLEw2vXgfootPCoyNhFWoPHj1DyuRJ4OzsFB7d5T1IwCoEKNSsgpGNRGECFGpRePJM7DqFmomgWI0E/keAQo1LIVQCFGqhImIFEiABEnAoAmEVag4Fi4O1GwIUanYzlRyIhQQo1CwEF4Uuo1CLQpPFrkYKAhRqkWIaIncnKNQi9/ywdyRAAiQQ3gQo1MKbOO8XGQhQqEWGWWAfIpIAhVpE0g+fe1OohQ9n3sV+CFCo2c9c2mwkFGo2Q8uGSYAESCBKEqBQi5LTxk6HkQCFWhgB8vIoT4BCLcpPYagDiEih9uXTZ7y/d0f2pAq1n1LBySU6YmfKCKdokeekT5M6zkp2RYBCza6m0zaDoVCzDVe2SgIkQAJRlQCFWlSdOfY7LAQo1MJCj9faAwEKNXuYxZDHEJFC7ePzF/CZOhhOj+6YBPpr4Z8Qv3V3uLqEbT9WX18/vH77AYkTxYOLs7NJ947oSnIq+mdfP8SOFSPYruzYfwJF3HIhUYJ4Ed1du74/hZpdT691BkehZh2ObIUESIAE7IUAhZq9zCTHYQ4BCjVzaLGuPRKgULPHWQ06pogWap9GecLp/i2TQH/9sTLiefSzWKidv3wTv6/aARFPWimYLzvGDWyPVCmSoM/IOWjjXhXZMqU1qT/hWenoqUto03M8Dm+YgYQJ4mL+8q1ImyopKpYpoutGnjItsGTGALjlzRaeXTP7XgeOnseFK7fQuVUts6+NDBdQqEWGWYjkfaBQi+QTxO6RAAmQQDgToFALZ+C8XaQgQKEWKaaBnYhAAhRqEQg/nG7tKELN55MvStXqirI/uqFTi5pInDA+bt55qARbG/cqyJ09I0RILZzcF0XccoYTfdNv8/6DD+7cf4IcWdOpqLquXtOQM2sGeDSvEeWE2tJ1u7F93wn8Mb2/6QAiUU0KtUg0GZG1KxRqkXVm2C8SIAESiBgCFGoRw513jVgCFGoRy593j3gCFGoRPwe27oGjCLXbdx+hWrN+WObthfy5s3yDddKcVf+L+kqGhPHjolaVkmhYoyz2HTmLyXNWK/km0Wxens2QPXNgBFsjj+EoUSgv9vx1Gtdv3Uf1CsUxyLO5Ssu89/ApxsxYhhNnryJmDFcU+z4PRvRpjejRXYPce9POIzh86iLG9G+nvj5h9kokTZQALRpUUn9v0X0MurWpg/jx4qD/qLmq/7sPncLAsQtUu6lTJEW2zGlV2yIEJcLu8MmLSr5J/z1a1ESsmNG/Ge/rN+/Rsd9k/HP7gfpenhwZ0a9LY+TIkk43tnZNquHQ8Qu4cuOOan/g2Pkw/Jrcf+q8Ndiy+6hKNW1Q4yfUrlJa3fPY6cuY/Ntq3Lr7CMmSJECtyiVRoXRhNOk8Ai9fv0PeHJnUvX6f1g/nLv7zTd22javZevlb1D6FmkXYHOsiCjXHmm+OlgRIgARCI0ChFhohft8eCVCo2eOsckzmEKBQM4dW1KzrKEItICAAldx7I0Z0V7RsWBn5cmZGxvQpdXuo3bh9HzVbDkTvTo2QO1sGpEyeGJ8/+6FGywEQsVPqh++wZO0unDx3FTuWT1DSTASWSKHW7lXx7MVrTJn7f+ydZ4BVVbZuv0rkJFExtakNbcJraAMmVNosmMWsCCKomEgqoIIEAUVRQUFExYQiaqsYURQMGBBzxASC5ExR4b216SopioJz6uyw1t7j/HlXWHuuOce3fLd73B3GqfuVbTxxdNn1dygnJ0dXtz1NS5Yu17j/vu3Jtpo1qpU5KJ/M+E7ndeqraa+MUHZ2lvY5pq2aNNpMbzw1WL/P/svr2Tzm+cef83RGu16a/sZIzV+wRNf2vlfbbNnY26tWzeradadtvX522Lap2p9/stff9bfer8G9Oqj5AXuWO5yLly7X+Jcna5/dd/Ik36jHX/LE17gHeq8VbIdf6P2/bVofraabN/AeLT3qjGvK/dnwMc97wq1zu9OVlZWl3oNG6/LzT9bRh+2r/2t5mdqdiNpGnQAAIABJREFUd6KOb/Fvzfxtjt7/5Et1vuwMDRnxlD745GtPTpqfuTtw/+Pal1vb46rzrPyXCqFmZSx2NYVQsysPuoEABCAQNQGEWtQJsH8UBBBqUVBnT5sIINRsSiOYXpIi1Aw9c9fW8Eee14SJ73kwa1Sv5r3Hq03rozyxtv4jn0NHPqP/vv6+Jj4+0Fs/f+ES77HRe/pepSMOauatX/edZX3uekRLl6/07jY7t2MfNaxfV92vPFeNG9arMDzzgYRmx7TVI3f30PIVq7z+vv3xN40Z2k2//jFH9495XuNH3aYvv51ZKtRSfeTTvBPO3O12fYezNri/eQz2869/1MxfZ2vGNz97gu3LSaNLhdr9/a9V8wP2KL3WzLvun5nr9/3PZTLiq9nuO3rrnn3pHc2Zt1B9u7bVAcdfrisvOVXnnXa0x7rkt/4jn+Zx1orWBnPqM6uKUMuMXyKuRqglImaGhAAEIJAyAYRayqhYGCMCCLUYhckolSKAUKsUNqcuSpJQKwnGSCxzN9br73ys+8ZM0IiB1+ng/XYvJ9S69h3hXVLyOKb5n488vbN3x9rZp7QoJ9SemPCmHnriZU/AmUc9u/Ydrjl/LdRWWzTSpW2O1+knHL7Bs2HuZjOPhP46a673yKV5fLThZnVkRJO5y+3a9mdUSqgZwVdQWKSe11xQbl/zqOdFnfupdq0a2m/vXbwviJrHT9cVaut/4GB9gVjyGK25O65a1b8fKzUCcXCvKzR2/BsyPZif+VCCuVtv37121obeoVbRWhv/ZUKo2ZiKZT0h1CwLhHYgAAEIREwAoRZxAGwfCQGEWiTY2dQiAgg1i8IIqJWkCLVVq/OVl5urnJzsMiSbn9JJ57Q+yntM0QijkYNv0L/32c1bM/DeJzRl2hfeHWLmZ+4gM48mmscozSOQ6wummwaM8t6dNvrOrt76wsIiGen02uRpumfUeL045nZtt80W5ZI0Eu7Dz77RtOnfemt++mWWbr1zjGrXrOHdQWce2dzgHWo7bOO9I63kt6E75ioSav2HPe49qjly0A0eE/MF1HM63JqWUDOPjR504hV6ekQv77HNDf0Md3PHnfn4w0effa1Jz9ylJ59/Sy+98b53d9+6vw2tXT+vgP41SKssQi0tXMlcjFBLZu5MDQEIQKAiAgg1zkYSCSDUkpg6M69LAKEW//OQFKH2wadfe4Ks08Wttceu26ugoFCvvfOR+g59rPTLnhd37q/9mu2iS885QStWrNJX383UpdcN9ATaQfvurjFPT9S9D0/QpGfuVKMG9Tyh1uu6C713hJmX95uX9pu7yczHAAbd/5ROO+Ew7z1n3/zwq05r29N7P5m5m2v9n3nc8qz2vbXnbjvo8Xtv0pqCQk9UrVi5SlNfvFd1atUoJ9RGPPqCJ+Du7nOVJ/rq16u9wUdQKxJqwx4ar7emfKb7+nX2WAwb/Vy5Rz43dYeamcMwM/0OuKm994jrtz/+qo8//07HHLqv92it+UhB3dq1ZO7eMx8omPL8PZrxzU9qd8NgvfxYf0/mrVy5Ws+/OmWDa/Pycq37lxChZl0k9jWEULMvEzqCAAQgECUBhFqU9Nk7KgIItajIs68tBBBqtiQRXB9JEWrmBf+33/2YJk35rBSmea9Xt07nqPVxh3p/9sbkT9Rr0EPeFyjNHWvm7jDzSKi5u8z8zHrz+GeL5vt4/2yEmhFZZr35ndOqhbp0PMd7H1unHnfpzfc+9f7cfGTgnFZHeV/g3NCvoLBQB55wha68pLXOO+0Yb4m52+27H3/Tk8N7ev9s5N7pl639KIGpb+58u6bXMO/xUPM4pZFfG7pDrbCoWDf/7+X/6+49e+4Cr0dzl5r5mXelGSmYziOf5jrzSGuvQaP1zvvTS8ubDxGYR2IvuOp277115mdEopGZhx24l8y8Hbvf6e1nfi8/NkDtuwza4NrgTn7lKyPUKs8uMVci1BITNYNCAAIQSIkAQi0lTCyKGQGEWswCZZy0CSDU0kbm3AVJEWolwRiZs3DRUmVnZ6vBZnXK5WUe01y4eKn3d+arleZnHkWct2Cx9+VPI7NKfiUCa/ttmqpq1bwy7xEruW7J0hUb/ShBpgfGfCihTu2aysv9u690as76c57q1a3tfRU0k59htHjJcjWoX6cMoyXLVqiwsFCb1a1drrx5ZLRKXp6qV1v7/rWNrc2kN7+vRaj5TTSG9RBqMQyVkSAAAQhkQAChlgE8LnWWAELN2eho3CcCCDWfQFpcJkqhtmrxEi2fOlnZq1ekRKi4XgPVOeQI5easFV1R/9a/Iyzqftg/HAIItXA4O70LQs3p+GgeAhCAgO8EEGq+I6WgAwQQag6ERIuBEkCoBYrXiuJRCjUDwDySmOrPaLTsbDtkmunZvCPMfB3UvDuMX3IIINSSk3WlJ0WoVRodF0IAAhCIJQGEWixjZahNEECocUSSTgChFv8TELVQiz9hJowbAYRa3BINYB6EWgBQKQkBCEDAYQIINYfDo/VKE0CoVRodF8aEAEItJkFuZAyEWvwzZkJ/CSDU/OUZy2oItVjGylAQgAAEKk0AoVZpdFzoMAGEmsPh0bovBBBqvmC0ughCzep4aM5CAgg1C0OxraWRY/P159ov3PKDAAQgAAEI6Mhmf2mnTx9U9vy1/8thzUHHqeCAFrLnTSaEBAH/CSDU/GdKRbcIINTcyqsy3SLUKkONa5JMAKGW5PRTnD2/oEjzl6xOcTXLIBA/Ag3qVOXfgfjFykRpEKhWJUc52VlavqrAu6q4WPrf1+NL/zmNciyFgJMEEGpOxkbTPhJAqPkI09JSCDVLg6Etawkg1KyNxq7GZs1faVdDdAOBEAmY/3DBvwMhAmcr6wjUrJbrfZZ+8fI11vVGQxAIiwBCLSzS7GMrAYSarcn41xdCzT+WVEoGAYRaMnLOeEpkQsYIKeAwAYSaw+HRui8EEGq+YKSI4wQQao4HSPsZE0CoZYzQ+gIINesjokHLCCDULAvE1nYQarYmQ19hEECohUGZPWwmgFCzOR16C4sAQi0s0uxjKwGEmq3J+NcXQs0/llRKBgGEWjJyznhKhFrGCCngMAGEmsPh0bovBBBqvmCkiOMEEGqOB0j7GRNAqGWM0PoCCDXrI6JBywgg1CwLxNZ2EGq2JkNfYRBAqIVBmT1sJoBQszkdeguLAEItLNLsYysBhJqtyfjXF0LNP5ZUSgYBhFoycs54SoRaxggp4DABhJrD4dG6LwQQar5gpIjjBBBqjgdI+xkTQKhljND6Agg16yOiQcsIINQsC8TWdhBqtiZDX2EQQKiFQZk9bCaAULM5HXoLiwBCLSzS7GMrAYSarcn41xdCzT+WVEoGAYRaMnLOeEqEWsYIKeAwAYSaw+HRui8EEGq+YKSI4wQQao4HSPsZE0CoZYzQ+gIINesjokHLCCDULAvE1nYQarYmQ19hEECohUGZPWwmgFCzOR16C4sAQi0s0uxjKwGEmq3J+NcXQs0/llRKBgGEWjJyznhKhFrGCCngMAGEmsPh0bovBBBqvmCkiOMEEGqOB0j7GRNAqGWM0PoCCDXrI6JBywgg1CwLxNZ2EGq2JkNfYRBAqIVBmT1sJoBQszkdeguLAEItLNLsYysBhJqtyfjXF0LNP5ZUSgYBhFoycs54SoRaxggp4DABhJrD4dG6LwQQar5gpIjjBBBqjgdI+xkTQKhljND6Agg16yOiQcsIINQsC8TGdvILijR/yeoNtlZcnCWp2Ma26QkCvhFAqPmGkkKOEkCoORocbftKAKHmK06KOUgAoeZgaGm2jFBLExjLE08AoZb4I7BpACPH5uvPORte1+qEVapbN0dZOdmbLsQKCDhKAKHmaHC07RsBhJpvKCnkMAGEmsPh0bovBBBqvmC0ughCzep4aM5CAgg1C0OxraXbBudr5i/mTrTyv6var1T9Bgg12zKjH38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYRaktNPcXaEWoqgWBZbAgi12EbLYCkSQKilCIplsSaAUIt1vAyXAgGEWgqQHF+CUHM8QNoPnQBCLXTk7m2IUHMvMzr2lwBCzV+eVHOPAELNvczo2H8CCDX/mVLRLQIINbfyqky3CLXKUOOaJBNAqCU5/RRnR6ilCIplsSWAUItttAyWIgGEWoqgWBZrAgi1WMfLcCkQQKilAMnxJQg1xwOk/dAJINRCR+7ehgg19zKjY38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYRaktNPcXaEWoqgWBZbAgi12EbLYCkSQKilCIplsSaAUIt1vAyXAgGEWgqQHF+CUHM8QNoPnQBCLXTk7m2IUHMvMzr2lwBCzV+eVHOPAELNvczo2H8CCDX/mVLRLQIINbfyqky3CLXKUOOaJBNAqCU5/RRnR6ilCIplsSWAUItttAyWIgGEWoqgWBZrAgi1WMfLcCkQQKilAMnxJQg1xwOk/dAJINRCR+7ehgg19zKjY38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYRaktNPcXaEWoqgWBZbAgi12EbLYCkSQKilCIplsSaAUIt1vAyXAgGEWgqQHF+CUHM8QNoPnQBCLXTk7m2IUHMvMzr2lwBCzV+eVHOPAELNvczo2H8CCDX/mVLRLQIINbfyqky3CLXKUOOaJBNAqCU5/RRnR6ilCIplsSWAUItttAyWIgGEWoqgWBZrAgi1WMfLcCkQQKilAMnxJQg1xwOk/dAJINRCR+7ehgg19zKjY38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYRaktNPcXaEWoqgWBZbAgi12EbLYCkSQKilCIplsSaAUIt1vAyXAgGEWgqQHF+CUHM8QNoPnQBCLXTk7m2IUHMvMzr2lwBCzV+eVHOPAELNvczo2H8CCDX/mVLRLQIINbfyqky3CLXKUOOaJBNAqCU5/RRnR6ilCIplsSWAUItttAyWIgGEWoqgWBZrAgi1WMfLcCkQQKilAMnxJQg1xwOk/dAJINRCR+7ehgg19zKjY38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYRaktNPcXaEWoqgWBZbAgi12EbLYCkSQKilCIplsSaAUIt1vAyXAgGEWgqQHF+CUHM8QNoPnQBCLXTk7m2IUHMvMzr2lwBCzV+eVHOPAELNvczo2H8CCDX/mVLRLQIINbfyqky3CLXKUOOaJBNAqCU5/RRnR6ilCIplsSWAUItttAyWIgGEWoqgWBZrAgi1WMfLcCkQQKilAMnxJQg1xwOk/dAJINRCR+7ehgg19zKjY38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYSaA+kXFRVrzryFqlu7pmpUr7rJjqdN/1ab1a2lHf6x5SbXprIAoZYKJdbEmQBCLc7pMlsqBBBqqVBiTdwJINTinjDzbYoAQm1ThNz/e4Sa+xkyQbgEEGrh8k5rtzVrCjT8kRd035gJpdftudsOuvX6i7Xjdmtl2dtTp2vG1z+p48WtStdc3nWI9tljJ7Vtc0Ja+1W0uLJCraCwUNlZ2crOzipX2vzdwkVL1ahBPV96pAgEgiSAUAuSLrVdIIBQcyElegyaAEItaMLUt50AQs32hDLvD6GWOUMqJIsAQs3ivAfd/5SemPCmBvfqoP2b7aoFi5Zq4L2Pa/IHM/T6k4NUt05NPfbs63rlrQ/1yN3drRJqq1blq2OXfjr71P+oxaH7l/ZmRNq9I5/S5Pc/9f6sZo3quuDME3VE830tToLWkk4AoZb0E8D8CDXOAAQkhBqnIOkEEGrxPwEItfhnzIT+EkCo+cvTt2pGnjU/pZNu795WJx1zcGndVavzdfSZ1+rsVkfp+Bb/1rkdb/NE2+47b+eteXhoN3XuOUx1atfQkqUrZB7/POKgvdXpktbaumljb435s4H3PqGffp2tow/9P6/WHrtspx9+/kM9+j2orp3O0SPjXtXceYv06D09lO4daiPGPKunJ7zm7dX1qovKCLWXXntX949+RmPuvUX16tbWxDenaNjIp/Xkg7erevVqvvGjEAT8JIBQ85MmtVwkgFBzMTV69psAQs1votRzjQBCzbXE0u8XoZY+M65INgGEmqX5fzLjO53Xqa+mvDDMe3faur/egx/W/IWL1a97Ow0Z8ZQ++ORr3dT5fG/JPnv8Ux173OVJs6vbnqodt9tKg+9/Sgfss6uuaXeGfv1jro5tc4OubX+Gmh+wpya+9ZGeffkdvfHUYH3xzc866/Jb1KTRZjr1uENVrVpVXXL2caVCzfiuvf6Vrfc/Lipt56r2K1W/QY6ycrJL/2zJkmVatWaNruo2QJee26qMUHvkyRf12tsf6IE7b1bVKnn6Y/ZcXdixpx657zZt3riBpWnQVtIJINSSfgKYH6HGGYAAd6hxBiCAUIv/GUCoxT9jJvSXAELNX56+VZs46UNd0+tefTlpdLma94war0lTP9O4B3qn9MjnM/99R48+86rGj7pN945+Ti++PlWDenbw6hYUFHoS7ZkHb5F5Z5v5nz986X7VrPH33WIld6hlZ0unHJ+j8S8Wqrh4bVsbEmolDZ/f4SZdcNaJZYSaEWhX97hD9evV0dmt/6NJU6aperVq6nLlhb6xoxAE/CaAUPObKPVcI4BQcy0x+g2CAHeoBUGVmi4RQKi5lFblekWoVY4bVyWXAELN0uw/mfG9zuvUR1OeH+a9K23dX687RmvB4iUaeuuVKQk1I+cGD39aEx8fqK59R+iNyZ9o5x22LlPz8gtOVp1aNTyh9sVbDykr6+8PCZQINfNHZ7XO0RPPVl6omXer9Rs6SitX5evX32dr3vxF6nVDex18wF6WJkFbEJAQapyCpBNAqCX9BDC/IYBQ4xwknQBCLf4nAKEW/4yZ0F8CCDV/efpWbeHipTrk5E66rcslanVs89K6RkQdc9a1OvfUY9TuvBM1dvwbeumN9713nZX81v/K57pCzXzoYOZvs3V3n6vK9Wq+FropoXbMEdl69a2iSt+hNvLR5/T1dz9rQK+rVVxcrGdffEPmnWsjhtyo7bZZ++VSfhCwjQBCzbZE6CdsAgi1sImzn40EEGo2pkJPYRJAqIVJO5q9EGrRcGdXdwkg1CzOruQrnwNvaq8D9/2XFixcotvveUxTp32l158a5L1bzbxrrd0Ng/XyY/2Vk5OtenVqqUO3O7XPHjupbZsTvOnWFWol72br1/0yHdviAC1eslyvvTNN++65s1auWr1RoWZqmbvUSh73NP+c7iOfHW/op3/ttqMuv/A0r7eiomK1PL2DrrzsbJ3Y8lCL06C1JBNAqCU5fWY3BBBqnAMIcIcaZwACCLX4nwGEWvwzZkJ/CSDU/OXpazXzTrPhj7yg+8ZMKK1rvubZp+ul2nG7tXdzFRQWqmP3OzX5gxneP097ZYSu6TVM/7fnP3XpOcf/T6h9pMHDn/Ie+TS/Z196R7ffPVYrVq7y/nnbrZro/v7XaPHSFTqrfe8KH/nc0HAbEmqmp+KiYl1yVW+1Oe1YHdl8f+Xl5XqX3zl8rN774DPd2ed6Nd28oSa//5luvWMEHyXw9eRQzG8CCDW/iVLPNQIINdcSo98gCHCHWhBUqekSAYSaS2lVrleEWuW4cVVyCSDUHMje3MX159z5qlunVpmPBazb+uKly1UlL0/Vq1VJaSLzuOX8hUs80bX+V0TXL1DyDrVUhdqtgx7UO1M+LrN81NCe2nrLzWW+ADrqsQl6891p3t9v2bSxTjuxRZkPF6Q0AIsgECIBhFqIsNnKSgIINStjoamQCSDUQgbOdtYRQKhZF4nvDSHUfEdKwZgTQKjFPGA/xktXqKWyp7mLbcGiJWrcYLNUlrMGApESQKhFip/NLSCAULMgBFqInABCLfIIaCBiAgi1iAMIYXuEWgiQ2SJWBBBqsYozmGGCEGrBdEpVCARDAKEWDFequkMAoeZOVnQaHAGEWnBsqewGAYSaGzll0iVCLRN6XJtEAgi1JKae5swItTSBsTx2BBBqsYuUgdIkgFBLExjLY0kAoRbLWBkqDQIItTRgOboUoeZocLQdGQGEWmTo3dkYoeZOVnQaDAGEWjBcqeoOAYSaO1nRaXAEEGrBsaWyGwQQam7klEmXCLVM6HFtEgkg1JKYepozI9TSBMby2BFAqMUuUgZKkwBCLU1gLI8lAYRaLGNlqDQIINTSgOXoUoSao8HRdmQEEGqRoXdnY4SaO1nRaTAEEGrBcKWqOwQQau5kRafBEUCoBceWym4QQKi5kVMmXSLUMqHHtUkkgFBLYuppzoxQSxMYy2NHAKEWu0gZKE0CCLU0gbE8lgQQarGMlaHSIIBQSwOWo0sRao4GR9uREUCoRYbenY0Rau5kRafBEECoBcOVqu4QQKi5kxWdBkcAoRYcWyq7QQCh5kZOmXSJUMuEHtcmkQBCLYmppzkzQi1NYCyPHQGEWuwiZaA0CSDU0gTG8lgSQKjFMlaGSoMAQi0NWI4uRag5GhxtR0YAoRYZenc2Rqi5kxWdBkMAoRYMV6q6QwCh5k5WdBocAYRacGyp7AYBhJobOWXSJUItE3pcm0QCCLUkpp7mzAi1NIGxPHYEEGqxi5SB0iSAUEsTGMtjSQChFstYGSoNAgi1NGA5uhSh5mhwtB0ZAYRaZOjd2Rih5k5WdBoMAYRaMFyp6g4BhJo7WdFpcAQQasGxpbIbBBBqbuSUSZcItUzocW0SCSDUkph6mjMj1NIExvLYEUCoxS5SBkqTAEItTWAsjyUBhFosY2WoNAgg1NKA5ehShJqjwdF2ZAQQapGhd2djhJo7WdFpMAQQasFwpao7BBBq7mRFp8ERQKgFx5bKbhBAqLmRUyZdItQyoce1SSSAUEti6mnOjFBLExjLY0cAoRa7SBkoTQIItTSBsTyWBBBqsYyVodIggFBLA5ajSxFqjgZH25ERQKhFht6djRFq7mRFp8EQQKgFw5Wq7hBAqLmTFZ0GRwChFhxbKrtBAKHmRk6ZdIlQy4Qe1yaRAEItiamnOTNCLU1gLI8dAYRa7CJloDQJINTSBMbyWBJAqMUyVoZKgwBCLQ1Yji5FqDkaHG1HRgChFhl6dzZGqLmTFZ0GQwChFgxXqrpDAKHmTlZ0GhwBhFpwbKnsBgGEmhs5ZdIlQi0TelybRAIItSSmnubMCLU0gbE8dgQQarGLlIHSJIBQSxMYy2NJAKEWy1gZKg0CCLU0YDm6FKHmaHC0HRkBhFpk6N3ZGKHmTlZ0GgwBhFowXKnqDgGEmjtZ0WlwBBBqwbGlshsEEGpu5JRJlwi1TOhxbRIJINSSmHqaMyPU0gTG8tgRQKjFLlIGSpMAQi1NYCyPJQGEWixjZag0CCDU0oDl6FKEmqPB0XZkBBBqkaF3Z2OEmjtZ0WkwBBBqwXClqjsEEGruZEWnwRFAqAXHlspuEECouZFTJl0i1DKhx7VJJIBQS2Lqac48cmy+/pyz4Ytan7BKdermKCsnO82qLIeAOwQQau5kRafBEECoBcOVqm4RQKi5lRfd+k8AoeY/U9sqItRsS4R+bCeAULM9IQv6yy8o0vwlqzfYSXGxBQ3SAgQCJoBQCxgw5a0ngFCzPiIaDIEAQi0EyGxhNQGEmtXx+NIcQs0XjBRJEAGEWoLCzmTUWfNXZnI510LAaQIINafjo3kfCCDUfIBICecJINScj5ABMiSAUMsQoAOXI9QcCIkWrSKAULMqDnubQajZmw2dBU8AoRY8Y3awmwBCze586C4cAgi1cDizi70EEGr2ZuNXZwg1v0hSJykEEGpJSTrDORFqGQLkcqcJINScjo/mfSCAUPMBIiWcJ4BQcz5CBsiQAEItQ4AOXI5QcyAkWrSKAELNqjjsbQahZm82dBY8AYRa8IzZwW4CCDW786G7cAgg1MLhzC72EkCo2ZuNX50h1PwiSZ2kEECoJSXpDOdEqGUIkMudJoBQczo+mveBAELNB4iUcJ4AQs35CBkgQwIItQwBOnA5Qs2BkGjRKgIINavisLcZhJq92dBZ8AQQasEzZge7CSDU7M6H7sIhgFALhzO72EsAoWZvNn51hlDziyR1kkIAoZaUpDOcE6GWIUAud5oAQs3p+GjeBwIINR8gUsJ5Agg15yNkgAwJINQyBOjA5Qg1B0KiRasIINSsisPeZhBq9mZDZ8ETQKgFz5gd7CaAULM7H7oLhwBCLRzO7GIvAYSavdn41RlCzS+S1EkKAYRaUpLOcE6EWoYAudxpAgg1p+OjeR8IINR8gEgJ5wkg1JyPkAEyJIBQyxCgA5cj1BwIiRatIoBQsyoOe5tBqNmbDZ0FTwChFjxjdrCbAELN7nzoLhwCCLVwOLOLvQQQavZm41dnCDW/SFInKQQQaklJOsM5EWoZAuRypwkg1JyOj+Z9IIBQ8wEiJZwngFBzPkIGyJAAQi1DgA5cjlBzICRatIoAQs2qOOxtBqFmbzZ0FjwBhFrwjNnBbgIINbvzobtwCCDUwuHMLvYSQKjZm41fnSHU/CJJnaQQQKglJekM5swvKNL8JavLVShWllRcnEFlLoWAGwQQam7kRJfBEUCoBceWyu4QQKi5kxWdBkMAoRYMV5uqItRsSoNeXCCAUHMhpYh7HDk2X3/OKdvEZvWk/xxdoGrVsyLuju0hEDwBhFrwjNnBbgIINbvzobtwCCDUwuHMLvYSQKjZm41fnSHU/CJJnaQQQKglJekM5rxtcL5m/lJWnDVpJF1ywRpVq4FQywAtlzpCAKHmSFC0GRgBhFpgaCnsEAGEmkNh0WogBBBqgWC1qihCzao4aMYBAgg1B0KKukWEWtSUxDWOAAAgAElEQVQJsH/UBBBqUSfA/lETQKhFnQD720AAoWZDCvQQJQGEWpT0w9kboRYOZ3aJDwGEWnyyDGwShFpgaCnsCAGEmiNB0WZgBBBqgaGlsEMEEGoOhUWrgRBAqAWC1aqiCDWr4qAZBwgg1BwIKeoWEWpRJ8D+URNAqEWdAPtHTQChFnUC7G8DAYSaDSnQQ5QEEGpR0g9nb4RaOJzZJT4EEGrxyTKwSRBqgaGlsCMEEGqOBEWbgRFAqAWGlsIOEUCoORQWrQZCAKEWCFariiLUrIqDZhwggFBzIKSoW0SoRZ0A+0dNAKEWdQLsHzUBhFrUCbC/DQQQajakQA9REkCoRUk/nL0RauFwZpf4EECoxSfLwCZBqAWGlsKOEECoORIUbQZGAKEWGFoKO0QAoeZQWLQaCAGEWiBYrSqKULMqDppxgABCzYGQom4RoRZ1AuwfNQGEWtQJsH/UBBBqUSfA/jYQQKjZkAI9REkAoRYl/XD2RqiFw5ld4kMAoRafLAObBKEWGFoKO0IAoeZIULQZGAGEWmBoKewQAYSaQ2HRaiAEEGqBYLWqKELNqjhoxgECCDUHQoq6RYRa1Amwf9QEEGpRJ8D+URNAqEWdAPvbQAChZkMK9BAlAYRalPTD2RuhFg5ndokPAYRafLIMbBKEWmBoKewIAYSaI0HRZmAEEGqBoaWwQwQQag6FRauBEECoBYLVqqIINavioBkHCCDUHAgp6hYRalEnwP5RE0CoRZ0A+0dNAKEWdQLsbwMBhJoNKdBDlAQQalHSD2dvhFo4nNklPgQQavHJMrBJEGqBoaWwIwQQao4ERZuBEUCoBYaWwg4RQKg5FBatBkIAoRYIVquKItSsioNmHCCAUHMgpKhbRKhFnQD7R00AoRZ1AuwfNQGEWtQJsL8NBBBqNqRAD1ESQKhFST+cvRFq4XBml/gQQKjFJ8vAJkGoBYaWwo4QQKg5EhRtBkYAoRYYWgo7RACh5lBYtBoIAYRaIFitKopQsyoOmnGAAELNgZCibhGhFnUC7B81AYRa1Amwf9QEEGpRJ8D+NhBAqNmQAj1ESQChFiX9cPZGqIXDmV3iQwChFp8sA5sEoRYYWgo7QgCh5khQtBkYAYRaYGgp7BABhJpDYdFqIAQQaoFgtaooQs2qOGjGAQIINQdCirpFhFrUCbB/1AQQalEnwP5RE0CoRZ0A+9tAAKFmQwr0ECUBhFqU9MPZG6EWDmd2iQ8BhFp8sgxsEoRaYGgp7AgBhJojQdFmYAQQaoGhpbBDBBBqDoVFq4EQQKgFgtWqogg1q+KgGQcIINQcCCnqFhFqUSfA/lETQKhFnQD7R00AoRZ1AuxvAwGEmg0p0EOUBBBqUdIPZ2+EWjic2SU+BBBq8ckysEkQaoGhpbAjBBBqjgRFm4ERQKgFhpbCDhFAqDkUFq0GQgChFghWq4oi1KyKg2YcIJAYoVZYWKTV+WtUo3pVB2JJvcUw5kKopZ4HK+NJAKEWz1yZKnUCCLXUWbEyvgQQavHNlslSI4BQS42Ty6sQai6nR+9RELBWqB15emfN+WuhHrzjeh247788Nm9Pna7eg0frzaeHbJJVlz7Ddek5x2un7bby1k6d9qUuvW6g3ptwj+rVrbXJ69Nd8OxL7+imAaN05slH6ubO56d7eaXXBz2XaawyQq2gsFC5OTnl5lq1Kl+LlyxVo4b1lZ2dVem5uRACYRJAqIVJm71sJIBQszEVegqbAEItbOLsZxsBhJptifjfD0LNf6ZUjDeBjQq14uJizfztT/05d4G237apmjTaTL/+MUc1qldTw/p1AyVjhNqaNQVq2qShnrj/ZmVlZaUl1P51+IV6aEhX7d9sF6/PZctX6pff52jnHbfeoOjJdJjzOvXV/IWL9df8xXp3wt2qWiUv05IpXR/0XJURan/M/ksXdrxZj953m5o0blA6R89+92nKR597/1yvbm0dc/iBant+q5TmZBEEoiSAUIuSPnvbQAChZkMK9BA1AYRa1Amwf9QEEGpRJxD8/gi14BmzQ7wIVCjUlq9YpfZdBuuTGd95E/frfplOPOYgXXnTUM389U89/3DfQEkYodbhglPU846HdPdtV+rIQ/YpJ9TMXWhTPvpCCxYt1Q7bNtUVF7VSy8P30+DhT2nk4y9pqy0aqV6dWmp1XHPtt/cu6t73AY299yZN+/xb3T3yWT1wx/WqXq2KN8fkDz7XQ0+8rAcH3eA9GnrXg+P039enarO6tXXmyUeo9XGHla5df/BZf87T0Wddp6eG99IZ7XqV9mvW/fDzH+rad4SOa3GAHn3mNU8SXtPuDFWpkqfhY57XwsVLdd5px+iyc0/0yhqJ+dTzb+nhpydq6bIVan3coTq7VQtt3qi+Xnh1ij778gft9a8d9OJrU72771off2jpXDk52Zo9Z74G3vekPvrsa+Xl5eqo5v+n7leeq0fGvaqHnnzZu+uvfr3aOvuUFrr8gpM9UWnqvv3+dNWtXVPPvzpFu+y4jTpe3EoHNNvV6ymdO9Q6dRugb7772btufaH28BMvqvmBzdR080b67PNvdFO/+3R3vy7aZad/BHqWKA6BTAkg1DIlyPWuE0CouZ4g/ftBAKHmB0VquEwAoeZyeqn1jlBLjROrIFBCoEKh9tQLk3T3yGd0Q4ezPRF07qlHe0Ltw0+/0UWd++mtcXeqccN6gZE0Qq3nNRfqi29+0sRJH2n8qNv07oczyjzy+dizr2nH7bZSg3p1NGnqZxoy4mlNeX6Y5s5fqFMuulE3XHG2dttpW23euL6WLF3hya7pb4zUmjWFOrTVlbrl+ot07JEHeDNc0f1Obd20sbp2PEe97hitr7//RZ3bne4Jp96DRuvy80/25t/Qb9QTL2niWx/pyeE9ZSSfkWaDe13hLZ3x9U866/JbdPSh++r0Ew/X9K9+1LCHxmvXnbb1JFpBQaGuv/U+vTjmdm23zRb67xvve/v3vu4ibbfN5rpvzATVrV1Lt95wsUY/+YoG3veE9txtB0+UbdG4gbbdqknpXMVFxTr5oh5q3HAzXXL2cSoqKtYDj72oR+/poVffnqbc3Bxt3bSRfvtjrjrdOFT33t5Zhx24V2ndi846Vofsv4defvMDffntTI17oHfaQm3egsX6a94CXdltQDmhtj67sy/rphNbHqpzTj02sHNEYQj4QQCh5gdFarhMAKHmcnr07hcBhJpfJKnjKgGEmqvJpd43Qi11VqyEgCFQoVBrdfGNann4/mp//km67Po7dOLRB3lCydwN1vyUTnri/p7aY5ftAqNYItT23n1HHXXGtep13YWqVaN6GaFmXsj/7Y+/6psfftXceYt096hnPam1+87baf1HPo0gKhFq5t1efYc+ppm/zdaIgdfpr/mLdPipV+vZkbdqmy2baN//XKYeV52nZrvv6M1n3o82Z95CDb31yg3Oe9y5XdSm9dFq0/oo7y66Dt2GaMoLw7w7vkqE2hdvPeTJuRUrV2m/Y9t7d7P9a+e1d2YZ1uef3lKtjm2uczv28SSZEZjmZ8Te7XeP1dQXh+nRca9p4tsf6bF7bix9/9i6c3306Tfee+JeerS/V2P9348z/9BX3/2ivxYs8u7Gu7TNCbrg9JaeUHv3oxne++rM7+dfZ+uE87t5crJunZpl7lDLy5PWrJGaNJIuuWCNqtUo/x40w/Ocy7ptVKj9PmuuLurUU7d266B/77tHYOeIwhDwgwBCzQ+K1HCZAELN5fTo3S8CCDW/SFLHVQIINVeTS71vhFrqrFgJgY0KtZMu6K5Tjj1EF591XBmhZqTMSRf20KtP3KEtN28YGMUSoWbuoHpw7H/19AuTdH2Hs9R36KPeRwlKHkk1Mu3IQ5p5d2uZu7Eev/cm7w6uTQk1I6pOa9tTrz1xh16b/LFeeetD79oSmWTuIKtWde3joOZn7sYruets3aFL6hx5cDM1bFBP+flr9Nwr7+q2Lpd4gmx9oWYk4J4tLi4Vf6aWkWjHtfi3zmnVwpOV5h11jRqUvfvvzls6eo95riu+zLXrCrUJr7ynfveM1Ucv318uF/Pn5rFP0+e2W2+ul954X+edeozMXWnrCzUjJ4847Wq98fRg71HTdR/5rJonrc5QqBmp2LnHHapRo7ru6N1Z5lFVfhCwmQBCzeZ06C0MAgi1MCizh+0EEGq2J0R/QRNAqAVNOPr6CLXoM6ADtwhUeIfarUPGeI9YPjy0m24eMMq7Q61F8//zHk/8/KsfNemZuwIVIesKNSNgDmt9tXfH2A8z//CE2huTP/He51ZyJ5jBbiTaukJt5OAb9O99dvMSWf8ONfNnRqiZRzEnTHxXbduc4AmwxUuX66ATr9DTI3ppt39u+t1e5n1tk6Z8pv8csX9p8lM//spjM/rOruWEmnkMc48jL6pQqJmeTm55sPdetfV/64uv9ed694MZ3qOrbz97V5mPRsxfuMR7xHXUkC6l70Vr32WQDmi2W9pCraSnyt6hZr7y2XvgcP01b6EG33qN6tTx/4urbv0rSLcuEECouZASPQZJAKEWJF1qu0IAoeZKUvQZFAGEWlBk7amLULMnCzpxg0CFQs28LP/US2/2XmJvfuYF/+ZxTyO37ul7lY44qFmgE64r1MxGY8e/oT53PeJ9adQItfc//kqXXDvAe0zT3EVl3j1m/r5EqF3cub/2a7aLLj3nBK1YsUq/z/6rzCOfpuYz/31HNw8c5c1h7uoyd4aZn7l2TUGhBtzU3hNT5rHSjz//zns8ct1fQWGhjjj1anW+7HTv4wElv48++0YXXt1Prz85SOadYuYdaiWPfG5KqI149AXvTjLzfjMj9P74c57GvTjJ+5DBpoSa+YjBMWddrxOOPtB755t5Z9qYpyfq4rOP04EndPDumjvmsP00bfq3uu6W+9ThgpNDFWpLl69Q7/7DtWrVavW9sSMyLdB/gyjuJwGEmp80qeUiAYSai6nRs98EEGp+E6WeawQQaq4lln6/CLX0mXFFsglUKNQMlpWr8vXUC2/py29+1tLlK7Xd1pt7X8w0X5cM+re+UDNf3jzqjGu8L1caoWbE1DW9hum1d6Z5rZhHGd9871M9cd/N2mPX7b072HoNesiTgEYumcdCT79s7UcJzDvUzG/Z8pU64PjLvUctzTvTSn5GIvYaNFrvvD+99M/anXeirrzk1DJjl3yg4b0J96he3b/vtDKPdR5+6lW65Jzj9X977qyz2vfeqFA7r1Nf7yug5sub5pHRIQ+M80RYyc98odTc7Tb6qVe8r5qa976V/L76bmaZuaZO+1I9+j9YKkL32eOfeuTu7t5XT83ddOZnvohqeJr9LjzzP+XqlrxTznA2AjOdr3waEWk+SnDBFTfrobt7q0njBsrLzdHKlavVqWt/GQl503VtVbNGda+X7Oxs7yMK/CBgMwGEms3p0FsYBBBqYVBmD9sJINRsT4j+giaAUAuacPT1EWrRZ0AHbhGoUKiZO6vMY5LmxfnmLq2S3+QPZqhh/TreVypt+Jk+zeOVm9WtXa4dI7bMnXYNNqvjfRAg3d+q1flavGS5GtSvUyrh0q1R2fVGPM1fsER1atdU9Wp/v8st1XrmMU/zDriaNdbedWd+5r1zS5at0BaN66daxluXjlA7qU1nrVy1qrR+vbq19fSoAd6HH8yHCtb/lfx9Wg2xGAIhE0CohQyc7awjgFCzLhIaioAAQi0C6GxpFQGEmlVxBNIMQi0QrBSNMYEKhdqg+5/Sc69M9r4YWbtWjVIE/Yc9rhdfm6K3nrkzdMkU4xysHi0doWb1IDQHgUoSQKhVEhyXxYYAQi02UTJIBgQQahnA49JYEECoxSLGjQ6BUIt/xkzoL4EKhdqZ7XrrwH3/pavbnlZmx5KvYBrRtu1WTfzthmpWEkCoWRkLTYVIAKEWImy2spIAQs3KWGgqZAIItZCBs511BBBq1kXie0MINd+RUjDmBCoUaidd0N37cmWHC08pg+CnX2frxPO76ZkHb9EuO24TczyMZwgg1DgHSSeAUEv6CWB+hBpnAAISQo1TkHQCCLX4nwCEWvwzZkJ/CVQo1Lr0Ge69AP+1Jwd57+Iq+fW7Z6z3FcoPX7q/zPu5/G2LajYRQKjZlAa9REEAoRYFdfa0iQBCzaY06CUqAgi1qMizry0EEGq2JBFcHwi14NhSOZ4EKhRqP878Qydd2MObuuXh+3tfe3zz3U/0++y/dPFZx+na9mfEkwhTlSOAUONQJJ0AQi3pJ4D5EWqcAQhwhxpnAAIItfifAYRa/DNmQn8JVCjUzDZff/+L7npwnD7+/HutWLlKO2zbVGeefITOPPlIPkjgbw5WV0OoWR0PzYVAAKEWAmS2sJoAQs3qeGguJALcoRYSaLaxlgBCzdpofGsMoeYbSgolhMBGhdq6DIqKipWdnZUQLIy5LgGEGuch6QQQakk/AcyPUOMMQIA71DgDEECoxf8MINTinzET+ktgk0Jt2fKVWrlqdbldG9avq6wsBJu/cdhZDaFmZy50FR4BhFp4rNnJTgIINTtzoatwCXCHWri82c0+Agg1+zLxuyOEmt9EqRd3AhUKtTl/LdSVNw7VF9/+vEEGU14Yprq1a8adD/PxlU/OAASEUOMQJJ0AQi3pJ4D5DQGEGucg6QQQavE/AQi1+GfMhP4SqFCo9R78sF5/Z5ratjlB/Yc9rtu6XKLN6tbW4OFPafPG9TXs9s7Ky83xtxuqWUmAO9SsjIWmQiSAUAsRNltZSQChZmUsNBUyAYRayMDZzjoCCDXrIvG9IYSa70gpGHMCFQq1VhffqBOOPkjnnXq0mh3TVs8/3Nf7KMHbU6erQ7ch+vCl+1WzRrWY42E8QwChxjlIOgGEWtJPAPMj1DgDEOAONc4ABBBq8T8DCLX4Z8yE/hKoUKi1PPt6XXLO8TrjxMO137HtNeCmdjrioGb6ffZfMn839t6btNduO/jbDdWsJIBQszIWmgqRAEItRNhsZSUBhJqVsdBUyAS4Qy1k4GxnHQGEmnWR+N4QQs13pBSMOYEKhdrZHW5Vs3/tqBuuOFvX9BqmRYuXaVCvDnrh1SneI6CvPzVYWzSuH3M8jGcIINQ4B0kngFBL+glgfoQaZwAC3KHGGYAAQi3+ZwChFv+MmdBfAhUKtaEjn9G3P/6mYX2v1vSvftQ5HW4t3bnl4ftpcK8r/O2EatYSQKhZGw2NhUQAoRYSaLaxlgBCzdpoaCxEAtyhFiJstrKSAELNylh8bQqh5itOiiWAwEa/8rk6P1/bbNnEw/D9z7/r/Y+/0s47bKP99t5ZWVlZCcDDiIYAQo1zkHQCCLWknwDmR6hxBiDAHWqcAQgg1OJ/BhBq8c+YCf0lUKFQM495Lli0VKPv7OrvjlRzjgBCzbnIaNhnAgg1n4FSzjkCCDXnIqPhAAhwh1oAUCnpFAGEmlNxVapZhFqlsHFRgglUKNQGDHtcH372jcY90DvBeBjdEECocQ6STgChlvQTwPwINc4ABLhDjTMAAYRa/M8AQi3+GTOhvwQqFGpff/+LTmvbUy+MuV3bb7OFv7tSzSkCCDWn4qLZAAgg1AKASkmnCCDUnIqLZgMiwB1qAYGlrDMEEGrORFXpRhFqlUbHhQklUKFQe+CxF3XnA+O01RaNtPOOW5fD06/7ZapRvVpCsSVrbIRasvJm2vIEEGqciqQTQKgl/QQwvyGAUOMcJJ0AQi3+JwChFv+MmdBfAhUKtfvGTNDnX/1U4W6Del6OUPM3C2urIdSsjYbGQiKAUAsJNNtYSwChZm00NBYiAYRaiLDZykoCCDUrY/G1KYSarzgplgACFQq1BMzOiCkSQKilCIplsSWAUItttAyWIgGEWoqgWBZrAgi1WMfLcCkQQKilAMnxJQg1xwOk/dAJINRCR+7ehgg19zKjY38JINT85Uk19wgg1NzLjI79J4BQ858pFd0igFBzK6/KdItQqww1rkkyAYRaktNPcfaRY/P155yyi+vVk449ulDVqqdYhGUQcJgAQs3h8GjdFwIINV8wUsRxAgg1xwOk/YwJINQyRmh9AYSa9RHRoGUEEGqWBWJjO/kFRZq/ZHW51oqKpSwbG6YnCPhMAKHmM1DKOUcAoeZcZDQcAAGEWgBQKekUAYSaU3FVqlmEWqWwcVGCCSDUEhx+OqPPmr8yneWshUCsCCDUYhUnw1SCAEKtEtC4JHYEEGqxi5SB0iSAUEsTmIPLEWoOhkbLkRKoUKhNnfallixbrpaH7x9pg2xuBwGEmh050EU0BBBq0XBnV3sIINTsyYJOoiOAUIuOPTvbQQChZkcOQXaBUAuSLrXjSKBCoXZNr2FatnylRgy8Lo5zM1OaBBBqaQJjeawIINRiFSfDVIIAQq0S0LgkdgQQarGLlIHSJIBQSxOYg8sRag6GRsuREqhQqN378ARNeOVdTXx8YKQNsrkdBBBqduRAF9EQQKhFw51d7SGAULMnCzqJjgBCLTr27GwHAYSaHTkE2QVCLUi61I4jgQqF2rwFi3Vsmy4a3KuDmh+wZxxnZ6Y0CCDU0oDF0tgRQKjFLlIGSpMAQi1NYCyPJQGEWixjZag0CCDU0oDl6FKEmqPB0XZkBCoUatfdcp9efvODChub8sIw1a1dM7LG2ThcAgi1cHmzm10EEGp25UE34RNAqIXPnB3tI4BQsy8TOgqXAEItXN5R7IZQi4I6e7pMoEKh9sbkT/TbrLkVznZ2qxaqWiXP5dnpPQ0CCLU0YLE0dgQQarGLlIHSJIBQSxMYy2NJAKEWy1gZKg0CCLU0YDm6FKHmaHC0HRmBCoVaZB2xsZUEEGpWxkJTIRFAqIUEmm2sJYBQszYaGguRAEItRNhsZSUBhJqVsfjaFELNV5wUSwCBjQq1Dz79WuNfnqxffp+j9uedpMMO3Et33P+kGtSro4vOOjYBeBixhABCjbOQZAIItSSnz+yGAEKNcwABCaHGKUg6AYRa/E8AQi3+GTOhvwQqFGpffjtTZ7TrpSaNNtPSZSt1c+fzdeIxB2ns+DfU565H9PHEEapWtYq/3VDNWgIINWujobEQCCDUQoDMFlYTQKhZHQ/NhUQAoRYSaLaxlgBCzdpofGsMoeYbSgolhECFQu2mAaO0eOky3XVLJ7W7YZBOPPogT6j9/OtsnXB+Nz0/uo92+MeWCcHEmAg1zkCSCSDUkpw+sxsCCDXOAQS4Q40zAAGEWvzPAEIt/hkzob8EKhRqzU/ppM6Xna7Wxx2qy66/o1SoLVi0VObvxj3QW7vutK2/3VDNWgIINWujobEQCCDUQoDMFlYTQKhZHQ/NhUSAO9RCAs021hJAqFkbjW+NIdR8Q0mhhBCoUKhdet1ANdisjvr3aFdGqL342lR16TNc7794r2rXqpEQTMkeM7+gSPOXrE42BKZ3gkCxpKwNdVqcpWKZv63cD6FWOW5cFR8CCLX4ZMkklSeAUKs8O66MBwGEWjxy3NgUCLX4Z8yE/hKoUKi99s40XX3zPTqnVQt98MnXOvygvVW/Xh0NvO8JnfKfQ9Sn66X+dkI1awmMHJuvP+dY2x6NQcAjkJ0tnbPPdNWe+FAZIsV1NlP+CRequMlWlSaFUKs0Oi6MCQGEWkyCZIyMCCDUMsLHxTEggFCLQYibGAGhFv+MmdBfAhv9yudTL0zSwHuf0IqVq0p3Pb7Fv9Xj6vNUt3ZNfzuhmrUEbhucr5m/bPC+H2t7prHkETBCrfvxH6jeiK5lhVr9xlrVsa+Kt6j8I+oIteSdJyYuSwChxomAAO9Q4wxAAKEW/zOAUIt/xkzoL4GNCjWzVX7+Gv3+5zxPqm21eSPVq1vL3w6oZj0BhJr1EdHg/+5QQ6hxFCAQDAGEWjBcqeoWAe5QcysvuvWfAELNf6a2VUSo2ZYI/dhOoEKh9tATL2urpo10+IF7Ky8v1/Y56C9AAgi1AOFS2jcC3KHmG0oKQaAcAYQahwIC3KHGGYAAQi3+ZwChFv+MmdBfAhUKtVuGjNGTE95U/Xq1deZJR+qUYw/RVls08nd3qjlBAKHmREyJbxKhlvgjAIAACSDUAoRLaWcIcIeaM1HRaEAEEGoBgbWoLELNojBoxQkCG33k87uffteEV96VeZeaeeTz0H/vpTNPOkKHHLCHcnNynBiQJjMngFDLnCEVgieAUAueMTsklwBCLbnZM/nfBBBqnIakE0Coxf8EINTinzET+ktgk+9QM9uZ96hNmjpdz770tiZ/MMO7a23i4wNVo3o1f7uhmpUEEGpWxkJT6xFAqHEkIBAcAYRacGyp7A4BhJo7WdFpMAQQasFwtakqQs2mNOjFBQIpCbXVRqhN+VRPv/i2pk770hNpb40bolo1q7swIz1mSAChliFALg+FAEItFMxsklACCLWEBs/YZQgg1DgQSSeAUIv/CUCoxT9jJvSXwCYf+Xzu5cmeSDOPfO652w46+5QjdfSh+6l6tSr+dkI1awkg1KyNhsbWIYBQ4zhAIDgCCLXg2FLZHQIINXeyotNgCCDUguFqU1WEmk1p0IsLBCoUarcOGaMnJrzpzdCm9VE69fjDtPMOW7swEz36TACh5jNQygVCAKEWCFaKQsAjgFDjIECAr3xyBiCAUIv/GUCoxT9jJvSXQIVC7d6HJ2iLxvXV8vD9VaN6VX93pZpTBBBqTsWV2GYRaomNnsFDIIBQCwEyW1hPgDvUrI+IBgMmgFALGLAF5RFqFoRAC04RSOkdak5NRLO+E0Co+Y6UggEQQKgFAJWSEPgfAYQaRwEC3KHGGYAAQi3+ZwChFv+MmdBfAmWE2o+/zNILr07RBWe01Kdf/KDfZ82tcLczTz5SVavk+dsN1awkgFCzMhaaWo8AQo0jAYHgCCDUgmNLZXcIcIeaO1nRaTAEEGrBcLWpKkLNpjToxQUCZYTa21Onq0O3IXrp0f6668FnNHHShxXOMOWFYapbu6YLM9JjhgQQaqzOkqAAACAASURBVBkC5PJQCCDUQsHMJgklgFBLaPCMXYYAQo0DkXQCCLX4nwCEWvwzZkJ/CZQRaoWFRVqdv8b7gufceYu0Oj9f22zZxN8dqeYcAYSac5ElsmGEWiJjZ+iQCCDUQgLNNlYTQKhZHQ/NhUAAoRYC5Ii3QKhFHADbO0egwneoXdNrmBYsWqrRd3Z1biga9pcAQs1fnlQLhgBCLRiuVIWAIYBQ4xxAgHeocQYggFCL/xlAqMU/Yyb0l0CFQm3AsMf14WffaNwDvf3dkWrOEUCoORdZIhtGqCUydoYOiQBCLSTQbGM1Ae5QszoemguBAEItBMgRb4FQizgAtneOQIVC7evvf9FpbXvqhTG3a/tttnBuMBr2jwBCzT+WVAqOAEItOLZUhgBCjTMAAe5Q4wxAAKEW/zOAUIt/xkzoL4EKhdoDj72oOx8Yp622aKSdd9y63K79ul+mGtWr+dsN1awkgFCzMhaaWo8AQo0jAYHgCCDUgmNLZXcIcIeaO1nRaTAEEGrBcLWpKkLNpjToxQUCFQq1+8ZM0Odf/VThDIN6Xo5QcyFhH3pEqPkAkRKBE0CoBY6YDRJMAKGW4PAZvZQAQo3DkHQCCLX4nwCEWvwzZkJ/CVQo1PzdhmouE0CouZxecnpHqCUnayYNnwBCLXzm7GgfAYSafZnQUbgEEGrh8o5iN4RaFNTZ02UCmxRqK1auVm5OtqpUyXN5TnrPgABCLQN4XBoaAYRaaKjZKIEEEGoJDJ2RyxFAqHEokk4AoRb/E4BQi3/GTOgvgQ0KtZWr8nXfw89pyrQvZT5OYH4HNNtVRx+2r84+pYW/HSS4WmFhkVbnr1GN6lUjobCmoFCFhYWqVrXKRvdHqEUSD5umSQChliYwlkMgDQIItTRgsTS2BBBqsY2WwVIkgFBLEZTDyxBqDodH65EQKCfUli5boU43DtVHn32jA/f9l3bfeTsVFBZq+pc/6pMZ3+msk49U9yvPVU5OdiQNu7LpC69O0ZAHntabTw8p03LLs69X+/NPUqtjm2vqtC916XUD9d6Ee1Svbq3QR7tn1Hi98e7HGj/qNoRa6PSTuWFWltSkkVSndpZ++6NYK1eV57BZXalKFWnOXxtmlJsjFRZJxcVl/74yQq24uFiFRUXKzcnZaCDmP1zMmr9yo2uKioo1b+Ei1alZU9WqbVxSJzN9pnaZAELN5fTo3S8CCDW/SFLHVQIINVeTS71vhFrqrFgJAUOgnFC7ZcgYPTnhTd17e2cdduBeZSg9/twbuu3OR9Trugt1+gmHQ3AjBIxQG3Dv45r83N1lVh15emd1uri1J9SWLV+pX36f431FdVP/hT4I2HPnLdLSZcu1wz+2RKgFAThGNatVlQbekifj0Ttcv6bcZCe2zNbJx+VowkuFemFi0QYnP2j/bF10To6MVDM/I8Te+6BIox8v9P65Tm2p5w15qltn7d+vXi31GVKgWbP/Nme1akp33JKnyVOL9Ni4tdeV/Coj1F5/+wONfOw5PT7i9o2mta5QG/noc3pi/EQ9O2aQates4V037bOv1H/oaC1avNT755OPPUwdLj5T2dlZ3p+dfvEN5er373WV9tljlxidEkaJMwGEWpzTZbZUCSDUUiXFurgSQKjFNdm/50KoxT9jJvSXQBmhlp+/Rs2OaasrLmqlDhecvMGdrrxpqObMXagnh/f0t5OYVUtFqP34yyx17/uAxt57k3fH39jxb+jRZ17VX/MXa9utmqjjRa10+EF7q989Yz06P/0yS+999IWa7b6T+nZrq222bKxFi5fp8m5D9MPPf3hr/rXzP9StUxvtvMPW3p917TtCJxx9oB4f/4b395ecfZzOOOkI73/+7xvv6+PPv9PNnc/3/tncgThkxDh988Ov2mqLhjrvtGPU+rhDxSOfMTucaY5jBFifHnlq3EjKzy8v1PbZM0uXX5zribKNCbVDDsjWP3fM0kuvFWrBQqlzh1zttH2WOnVZ492pdnX7XO36zyz1GVSgpcuKdWuPPC1eLPXos1bg9bg2V9tts9bGvTU5M6H2x+y56nbr3Zo9Z54aNqiXslCb+OYU3THsEa+HEqG2YOFinXlpV53d+j86u3VLzZ47X+2uuU3XXXGeWh55kBYuWqIzLumiPj06qunmjUrpN6xfjzvZ0jyLLI+OAEItOvbsbA8BhJo9WdBJNAQQatFwD3NXhFqYtNkrDgTKCLXZcxfoqDOu0bgHemvXnbbd4HxGwtxw6/36ctLoOMwf2AxGqBmZdfn5ZcXkw09PVPcr23h3qH357Uyd0a6Xpr8xUjO+/knnduyjwb06aPttm+rTL35QQUGhzmnVQpd3HaIvvvnJE2zm0dBhDz2nPXbdXn26XqrFS5dr/MuTtc//l2zmwxGjHn9JP/0628vQ1Dzr8lt05MHNPIn226y/1OeuRzTlhWGqW7umxjw9UZOmfKZRQ7ro1z/m6Ng2XTyB1vq45pr525/67Msf1Pu6ixBqgZ0SNwp3vjxX/9whS998X6ydd8wqc4faVk2zdNP1uXrnvSIdfki2nn+54jvU1p/2knNz9O99s3XF9WuUv0a6d2CevvuxWHfeX+AtPf3kHLU8Mlttr17j3c3WuKFUvXqWul+zdr9M7lAzj7EvWLREUz/8XE+MfyUlofby29N10+336ZrL26jPkJGlQm3Kh9PVs//9eubhO1TH3EIn6b7R4zRr9lzd2q1DqVAbNbSntt5yczdCp0sIrEcAocaRgICEUOMUJJ0AQi3+JwChFv+MmdBfAmWE2lffzdTpl/XS28/epYb1625wp/c/+UqXXDNA014Zoeq8J6jCNEqE2in/OaTMmudeeVe3dbmknFD76NNvvPep3d//Wh24725lHgE1Qm2fPXZS2zYneLUmTvrQe/T2nfFDlZWVJfMRic+//lEzf52tGd/87Ak2IzxLhNoXbz3krTO/5qd00i03XKwjDmpWRqiZ96k9+fybpTXXbZo71Pz9l86laqedtFZq3TaoQEcfnq199swuFWrmaccBvfP0y2/FGjC0QA/cmZeSUDuiebZaHJqjRg2lt98t0thn1j66aa5/9a0iPT1h7T/vv0+2LrsgR116r9H8BX9TGz44T+9MyUyolVSb9O40DR/zzCaF2pqVS3TqpT118/VtZe4sa9v51lKh9uEnX6pHn3s0fswg1frfI6ATXn5bL7zyth686+ZSoXbQfnuqdu1a2m6bpjr6iH+XyjeXzgO9JpcAQi252TP53wQQapyGpBNAqMX/BCDU4p8xE/pLoIxQ+2TG9zqvUx998N/7VKtm9Q3uNP2rH3VOh1tL73Lyt534VEvlkc9171ArLirW7feM9d5fZ34tD99f17Q7XVtt0ci7Q21dofbdT7+r1cU36q1xd2rJ0uW6qHM/1a5VQ/vtvYv31VCzd0VC7bhzu6jjRa11XIsDygi1Ln2Ge/v279GuXAgItficy3QmOXC/bF3cJkejHivU1I+KdOl5OaVCzfjZ/j3zvHJGeJk7yFIVam1Oy9H/7Z2t2rWkTz4v1n2jCrzHRc31E8wdbq+sfQfbHrtl6ap2ueozuEA///L3e9TCFmrm37GruvXXKce38N6NNvPXWWWE2pJly3XJlb31j62b6oSWzWU+7GJkmvmKrxFqy1es1ENjJ6hB/XpavnylJr41VfXr1dHd/bp4d5Xyg4ALBBBqLqREj0ETQKgFTZj6thNAqNmeUOb9IdQyZ0iFZBHYoFBr0mizCimsWVOgBYuWItQ2cU7SFWolHyVYvGS5d7fZ4OFPaecdt1G/7peVE2old799+uoDGvLAOH39/S8aOegG7z1sJcIzXaF2x/1P6p2p0/X8w30Rasn6/wMqnLZ311w1aZylP2atlVmNGmapejXp19+L9eyLhTKPgv4513w8YO3fb7t1lpYslSffSu4y2xhKc6eakWv97yrQ9z8Ve0Jt4ptFGve8XXeovT3lY9026EG1PrGFzH2ei5csk/mYwQktD9XxRx2sHbffRr/Pmut9qMC8m23zxg30/Y+/aovNG3qPfK7/++2PP3Xxlb019PYbtOs/t+O0QcAJAgg1J2KiyYAJINQCBkx56wkg1KyPKOMGEWoZI6RAwgiUEWrmPVoPPflKSghu6HA2j3xuhFS6Qm3qtC+1ZNkKHXnwPsrJztKN/UeqVq0a3gcDzB1qjRvW03Xtz9QPM/9Qv7vHasstGmpwrys07KHxemvKZ7qvX2fvnWvDRj+30Uc+K7pD7f2Pv9Il1w7w9jvxmIO9F6tP+egL78ME3KGW0r8SsVt0/DHZ2nnH7NK5zPvSzF1lX39XrCeeLdBZrXPLzLzbzlmat0CaPLVQ/311w1/6XPeCpltk6ZauuRrzZKH3COf671A785QcHX3E3+9QK7k27DvUfvltlmZ88ZWWrFj7cQTzkYHnXpqkc047Vkcesq+23bppGQ4rV67SSed21uUXna7WJxxZ7lysWLlKJ5/bWQN6X61mu+8cu3PDQPEkgFCLZ65MlR4BhFp6vFgdPwIItfhluv5ECLX4Z8yE/hIoI9T8LZ3sahUJtZZnX6/255/kvUOt5J115qME0z77Vp1uHCrzX7bN7+D9dlevay9U080bekJt2vRvS//ugGa7asBN7b333JkPSXTqcZd3l5r5NT9gD03+YMbaRz6/+Vlnte+tdd+hZoRap4tb69gjD9Aj417VW+996n2UwPxGP/WKBt77RGlwpk+zFqGW7LNcMv26j3xuiMj6j3ya9/MP6JWnz78q1v0PFeiCs3K0eOla4VZUuPYrn1s0ydINPddo4eK/v/Jp3tdmvvJ523pf+czNkXJypKH98jTlwyI98WyhVuf/3Ul2ttT9+A9Ub0TXMu0V12+sVR37qniLvz+0Ulxc7Aloc/fZyMee05hhtyorO6v03YVfffez7n7gCXW85Az9a5cdZP7Dxaz5K7266z/yaf7MSLZatWpq4eIlevjxF/ThJ19ozLBbVL16Nb0/bYZW5+er2Z67KC8nR6PGPq+Jb07Vo8Nv4z1q/KvlDAGEmjNR0WiABBBqAcKltBMEEGpOxJRRkwi1jPBxcQIJINQsCt38l/z5C5eoRvVqqlG9amlnJe9Qa9P6aJmvE9apVaNc17P+nKd6dWuXua4yo5n3Ppke6tWpWfp+J4RaZUjG75p0hdoxR2TrjFNydNfwAs34qljmq57mvWwlv8Ii6ZnnC70PEZhf3TpSzxvyVKf22hVGlvW7s0C//bH2kVIj5+qv9zT64HsL9NW3a/8+HaFWIsXWTemoww5Qlysv9P5ozJMv6oWJ72jsiNuVl5uzSaE26rEJevzZtXf37r/Pv3R1+3PVqEE9758nv/+pBt49RitXrZXl5t/T7ldf7Ak2fhBwhQBCzZWk6DNIAgi1IOlS2wUCCDUXUsqsR4RaZvy4OnkEEGoOZL7+RwnCbhmhFjbxeOzX9apcbd4kS1d3X/uopPmZu8y2bLr2i7PmXWzmYwbr/xrWl6pUzdKs2Rv4y42gSUeobYpwp24DdPD+e+msVi29peveobaha1euXO3dndaoYX1PwK3/MyJ84aKl3h+bO0tLvrq7qT74ewjYQgChZksS9BElAYRalPTZ2wYCCDUbUgi2B4RasHypHj8CCDUHMn3voy+8/xK+8w5bR9ItQi0S7M5vat6J9vLrhXph4qbfp+bHsH4JNfPVzlMvuE5Pjxrg3U2WilDzo39qQMBmAgg1m9Oht7AIINTCIs0+thJAqNmajH99IdT8Y0mlZBBAqCUj54ymRKhlhC+xF/9zhyz9+HOxzKOdYfz8Emrel4wXLlaTxg1K297UHWphzMceEIiSAEItSvrsbQsBhJotSdBHVAQQalGRD29fhFp4rNkpHgQQavHIMdApEGqB4qW4TwT8Emobageh5lNIlHGWAELN2eho3EcCCDUfYVLKSQIINSdjS6tphFpauFgMASHUOASbJIBQ2yQiFlhAAKFmQQi0EFsCCLXYRstgaRBAqKUBi6WxJIBQi2WsZYZCqMU/Yyb0lwBCzV+esayGUItlrLEbCqEWu0gZyCICCDWLwqCVyAgg1CJDz8aWEECoWRJEgG0g1AKES+lYEkCoxTJWf4dCqPnLk2rBEECoBcOVqhAwBBBqnAMISAg1TkHSCSDU4n8CEGrxz5gJ/SWAUPOXZyyrIdRiGWvshkKoxS5SBrKIAELNojBoJTICCLXI0LOxJQQQapYEEWAbCLUA4VI6lgQQarGM1d+hEGr+8qRaMAQQasFwpSoEDAGEGucAAtyhxhmAAEIt/mcAoRb/jJnQXwIINX95xrIaQi2WscZuKIRa7CJlIIsIINQsCoNWIiPAHWqRoWdjSwgg1CwJIsA2EGoBwqV0LAkg1GIZq79DIdT85Um1YAgg1ILhSlUIGAIINc4BBLhDjTMAAYRa/M8AQi3+GTOhvwQQav7yjGU1hFosY43dUAi12EXKQBYRQKhZFAatREaAO9QiQ8/GlhBAqFkSRIBtINQChEvpWBJAqMUyVn+HQqj5y5NqwRBAqAXDlaoQMAQQapwDCHCHGmcAAgi1+J8BhFr8M2ZCfwkg1PzlGctqCLVYxhq7oRBqsYuUgSwigFCzKAxaiYwAd6hFhp6NLSGAULMkiADbQKgFCJfSsSSAUItlrP4OhVDzlyfVgiGAUAuGK1UhYAgg1DgHEOAONc4ABBBq8T8DCLX4Z8yE/hJAqPnLM5bVEGqxjDV2QyHUYhcpA1lEAKFmURi0EhkB7lCLDD0bW0IAoWZJEAG2gVALEC6lY0kAoRbLWP0dCqHmL0+qBUMAoRYMV6pCwBBAqHEOIMAdapwBCCDU4n8GEGrxz5gJ/SWAUPOXZyyrIdRiGWvshkKoxS5SBrKIAELNojBoJTIC3KEWGXo2toQAQs2SIAJsA6EWIFxKx5IAQi2Wsfo7FELNX55UC4YAQi0YrlSFgCGAUOMcQIA71DgDEECoxf8MINTinzET+ksAoeYvz1hWQ6jFMtbYDYVQi12kDGQRAYSaRWHQSmQEuEMtMvRsbAkBhJolQQTYBkItQLiUjiUBhFosY/V3KISavzypFgwBhFowXKkKAUMAocY5gAB3qHEGIIBQi/8ZQKjFP2Mm9JcAQs1fnrGshlCLZayxGwqhFrtIGcgiAgg1i8KglcgIcIdaZOjZ2BICCDVLggiwDYRagHApHUsCCLVYxurvUCPH5uvPOf7WpBoE/CaQlS2d+3/TVeuVh8qULq6zmdaccKGKmmxV6S3Nf7iYNX9lpa/nQgi4TgCh5nqC9O8HAYSaHxSp4TIBhJrL6aXWO0ItNU6sgkAJAYQaZ2GTBPILijR/yepNrmMBBKImUFwsZWWV78L8eSY/hFom9Lg2DgQQanFIkRkyJYBQy5Qg17tOAKHmeoKb7h+htmlGrIDAugQQapyHlAhwd05KmFgUUwIItZgGy1gpE0CopYyKhTEmgFCLcbiMlhIBhFpKmJxehFBzOj6aj4AAQi0C6C5uiVBzMTV69osAQs0vktRxlQBCzdXk6NtPAgg1P2lSy0UCCDUXU0uvZ4RaerxYDQGEGmcgJQIItZQwsSimBBBqMQ2WsVImgFBLGRULY0wAoRbjcBktJQIItZQwOb0IoeZ0fDQfAQGEWgTQXdwSoeZiavTsFwGEml8kqeMqAYSaq8nRt58EEGp+0qSWiwQQai6mll7PCLX0eLEaAgg1zkBKBBBqKWFiUUwJINRiGixjpUwAoZYyKhbGmABCLcbhMlpKBBBqKWFyehFCzen4aD4CAgi1CKC7uCVCzcXU6NkvAgg1v0hSx1UCCDVXk6NvPwkg1PykSS0XCSDUXEwtvZ4RaunxYjUEEGqcgZQIINRSwsSimBJAqMU0WMZKmQBCLWVULIwxAYRajMNltJQIINRSwuT0IoSa0/HRfAQEEGoRQHdxS4Sai6nRs18EEGp+kaSOqwQQaq4mR99+EkCo+UmTWi4SQKi5mFp6PSPU0uPFaggg1DgDKRFAqKWEiUUxJYBQi2mwjJUyAYRayqhYGGMCCLUYh8toKRFAqKWEyelFCDWn46P5CAgg1CKA7uKWCDUXU6Nnvwgg1PwiSR1XCSDUXE2Ovv0kgFDzkya1XCSAUHMxtfR6Rqilx4vVEECocQZSIoBQSwkTi2JKAKEW02AZK2UCCLWUUbEwxgQQajEOl9FSIoBQSwmT04sQak7HR/MREECoRQDdxS0Rai6mRs9+EUCo+UWSOq4SQKi5mhx9+0kAoeYnTWq5SACh5mJq6fWMUEuPF6shgFDjDGySQH5BkeYvWb3JdSyAQFwJNKhTlX8H4houc6VEoFqVHOVkZ2n5qoKU1meyqFhZylJxJiW4FgKBEKhfu6oWLlutYo5nIHwpaj+Bqnk5ysvN1rKVa+xvNtUOi7OlrKJUV6e1rrg4S3Lsf58h1NKKmMUQEEKNQ7BJAiPH5uvPOZtcxgIIQAACEIBAxgQKi6Sc7IzLUAACEIAABCCwSQIn/d/PavreaGUtX7zJteksKK5RW2tOvFBFTf+RzmWRr0WoRR4BDThGAKHmWGBRtHvb4HzN/MX8X1j4QQACEIAABCAAAQhAAAIQiAeBDif+oH882VXZi+f7OlBxnfpafeXtKtpye1/rBl0MoRY0YerHjQBCLW6JBjAPQi0AqJSEAAQgAAEIQAACEIAABCIlgFArix+hFulxZHMHCSDUHAwt7JYRamETZz8IQAACEIAABCAAAQhAIGgCCDWEWtBnjPrxJoBQi3e+vkyHUPMFI0UgAAEIQAACEIAABCAAAYsIINQQahYdR1pxkABCzcHQwm4ZoRY2cfaDAAQgAAEIQAACEIAABIImgFBDqAV9xqgfbwIItXjn68t0CDVfMFIEAhCAAAQgAAEIQAACELCIAEINoWbRcaQVBwkg1BwMLeyWEWphE2c/CEAAAhCAAAQgAAEIQCBoAgg1hFrQZ4z68SaAUIt3vr5Mh1DzBSNFIAABCEAAAhCAAAQgAAGLCCDUEGoWHUdacZAAQs3B0MJuGaEWNnH2gwAEIAABCEAAAhCAAASCJoBQQ6gFfcaoH28CCLV45+vLdAg1XzBSBAIQgAAEIAABCEAAAhCwiABCDaFm0XGkFQcJINQcDC3slhFqYRNnPwhAAAIQgAAEIAABCEAgaAKbEmrPrMzRFjnSQVUKvVZmF0r5yiptq6qKtXlO+S6L69TX6itvV9GW2wc9gq/1mzao7ms9ikEg7gQQanFP2If5EGo+QKQEBCAAAQhAAAIQgAAEIGAVgY0JtWXF0kWLqqtHzVXau0qx1/d1i6vql6Ls0hk2zy7S3XVXl5sJoWZVzDQDgcAIINQCQxufwgi1+GTJJBCAAAQgAAEIQAACEIDAWgIbE2rfF2Sp+9JqerzeCuVmrb0rre/SKmqcXaTW1Qv19upsvZmfi1DjMEEgwQQQagkOP9XREWqpkmIdBCAAAQhAAAIQgAAEIOAKgY0JtZ8LsnTD0moaW2+F8v4n1LosqaL984p0avUCvb4qWxNW5yHUXAmbPiEQAAGEWgBQ41YSoRa3RJkHAhCAAAQgAAEIQAACENiYUFtTLF2wsJoOqFKoc2oU6KeCbN2xvIq61lqt/8srQqhxfCAAASHUOASbJIBQ2yQiFkAAAhCAAAQgAAEIQAACjhHY1EcJPsrP1h3Lqqjof3eo7ZFbqJtqrVZWVhZCzbGsaRcCQRBAqAVBNWY1EWoxC5RxIAABCEAAAhCAAAQgAIGNvkOtBM/KYmlmYbbqZBWraXaRJ9PMb3GRtKgoS9vmrv1gwbo/PkrA4YJAMggg1JKRc0ZTItQywsfFEIAABCAAAQhAAAIQgICFBDZ1h1plW0aoVZYc10HALQIINbfyiqRbhFok2NkUAhCAAAQgAAEIQAACEAiQwIaE2lcF2eq/rIqa5RZ670rbM69QdbPTawKhlh4vVkPAVQIINVeTC7FvhFqIsNkKAhCAAAQgAAEIQAACEAiFwIaEWnFxsT5Zk6NnV+Xqu8Ic/SO7UAPr5qfVD0ItLVwshoCzBBBqzkYXXuMItfBYsxMEIAABCEAAAhCAAAQgEA6BTT3y+XuB9HVhjo6uWphWQwi1tHCxGALOEkCoORvd341//Pl3qlu7pnbcbstKT/P65I+11247qFGDeuVqINQqjZULIQABCEAAAhCAAAQgAAFLCWxKqFW2bYRaZclxHQTcIoBQcyCvI0/vrDl/LSztdIdtm+ra9mfqsAP38v7siu53as9dd1C7806s9DT7Hdted97SUQfvtztCrdIUuRACEIAABCAAAQhAAALxJmA+crl5Y2nNGmnegg3Patbk5EgFBeX/vl5dqVGDLM2dV6zFSzJnlZsrbblFln75rfzXNjdVfVNC7ffCLN29PE9/FmXrgLxCXVYjX5+uydGk/Bz9I6dIp1Yv1IZer4ZQ2xR5/h4C8SCAUHMgRyPUzj+9pVoevr9WrFyl0U++omdfekfT3xip3JwchJoDGdIiBCAAAQhAAAIQgAAEXCfQ8shsnXZSjowwM78VK6Wx4wr1/rSiMqO1OT1Hhx6UrXad15T+eZ3aUv+eecrL+3vp77OKdevAAhWWvbx0wf2D8mSE2bq/b78v1sB7CpSbI910fa6abr62GVPj7feK9PgzZR/PrFZVGnhLnnKypQ7X/92PuWZTQq3r4iqaV5yt5lUKNH1NjqplFev7whxtmV2k2YVZOqP6Gk+qrf9DqLl+0ukfAqkRQKilxinSVUaoXd32NJ10zMFeHxMnfaQb+4/U1BeHlRNq06Z/q1sGP6zZc9f+n4uOOGhv9bj6PO+RUPP7ZMZ3GjJinL754VdttUVDnXfaMWp93KFa9w61+QuXqFvfETpov9114Rn/EY98Rho/m0MAAhCAAAQgAAEIQMAKAkcfnq0mjbP08uuFqlUzS1e1W2u7rrlxrajaeacsXXN5rnd3mhFcIX3zmgAAIABJREFU6wo1c2faZRfkavyLhfppZrGOPSpbpxyfo0efKtSk9zZs1IxQ++7HYm+/kt/8BcWaO0+6uE2ODtwvWzf1XaM/50oXnJWjQ/6drWtvWqMlS9euNuKvT488NW4k5eenJ9SWFUsXLaqukXVXqk62VFBcrLaLqumfuUXqVnuNZqzJ1gPLczW0XvkPFiDUrDiuNAGBwAkg1AJHnPkGRqjtu+fO2nv3nbR46TKNffZ1XdPuDLU6trlXfN1HPr/49md9/9Pv2nWnbbVy1Wr1HPiQDj9ob2/9r3/M0bFtungCrfVxzTXztz/12Zc/qPd1F5UKtd132U4XXnW7tttmCw24qb0n7BBqmWdIBQhAAAIQgAAEIAABCMSNwLln5Ojwg7PV/po1KiiUdzeZefzy2BbZarZX2TvU1p99j93WCrm7RxRo+pcbflzTCLX3Py7S6LHl7wK7vmOudtw+S1d3X6OVq6RddsrSdR1z1e/OAv3w89p6nS/P1T93yNI33xdr5x2z0rpD7eeCLPVaVlUP11vl1VpQKLVbUl0Daq/SdrnFmluUpasXVdXY+mv/ft0fQi1uJ515ILBhAgg1B06GEWr169XRNls2UUGh+V8Qf3iia8gtHWXep7b+O9T+mr9In8z4XnPnLdSrb09Tndo1NKzv1bpn1Hg9+fybemf8UGWV3Kf9v/nNHWp9ul6qMU9PVP3NamtQzyuUZ+6jlhBqDpwRWoQABCAAAQhAAAIQgEDYBPrdnCfzKOf6j1Ke1TpHRzTfsFAzEuyMU3K0zVZZ3p1qA4Zu4EVr/xvECLXCQmnREmnRomI9P7FQ5pFP8zMC7dorcr33tL09pUj7Ncv23uvW9Za1d8uZR1PNI6q3DSqQubNunz2z0xJqpsZFC6vq/BoF+neVQg1elqfPCnK1T26BWlUr0Aurc1WkLHWpxR1qYZ879oOALQQQarYksZE+1n/ks6CwUO27DNZ2W2+uHledV0aovfzmB7rulvu0zx7/1K47baPvfvpd1arm6f7+16pLn+HeLv17tCu3mxFq5mfe0fbyY/09eVfy4w41Bw4JLUIAAhCAAAQgAAEIQCBEAuY9aUcckq2nJxRq4pv/r737Doyizv8//tpsEnrviHrq2UXFEz3wFMU7wIqoqGABRBARpAjSpSMdpChIEUWQ4tcuKic27J5ixXYWPJHeQ0vZ/f0+E7MGEpLN7uzuzOxz/pJk5vP5vB/viRteTDn0ls2iAjUTfN3Yyq9KFWXdujlifJYOFsykrEr6dk9VIJB76+bxx/qs569NmpltXXFWvpw0vH/uM9ZKl5b1jLQV/w7o6RdzrFtBzS2h8xfl6P2PA7rjVn9EgdrzB1K1cP+fD30bW+Gg5u1LtZ6jVs0X0L3lM3ViasGr67hCLY4nIlMhkEABArUE4oc79eGBmjluzLQn9NOvGzR3Yt9DArWr2w1Ui6bnq2u7ltbw85es0EdrvrECtYmzlurt9z/X84+NKTRQu6pZY23YtE3rftuoxTOHqHKl8tZ+BGrhdor9EEAAAQQQQAABBBDwvoB5/tl1V/mtlxHMXVjwdsyiArU8nWpVJXOF29vvBbRwWcExDlcslS5NG5emr74JWreJDuyVqtq1fOoxIEspPqnrHak663SfZszNVqsr/Naz3tb/nht21ajuU5nS0q+/BTVjTrZ27ModvbiXEph9fsj2aX1Ois5MzVHV3Bt4tC0gVfUFC9z1k7dmAjXv/wxQIQJGgEDNBedB/rd8mueiff3tz+o/5hHdd3cbtWvd/JBA7ZZuo3Xi8fXUu3Nr/bZhi4ZNXKAqlctbgdoHn6xVx3vH6/5et+mqZhdow+Zteu/jr6wXE+S9lKDBGSda+5ht3qT7VLZMKQI1F5wjLBEBBBBAAAEEEEAAgXgItG6Zeyvl6vcDemxJ4UFYOIGaWeusyWn69vugps468m2f+WuaOSFNP68LauKMbJn/3rQ5qBETco81V7HNmZqmDz8J6PeN5plpKaFD69X1qUJ56Zvvg5q7MDv00oJwArVITAnUIlHjGATcJ0Cg5oKemUBt05YdoZUeW6+Wrr+yidq1biG/P0XdBz2o+qcer863XKV3P/5K/UfP1vade1S2TGmdfMLRqlC+rB4e28s6fsGyVzThoSWhsbrcdrW6336tFahNG9ldjc49XTt3Zajt3SN1zFE1NXNMLz3wYLZ+WffHu7Fd4MUSEUAAAQQQQAABBBBAwH6BW2/0q0njFH36RVArX/8zTNu8NWiFVCbUSk+TWl/j14WNUnRPvyzrGWjmhQXmz6ed7LNuy9yyNSgTupm3ci56KkdvrM69ZXTM4DSlpOQ+B828MfRfTfx64dUcbdgYlAnyzHPZ8vYfOTBNtWtKE6Zn64efgtYVcy0uTTnkpQR5ApHe8tlzVyk1TMvRzWULBn4P703TqakBXVyqYKhIoGb/uceICDhRgEDNiV2Jck3mGWvm1s3aNauFXiyQf8icnIC27dityhXLKd184hWzcctncUJ8HwEEEEAAAQQQQAAB7wuMGJCqurUL/kP7Ox8EtODJHOuWy+6dUw+B2LotNyBrfF6KOrT1W6Fb3rbmi6BmzssNq8zLDSaPSrOeeTbviRwrUOvdNdV6Nlph+9esLnXvnBuqmc28kODdDwNW4Hb4FkmgZm7r7LKrjKZU2K96h5ZkDb9oX6o+yPJreqWDBeYjUPP+zwIVImAECNQ4D4oVIFArlogdEEAAAQQQQAABBBBAoBgBE6aZIKxiBZ/W/S+ozNwXclqbubrMXGXWa1CWMvbmfs3sbwKz8uV8+vnXoPVGz8M381KCo+rkjlfSrahbPr/J8un+jNJaXmV/aNi+u9J1Y5lsnZse0JdZPo3aU0pLqx4oMC2BWkk7wf4IuFOAQM2dfYvrqgnU4srNZAgggAACCCCAAAIIJJ3AwN65l4GNmRze89TsACoqUFuf41PP3aU1q9J+VUuRzE2pbbaX1qWlstW5XLY+zkzRlIx0LSZQs6MVjIGAKwUI1FzZtvgumkAtvt7MhgACCCCAAAIIIIBAsgkcfZRPO3YGQ1enxaP+ogK1QDCorrtKy++TWpTK1hdZKdoRSNHvOT6dmBbQT9k+nZwa1OAKmQWWyhVq8egecyCQeAECtcT3wPErIFBzfItYIAIIIIAAAggggAACCJRQoLi3fJqr1KbtTdMv2SmqlRLQfeUztTvo07L9aSrrC+rOclmqlO8Zb3nTE6iVsBHsjoBLBQjUXNq4eC6bQC2e2syFAAIIIIAAAggggAAC8RAoLlCLdA0EapHKcRwC7hIgUHNXvxKyWgK1hLAzKQIIIIAAAggggAACCMRQIJxAbUOO9GmW37rVM90n1UoJ6rz0gKqmHPklCARqMWwaQyPgIAECNQc1w6lLIVBzamdYFwIIIIAAAggggAACCEQqUFyg9vIBv+bvT1dpBVQjRfpf4M/7O68plaWbyxb+AgUCtUg7wnEIuEuAQM1d/UrIagnUEsLOpAgggAACCCCAAAIIIBBDgaICtYyA1GFXGbUvk6krSudYq3ggI13HpQSs56ctPJCuu8tm6uJSud/LvxGoxbBpDI2AgwQI1BzUDKcuhUDNqZ1hXQgggAACCCCAAAIIIBCpQFGB2rdZPg3dU0pLqx4IDb9oX6o2B3zqVT5L4zLStSNHGluJt3xG6s9xCLhdgEDN7R2Mw/oJ1OKAzBQIIIAAAggggAACCCAQV4GiArWtOdJdu8toVIUDOjk1qGAwqMF7SumolIC6ls/WfzJTNDkjXYvzBW55i+cKtbi2kckQSJgAgVrC6N0zMYGae3rFShFAAAEEEEAAAQQQQCA8geKeoTYhI00fZaXqeH+O9gV92hhI0egKB3VSakAfZvr1xP5UTa90sMBkBGrh+bMXAm4XIFBzewfjsH4CtTggMwUCCCCAAAIIIIAAAgjEVaC4QC0g6cX9fn2WlaIKKT41L52t01LNV4veCNSKE+L7CHhDgEDNG32MaRUEajHlZXAEEEAAAQQQQAABBBBIgEBxgVqkSyJQi1SO4xBwlwCBmrv6lZDVEqglhJ1JEUAAAQQQQAABBBBAIIYCBGqH4tatViaG2gyNgPcECNS811PbKyJQs52UARFAAAEEEEAAAQQQQCDBAgRqBGoJPgWZ3uUCBGoub2A8lk+gFg9l5kAAAQQQQAABBBBAAIF4ChCoEajF83xjLu8JEKh5r6e2V0SgZjspAyKAAAIIIIAAAggggECCBQjUCNQSfAoyvcsFCNRc3sB4LJ9ALR7KzIEAAggggAACCCCAAALxFCBQI1CL5/nGXN4TIFDzXk9tr4hAzXZSBkQAAQQQQAABBBBAAIEECxCoEagl+BRkepcLEKi5vIHxWD6BWjyUmQMBBBBAAAEEEEAAAQTiKUCgRqAWz/ONubwnQKDmvZ7aXhGBmu2kDIgAAggggAACCCCAAAIJFiBQI1BL8CnI9C4XIFBzeQPjsXwCtXgoMwcCCCCAAAIIIIAAAgjEU4BAjUAtnucbc3lPgEDNez21vaJ5izO1cZPtwzIgAggggAACBQRycnzy+4PIIIAAAgggEHOBqxv+orqrH5Vv7y5b5wqWq6isq9orUOdYW8eN9WB1q5WJ9RSMj4CnBAjUPNXO2BSTmR3Qtt0HYzM4oyLgAoFqFUvxM+CCPrHE2AmUTvfLn+LT3gPZsZvkj5EDQSnFF/NpmACBEgtUrVBKOzIOKkjeW2I7DvCGQKk0v9JSU5SxP8sbBUkKBiRfSmzKMWPLZZ9nBGqxORcY1bsCBGre7a2tlf2+bb+t4zEYAm4SML9c8DPgpo6xVrsFypVOVarfp117vfOXKLuNGM/7ArWrltHmHftlQl82BJJRoGwpv9LT/NqZkZmM5SdFzQRqSdFmirRRgEDNRkwvD0WY4OXuUltxAgRqxQnxfa8LEKh5vcPUF44AgVo4SuzjZQECNS93N7c2AjXv95gK7RUgULPX07OjEah5trUUFoYAgVoYSOziaQECNU+3l+LCFCBQCxOK3TwrQKDm2daGCiNQ836PqdBeAQI1ez09OxqBmmdbS2FhCBCohYHELp4WIFDzdHspLkwBArUwodjNswIEap5tLYGa91tLhTESIFCLEazXhiVQ81pHqackAgRqJdFiXy8KEKh5savUVFIBArWSirG/1wQI1LzW0YL1cIWa93tMhfYKEKjZ6+nZ0QjUPNtaCgtDgEAtDCR28bQAgZqn20txYQoQqIUJxW6eFSBQ82xrQ4URqHm/x1RorwCBmr2enh2NQM2zraWwMAQI1MJAYhdPCxCoebq9FBemAIFamFDs5lkBAjXPtpZAzfutpcIYCRCoxQjWa8MSqHmto9RTEgECtZJosa8XBQjUvNhVaiqpAIFaScXY32sCBGpe62jBerhCzfs9pkJ7BQjU7PX07GgEap5tLYWFIUCgFgYSu3hagEDN0+2luDAFCNTChGI3zwoQqHm2taHCCNS832MqtFeAQM1eT8+ORqDm2dZSWBgCBGphILGLpwUI1DzdXooLU4BALUwodvOsAIGaZ1tLoOb91lJhjAQI1GIE67VhCdS81lHqKYkAgVpJtNjXiwIEal7sKjWVVIBAraRi7O81AQI1r3W0YD1coeb9HlOhvQIEavZ6enY0AjXPtpbCwhAgUAsDiV08LUCg5un2UlyYAgRqYUKxm2cFCNQ829pQYQRq3u8xFdorQKBmr6cnR8vMDmjb7oMxrs2nYDAY4zkYHoHIBAjUInPjKO8IEKh5p5dUErkAgVrkdhzpDQECNW/0sagqCNS832MqtFeAQM1eT0+ONm9xpjZuil1pFStIVzY7oFLl0mI3CSMjEIUAgVoUeBzqCQECNU+0kSKiFCBQixKQw10vQKDm+hYWWwCBWrFE7IDAIQIEapwQxQqMmpypX9b5it0v0h2qVpG6dNiv0uUJ1CI15LjYChCoxdaX0Z0vQKDm/B6xwtgLEKjF3pgZnC1AoObs/tixOgI1OxQZI5kECNSSqdsR1kqgFiEch3lGgEDNM62kkAgFCNQihOMwTwkQqHmqnRQTgQCBWgRoLjuEQM1lDWO5CRcgUEt4C5y/AAI15/eIFcZWgEAttr6M7nwBAjXn94gVxl6AQC32xszgbAECNWf3x47VEajZocgYySRAoJZM3Y6wVgK1COE4zDMCBGqeaSWFRChAoBYhHId5SoBAzVPtpJgIBAjUIkBz2SEEai5rGMtNuACBWsJb4PwFEKg5v0esMLYCBGqx9WV05wsQqDm/R6ww9gIEarE3ZgZnCxCoObs/dqyOQM0ORcZIJgECtWTqdoS1EqhFCMdhnhEgUPNMKykkQgECtQjhOMxTAgRqnmonxUQgQKAWAZrLDiFQc1nDWG7CBQjUEt4C5y+AQM35PWKFsRUgUIutL6M7X4BAzfk9YoWxFyBQi70xMzhbgEDN2f2xY3UEanYoMkYyCRCoJVO3I6yVQC1COA7zjACBmmdaSSERChCoRQjHYZ4SIFDzVDspJgIBArUI0Fx2CIGayxrGchMuQKCW8BY4fwEEas7vESuMrQCBWmx9Gd35AgRqzu8RK4y9AIFa7I2ZwdkCBGrO7o8dqyNQs0ORMZJJgEAtmbodYa0EahHCcZhnBAjUPNNKColQgEAtQjgO85QAgZqn2kkxEQgQqEWA5rJDCNRc1jCWm3ABArWEt8D5CyhJoNa6pV8N6qeoYkUpJ0fKyJDe/zhHL/07oGCw8FqrVpG6dNiv0uXTnI/BCpNSgEAtKdtO0fkECNQ4HRCQCNQ4C5JdgEDN+2cAgZr3e0yF9goQqNnr6cnRwg3UhvdP1VF1fNq0Wdq2I6hTT/IpEJD8fmn3Hum+oVnKzilIRKDmydPGU0URqHmqnRQTgQCBWgRoHOI5AQI1z7WUgkooQKBWQjAX7k6g5sKmseSEChCoJZTfHZOHE6jVrePTiP6pmv5Itj7/OvdStCF9UrVzt/T62znq2SVVX64Natoj2QWKJlBzx3mQzKskUEvm7lO7ESBQ4zxAgCvUOAcQIFDz/jlAoOb9HlOhvQIEavZ6enK0cAK1hg1S1LmdX116ZyknkMvQ485UmbBs6Nhs9e2eqqOP8ume/lkEap48S7xdFIGat/tLdcULEKgVb8Qe3hfgCjXv95gKixYgUPP+GUKg5v0eU6G9AgRq9np6crRwArXKlaSJI9L07ocBLVqeo3JlpdGD0/Tfn4Oa/FC2LmyUottu9KtTTwI1T54kHi+KQM3jDaa8YgUI1IolYockECBQS4ImU2KRAgRq3j9BCNS832MqtFeAQM1eT0+OFk6gZgrv0NavC85PCRmYlxIMn5Ct3zcE1fi8FDVpnKIHpnLLpydPEo8XRaDm8QZTXrECBGrFErFDEggQqCVBkymRQC3JzwECtSQ/ASi/xAIEaiUmS74Dwg3UjEz903z629kp2rtXemN1jrZuL96LZ6gVb8QeiRUgUEusP7MnXoBALfE9YAWJFyBQS3wPWEFiBbhCLbH+8ZidQC0eyszhJQECNS91M0a1lCRQi2QJBGqRqHFMPAUI1OKpzVxOFCBQc2JXWFO8BQjU4i3OfE4TIFBzWkfsXw+Bmv2mjOhtAQI1b/fXluqKCtTMrZztbvLr941Bff5VUO98EN5VafkXRqBmS5sYJIYCBGoxxGVoVwgQqLmiTSwyxgIEajEGZnjHCxCoOb5FUS+QQC1qQgZIMgECtSRreCTlFhWo+XzSpRel6LJ/+lWpopSxV+o5sOCLB4qal0Atkq5wTDwFCNTiqc1cThQgUHNiV1hTvAUI1OItznxOEyBQc1pH7F8PgZr9pozobQECNW/315bqwr3l88Tjc5+ftuTpnBLNS6BWIi52ToAAgVoC0JnSUQIEao5qB4tJkACBWoLgmdYxAgRqjmlFzBZCoBYzWgb2qACBmkcba8rat/+g0tNTler3R1VluIFapJMQqEUqx3HxEiBQi5c08zhVgEDNqZ1hXfEUIFCLpzZzOVGAQM2JXbF3TQRq9noymvcFCNRc0uOnV7ytIePn68aWTXV/r9uKXfX+A5k6t0VnTR/dQ00vaFDs/kXtEG6gdmc7v9ZvCOrFlQFruOP/4lPpUn+OvH+/9POvwQJTHSlQCwaD2rU7Q3v3HVD1apVVKj3tkGMPHMjUrt17VKN6VaWk+KKqkYMRKEqAQI3zI9kFCNSS/QygfiNAoMZ5kOwCBGrePwMI1LzfYyq0V4BAzV7PmI12a/cx2rZjl7Zs26V3npteIFw6fOJAIKhv/7tO9erWVMXyZaNaVziBWpVK0oQRaVq4LEdvvZsbqE0dk6by5f6c+sBBqdt9BZ+vVlig9s33P+v+sQ9r56491gBlSpfW3R1bq3nTxtafh459WO99/IX135UrVVCzixup022toqqTgxE4kgCBGudGsgsQqCX7GUD9BGqcAwhIBGrePwsI1LzfYyq0V4BAzV7PmIz2+8at+tdNfbRs9jDdcOcwTR91j5r+4xxrrgMHMzVp1lK98sZHOnAwS2edfoIG3XOLjjumjm7pNlqDetyiU088VgufWqlHl76sTVt2qGrlCmpzzaW6q11L+Xw+vbDyPb31weeqVKGcnl/5nk756zHqdnsrnd/gVGuOcAK1c870qWvHVHW5N0vZ2bkMYwanaceuoJ5Ylq3L/+VXgzNTwg7U1n7/s35Zt16NzztL5cqV1aKnVmjR8hV68clpVpj42JIXdWGjBqpbu4Y+++JbDRn7sKaP7adTTvxLTHrAoMktQKCW3P2neolAjbMAAa5Q4xxAgEDN++cAgZr3e0yF9goQqNnrGZPR5i9ZoVff+FhLZw9Vv9GzlZWVrcnD7rbmmrv4JT227BXNGNNTfn+K3nh3jf5+zmlqePYpOv3i9np82kD97cyTtPKt/yg11a+j69bQ/9ZvVvfB0/TQA73UpNFZWrD0FU14eIk63HSZ/nFefb38+of6+rtf9NSc4WEHavVP86nHnanq2idLmX9chDZ5VJq++29Asxfk6MZr/LqwcfiB2uGQL65crceWvKDFjzygtNSCz4Rr03mArmp+kdped1lMesCgyS1AoJbc/ad6AjXOAQSMALd8ch4kuwCBmvfPAAI17/eYCu0VIFCz1zMmo11+Sz/dfO2/dPO1/9Rb73+urgOm6L0XZlpXlM2Y/4xe+Pd7mjbqHp10fD3rirO8LX+gZr724y/rtfb7ddqyfaceXfKy7rj5SrVr3dwK1N75+EvNndjXOvTnXzfoytsG6L3nZ6pSxXJhXaFWKl2aMT5N/1sf1KOLc3TGqT5dd5XfeuPna28FIg7Uvlz7X7329of66NOv1OnWa9X0woYFjH/7fbM6dB+qkQO66u/n1o9JDxg0uQUI1JK7/1RPoMY5gACBGucAAtzymQznAIFaMnSZGu0UIFCzUzMGY33zwzpd32mo9WIB82D+zMwsPfvKOxrVr6NaXXahNmzerkEPzNGHa75R2TKl1eaapupyW0uVLVPqkCvUxs5YbN32acY59ujaWrHqA916XTPrqrTDA7XNW3fqkut7atXyyapdo2pYgZopvXnTFF1/tV95md627VL/EVkKBhVxoLbq7Y/0+jv/0ff//UU3X3+Zrrn8kkOU9+0/oF6DJqps2TKaOLyXdZUeGwJ2CxCo2S3KeG4T4JZPt3WM9cZCgCvUYqHKmG4S4Ao1N3UrsrUSqEXmxlHJK0Cg5vDeT569TG++95laXHJeaKXvf7LWCo4WTO0f+tqGTdv00WffatTUhRrQva2uvfyiUKD2l6Nr66JW92j+lH6h56J16TdJ5zc4zdZAzSzGvITg9FNStG1HUD/+HLTCNLNVryrVqunT19+G/5bP/K0xV6r1HjJJj80cYT03zWzmLZ/DJ8zWlq07NHlkb1WsWN7h3WR5bhUgUHNr51i3XQIEanZJMo6bBQjU3Nw91m6HAIGaHYrOHoNAzdn9YXXOEyBQc15PQivKzsnRJdf1VK/Ora2ALG/7+LNv1b7nWL22dJJef/dT66UDZ552gvbuO6BWtw9W37tu0mVNzw8FaiceX0+NruxqXdXWrElD/efz79RnxMPq2q6l7YFaJJyFveXz8HG279ilG+/or6mj++j0U07Qnr37NHzcbB04cFBjBncjTIsEnmPCFiBQC5uKHT0qQKDm0cZSVokECNRKxMXOHhQgUPNgUw8riUDN+z2mQnsFCNTs9bR1tI/WfKsOvcbq3edmqHKlP6++yskJ6OLreqhj2ysUCAQ0adYya15zy2ezJudqeN8OSvX7rUBt4fSBOqf+SZr35AqZq93MdsKxdXUwM8t602f7G1towbJX9N7HX+mRCX2s72/ZtlMXX9dTry+folo1qoR9y+f4YWn69oeA5i/Ksca55gq/Klf6k2T7Dun5l3O/l38rLFB79fX3VKF8OZ1x2l+V4vNp3qLntOqtj7T4kdHyp/jVvf84mcBxSJ9OKle2jDVcSkqKalavYmsPGAwBI0CgxnmQ7AIEasl+BlC/ESBQ4zxIdgECNe+fAQRq3u8xFdorQKBmr2dCRjPB0rbtu1WtakUrSDvSZq5g252xT3VqVi3ROkdNztQv6/582UFhB9er69Owfqma/FC21n6Xe1vnpJFpqlhBysmRzLIOZkrd7vvjFaD5BiksUDNv9Xxw9uLQXub5cfd1a6cGZ55iBX5tOw8osIzKlSpo+fzxJaqNnREIR4BALRwl9vGyAIGal7tLbeEKEKiFK8V+XhUgUPNqZ/+si0DN+z2mQnsFCNTs9fTkaOEEauf/LUWdbvOrU8/clxCYbczgNG3YFNT0OdkRvZTABIU7du5RUEFVr1JZKSlFh3qexKcoRwgQqDmiDSwigQIEagnEZ2rHCBCoOaYVLCRBAgRqCYKP47QEanHEZipPCBCoeaKNsS0inEDtr8f51L9nqgaOzNLmrbnrmTE+TWu+CGjeEzmPcsj+AAAgAElEQVQRBWqxrYrREQhfgEAtfCv29KYAgZo3+0pVJRMgUCuZF3t7T4BAzXs9PbwiAjXv95gK7RUgULPX05OjhROo+XzSzPFpyglIb78X0AnH+WRCtgdnZ+vLtUECNU+eGclTFIFa8vSaSgsXIFDjzECAZ6hxDiBAoOb9c4BAzfs9pkJ7BQjU7PX05GjhBGqmcBOgde2YmvvctID00Se5V6eZ7fqr/bqwUYp6DAjvGWqehKQo1woQqLm2dSzcJgECNZsgGcbVAlyh5ur2sXgbBAjUbEB0+BAEag5vEMtznACBmuNa4rwFhRuo5a3cXK2W9xy1cKop7KUE4RzHPgjES4BALV7SzONUAQI1p3aGdcVTgEAtntrM5UQBAjUndsXeNRGo2evJaN4XIFDzfo+jrjCcQK1UutSujV9rvgjq4zWBAnM2bJCi9RuD+n3DH28syLcHgVrULWKAGAsQqMUYmOEdL0Cg5vgWscA4CBCoxQGZKRwtQKDm6PbYsjgCNVsYGSSJBAjUkqjZkZYaTqBWpZI0YUSadWXa5Iey9c33hwZn44alSUGp33Bu+Yy0DxyXOAECtcTZM7MzBAjUnNEHVpFYAQK1xPoze+IFCNQS34NYr4BALdbCjO81AQI1r3U0BvWUJFDbsEmqWUMaNTFb/1v/Z6h2ZbMUXXWZX3f2IlCLQYsYMsYCBGoxBmZ4xwsQqDm+RSwwDgIEanFAZgpHCxCoObo9tiyOQM0WRgZJIgECtSRqdqSlliRQ6z88S326palKZWnSzGx9/2NuqPavi1N0wzV+depJoBZpHzgucQIEaomzZ2ZnCBCoOaMPrCKxAgRqifVn9sQLEKglvgexXgGBWqyFGd9rAgRqXutoDOopSaB237AsZWRID9yfZr3t890PA9btnze28mvvPmnIGAK1GLSIIWMsQKAWY2CGd7wAgZrjW8QC4yBAoBYHZKZwtACBmqPbY8viCNRsYWSQJBIgUEuiZkdaakkDte07pPQ0qW/3VB13rM+aNjNTenRxTqEvLOClBJF2huPiJUCgFi9p5nGqAIGaUzvDuuIpQKAWT23mcqIAgZoTu2LvmgjU7PVkNO8LEKh5v8dRVxhOoFa2jNSne6omTs/Wvv1/Tlm9qlS7lk9ffVPw7Z55exGoRd0iBoixAIFajIEZ3vECBGqObxELjIMAgVockJnC0QIEao5ujy2LI1CzhZFBkkiAQC2Jmh1pqeEEapGObY4jUItGj2PjIUCgFg9l5nCyAIGak7vD2uIlQKAWL2nmcaoAgZpTO2PfugjU7LNkpOQQIFBLjj5HVSWBWlR8HOwBAQI1DzSREqISIFCLio+DPSJAoOaRRlJGxAIEahHTueZAAjXXtIqFOkSAQM0hjXDyMgjUnNwd1hYPAQK1eCgzh5MFCNSc3B3WFi8BArV4STOPUwUI1JzaGfvWRaBmnyUjJYcAgVpy9DmqKgnUouLjYA8IEKh5oImUEJUAgVpUfBzsEQECNY80kjIiFiBQi5jONQcSqLmmVSzUIQIEag5phJOXQaDm5O6wtngIEKjFQ5k5nCxAoObk7rC2eAkQqMVLmnmcKkCg5tTO2LcuAjX7LBkpOQQI1JKjz1FVSaAWFR8He0CAQM0DTaSEqAQI1KLi42CPCBCoeaSRlBGxAIFaxHSuOZBAzTWtYqEOESBQc0gjnLwMAjUnd4e1xUOAQC0eyszhZAECNSd3h7XFS4BALV7SzONUAQI1p3bGvnURqNlnyUjJIUCglhx9jqpKArWo+DjYAwIEah5oIiVEJUCgFhUfB3tEgEDNI42kjIgFCNQipnPNgQRqrmkVC3WIAIGaQxrh5GUQqDm5O6wtHgIEavFQZg4nCxCoObk7rC1eAgRq8ZJmHqcKEKg5tTP2rYtAzT5LRkoOAQK15OhzVFUSqEXFx8EeECBQ80ATKSEqAQK1qPg42CMCBGoeaSRlRCxAoBYxnWsOJFBzTatYqEMECNQc0ggnL2Pe4kxt3BS7FVaoIF3d/IDSy6bFbhJGRiAKAQK1KPA41BMCBGqeaCNFRClAoBYlIIe7XoBAzfUtLLYAArViidgBgUMECNQ4IYoVyMwOaNvug8XuF80OgaDki2YAjkUghgIEajHEZWhXCBCouaJNLDLGAgRqMQZmeMcLEKg5vkVRL5BALWpCBkgyAQK1JGt4pOX+vm1/pIdyHAKuFyBQc30LKSBKAQK1KAE53BMCBGqeaCNFRCFAoBYFnksOJVBzSaNYpmMECNQc0wpnL4RAzdn9YXWxFSBQi60voztfgEDN+T1ihbEXIFCLvTEzOFuAQM3Z/bFjdQRqdigyRjIJEKglU7ejqJVALQo8DnW9AIGa61tIAVEKEKhFCcjhnhAgUPNEGykiCgECtSjwXHIogZpLGsUyHSNAoOaYVjh7IQRqzu4Pq4utAIFabH0Z3fkCBGrO7xErjL0AgVrsjZnB2QIEas7ujx2rI1CzQ5ExkkmAQC2Zuh1FrQRqUeBxqOsFCNRc30IKiFKAQC1KQA73hACBmifaSBFRCBCoRYHnkkMJ1FzSKJbpGAECNce0wtkLIVBzdn9YXWwFCNRi68vozhcgUHN+j1hh7AUI1GJvzAzOFiBQc3Z/7FgdgZodioyRTAIEasnUbWpFAAEEEEAAAQQQQAABBBBAAAEEEIhagEAtakIGQAABBBBAAAEEEEAAAQQQQAABBBBIJgECtWTqNrUigAACCCCAAAIIIIAAAggggAACCEQtQKAWNaG3B9iTsU/ZOTmqUqmCtwulOgSKENi6fZfKlS2jMqXTQ3v9un6T1m/Yqkbnno4dAq4UCASCCgaD8vtTCqzffG/zth2qXrWSUv3+At8/0mfDa6s/0VmnnaAa1Sq70oRFJ5+A+R2nsHO8OIkj/Yzw2VCcHN93koA5/7ds26WqlSuoVHpaiT8LMjOztGNXhmpWryyfzxc6ns8CJ3WZtSCAQCwFCNRiqevisfftP6B+o2br9XfXWFWcedoJmj7qHusvV2wIeEVg1epPdc+QaQXK+XTlHOsXS/MXoy79Jmvdb5usfa69/CLd37ud0lL9Wvb8G3rmlXf05ENDvMJBHUkkYIK0YZMWWBUP79PhkMrfev9z9RnxsMzngNmG3tteN1x1sfXfxX02NLysi6aO6KYLGp6RRJqU6laBX9dv1mU336d/L5mourWrh8oo7rOhqJ8RPhvcejYk37rnLHpRU+c8FSq8+cUNNbR3e1WqWM76WlHnufkMefjx5zXz0WesfU0gN2NMT+sfVMzGZ0HynU9UjECyChCoJWvni6l77uKXtPyFN7Vw+iDrqpy7+k/RccfU0cj7bkcMAc8ImH9BHTBmjp6aM/yQmo45qqb1L62d+05U+XJlNLp/J23cvE033Dlc9/e6TVc1a0yg5pmzIPkKefXNjzRq6kJt37lH11/Z5JBAbf+BTF3U6h51u72Vbr72n3rzvc/UY8h0vfrkBNWrU0PFfTbwl6jkO5/cWnGbriP1xdofreUfHqgV9dlw4GBWkT8jBGpuPSOSb93LX3xTR9etqbNO+6v+9/tmdew9Th3bXKH2N7ZQcZ8Fa776Qbd0G62F0weq/inHa9q8p/XSqvf12tLJSknxEagl3+lExQgkrQCBWtK2vujCr+80VOZfqjrdfKW1o/kLWO9hD+mrNx495JJu+BBws4D5S9PwSQu0+tnpBcrYtWevGl91t56YMUgNzjjR+v7oBxdq4+btmj66R4FAbelzr+vlNz7S+MFdrFsf2BBwqsC+/Qe1O2OvpjyyXKVLpR8SqJkrEroOmKI1K+co/Y/bfy6/pZ8Vrt187b9U3GdD/kBt247dGjDmETVueIba39DCqRysK0kFNm/daf1DiQnWCgvUjvTZUNzPyOGBGp8NSXqCubDsIePna/2GLZo/pZ91dVpRnwWTZi3TN/9dp7kT+1qVmp+nS67vaf0D5aknHntIoMZngQtPBpaMAAJhCxCohU2VXDuavxSN6tfRCtXMtvb7X9S68zC998JMVaqQeyk4GwJuFzCBmrn6pmXzC1SqVLrOPetk65w3z9P58Zf1urr9IL35f1NDz4Na+NRKPffqu9YvjPn/0vTMy6s1eNy8Q8I3t9uwfu8LjJjyuHJycg4J1Ja98KYWLH1ZK54YFwLoPuhB/eXoOrq3yw3WX5KK+mzIC9TOOOU4te/xgHVl8/ghXSJ6RpX3O0CFiRbYtGWHmrbuVWigdqTPhuJ+RvhsSHRXmT8SgazsHDVv00dXXNrI+n99cee5eSxAlUrlNajHraHpTr+4vR56oJeaNDorFKjxWRBJNzgGAQTcJECg5qZuxWmt5rkIZ1zSIfShaKbNCxdeWzpJdWpVi9NKmAaB2Ap8+e3P1tWXJiT+fdM2KyRr2+pS6xfEvNsZ8ofI5hfMWY8/p9eXTwkFaubKm97DZuqxBwdYgRwbAm4RKCxQM7d0vvLGR4fcBm3+4lS+bBkNvbddsZ8NJlAb3f8OPb78VVWtUkGTht5tPXOQDQEnChwpUCvqs6Gon5Fhfdrz2eDERrOmYgWGTnxUK1Z9qJcWjrWusi/uPDePxDj5hGOs8C1vM///Nz8DV1z6dytQ47OgWHZ2QAABDwgQqHmgibEoIe+DsFmTc63huUItFsqM6TSBp1e8LXPLw+er5mnd/zZaV6i99fSDoZdxHH6F2vDJj1klXNPiH9YvjmwIuEkg0ivUzLl+pM8G89lhNvPygpcXjdMxR9VyEwlrTTKBIwVqhzPk/2x4esXqIq/iNP8ww2dDkp1ILi/3oQXPauaCZ7Vk1lDVP+U4q5pwrlAzLyIYeM8toeoPv0KNzwKXnxgsHwEEwhIgUAuLKfl2Ms/JaXHJebqj7RVW8TxDLfnOgWSsePWHX6pLv0n65NVHdDAzq8Az1EZOeVybt+4IPUNtwsNL1bfrTdZz2MzLCm5s2TQZ2ajZpQKFBWp5z8357N9zlZaWalXWvE1f3da6WegZakV9NphAzby0Y8OmbVr320YtnjlElSuVd6kQy/a6QLiBWv7Phg8//cZ6ttSRfkZMoMZng9fPHG/UFwgENWnWUis8e+zB/jrtpL+ECivus8A8Q+27H3/VIxP6WMcU9gw1Pgu8cZ5QBQIIFC1AoMYZUqiAeZX2Uy++Zb3ls2yZUurSbzJv+eRc8ZzA4mdW6eQTjrZ+idy1J0N9R8yybk8zD+Q12x19Jqhi+XLW1WdFveVz5Vv/Ua+hMzR52N2h5w56DouCPCOQkxNQIBDQqAcXKjs7R8PubS+/32+9mc28sKDhZXeq391t1LaQt3wW99mQ9ww18yKPjveOt8zmTbrP+hxhQ8BJAuaZUeb/6y3a3mc9M7Bu7eqh25OL+mwo7mck/zPU+GxwUsdZy+EC5tmv5hmws8bdq+OPrRP6dq0aVZSZmV3kZ8Gfb/kcpPqnHq8H5z6lFas+KPCWTz4LOO8QQMDrAgRqXu9whPXt3XdA5rk5b3/wuTXCGScfZ12Vw9sLIwTlMEcKTJ69TPOeXBFa25mnnaAJQ7qoXp0a1td+/nWDFSb/tmGL9Wdza6cJH8yVO+ZfdM0vok8+NMT63pPPrtKoqQt5lpojO82i8gvkvyUt7+sj77td115+kfXH199dI/MigrxtcM9b1eaaS60/FvfZYAK1aSO7q9G5p2vnrgy1vXukjjmqpmaO6SW/P4VGIOAYAXOumluT8zZz+1reG5+L+2wo6meEzwbHtJiFFCNgrj7O+/0m/64mYD62Xq0iPwvM85ZnPPqMZj3+vHVo2TKl9ciEe0NvReezgNMPAQSSRYBALVk6HWGdu/bsVVZWdugZUhEOw2EIOFbgwMFMbdm2UxXKlT3irWnmtqDy5cqoXNnSjq2DhSFgp4C5im3jlu2qWa1y6NbP/OPz2WCnNmM5UaC4z4bifkacWBNrQqCkAsWd5+bnZPuO3apds5p1lTMbAgggkGwCBGrJ1nHqRQABBBBAAAEEEEAAAQQQQAABBBCISoBALSo+DkYAAQQQQAABBBBAAAEEEEAAAQQQSDYBArVk6zj1IoAAAggggAACCCCAAAIIIIAAAghEJUCgFhUfByOAAAIIIIAAAggggAACCCCAAAIIJJsAgVqydZx6EUAAAQQQQAABBBBAAAEEEEAAAQSiEiBQi4qPgxFAAAEEEEAAAQQQQAABBBBAAAEEkk2AQC3ZOk69CCCAAAIIIIAAAggggAACCCCAAAJRCRCoRcXHwQgggAACCCCAAAIIIIAAAggggAACySZAoJZsHadeBBBAAAEEEEAAAQQQQAABBBBAAIGoBAjUouLjYAQQQAABBBBAAAEEEEAAAQQQQACBZBMgUEu2jlMvAggggAACCCCAAAIIIIAAAggggEBUAgRqUfFxMAIIIIAAAggggAACCCCAAAIIIIBAsgkQqCVbx6kXAQQQQAABBBBAAAEEEEAAAQQQQCAqAQK1qPg4GAEEEEAAAQQQQAABBBBAAAEEEEAg2QQI1JKt49SLAAIIIIAAAggggAACCCCAAAIIIBCVAIFaVHwcjAACCCCAgDsEDhzM1Bdrf9JPv/6ug5lZOqp2dZ3f4FRVKF/WHQUcYZWfr/1Rz77yjj78dK1aXHKe7ul4nevq2bvvgO68b5K6d7zW6gkbAggggAACCCCAgPMFCNSc3yNWiAACCCCAQFQCn375gwaMeUS/bdiiWjWqKCsrW9t37rHGHNWvo1pddmFU45fk4Icee05PPvOaVj87vSSHFbrvvv0H1PCyLmp07um68PwzVaVSeV3d7IISjfvhmm90e69xennReB1zVM0SHWvXzs+9+q4GPjBHH62YpXJlS9s1rC3jmPD1nGadNGZAJ7VsXjJbWxbAIAgggAACCCCAgEMFCNQc2hiWhQACCCCAgB0Cm7fu1CXX99SpJx6rCUO66Lhj6ljDbtqyQ9Pm/Z9qVKusnp2ut2OqsMaY+egzWvLc67YEaq+t/kQ9hkzXu8/NUOVK5cOa//CdPvhkrTreO14vLxqnY46qFdEY0R50S7fR+utfjtKwPu2jHcr2482VjX9r3jnuwavthTAgAggggAACCCBgswCBms2gDIcAAggggICTBIZPfkzLnn/jiIHRvv0HVbZMKWvJL6x8T/OXrND3P/2mk46vp45trtCV/2pkfW/Hrj3qPmia7u1ygxqccaL1teycHLXvMVYd216uSxo3kLn9csJDS9S21T+17IU39PV3v+iSxmer3Q0tdPrJf9HqD7+wrsQyV8fljXF1s8a64epLCiXbun2Xxs98Uu9/8rUOHMxS0380UN+7blL1qpX0wadrrbFMMJg31sj7bg8FhvkHNPs8OPcp65g9Gft18glH68arL9F5DU5Vh15jte63TVbgWLpUeijYMlfxPfz4c3rptQ+sK/vMrZj3drnRqsNsebWaq/ueeXm11nz1g844+TgN7nmr6p96vLXPkea9qlnj0PJ+/nWDrrxtgJ6YMShUR+9hD+nr73625q1auYIuOK++enVqbV1daLalz72uD9d8q7vbt9SiZ1bpp3W/656O1+qHn34r9Ovn1D9Jqz/8UrMXPm+ts16dGmrZ4h/qdPOVSkv1KzMzS7MWPq9X3vhIW7btUp2aVXVx47PV+84bdPfAqXrzvc+sY0z4arY5E/tq9569hZrmr81JPwesBQEEEEAAAQQQsFuAQM1uUcZDAAEEEEDAQQJXtxuoo+rU0MNjexW5qpdWfaD7Rs7SBQ3PsJ5FZsKVdz/+ShOG3KXLLz3fCoeatu6lhx7opSaNzgoFamdd2lHD+3TQ9Vc2sQKzLv0mW9+7rXVzHV23ph5b9ooqVyyvpbOH6sd1v2vcjMXWuCZ4Mtspfz0mFCTlX2BWdo5ath9oBTwdbrrM+tajS15WjWqV9NyCMdqwaavGzXzSCnvyxmrWpKGqValYoE5zBdjvm7aq++3XqlR6uj7+/Ftt3Lxd4wffaV2lt/iZVerarqWqVqloBVjNLz5PwyYu0PIX37TqMmHb48tftYK3VxaPt+rKq7VsmdJqc01T+Xw+axyzvfHUFJUvV0ZHmjd/L6bOeUor3/pYLy0ca41htnuGTNPZp/9V9erU1I6duzXj0Wd08l+P0dyJfa3vT569TPOeXGH9twnLTNBmAkKzpsK+bq4yM30xYdc/L/ybvlj7o7WfCUdvv+lyzZj/jBUemrCyXt0a+u6/v2rBslf18cuzLANjccWlf1eD+rlB6vVXXqwOPccWalrceeagHw2WggACCCCAAAIIRCVAoBYVHwcjgAACCCDgXAFzBZkJvEy41e/uNkUu9PJb+smEQ0/NGR7ar9Xtg60XGKx4YlyJArX/mzvCCsrMtmr1p1ZA9MZTU1WzemWFe8vnq29+rN7DZh4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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = px.bar(\n", + " df.melt(id_vars=[\"agency\", \"driver_race\"], value_vars=[\"Stops without arrests\", \"Stops with arrests\"], var_name=\"count_type\", value_name=\"count\"),\n", + " x=\"count\",\n", + " y=\"driver_race\",\n", + " color=\"count_type\",\n", + " # color_discrete_map=color_map,\n", + " facet_col=\"agency\",\n", + " facet_col_wrap=1,\n", + " title=\"Count of stops and arrests for a given race / ethnic group\",\n", + " labels={\n", + " \"search_arrest_rate\": \"Arrest rate by searches\",\n", + " \"driver_race\": \"Driver race\",\n", + " \"count\": \"Count of stops/arrests\",\n", + " \"count_type\": \"Count type\",\n", + " },\n", + " text='count',\n", + " text_auto=',',\n", + " orientation='h',\n", + " height=600,\n", + ")\n", + "fig" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "751ecb36-fa50-4d91-b722-99c1469de641", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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agencydriver_raceStopsStops without arrestsStops with arrests
0Durham Police DepartmentAsian6584655232
1Durham Police DepartmentBlack2194202135845836
2Durham Police DepartmentHispanic45796443011495
3Durham Police DepartmentNative American1654164212
4Durham Police DepartmentOther2001198318
5Durham Police DepartmentWhite1019771009751002
\n", + "
" + ], + "text/plain": [ + " agency driver_race Stops Stops without arrests \\\n", + "0 Durham Police Department Asian 6584 6552 \n", + "1 Durham Police Department Black 219420 213584 \n", + "2 Durham Police Department Hispanic 45796 44301 \n", + "3 Durham Police Department Native American 1654 1642 \n", + "4 Durham Police Department Other 2001 1983 \n", + "5 Durham Police Department White 101977 100975 \n", + "\n", + " Stops with arrests \n", + "0 32 \n", + "1 5836 \n", + "2 1495 \n", + "3 12 \n", + "4 18 \n", + "5 1002 " + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "markdown", + "id": "c75eeb17-0187-4b88-b482-d470adcd80f4", + "metadata": {}, + "source": [ + "# 4a. Percentage of stops that led to an arrest for a given stop purpose group" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "309a9dc7-1b7a-4a29-9098-368179235904", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stops AS ({stops_summary_sql})\n", + " SELECT\n", + " agency\n", + " , stop_purpose_group\n", + " , count(*) AS stop_count\n", + " , count(*) FILTER (WHERE driver_searched = true) AS search_count\n", + " , count(*) FILTER (WHERE driver_arrest = true) AS arrest_count\n", + " FROM stops\n", + " GROUP BY 1, 2\n", + " \"\"\",\n", + " pg_engine,\n", + ")\n", + "df[\"search_arrest_rate\"] = df.arrest_count / df.search_count\n", + "df[\"stop_arrest_rate\"] = df.arrest_count / df.stop_count" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "9e89b4b9-2d62-41af-bf79-4cbe7b791f91", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "Stop Purpose Group=%{y}
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agencystop_purpose_groupstop_countsearch_countarrest_countsearch_arrest_ratestop_arrest_rate
0Durham Police DepartmentInvestigatory29507379415880.4185560.053818
1Durham Police DepartmentRegulatory and Equipment1575471320138710.2932350.024570
2Durham Police DepartmentSafety Violation190378681429360.4308780.015422
\n", + "
" + ], + "text/plain": [ + " agency stop_purpose_group stop_count \\\n", + "0 Durham Police Department Investigatory 29507 \n", + "1 Durham Police Department Regulatory and Equipment 157547 \n", + "2 Durham Police Department Safety Violation 190378 \n", + "\n", + " search_count arrest_count search_arrest_rate stop_arrest_rate \n", + "0 3794 1588 0.418556 0.053818 \n", + "1 13201 3871 0.293235 0.024570 \n", + "2 6814 2936 0.430878 0.015422 " + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "markdown", + "id": "0bc34780-1a41-419c-a184-274505f9b342", + "metadata": {}, + "source": [ + "# 4b. Percentage of stops that led to arrest for a given stop purpose" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "id": "6c6f51c4-c132-4e10-941e-fc6418aea8a1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 2.59 ms, sys: 904 µs, total: 3.49 ms\n", + "Wall time: 1.47 s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stops AS ({stops_summary_sql})\n", + " SELECT\n", + " agency\n", + " , stop_purpose\n", + " , count(*) AS stop_count\n", + " , count(*) FILTER (WHERE driver_searched = true) AS search_count\n", + " , count(*) FILTER (WHERE driver_arrest = true) AS arrest_count\n", + " FROM stops\n", + " GROUP BY 1, 2\n", + " \"\"\",\n", + " pg_engine,\n", + ")\n", + "df[\"search_arrest_rate\"] = df.arrest_count / df.search_count\n", + "df[\"stop_arrest_rate\"] = df.arrest_count / df.stop_count" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "id": "f2d8554a-09c6-4f2f-8c9d-fae54552b167", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "Stop Purpose=%{y}
agency=Durham Police Department
Arrest rate by stops=%{x}
search_arrest_rate=%{text}", + "legendgroup": "Checkpoint", + "marker": { + "color": "rgb(102, 197, 204)", + "pattern": { + "shape": "" + } + }, + "name": "Checkpoint", + "offsetgroup": "Checkpoint", + "orientation": "h", + "showlegend": true, + "text": [ + 0.5214899713467048 + ], + "textposition": "auto", + "texttemplate": "%{x:,.1%}", + "type": "bar", + "x": [ + 0.034482758620689655 + ], + "xaxis": "x", + "y": [ + "Checkpoint" + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "Stop Purpose=%{y}
agency=Durham Police Department
Arrest rate by stops=%{x}
search_arrest_rate=%{text}", + "legendgroup": "Driving While Impaired", + "marker": { + "color": "rgb(246, 207, 113)", + "pattern": { + "shape": "" + } + }, + "name": "Driving While Impaired", + "offsetgroup": "Driving While Impaired", + "orientation": "h", + "showlegend": true, + "text": [ + 1.3121951219512196 + ], + "textposition": "auto", + "texttemplate": "%{x:,.1%}", + "type": "bar", + "x": [ + 0.63046875 + ], + "xaxis": "x", + "y": [ + "Driving While Impaired" + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "Stop Purpose=%{y}
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agencystop_purposestop_countsearch_countarrest_countsearch_arrest_ratestop_arrest_rate
0Durham Police DepartmentCheckpoint52783491820.5214900.034483
1Durham Police DepartmentDriving While Impaired12806158071.3121950.630469
2Durham Police DepartmentInvestigation24229344514060.4081280.058030
3Durham Police DepartmentOther Motor Vehicle Violation1451612254460.3640820.030725
4Durham Police DepartmentSafe Movement Violation2971122417120.3177150.023964
5Durham Police DepartmentSeat Belt Violation122687892320.2940430.018911
6Durham Police DepartmentSpeed Limit Violation13134326659380.3519700.007142
7Durham Police DepartmentStop Light/Sign Violation2804412934790.3704560.017080
8Durham Police DepartmentVehicle Equipment Violation53443526513730.2607790.025691
9Durham Police DepartmentVehicle Regulatory Violation77320592218200.3073290.023539
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agencystop_purpose_groupstop_countsearch_countarrest_countsearch_arrest_ratestop_arrest_rate
0Durham Police DepartmentInvestigatory29507379415880.4185560.053818
1Durham Police DepartmentRegulatory and Equipment1575471320138710.2932350.024570
2Durham Police DepartmentSafety Violation190378681429360.4308780.015422
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agencystop_purposestop_countsearch_countarrest_countsearch_arrest_ratestop_arrest_rate
0Durham Police DepartmentCheckpoint52783491820.5214900.034483
1Durham Police DepartmentDriving While Impaired12806158071.3121950.630469
2Durham Police DepartmentInvestigation24229344514060.4081280.058030
3Durham Police DepartmentOther Motor Vehicle Violation1451612254460.3640820.030725
4Durham Police DepartmentSafe Movement Violation2971122417120.3177150.023964
5Durham Police DepartmentSeat Belt Violation122687892320.2940430.018911
6Durham Police DepartmentSpeed Limit Violation13134326659380.3519700.007142
7Durham Police DepartmentStop Light/Sign Violation2804412934790.3704560.017080
8Durham Police DepartmentVehicle Equipment Violation53443526513730.2607790.025691
9Durham Police DepartmentVehicle Regulatory Violation77320592218200.3073290.023539
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agencycontraband_typeall_stop_countall_search_countcontraband_countcontraband_and_driver_arrest_countdriver_contraband_arrest_ratedriver_stop_arrest_rate
0Durham Police DepartmentAlcohol377433238095262250.4277570.000596
1Durham Police DepartmentNone3774332380900NaN0.000000
2Durham Police DepartmentMoney377433238097445060.6801080.001341
3Durham Police DepartmentOther377433238094261520.3568080.000403
4Durham Police DepartmentDrugs37743323809469016740.3569300.004435
5Durham Police DepartmentWeapons3774332380911855950.5021100.001576
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" + ], + "text/plain": [ + " agency contraband_type all_stop_count all_search_count \\\n", + "0 Durham Police Department Alcohol 377433 23809 \n", + "1 Durham Police Department None 377433 23809 \n", + "2 Durham Police Department Money 377433 23809 \n", + "3 Durham Police Department Other 377433 23809 \n", + "4 Durham Police Department Drugs 377433 23809 \n", + "5 Durham Police Department Weapons 377433 23809 \n", + "\n", + " contraband_count contraband_and_driver_arrest_count \\\n", + "0 526 225 \n", + "1 0 0 \n", + "2 744 506 \n", + "3 426 152 \n", + "4 4690 1674 \n", + "5 1185 595 \n", + "\n", + " driver_contraband_arrest_rate driver_stop_arrest_rate \n", + "0 0.427757 0.000596 \n", + "1 NaN 0.000000 \n", + "2 0.680108 0.001341 \n", + "3 0.356808 0.000403 \n", + "4 0.356930 0.004435 \n", + "5 0.502110 0.001576 " + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/nc/notebooks/2024-01-arrest-data/arrest.ipynb b/nc/notebooks/2024-01-arrest-data/arrest.ipynb new file mode 100644 index 00000000..0daa6053 --- /dev/null +++ b/nc/notebooks/2024-01-arrest-data/arrest.ipynb @@ -0,0 +1,9285 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ae95c93d-6ad9-4d15-a75a-8d8932fd40ad", + "metadata": {}, + "source": [ + "# Arrest data v5\n", + "\n", + "Date: February 14, 2024" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "55672bb9-b1e1-4f36-bbac-a131b14c8d19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + " \n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# jupyter nbconvert arrest.ipynb --to html --no-input --output=arrest-data-preview-v5.html\n", + "# inv deploy-html-notebooks --dir-name 2024-01-arrest-data\n", + "\n", + "import os\n", + "\n", + "from sqlalchemy import create_engine\n", + "\n", + "from dash import Dash, html, dcc\n", + "import plotly.express as px\n", + "import pandas as pd\n", + "\n", + "import plotly\n", + "plotly.offline.init_notebook_mode()\n", + "\n", + "pg_engine = create_engine(\"postgresql://copelco@127.0.0.1:5432/traffic_stops_nc\")\n", + "pg_conn = pg_engine.connect()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "58efb8b8-a90f-4122-ba1c-05be7969d070", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idname
052Charlotte-Mecklenburg Police Department
180Durham Police Department
289Fayetteville Police Department
3105Greensboro Police Department
4225Raleigh Police Department
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" + ], + "text/plain": [ + " id name\n", + "0 52 Charlotte-Mecklenburg Police Department\n", + "1 80 Durham Police Department\n", + "2 89 Fayetteville Police Department\n", + "3 105 Greensboro Police Department\n", + "4 225 Raleigh Police Department" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def lookup_agencies(agency_names):\n", + " return pd.read_sql(\n", + " f\"\"\"\n", + " SELECT\n", + " id\n", + " , name\n", + " FROM nc_agency\n", + " WHERE name ~ '{\"|\".join(agency_names)}'\n", + " ORDER BY 2\n", + " \"\"\",\n", + " pg_conn,\n", + " )\n", + "df = lookup_agencies({\n", + " \"Durham Police\",\n", + " \"Raleigh Police\",\n", + " \"Greensboro Police\",\n", + " \"Fayetteville Police\",\n", + " 'Charlotte-Mecklenburg Police',\n", + " \n", + "})\n", + "agency_ids = df['id'].tolist()\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bf7fdb3d-3352-46a0-a592-2c6fdbe1c9ad", + "metadata": {}, + "outputs": [], + "source": [ + "durham_ids = lookup_agencies({\n", + " \"Durham Police\",\n", + "})['id'].tolist()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "19e0d5b4-9fb3-47bb-b5f7-75f3595d27a8", + "metadata": {}, + "outputs": [], + "source": [ + "from enum import Enum\n", + "\n", + "class StopPurpose(Enum):\n", + " SPEED_LIMIT_VIOLATION = 1 # Safety Violation\n", + " STOP_LIGHT_SIGN_VIOLATION = 2 # Safety Violation\n", + " DRIVING_WHILE_IMPAIRED = 3 # Safety Violation\n", + " SAFE_MOVEMENT_VIOLATION = 4 # Safety Violation\n", + " VEHICLE_EQUIPMENT_VIOLATION = 5 # Regulatory and Equipment\n", + " VEHICLE_REGULATORY_VIOLATION = 6 # Regulatory and Equipment\n", + " OTHER_MOTOR_VEHICLE_VIOLATION = 9 # Regulatory and Equipment\n", + " SEAT_BELT_VIOLATION = 7 # Regulatory and Equipment\n", + " INVESTIGATION = 8 # Investigatory\n", + " CHECKPOINT = 10 # Investigatory\n", + " \n", + " @classmethod\n", + " def safety_violation(cls):\n", + " return [cls.SPEED_LIMIT_VIOLATION.value, cls.STOP_LIGHT_SIGN_VIOLATION.value, cls.DRIVING_WHILE_IMPAIRED.value, cls.SAFE_MOVEMENT_VIOLATION.value]\n", + " \n", + " @classmethod\n", + " def regulatory_equipment(cls):\n", + " return [cls.VEHICLE_EQUIPMENT_VIOLATION.value, cls.VEHICLE_REGULATORY_VIOLATION.value, cls.OTHER_MOTOR_VEHICLE_VIOLATION.value, cls.SEAT_BELT_VIOLATION.value]\n", + " \n", + " @classmethod\n", + " def investigatory(cls):\n", + " return [cls.INVESTIGATION.value, cls.CHECKPOINT.value]" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "73b47c73-9ba7-4aae-80e7-83017396e58f", + "metadata": {}, + "outputs": [], + "source": [ + "colors = (\n", + " px.colors.qualitative.Pastel2[5], # Asian\n", + " px.colors.qualitative.Pastel[9], # Black\n", + " px.colors.qualitative.Antique[2], # Hispanic\n", + " px.colors.qualitative.Set2[2], # Native American\n", + " px.colors.qualitative.Set3[2], # Other\n", + " px.colors.qualitative.Pastel[0], # White\n", + ")\n", + "color_map = {\n", + " \"Asian\": px.colors.qualitative.Pastel2[5],\n", + " \"Black\": px.colors.qualitative.Pastel[9],\n", + " \"Hispanic\": px.colors.qualitative.Antique[2],\n", + " \"Native American\": px.colors.qualitative.Set2[2],\n", + " \"Other\": px.colors.qualitative.Set3[2],\n", + " \"White\": px.colors.qualitative.Pastel[0],\n", + "}\n", + "pd.set_option('display.max_rows', 500)\n", + "\n", + "def is_true(cell_value):\n", + " if cell_value is True:\n", + " return 'background-color: moccasin;'\n", + " return ''\n", + "\n", + "def gt_zero_or_true(cell_value):\n", + " default = ''\n", + " highlight = 'background-color: lightyellow;'\n", + " if type(cell_value) in [float, int]:\n", + " if cell_value > 0:\n", + " return highlight\n", + " elif cell_value is True:\n", + " return 'background-color: moccasin;'\n", + " return default" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "a011c202-0aa8-4c2c-8bfd-6a6196fee3a3", + "metadata": {}, + "outputs": [], + "source": [ + "stops_summary_sql = f\"\"\"\n", + "SELECT\n", + " nc_stop.stop_id\n", + " , nc_stop.agency_id\n", + " , nc_stop.agency_description AS agency\n", + " , nc_stop.purpose AS stop_purpose\n", + " , (CASE WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.safety_violation()))}) THEN 'Safety Violation'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.investigatory()))}) THEN 'Investigatory'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.regulatory_equipment()))}) THEN 'Regulatory and Equipment'\n", + " ELSE 'Other'\n", + " END) as stop_purpose_group\n", + " , (CASE WHEN nc_stop.action = '1' THEN 'Verbal Warning'\n", + " WHEN nc_stop.action = '2' THEN 'Written Warning'\n", + " WHEN nc_stop.action = '3' THEN 'Citation Issued'\n", + " WHEN nc_stop.action = '4' THEN 'On-View Arrest'\n", + " WHEN nc_stop.action = '5' THEN 'No Action Taken'\n", + " END) as stop_action\n", + " , (CASE WHEN nc_person.ethnicity = 'H' THEN 'Hispanic'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'A' THEN 'Asian'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'B' THEN 'Black'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'I' THEN 'Native American'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'U' THEN 'Other'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'W' THEN 'White'\n", + " END) as driver_race\n", + " , (CASE WHEN nc_person.gender = 'M' THEN 'male'\n", + " WHEN nc_person.gender = 'F' THEN 'female'\n", + " END) as driver_gender\n", + " , (nc_search.search_id IS NOT NULL) AS driver_searched\n", + " , (nc_contraband.contraband_id IS NOT NULL) AS contraband_found\n", + " , driver_arrest\n", + " , passenger_arrest\n", + "FROM \"nc_stop\"\n", + "INNER JOIN \"nc_person\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_person\".\"stop_id\" AND \"nc_person\".\"type\" = 'D')\n", + "LEFT OUTER JOIN \"nc_search\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_search\".\"stop_id\")\n", + "LEFT OUTER JOIN \"nc_contraband\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_contraband\".\"stop_id\")\n", + "WHERE nc_stop.agency_id IN ({\",\".join(map(str, agency_ids))})\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "73412fb8-6461-4087-bdda-4b9dda7eb7bd", + "metadata": {}, + "outputs": [], + "source": [ + "contraband_summary_sql = f\"\"\"\n", + " WITH \n", + " contraband_groups AS (\n", + " SELECT\n", + " *\n", + " , (CASE WHEN nc_contraband.pints > 0 OR nc_contraband.gallons > 0 THEN true\n", + " ELSE false\n", + " END) AS alcohol_found\n", + " , (CASE WHEN nc_contraband.ounces > 0 OR nc_contraband.pounds > 0 OR nc_contraband.dosages > 0 OR nc_contraband.grams > 0 OR nc_contraband.kilos > 0 THEN true\n", + " ELSE false\n", + " END) AS drugs_found\n", + " , (CASE WHEN nc_contraband.money > 0 THEN true\n", + " ELSE false\n", + " END) AS money_found\n", + " , (CASE WHEN nc_contraband.dollar_amount > 0 THEN true\n", + " ELSE false\n", + " END) AS other_found\n", + " , (CASE WHEN nc_contraband.weapons > 0 THEN true\n", + " ELSE false\n", + " END) AS weapons_found\n", + " FROM nc_contraband\n", + " ),\n", + " contraband_types_without_id AS (\n", + " SELECT\n", + " contraband_id\n", + " , person_id\n", + " , search_id\n", + " , stop_id\n", + " , unnest(ARRAY['Alcohol', 'Drugs', 'Money', 'Other', 'Weapons']) AS contraband_type\n", + " , unnest(ARRAY[alcohol_found, drugs_found, money_found, other_found, weapons_found]) AS contraband_found\n", + " FROM contraband_groups\n", + " ), \n", + " contraband_types AS (\n", + " SELECT\n", + " ROW_NUMBER() OVER () AS contraband_type_id\n", + " , *\n", + " FROM contraband_types_without_id\n", + " ),\n", + " contraband_summary AS (\n", + " SELECT\n", + " nc_stop.stop_id\n", + " , date AT TIME ZONE 'America/New_York' AS stop_date\n", + " , nc_stop.agency_id\n", + " , (CASE WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.safety_violation()))}) THEN 'Safety Violation'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.investigatory()))}) THEN 'Investigatory'\n", + " WHEN nc_stop.purpose IN ({\",\".join(map(str, StopPurpose.regulatory_equipment()))}) THEN 'Regulatory and Equipment'\n", + " ELSE 'Other'\n", + " END) as stop_purpose_group\n", + " , (CASE WHEN nc_stop.action = '1' THEN 'Verbal Warning'\n", + " WHEN nc_stop.action = '2' THEN 'Written Warning'\n", + " WHEN nc_stop.action = '3' THEN 'Citation Issued'\n", + " WHEN nc_stop.action = '4' THEN 'On-View Arrest'\n", + " WHEN nc_stop.action = '5' THEN 'No Action Taken'\n", + " END) as stop_action\n", + " , (CASE WHEN nc_person.ethnicity = 'H' THEN 'Hispanic'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'A' THEN 'Asian'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'B' THEN 'Black'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'I' THEN 'Native American'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'U' THEN 'Other'\n", + " WHEN nc_person.ethnicity = 'N' AND nc_person.race = 'W' THEN 'White'\n", + " END) as driver_race\n", + " , (CASE WHEN nc_person.gender = 'M' THEN 'Male'\n", + " WHEN nc_person.gender = 'F' THEN 'Female'\n", + " END) as driver_gender\n", + " , (nc_search.search_id IS NOT NULL) AS driver_searched\n", + " , nc_search.search_id\n", + " , (contraband_id IS NOT NULL) AS contraband_id_found\n", + " , contraband_found\n", + " , contraband_id\n", + " , contraband_type_id\n", + " , contraband_type AS contraband_type_found\n", + " , driver_arrest\n", + " FROM \"nc_stop\"\n", + " INNER JOIN \"nc_person\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_person\".\"stop_id\" AND \"nc_person\".\"type\" = 'D')\n", + " LEFT OUTER JOIN \"nc_search\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"nc_search\".\"stop_id\")\n", + " LEFT OUTER JOIN \"contraband_types\"\n", + " ON (\"nc_stop\".\"stop_id\" = \"contraband_types\".\"stop_id\")\n", + " )\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "5e750bd1-a120-430c-a59f-f4430385f391", + "metadata": {}, + "outputs": [], + "source": [ + "# pd.read_sql(\n", + "# f\"\"\"\n", + "# SELECT\n", + "# nc_stop.stop_id\n", + "# , *\n", + "# , agency_id\n", + "# , (CASE WHEN nc_contraband.pints > 0 OR nc_contraband.gallons > 0 THEN true\n", + "# ELSE false\n", + "# END) AS alcohol_found\n", + "# , (CASE WHEN nc_contraband.ounces > 0 OR nc_contraband.pounds > 0 OR nc_contraband.dosages > 0 OR nc_contraband.grams > 0 OR nc_contraband.kilos > 0 THEN true\n", + "# ELSE false\n", + "# END) AS drugs_found\n", + "# , (CASE WHEN nc_contraband.money > 0 THEN true\n", + "# ELSE false\n", + "# END) AS money_found\n", + "# , (CASE WHEN nc_contraband.dollar_amount > 0 THEN true\n", + "# ELSE false\n", + "# END) AS other_found\n", + "# , (CASE WHEN nc_contraband.weapons > 0 THEN true\n", + "# ELSE false\n", + "# END) AS weapons_found\n", + "# FROM nc_contraband\n", + "# JOIN nc_stop ON (nc_contraband.stop_id = nc_stop.stop_id)\n", + "# WHERE agency_id IN ({\",\".join(map(str, durham_ids))})\n", + "# AND gallons > 0\n", + "# ORDER BY random()\n", + "# \"\"\",\n", + "# pg_engine,\n", + "# )\n", + "# pd.read_sql(\n", + "# f\"\"\"\n", + "# SELECT\n", + "# nc_stop.stop_id\n", + "# FROM nc_stop\n", + "# LEFT OUTER JOIN nc_contraband ON (nc_contraband.stop_id = nc_stop.stop_id)\n", + "# WHERE agency_id IN ({\",\".join(map(str, durham_ids))})\n", + "# AND contraband_id is null\n", + "# AND nc_stop.driver_arrest = true\n", + "# ORDER BY random()\n", + "# \"\"\",\n", + "# pg_engine,\n", + "# )\n", + "# pd.read_sql(\n", + "# f\"\"\"\n", + "# SELECT\n", + "# nc_stop.stop_id\n", + "# FROM nc_stop\n", + "# LEFT OUTER JOIN nc_search ON (nc_search.stop_id = nc_stop.stop_id)\n", + "# LEFT OUTER JOIN nc_contraband ON (nc_contraband.stop_id = nc_stop.stop_id)\n", + "# WHERE agency_id IN ({\",\".join(map(str, durham_ids))})\n", + "# AND nc_search.search_id is not null\n", + "# AND nc_contraband.contraband_id is null\n", + "# AND nc_stop.driver_arrest = true\n", + "# ORDER BY random()\n", + "# \"\"\",\n", + "# pg_engine,\n", + "# )" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "eb7c74b3-a101-4801-a043-6dee2f74c73c", + "metadata": {}, + "outputs": [], + "source": [ + "durham_stop_ids = (1455166, 1466790, 6034630, 15222320, 20281365, 27310867, 29727119, 24799552, 16228927, 1281717)" + ] + }, + { + "cell_type": "markdown", + "id": "04a668c6-80fe-4e69-b3c6-b25950e1cd45", + "metadata": {}, + "source": [ + "# Durham baseline stop, search, contraband, and arrest counts" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "27a6fed9-f550-426a-bbbb-3fc96507c1dc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 3.89 ms, sys: 2.16 ms, total: 6.05 ms\n", + "Wall time: 7.2 s\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencystop_countsearch_countcontraband_found_countarrest_count
0Durham Police Department3774322380974008395
1Greensboro Police Department703839349351231224586
2Fayetteville Police Department78664632032986613491
3Raleigh Police Department114311746401907516801
4Charlotte-Mecklenburg Police Department21639951208883879138256
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" + ], + "text/plain": [ + " agency stop_count search_count \\\n", + "0 Durham Police Department 377432 23809 \n", + "1 Greensboro Police Department 703839 34935 \n", + "2 Fayetteville Police Department 786646 32032 \n", + "3 Raleigh Police Department 1143117 46401 \n", + "4 Charlotte-Mecklenburg Police Department 2163995 120888 \n", + "\n", + " contraband_found_count arrest_count \n", + "0 7400 8395 \n", + "1 12312 24586 \n", + "2 9866 13491 \n", + "3 9075 16801 \n", + "4 38791 38256 " + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "\n", + "pd.read_sql(\n", + " f\"\"\"\n", + " WITH stopsummary AS ({stops_summary_sql})\n", + " SELECT\n", + " agency\n", + " , count(stop_id) AS stop_count\n", + " , count(stop_id) FILTER (WHERE driver_searched = true) AS search_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true) as contraband_found_count\n", + " , count(stop_id) FILTER (WHERE driver_arrest = true) AS arrest_count\n", + " FROM stopsummary\n", + " WHERE agency_id IN ({\",\".join(map(str, agency_ids))})\n", + " GROUP BY 1\n", + " ORDER BY 2\n", + " \"\"\",\n", + " pg_engine,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "0d536eb9-7487-4ad1-8b45-9a0ff14a24b8", + "metadata": {}, + "source": [ + "## Stop counts by search, contraband, and arrest values" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "ec402894-467c-4a66-b34c-a0ee3bda6b8b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 8.61 ms, sys: 1.75 ms, total: 10.4 ms\n", + "Wall time: 897 ms\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencydriver_searchedcontraband_founddriver_arrestpassenger_arreststop_actioncount
0Durham Police DepartmentFalseFalseFalseFalseCitation Issued175967
1Durham Police DepartmentFalseFalseFalseFalseNo Action Taken12236
2Durham Police DepartmentFalseFalseFalseFalseOn-View Arrest417
3Durham Police DepartmentFalseFalseFalseFalseVerbal Warning138562
4Durham Police DepartmentFalseFalseFalseFalseWritten Warning23443
5Durham Police DepartmentFalseFalseFalseTrueCitation Issued64
6Durham Police DepartmentFalseFalseFalseTrueNo Action Taken5
7Durham Police DepartmentFalseFalseFalseTrueOn-View Arrest102
8Durham Police DepartmentFalseFalseFalseTrueVerbal Warning35
9Durham Police DepartmentFalseFalseFalseTrueWritten Warning11
10Durham Police DepartmentFalseFalseTrueFalseCitation Issued852
11Durham Police DepartmentFalseFalseTrueFalseNo Action Taken33
12Durham Police DepartmentFalseFalseTrueFalseOn-View Arrest1536
13Durham Police DepartmentFalseFalseTrueFalseVerbal Warning239
14Durham Police DepartmentFalseFalseTrueFalseWritten Warning41
15Durham Police DepartmentFalseFalseTrueTrueCitation Issued20
16Durham Police DepartmentFalseFalseTrueTrueNo Action Taken1
17Durham Police DepartmentFalseFalseTrueTrueOn-View Arrest41
18Durham Police DepartmentFalseFalseTrueTrueVerbal Warning17
19Durham Police DepartmentFalseFalseTrueTrueWritten Warning1
20Durham Police DepartmentTrueFalseFalseFalseCitation Issued5588
21Durham Police DepartmentTrueFalseFalseFalseNo Action Taken595
22Durham Police DepartmentTrueFalseFalseFalseOn-View Arrest610
23Durham Police DepartmentTrueFalseFalseFalseVerbal Warning5148
24Durham Police DepartmentTrueFalseFalseFalseWritten Warning1162
25Durham Police DepartmentTrueFalseFalseTrueCitation Issued89
26Durham Police DepartmentTrueFalseFalseTrueNo Action Taken6
27Durham Police DepartmentTrueFalseFalseTrueOn-View Arrest192
28Durham Police DepartmentTrueFalseFalseTrueVerbal Warning34
29Durham Police DepartmentTrueFalseFalseTrueWritten Warning12
30Durham Police DepartmentTrueFalseTrueFalseCitation Issued513
31Durham Police DepartmentTrueFalseTrueFalseNo Action Taken3
32Durham Police DepartmentTrueFalseTrueFalseOn-View Arrest2236
33Durham Police DepartmentTrueFalseTrueFalseVerbal Warning53
34Durham Police DepartmentTrueFalseTrueFalseWritten Warning8
35Durham Police DepartmentTrueFalseTrueTrueCitation Issued33
36Durham Police DepartmentTrueFalseTrueTrueNo Action Taken2
37Durham Police DepartmentTrueFalseTrueTrueOn-View Arrest119
38Durham Police DepartmentTrueFalseTrueTrueVerbal Warning4
39Durham Police DepartmentTrueFalseTrueTrueWritten Warning2
40Durham Police DepartmentTrueTrueFalseFalseCitation Issued2624
41Durham Police DepartmentTrueTrueFalseFalseNo Action Taken72
42Durham Police DepartmentTrueTrueFalseFalseOn-View Arrest253
43Durham Police DepartmentTrueTrueFalseFalseVerbal Warning980
44Durham Police DepartmentTrueTrueFalseFalseWritten Warning346
45Durham Police DepartmentTrueTrueFalseTrueCitation Issued125
46Durham Police DepartmentTrueTrueFalseTrueNo Action Taken1
47Durham Police DepartmentTrueTrueFalseTrueOn-View Arrest324
48Durham Police DepartmentTrueTrueFalseTrueVerbal Warning21
49Durham Police DepartmentTrueTrueFalseTrueWritten Warning13
50Durham Police DepartmentTrueTrueTrueFalseCitation Issued212
51Durham Police DepartmentTrueTrueTrueFalseNo Action Taken5
52Durham Police DepartmentTrueTrueTrueFalseOn-View Arrest1797
53Durham Police DepartmentTrueTrueTrueFalseVerbal Warning22
54Durham Police DepartmentTrueTrueTrueFalseWritten Warning26
55Durham Police DepartmentTrueTrueTrueTrueCitation Issued65
56Durham Police DepartmentTrueTrueTrueTrueOn-View Arrest495
57Durham Police DepartmentTrueTrueTrueTrueVerbal Warning9
58Durham Police DepartmentTrueTrueTrueTrueWritten Warning10
TotalNaN39192929NaN377432
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" + ], + "text/plain": [ + " agency driver_searched contraband_found \\\n", + "0 Durham Police Department False False \n", + "1 Durham Police Department False False \n", + "2 Durham Police Department False False \n", + "3 Durham Police Department False False \n", + "4 Durham Police Department False False \n", + "5 Durham Police Department False False \n", + "6 Durham Police Department False False \n", + "7 Durham Police Department False False \n", + "8 Durham Police Department False False \n", + "9 Durham Police Department False False \n", + "10 Durham Police Department False False \n", + "11 Durham Police Department False False \n", + "12 Durham Police Department False False \n", + "13 Durham Police Department False False \n", + "14 Durham Police Department False False \n", + "15 Durham Police Department False False \n", + "16 Durham Police Department False False \n", + "17 Durham Police Department False False \n", + "18 Durham Police Department False False \n", + "19 Durham Police Department False False \n", + "20 Durham Police Department True False \n", + "21 Durham Police Department True False \n", + "22 Durham Police Department True False \n", + "23 Durham Police Department True False \n", + "24 Durham Police Department True False \n", + "25 Durham Police Department True False \n", + "26 Durham Police Department True False \n", + "27 Durham Police Department True False \n", + "28 Durham Police Department True False \n", + "29 Durham Police Department True False \n", + "30 Durham Police Department True False \n", + "31 Durham Police Department True False \n", + "32 Durham Police Department True False \n", + "33 Durham Police Department True False \n", + "34 Durham Police Department True False \n", + "35 Durham Police Department True False \n", + "36 Durham Police Department True False \n", + "37 Durham Police Department True False \n", + "38 Durham Police Department True False \n", + "39 Durham Police Department True False \n", + "40 Durham Police Department True True \n", + "41 Durham Police Department True True \n", + "42 Durham Police Department True True \n", + "43 Durham Police Department True True \n", + "44 Durham Police Department True True \n", + "45 Durham Police Department True True \n", + "46 Durham Police Department True True \n", + "47 Durham Police Department True True \n", + "48 Durham Police Department True True \n", + "49 Durham Police Department True True \n", + "50 Durham Police Department True True \n", + "51 Durham Police Department True True \n", + "52 Durham Police Department True True \n", + "53 Durham Police Department True True \n", + "54 Durham Police Department True True \n", + "55 Durham Police Department True True \n", + "56 Durham Police Department True True \n", + "57 Durham Police Department True True \n", + "58 Durham Police Department True True \n", + "Total NaN 39 19 \n", + "\n", + " driver_arrest passenger_arrest stop_action count \n", + "0 False False Citation Issued 175967 \n", + "1 False False No Action Taken 12236 \n", + "2 False False On-View Arrest 417 \n", + "3 False False Verbal Warning 138562 \n", + "4 False False Written Warning 23443 \n", + "5 False True Citation Issued 64 \n", + "6 False True No Action Taken 5 \n", + "7 False True On-View Arrest 102 \n", + "8 False True Verbal Warning 35 \n", + "9 False True Written Warning 11 \n", + "10 True False Citation Issued 852 \n", + "11 True False No Action Taken 33 \n", + "12 True False On-View Arrest 1536 \n", + "13 True False Verbal Warning 239 \n", + "14 True False Written Warning 41 \n", + "15 True True Citation Issued 20 \n", + "16 True True No Action Taken 1 \n", + "17 True True On-View Arrest 41 \n", + "18 True True Verbal Warning 17 \n", + "19 True True Written Warning 1 \n", + "20 False False Citation Issued 5588 \n", + "21 False False No Action Taken 595 \n", + "22 False False On-View Arrest 610 \n", + "23 False False Verbal Warning 5148 \n", + "24 False False Written Warning 1162 \n", + "25 False True Citation Issued 89 \n", + "26 False True No Action Taken 6 \n", + "27 False True On-View Arrest 192 \n", + "28 False True Verbal Warning 34 \n", + "29 False True Written Warning 12 \n", + "30 True False Citation Issued 513 \n", + "31 True False No Action Taken 3 \n", + "32 True False On-View Arrest 2236 \n", + "33 True False Verbal Warning 53 \n", + "34 True False Written Warning 8 \n", + "35 True True Citation Issued 33 \n", + "36 True True No Action Taken 2 \n", + "37 True True On-View Arrest 119 \n", + "38 True True Verbal Warning 4 \n", + "39 True True Written Warning 2 \n", + "40 False False Citation Issued 2624 \n", + "41 False False No Action Taken 72 \n", + "42 False False On-View Arrest 253 \n", + "43 False False Verbal Warning 980 \n", + "44 False False Written Warning 346 \n", + "45 False True Citation Issued 125 \n", + "46 False True No Action Taken 1 \n", + "47 False True On-View Arrest 324 \n", + "48 False True Verbal Warning 21 \n", + "49 False True Written Warning 13 \n", + "50 True False Citation Issued 212 \n", + "51 True False No Action Taken 5 \n", + "52 True False On-View Arrest 1797 \n", + "53 True False Verbal Warning 22 \n", + "54 True False Written Warning 26 \n", + "55 True True Citation Issued 65 \n", + "56 True True On-View Arrest 495 \n", + "57 True True Verbal Warning 9 \n", + "58 True True Written Warning 10 \n", + "Total 29 29 NaN 377432 " + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "\n", + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stopsummary AS ({stops_summary_sql})\n", + " SELECT\n", + " agency\n", + " , driver_searched\n", + " , contraband_found\n", + " , driver_arrest\n", + " , passenger_arrest\n", + " , stop_action\n", + " , count(*) AS count\n", + " FROM stopsummary\n", + " WHERE agency_id IN ({\",\".join(map(str, durham_ids))})\n", + " GROUP BY 1, 2, 3, 4, 5, 6\n", + " ORDER BY 1, 2, 3, 4, 5, 6\n", + " \"\"\",\n", + " pg_engine,\n", + " dtype={\"count\": \"Int64\"}\n", + ")\n", + "df.loc['Total'] = df.sum(numeric_only=True)\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "f0575d7a-3f96-4816-a94b-010104073bf5", + "metadata": {}, + "outputs": [], + "source": [ + "# pd.read_sql(\n", + "# f\"\"\"\n", + "# SELECT\n", + "# agency.id AS agency_id\n", + "# , agency.name AS agency\n", + "# , sum(summary.count) AS stop_count\n", + "# FROM nc_stopsummary summary\n", + "# JOIN nc_agency agency ON (agency.id = summary.agency_id)\n", + "# WHERE agency_id IN ({\",\".join(map(str, agency_ids))})\n", + "# GROUP BY 1\n", + "# \"\"\",\n", + "# pg_engine,\n", + "# )" + ] + }, + { + "cell_type": "markdown", + "id": "0bcdc1dc-74f5-4318-87ee-61fac18ee3f7", + "metadata": {}, + "source": [ + "## Stops and searches sample (10 total)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "a76305c9-f95a-4fb1-a1ed-e662b16407dc", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + 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21466790On-View Arrest30537TrueTrueFalseTrueFalseFalseFalseTrueFalseTrue
36034630On-View Arrest236185TrueTrueFalseFalseFalseFalseFalseTrueFalseFalse
415222320On-View Arrest531079TrueTrueTrueTrueFalseTrueFalseTrueTrueFalse
516228927Citation Issued556462TrueTrueFalseFalseFalseFalseFalseFalseFalseFalse
620281365On-View Arrest653876TrueTrueTrueTrueFalseTrueTrueTrueTrueTrue
724799552On-View Arrest<NA>NoneNoneNoneNoneNoneNoneNoneFalseFalseTrue
827310867On-View Arrest864391TrueTrueFalseTrueFalseFalseTrueTrueFalseTrue
929727119Verbal Warning<NA>NoneNoneNoneNoneNoneNoneNoneFalseFalseFalse
\n", + "
" + ], + "text/plain": [ + " stop_id stop_action search_id vehicle_search driver_search \\\n", + "0 1281717 On-View Arrest 20361 True True \n", + "1 1455166 On-View Arrest 29910 True True \n", + "2 1466790 On-View Arrest 30537 True True \n", + "3 6034630 On-View Arrest 236185 True True \n", + "4 15222320 On-View Arrest 531079 True True \n", + "5 16228927 Citation Issued 556462 True True \n", + "6 20281365 On-View Arrest 653876 True True \n", + "7 24799552 On-View Arrest None None \n", + "8 27310867 On-View Arrest 864391 True True \n", + "9 29727119 Verbal Warning None None \n", + "\n", + " passenger_search property_search vehicle_siezed personal_property_siezed \\\n", + "0 False True False False \n", + "1 False True False False \n", + "2 False True False False \n", + "3 False False False False \n", + "4 True True False True \n", + "5 False False False False \n", + "6 True True False True \n", + "7 None None None None \n", + "8 False True False False \n", + "9 None None None None \n", + "\n", + " other_property_sized contraband_found passenger_arrest driver_arrest \n", + "0 False False False True \n", + "1 False True False True \n", + "2 False True False True \n", + "3 False True False False \n", + "4 False True True False \n", + "5 False False False False \n", + "6 True True True True \n", + "7 None False False True \n", + "8 True True False True \n", + "9 None False False False " + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " SELECT\n", + " nc_stop.stop_id\n", + " , (CASE WHEN nc_stop.action = '1' THEN 'Verbal Warning'\n", + " WHEN nc_stop.action = '2' THEN 'Written Warning'\n", + " WHEN nc_stop.action = '3' THEN 'Citation Issued'\n", + " WHEN nc_stop.action = '4' THEN 'On-View Arrest'\n", + " WHEN nc_stop.action = '5' THEN 'No Action Taken'\n", + " END) as stop_action\n", + " , nc_search.search_id\n", + " , nc_search.vehicle_search\n", + " , nc_search.driver_search\n", + " , nc_search.passenger_search\n", + " , nc_search.property_search\n", + " , nc_search.vehicle_siezed\n", + " , nc_search.personal_property_siezed\n", + " , nc_search.other_property_sized\n", + " , (nc_contraband.contraband_id IS NOT NULL) AS contraband_found\n", + " , passenger_arrest\n", + " , driver_arrest\n", + " FROM nc_stop\n", + " LEFT OUTER JOIN nc_search ON (nc_search.stop_id = nc_stop.stop_id)\n", + " LEFT OUTER JOIN nc_contraband ON (nc_contraband.stop_id = nc_stop.stop_id)\n", + " WHERE nc_stop.stop_id IN ({\",\".join(map(str, durham_stop_ids))})\n", + " \"\"\",\n", + " pg_conn.engine,\n", + " dtype={\n", + " \"stop_id\": \"Int64\",\n", + " \"search_id\": \"Int64\",\n", + " },\n", + ")\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "5a64af33-076c-44ae-9065-2e0d8b3da642", + "metadata": {}, + "source": [ + "## Contraband found sample (6 stops)\n", + "\n", + "\"The data indicates that sometimes illegal items are found during traffic stops, even though there is no direct match for the type of illegal item associated with that stop. This happens because very small amounts of illegal items seem to be changed to zero when the data is recorded by the local agency or the NCDOJ (North Carolina Department of Justice) computers. When the amounts of illegal items are entered into the system, they are rounded either up or down to the nearest whole number. \n", + "For example, if there's 0.49 units of an illegal item, it's recorded as 0 units. This issue with the data seems to affect only cases involving drugs and alcohol, where someone might be found with a tiny fraction of the illegal substance.”" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "id": "f6426c34-b778-42b1-b9e5-4173abf27351", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 stop_idcontraband_idalcohol_pintsalcohol_gallonsalcohol_founddrugs_ouncesdrugs_poundsdrugs_dosagesdrugs_gramsdrugs_kilosdrugs_foundmoneymoney_foundweaponsweapons_founddollar_amountother_found
0145516656911.0000000.000000True0.0000000.0000000.000000nannanFalse0.000000False0.000000False0.000000False
1146679058330.0000004.000000True0.0000000.0000000.000000nannanFalse0.000000False0.000000False0.000000False
26034630552600.1500000.000000True0.0000000.0000000.000000nannanFalse0.000000False0.000000False0.000000False
3152223201413000.0000000.000000False0.0000000.0000002.0000007.5000000.000000True26.000000True0.000000False1.000000True
4202813651798101.0000000.000000True0.0000000.0000000.00000012.0000000.000000True67.000000True1.000000True30.000000True
5273108672717231.0000000.000000True0.0000000.0000000.0000002.0000000.000000True0.000000False0.000000False0.000000False
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " {contraband_summary_sql}\n", + " SELECT\n", + " stop_id\n", + " , contraband_id\n", + " -- Alcohol\n", + " , pints AS alcohol_pints\n", + " , gallons AS alcohol_gallons\n", + " , alcohol_found\n", + " -- Drugs\n", + " , ounces AS drugs_ounces\n", + " , pounds AS drugs_pounds\n", + " , dosages AS drugs_dosages \n", + " , grams AS drugs_grams\n", + " , kilos AS drugs_kilos\n", + " , drugs_found\n", + " -- Money\n", + " , money\n", + " , money_found\n", + " -- Weapons\n", + " , weapons\n", + " , weapons_found\n", + " -- Other\n", + " , dollar_amount\n", + " , other_found\n", + " FROM contraband_groups\n", + " WHERE stop_id IN ({\",\".join(map(str, durham_stop_ids))})\n", + " ORDER BY stop_id\n", + " LIMIT 20\n", + " \"\"\",\n", + " pg_conn.engine,\n", + ")\n", + "df.style.map(gt_zero_or_true)" + ] + }, + { + "cell_type": "markdown", + "id": "77f9dd19-2c4a-4292-ba6c-0cfe42522be5", + "metadata": {}, + "source": [ + "## Durham PD sample stops (10 total, 4 w/o contraband)\n", + "\n", + "* 6 contraband stops * 5 types (alcohol, drugs, money, weapons, other) + 4 stops w/o contraband = 34 records\n", + "* " + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "0744be5c-13f4-41c8-91d5-2ede88e3ae20", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 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 stop_idsearch_iddriver_searchedstop_actioncontraband_type_idcontraband_typecontraband_founddriver_arrestpassenger_arrest
0128171720361TrueOn-View ArrestNoneNoneTrueFalse
1145516629910TrueOn-View Arrest26397AlcoholTrueTrueFalse
2145516629910TrueOn-View Arrest26398DrugsFalseTrueFalse
3145516629910TrueOn-View Arrest26399MoneyFalseTrueFalse
4145516629910TrueOn-View Arrest26400OtherFalseTrueFalse
5145516629910TrueOn-View Arrest26401WeaponsFalseTrueFalse
6146679030537TrueOn-View Arrest27107AlcoholTrueTrueFalse
7146679030537TrueOn-View Arrest27108DrugsFalseTrueFalse
8146679030537TrueOn-View Arrest27109MoneyFalseTrueFalse
9146679030537TrueOn-View Arrest27110OtherFalseTrueFalse
10146679030537TrueOn-View Arrest27111WeaponsFalseTrueFalse
116034630236185TrueOn-View Arrest274242AlcoholTrueFalseFalse
126034630236185TrueOn-View Arrest274243DrugsFalseFalseFalse
136034630236185TrueOn-View Arrest274244MoneyFalseFalseFalse
146034630236185TrueOn-View Arrest274245OtherFalseFalseFalse
156034630236185TrueOn-View Arrest274246WeaponsFalseFalseFalse
1615222320531079TrueOn-View Arrest612042AlcoholFalseFalseTrue
1715222320531079TrueOn-View Arrest612043DrugsTrueFalseTrue
1815222320531079TrueOn-View Arrest612044MoneyTrueFalseTrue
1915222320531079TrueOn-View Arrest612045OtherTrueFalseTrue
2015222320531079TrueOn-View Arrest612046WeaponsFalseFalseTrue
2116228927556462TrueCitation IssuedNoneNoneFalseFalse
2220281365653876TrueOn-View Arrest804197AlcoholTrueTrueTrue
2320281365653876TrueOn-View Arrest804198DrugsTrueTrueTrue
2420281365653876TrueOn-View Arrest804199MoneyTrueTrueTrue
2520281365653876TrueOn-View Arrest804200OtherTrueTrueTrue
2620281365653876TrueOn-View Arrest804201WeaponsTrueTrueTrue
2724799552FalseOn-View ArrestNoneNoneTrueFalse
2827310867864391TrueOn-View Arrest1253667AlcoholTrueTrueFalse
2927310867864391TrueOn-View Arrest1253668DrugsTrueTrueFalse
3027310867864391TrueOn-View Arrest1253669MoneyFalseTrueFalse
3127310867864391TrueOn-View Arrest1253670OtherFalseTrueFalse
3227310867864391TrueOn-View Arrest1253671WeaponsFalseTrueFalse
3329727119FalseVerbal WarningNoneNoneFalseFalse
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " SELECT\n", + " nc_contrabandsummary.stop_id\n", + " , search_id\n", + " , driver_searched\n", + " , stop_action\n", + " , contraband_type_id\n", + " , contraband_type\n", + " , contraband_found\n", + " , nc_contrabandsummary.driver_arrest\n", + " , nc_stop.passenger_arrest\n", + " FROM nc_contrabandsummary\n", + " JOIN nc_stop ON (nc_contrabandsummary.stop_id = nc_stop.stop_id)\n", + " WHERE nc_contrabandsummary.agency_id IN ({\",\".join(map(str, durham_ids))})\n", + " AND nc_contrabandsummary.stop_id IN ({\",\".join(map(str, durham_stop_ids))})\n", + " ORDER BY stop_id, contraband_type\n", + " \"\"\",\n", + " pg_conn.engine,\n", + " dtype={\n", + " \"search_id\": \"Int64\",\n", + " \"contraband_type_id\": \"Int64\",\n", + " },\n", + ")\n", + "\n", + "def by_stop_id(s):\n", + " con = s.copy()\n", + " color = px.colors.qualitative.Pastel[durham_stop_ids.index(s[\"stop_id\"])]\n", + " con[:] = f\"background-color: {color}\"\n", + " if s[\"contraband_found\"] is True:\n", + " con[\"contraband_found\"] = 'background-color: moccasin;'\n", + " return con\n", + "\n", + "df.style.apply(by_stop_id, axis=1)" + ] + }, + { + "cell_type": "markdown", + "id": "8fa0bb97-8615-4423-bf6f-7a1d6cab59ff", + "metadata": { + "tags": [] + }, + "source": [ + "## Sample stop counts" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "176650ae-4a7f-4989-bcf7-2a2e9a778095", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 agencydriver_searchedcontraband_typecontraband_founddriver_arrestcount
0Durham Police DepartmentFalseNoneNoneFalse1
1Durham Police DepartmentFalseNoneNoneTrue1
2Durham Police DepartmentTrueAlcoholTrueFalse1
3Durham Police DepartmentTrueAlcoholTrueTrue4
4Durham Police DepartmentTrueDrugsTrueFalse1
5Durham Police DepartmentTrueDrugsTrueTrue2
6Durham Police DepartmentTrueMoneyTrueFalse1
7Durham Police DepartmentTrueMoneyTrueTrue1
8Durham Police DepartmentTrueOtherTrueFalse1
9Durham Police DepartmentTrueOtherTrueTrue1
10Durham Police DepartmentTrueWeaponsTrueTrue1
Totalnan9nannan615
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stops AS (\n", + " SELECT\n", + " agency.id AS agency_id\n", + " , agency.name AS agency\n", + " , sum(summary.count) AS stop_count\n", + " FROM nc_stopsummary summary\n", + " JOIN nc_agency agency ON (agency.id = summary.agency_id)\n", + " WHERE agency_id IN ({\",\".join(map(str, agency_ids))})\n", + " GROUP BY 1\n", + " )\n", + " SELECT\n", + " agency\n", + " , driver_searched\n", + " , contraband_type\n", + " , contraband_found\n", + " , driver_arrest\n", + " , count(*) AS count\n", + " FROM nc_contrabandsummary summary\n", + " JOIN stops ON (stops.agency_id = summary.agency_id)\n", + " WHERE summary.agency_id IN ({\",\".join(map(str, durham_ids))})\n", + " AND stop_id IN ({\",\".join(map(str, durham_stop_ids))})\n", + " AND (contraband_found = true OR driver_searched = false)\n", + " GROUP BY 1, 2, 3, 4, 5\n", + " ORDER BY 1\n", + " \"\"\",\n", + " pg_engine,\n", + " dtype={\"count\": \"Int64\"}\n", + ")\n", + "df.loc['Total'] = df.sum(numeric_only=True)\n", + "df.style.map(is_true, subset=['contraband_found'])" + ] + }, + { + "cell_type": "markdown", + "id": "3fec36ab-53db-4e91-85b8-828b573c8ecd", + "metadata": {}, + "source": [ + "## Sample arrest rates" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "6be2b73d-0dbc-49a0-936a-3bc7d8424860", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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agencycontraband_typeall_stop_countall_search_countcontraband_countcontraband_and_driver_arrest_countdriver_contraband_arrest_ratedriver_stop_arrest_rate
0Durham Police DepartmentAlcohol108540.8000000.4
1Durham Police DepartmentDrugs108320.6666670.2
2Durham Police DepartmentMoney108210.5000000.1
3Durham Police DepartmentOther108210.5000000.1
4Durham Police DepartmentWeapons108111.0000000.1
5Durham Police DepartmentNone10800NaN0.0
\n", + "
" + ], + "text/plain": [ + " agency contraband_type all_stop_count all_search_count \\\n", + "0 Durham Police Department Alcohol 10 8 \n", + "1 Durham Police Department Drugs 10 8 \n", + "2 Durham Police Department Money 10 8 \n", + "3 Durham Police Department Other 10 8 \n", + "4 Durham Police Department Weapons 10 8 \n", + "5 Durham Police Department None 10 8 \n", + "\n", + " contraband_count contraband_and_driver_arrest_count \\\n", + "0 5 4 \n", + "1 3 2 \n", + "2 2 1 \n", + "3 2 1 \n", + "4 1 1 \n", + "5 0 0 \n", + "\n", + " driver_contraband_arrest_rate driver_stop_arrest_rate \n", + "0 0.800000 0.4 \n", + "1 0.666667 0.2 \n", + "2 0.500000 0.1 \n", + "3 0.500000 0.1 \n", + "4 1.000000 0.1 \n", + "5 NaN 0.0 " + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stops AS (\n", + " SELECT\n", + " agency_id\n", + " , agency_description AS agency\n", + " , count(*) as stop_count\n", + " , count(DISTINCT nc_search.search_id) AS search_count\n", + " FROM nc_stop\n", + " LEFT OUTER JOIN nc_search ON (nc_search.stop_id = nc_stop.stop_id)\n", + " WHERE nc_stop.stop_id IN ({\",\".join(map(str, durham_stop_ids))})\n", + " GROUP BY 1, 2\n", + " )\n", + " SELECT\n", + " agency\n", + " , contraband_type\n", + " , stop_count AS all_stop_count\n", + " , search_count AS all_search_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true) AS contraband_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true AND driver_arrest = true) AS contraband_and_driver_arrest_count\n", + " FROM nc_contrabandsummary summary\n", + " JOIN stops ON (stops.agency_id = summary.agency_id)\n", + " WHERE summary.agency_id IN ({\",\".join(map(str, durham_ids))})\n", + " AND stop_id IN ({\",\".join(map(str, durham_stop_ids))})\n", + " --AND contraband_found = true\n", + " GROUP BY 1, 2, 3, 4\n", + " ORDER BY 1\n", + " \"\"\",\n", + " pg_engine,\n", + " # dtype={\"year\": \"Int64\"}\n", + ")\n", + "df[\"driver_contraband_arrest_rate\"] = df.contraband_and_driver_arrest_count / df.contraband_count\n", + "df[\"driver_stop_arrest_rate\"] = df.contraband_and_driver_arrest_count / df.all_stop_count\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "fd0351bf-3348-4de5-96a7-42d626328227", + "metadata": {}, + "source": [ + "# Agency arrest rates" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "5b2120df-ef4d-479e-9bcd-bccade9a6d9e", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stops AS (\n", + " SELECT\n", + " agency_id\n", + " , agency_description AS agency\n", + " , count(*) as stop_count\n", + " , count(DISTINCT nc_search.search_id) AS search_count\n", + " FROM nc_stop\n", + " LEFT OUTER JOIN nc_search ON (nc_search.stop_id = nc_stop.stop_id)\n", + " WHERE nc_stop.agency_id IN ({\",\".join(map(str, agency_ids))})\n", + " GROUP BY 1, 2\n", + " )\n", + " SELECT\n", + " agency\n", + " , contraband_type\n", + " , stop_count AS all_stop_count\n", + " , search_count AS all_search_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true) AS contraband_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true AND driver_arrest = true) AS contraband_and_driver_arrest_count\n", + " FROM nc_contrabandsummary summary\n", + " JOIN stops ON (stops.agency_id = summary.agency_id)\n", + " WHERE summary.agency_id IN ({\",\".join(map(str, agency_ids))})\n", + " --AND contraband_found = true\n", + " GROUP BY 1, 2, 3, 4\n", + " ORDER BY 1\n", + " \"\"\",\n", + " pg_engine,\n", + " # dtype={\"year\": \"Int64\"}\n", + ")\n", + "df[\"driver_contraband_arrest_rate\"] = df.contraband_and_driver_arrest_count / df.contraband_count\n", + "df[\"driver_stop_arrest_rate\"] = df.contraband_and_driver_arrest_count / df.all_stop_count" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "ba04a913-347d-4933-8776-d38cd9a6e31b", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "Contraband Type=%{y}
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agency=Durham Police Department
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agency=Greensboro Police Department
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agency=Raleigh Police Department
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agency=Charlotte-Mecklenburg Police Department
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agency=Charlotte-Mecklenburg Police Department
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agency=Durham Police Department
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agency=Fayetteville Police Department
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agency=Raleigh Police Department
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agency=Charlotte-Mecklenburg Police Department
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agency=Durham Police Department
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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = px.bar(\n", + " df,\n", + " x=\"driver_stop_arrest_rate\",\n", + " y=\"contraband_type\",\n", + " color=\"contraband_type\",\n", + " color_discrete_map=color_map,\n", + " facet_col=\"agency\",\n", + " facet_col_wrap=3,\n", + " title=\"Percentage of stops that led to arrests after a search uncovered contraband for a specific contraband type\",\n", + " labels={\n", + " \"contraband_type\": \"Contraband Type\",\n", + " \"driver_stop_arrest_rate\": \"Driver stop arrest rate\",\n", + " },\n", + " text='driver_stop_arrest_rate',\n", + " text_auto=',.1%',\n", + " orientation='h',\n", + " height=1000,\n", + " # range_x=[0, 1],\n", + ")\n", + "fig.update_xaxes(tickformat=\",.0%\")\n", + "fig" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "id": "d75b04d9-32a5-4fa9-bac5-76d6ca9a223a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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agencycontraband_typeall_stop_countall_search_countcontraband_countcontraband_and_driver_arrest_countdriver_contraband_arrest_ratedriver_stop_arrest_rate
0Charlotte-Mecklenburg Police DepartmentAlcohol2163995120888518812360.2382420.000571
1Charlotte-Mecklenburg Police DepartmentDrugs21639951208881024227030.2639130.001249
2Charlotte-Mecklenburg Police DepartmentMoney2163995120888229312310.5368510.000569
3Charlotte-Mecklenburg Police DepartmentOther2163995120888545415240.2794280.000704
4Charlotte-Mecklenburg Police DepartmentWeapons2163995120888610630750.5036030.001421
5Charlotte-Mecklenburg Police DepartmentNone216399512088800NaN0.000000
6Durham Police DepartmentAlcohol377433238095262250.4277570.000596
7Durham Police DepartmentDrugs37743323809469016740.3569300.004435
8Durham Police DepartmentMoney377433238097445060.6801080.001341
9Durham Police DepartmentOther377433238094261520.3568080.000403
10Durham Police DepartmentWeapons3774332380911855950.5021100.001576
11Durham Police DepartmentNone3774332380900NaN0.000000
12Fayetteville Police DepartmentAlcohol7866463203214223820.2686360.000486
13Fayetteville Police DepartmentDrugs78664632032636520310.3190890.002582
14Fayetteville Police DepartmentMoney786646320324553280.7208790.000417
15Fayetteville Police DepartmentOther786646320325371300.2420860.000165
16Fayetteville Police DepartmentWeapons7866463203214875680.3819770.000722
17Fayetteville Police DepartmentNone7866463203200NaN0.000000
18Greensboro Police DepartmentAlcohol7038433493514545680.3906460.000807
19Greensboro Police DepartmentDrugs70384334935727030430.4185690.004323
20Greensboro Police DepartmentMoney703843349356854560.6656930.000648
21Greensboro Police DepartmentOther703843349355532180.3942130.000310
22Greensboro Police DepartmentWeapons7038433493518089000.4977880.001279
23Greensboro Police DepartmentNone7038433493500NaN0.000000
24Raleigh Police DepartmentAlcohol114311746401227330.1453740.000029
25Raleigh Police DepartmentDrugs114311746401608719210.3155910.001680
26Raleigh Police DepartmentMoney1143117464013882290.5902060.000200
27Raleigh Police DepartmentOther11431174640100NaN0.000000
28Raleigh Police DepartmentWeapons11431174640100NaN0.000000
29Raleigh Police DepartmentNone11431174640100NaN0.000000
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agencycontraband_typestop_actionall_stop_countall_search_countcontraband_countcontraband_and_driver_arrest_countdriver_contraband_arrest_ratedriver_stop_arrest_rate
0Charlotte-Mecklenburg Police DepartmentAlcoholCitation Issued21639951208881957460.0235052.125698e-05
1Charlotte-Mecklenburg Police DepartmentAlcoholNo Action Taken21639951208884910.0204084.621083e-07
2Charlotte-Mecklenburg Police DepartmentAlcoholOn-View Arrest2163995120888238511820.4955975.462120e-04
3Charlotte-Mecklenburg Police DepartmentAlcoholVerbal Warning216399512088874670.0093833.234758e-06
4Charlotte-Mecklenburg Police DepartmentAlcoholWritten Warning21639951208885100.0000000.000000e+00
5Charlotte-Mecklenburg Police DepartmentDrugsCitation Issued21639951208883073890.0289624.112764e-05
6Charlotte-Mecklenburg Police DepartmentDrugsNo Action Taken216399512088812100.0000000.000000e+00
7Charlotte-Mecklenburg Police DepartmentDrugsOn-View Arrest2163995120888640626050.4066501.203792e-03
8Charlotte-Mecklenburg Police DepartmentDrugsVerbal Warning216399512088857590.0156524.158974e-06
9Charlotte-Mecklenburg Police DepartmentDrugsWritten Warning21639951208886700.0000000.000000e+00
10Charlotte-Mecklenburg Police DepartmentMoneyCitation Issued2163995120888194300.1546391.386325e-05
11Charlotte-Mecklenburg Police DepartmentMoneyNo Action Taken21639951208882200.0000000.000000e+00
12Charlotte-Mecklenburg Police DepartmentMoneyOn-View Arrest2163995120888201711940.5919685.517573e-04
13Charlotte-Mecklenburg Police DepartmentMoneyVerbal Warning21639951208884970.1428573.234758e-06
14Charlotte-Mecklenburg Police DepartmentMoneyWritten Warning21639951208881100.0000000.000000e+00
15Charlotte-Mecklenburg Police DepartmentOtherCitation Issued21639951208881818740.0407043.419601e-05
16Charlotte-Mecklenburg Police DepartmentOtherNo Action Taken21639951208887800.0000000.000000e+00
17Charlotte-Mecklenburg Police DepartmentOtherOn-View Arrest2163995120888252014450.5734136.677465e-04
18Charlotte-Mecklenburg Police DepartmentOtherVerbal Warning216399512088899750.0050152.310541e-06
19Charlotte-Mecklenburg Police DepartmentOtherWritten Warning21639951208884100.0000000.000000e+00
20Charlotte-Mecklenburg Police DepartmentWeaponsCitation Issued216399512088811881420.1195296.561938e-05
21Charlotte-Mecklenburg Police DepartmentWeaponsNo Action Taken21639951208887400.0000000.000000e+00
22Charlotte-Mecklenburg Police DepartmentWeaponsOn-View Arrest2163995120888443729110.6560741.345197e-03
23Charlotte-Mecklenburg Police DepartmentWeaponsVerbal Warning2163995120888366220.0601091.016638e-05
24Charlotte-Mecklenburg Police DepartmentWeaponsWritten Warning21639951208884100.0000000.000000e+00
25Durham Police DepartmentAlcoholCitation Issued37743323809209170.0813404.504111e-05
26Durham Police DepartmentAlcoholNo Action Taken37743323809300.0000000.000000e+00
27Durham Police DepartmentAlcoholOn-View Arrest377433238092682080.7761195.510912e-04
28Durham Police DepartmentAlcoholVerbal Warning377433238093700.0000000.000000e+00
29Durham Police DepartmentAlcoholWritten Warning37743323809900.0000000.000000e+00
30Durham Police DepartmentDrugsCitation Issued3774332380918761670.0890194.424626e-04
31Durham Police DepartmentDrugsNo Action Taken377433238093320.0606065.298954e-06
32Durham Police DepartmentDrugsOn-View Arrest37743323809179314470.8070273.833793e-03
33Durham Police DepartmentDrugsVerbal Warning37743323809706260.0368276.888640e-05
34Durham Police DepartmentDrugsWritten Warning37743323809282320.1134758.478326e-05
35Durham Police DepartmentMoneyCitation Issued3774332380995360.3789479.538117e-05
36Durham Police DepartmentMoneyNo Action Taken37743323809310.3333332.649477e-06
37Durham Police DepartmentMoneyOn-View Arrest377433238095274460.8463001.181667e-03
38Durham Police DepartmentMoneyVerbal Warning377433238096180.1311482.119581e-05
39Durham Police DepartmentMoneyWritten Warning3774332380958150.2586213.974215e-05
40Durham Police DepartmentOtherCitation Issued37743323809183130.0710383.444320e-05
41Durham Police DepartmentOtherNo Action Taken37743323809900.0000000.000000e+00
42Durham Police DepartmentOtherOn-View Arrest377433238091811390.7679563.682773e-04
43Durham Police DepartmentOtherVerbal Warning377433238093800.0000000.000000e+00
44Durham Police DepartmentOtherWritten Warning377433238091500.0000000.000000e+00
45Durham Police DepartmentWeaponsCitation Issued37743323809372360.0967749.538117e-05
46Durham Police DepartmentWeaponsNo Action Taken377433238091100.0000000.000000e+00
47Durham Police DepartmentWeaponsOn-View Arrest377433238096755510.8162961.459862e-03
48Durham Police DepartmentWeaponsVerbal Warning377433238099330.0322587.948431e-06
49Durham Police DepartmentWeaponsWritten Warning377433238093450.1470591.324738e-05
50Fayetteville Police DepartmentAlcoholCitation Issued78664632032843280.0332153.559416e-05
51Fayetteville Police DepartmentAlcoholNo Action Taken78664632032500.0000000.000000e+00
52Fayetteville Police DepartmentAlcoholOn-View Arrest786646320324413510.7959184.461982e-04
53Fayetteville Police DepartmentAlcoholVerbal Warning7866463203200NaN0.000000e+00
54Fayetteville Police DepartmentAlcoholWritten Warning7866463203213330.0225563.813660e-06
55Fayetteville Police DepartmentDrugsCitation Issued7866463203231631120.0354091.423766e-04
56Fayetteville Police DepartmentDrugsNo Action Taken786646320323900.0000000.000000e+00
57Fayetteville Police DepartmentDrugsOn-View Arrest78664632032227718950.8322352.408962e-03
58Fayetteville Police DepartmentDrugsVerbal Warning786646320321010.1000001.271220e-06
59Fayetteville Police DepartmentDrugsWritten Warning78664632032876230.0262562.923806e-05
60Fayetteville Police DepartmentMoneyCitation Issued7866463203274110.1486491.398342e-05
61Fayetteville Police DepartmentMoneyNo Action Taken78664632032300.0000000.000000e+00
62Fayetteville Police DepartmentMoneyOn-View Arrest786646320323453130.9072463.978918e-04
63Fayetteville Police DepartmentMoneyVerbal Warning7866463203200NaN0.000000e+00
64Fayetteville Police DepartmentMoneyWritten Warning786646320323340.1212125.084879e-06
65Fayetteville Police DepartmentOtherCitation Issued7866463203229570.0237298.898539e-06
66Fayetteville Police DepartmentOtherNo Action Taken78664632032600.0000000.000000e+00
67Fayetteville Police DepartmentOtherOn-View Arrest786646320321491230.8255031.563600e-04
68Fayetteville Police DepartmentOtherVerbal Warning7866463203200NaN0.000000e+00
69Fayetteville Police DepartmentOtherWritten Warning786646320328700.0000000.000000e+00
70Fayetteville Police DepartmentWeaponsCitation Issued78664632032618230.0372172.923806e-05
71Fayetteville Police DepartmentWeaponsNo Action Taken786646320321600.0000000.000000e+00
72Fayetteville Police DepartmentWeaponsOn-View Arrest786646320326575390.8203966.851875e-04
73Fayetteville Police DepartmentWeaponsVerbal Warning78664632032500.0000000.000000e+00
74Fayetteville Police DepartmentWeaponsWritten Warning7866463203219160.0314147.627319e-06
75Greensboro Police DepartmentAlcoholCitation Issued703843349357431080.1453571.534433e-04
76Greensboro Police DepartmentAlcoholNo Action Taken70384334935300.0000000.000000e+00
77Greensboro Police DepartmentAlcoholOn-View Arrest703843349356194570.7382886.492925e-04
78Greensboro Police DepartmentAlcoholVerbal Warning703843349357410.0135141.420771e-06
79Greensboro Police DepartmentAlcoholWritten Warning703843349351520.1333332.841543e-06
80Greensboro Police DepartmentDrugsCitation Issued7038433493533435630.1684127.998943e-04
81Greensboro Police DepartmentDrugsNo Action Taken703843349352110.0476191.420771e-06
82Greensboro Police DepartmentDrugsOn-View Arrest70384334935335824370.7257303.462420e-03
83Greensboro Police DepartmentDrugsVerbal Warning70384334935441190.0430842.699466e-05
84Greensboro Police DepartmentDrugsWritten Warning70384334935107230.2149533.267774e-05
85Greensboro Police DepartmentMoneyCitation Issued70384334935102350.3431374.972700e-05
86Greensboro Police DepartmentMoneyNo Action Taken70384334935300.0000000.000000e+00
87Greensboro Police DepartmentMoneyOn-View Arrest703843349355424180.7712185.938824e-04
88Greensboro Police DepartmentMoneyVerbal Warning703843349352620.0769232.841543e-06
89Greensboro Police DepartmentMoneyWritten Warning703843349351210.0833331.420771e-06
90Greensboro Police DepartmentOtherCitation Issued70384334935248440.1774196.251394e-05
91Greensboro Police DepartmentOtherNo Action Taken70384334935300.0000000.000000e+00
92Greensboro Police DepartmentOtherOn-View Arrest703843349352531700.6719372.415311e-04
93Greensboro Police DepartmentOtherVerbal Warning703843349353920.0512822.841543e-06
94Greensboro Police DepartmentOtherWritten Warning703843349351020.2000002.841543e-06
95Greensboro Police DepartmentWeaponsCitation Issued70384334935626860.1373801.221863e-04
96Greensboro Police DepartmentWeaponsNo Action Taken703843349351610.0625001.420771e-06
97Greensboro Police DepartmentWeaponsOn-View Arrest7038433493510618110.7643731.152246e-03
98Greensboro Police DepartmentWeaponsVerbal Warning703843349358800.0000000.000000e+00
99Greensboro Police DepartmentWeaponsWritten Warning703843349351720.1176472.841543e-06
100Raleigh Police DepartmentAlcoholCitation Issued1143117464019960.0606065.248807e-06
101Raleigh Police DepartmentAlcoholNo Action Taken11431174640100NaN0.000000e+00
102Raleigh Police DepartmentAlcoholOn-View Arrest114311746401120270.2250002.361963e-05
103Raleigh Police DepartmentAlcoholVerbal Warning114311746401700.0000000.000000e+00
104Raleigh Police DepartmentAlcoholWritten Warning114311746401100.0000000.000000e+00
105Raleigh Police DepartmentDrugsCitation Issued11431174640132433460.1066913.026812e-04
106Raleigh Police DepartmentDrugsNo Action Taken1143117464012440.1666673.499204e-06
107Raleigh Police DepartmentDrugsOn-View Arrest114311746401213014630.6868541.279834e-03
108Raleigh Police DepartmentDrugsVerbal Warning1143117464016771080.1595279.447852e-05
109Raleigh Police DepartmentDrugsWritten Warning1143117464011300.0000000.000000e+00
110Raleigh Police DepartmentMoneyCitation Issued11431174640184280.3333332.449443e-05
111Raleigh Police DepartmentMoneyNo Action Taken114311746401100.0000000.000000e+00
112Raleigh Police DepartmentMoneyOn-View Arrest1143117464012771860.6714801.627130e-04
113Raleigh Police DepartmentMoneyVerbal Warning11431174640126150.5769231.312202e-05
114Raleigh Police DepartmentMoneyWritten Warning11431174640100NaN0.000000e+00
115Raleigh Police DepartmentOtherCitation Issued11431174640100NaN0.000000e+00
116Raleigh Police DepartmentOtherNo Action Taken11431174640100NaN0.000000e+00
117Raleigh Police DepartmentOtherOn-View Arrest11431174640100NaN0.000000e+00
118Raleigh Police DepartmentOtherVerbal Warning11431174640100NaN0.000000e+00
119Raleigh Police DepartmentOtherWritten Warning11431174640100NaN0.000000e+00
120Raleigh Police DepartmentWeaponsCitation Issued11431174640100NaN0.000000e+00
121Raleigh Police DepartmentWeaponsNo Action Taken11431174640100NaN0.000000e+00
122Raleigh Police DepartmentWeaponsOn-View Arrest11431174640100NaN0.000000e+00
123Raleigh Police DepartmentWeaponsVerbal Warning11431174640100NaN0.000000e+00
124Raleigh Police DepartmentWeaponsWritten Warning11431174640100NaN0.000000e+00
\n", + "
" + ], + "text/plain": [ + " agency contraband_type stop_action \\\n", + "0 Charlotte-Mecklenburg Police Department Alcohol Citation Issued \n", + "1 Charlotte-Mecklenburg Police Department Alcohol No Action Taken \n", + "2 Charlotte-Mecklenburg Police Department Alcohol On-View Arrest \n", + "3 Charlotte-Mecklenburg Police Department Alcohol Verbal Warning \n", + "4 Charlotte-Mecklenburg Police Department Alcohol Written Warning \n", + "5 Charlotte-Mecklenburg Police Department Drugs Citation Issued \n", + "6 Charlotte-Mecklenburg Police Department Drugs No Action Taken \n", + "7 Charlotte-Mecklenburg Police Department Drugs On-View Arrest \n", + "8 Charlotte-Mecklenburg Police Department Drugs Verbal Warning \n", + "9 Charlotte-Mecklenburg Police Department Drugs Written Warning \n", + "10 Charlotte-Mecklenburg Police Department Money Citation Issued \n", + "11 Charlotte-Mecklenburg Police Department Money No Action Taken \n", + "12 Charlotte-Mecklenburg Police Department Money On-View Arrest \n", + "13 Charlotte-Mecklenburg Police Department Money Verbal Warning \n", + "14 Charlotte-Mecklenburg Police Department Money Written Warning \n", + "15 Charlotte-Mecklenburg Police Department Other Citation Issued \n", + "16 Charlotte-Mecklenburg Police Department Other No Action Taken \n", + "17 Charlotte-Mecklenburg Police Department Other On-View Arrest \n", + "18 Charlotte-Mecklenburg Police Department Other Verbal Warning \n", + "19 Charlotte-Mecklenburg Police Department Other Written Warning \n", + "20 Charlotte-Mecklenburg Police Department Weapons Citation Issued \n", + "21 Charlotte-Mecklenburg Police Department Weapons No Action Taken \n", + "22 Charlotte-Mecklenburg Police Department Weapons On-View Arrest \n", + "23 Charlotte-Mecklenburg Police Department Weapons Verbal Warning \n", + "24 Charlotte-Mecklenburg Police Department Weapons Written Warning \n", + "25 Durham Police Department Alcohol Citation Issued \n", + "26 Durham Police Department Alcohol No Action Taken \n", + "27 Durham Police Department Alcohol On-View Arrest \n", + "28 Durham Police Department Alcohol Verbal Warning \n", + "29 Durham Police Department Alcohol Written Warning \n", + "30 Durham Police Department Drugs Citation Issued \n", + "31 Durham Police Department Drugs No Action Taken \n", + "32 Durham Police Department Drugs On-View Arrest \n", + "33 Durham Police Department Drugs Verbal Warning \n", + "34 Durham Police Department Drugs Written Warning \n", + "35 Durham Police Department Money Citation Issued \n", + "36 Durham Police Department Money No Action Taken \n", + "37 Durham Police Department Money On-View Arrest \n", + "38 Durham Police Department Money Verbal Warning \n", + "39 Durham Police Department Money Written Warning \n", + "40 Durham Police Department Other Citation Issued \n", + "41 Durham Police Department Other No Action Taken \n", + "42 Durham Police Department Other On-View Arrest \n", + "43 Durham Police Department Other Verbal Warning \n", + "44 Durham Police Department Other Written Warning \n", + "45 Durham Police Department Weapons Citation Issued \n", + "46 Durham Police Department Weapons No Action Taken \n", + "47 Durham Police Department Weapons On-View Arrest \n", + "48 Durham Police Department Weapons Verbal Warning \n", + "49 Durham Police Department Weapons Written Warning \n", + "50 Fayetteville Police Department Alcohol Citation Issued \n", + "51 Fayetteville Police Department Alcohol No Action Taken \n", + "52 Fayetteville Police Department Alcohol On-View Arrest \n", + "53 Fayetteville Police Department Alcohol Verbal Warning \n", + "54 Fayetteville Police Department Alcohol Written Warning \n", + "55 Fayetteville Police Department Drugs Citation Issued \n", + "56 Fayetteville Police Department Drugs No Action Taken \n", + "57 Fayetteville Police Department Drugs On-View Arrest \n", + "58 Fayetteville Police Department Drugs Verbal Warning \n", + "59 Fayetteville Police Department Drugs Written Warning \n", + "60 Fayetteville Police Department Money Citation Issued \n", + "61 Fayetteville Police Department Money No Action Taken \n", + "62 Fayetteville Police Department Money On-View Arrest \n", + "63 Fayetteville Police Department Money Verbal Warning \n", + "64 Fayetteville Police Department Money Written Warning \n", + "65 Fayetteville Police Department Other Citation Issued \n", + "66 Fayetteville Police Department Other No Action Taken \n", + "67 Fayetteville Police Department Other On-View Arrest \n", + "68 Fayetteville Police Department Other Verbal Warning \n", + "69 Fayetteville Police Department Other Written Warning \n", + "70 Fayetteville Police Department Weapons Citation Issued \n", + "71 Fayetteville Police Department Weapons No Action Taken \n", + "72 Fayetteville Police Department Weapons On-View Arrest \n", + "73 Fayetteville Police Department Weapons Verbal Warning \n", + "74 Fayetteville Police Department Weapons Written Warning \n", + "75 Greensboro Police Department Alcohol Citation Issued \n", + "76 Greensboro Police Department Alcohol No Action Taken \n", + "77 Greensboro Police Department Alcohol On-View Arrest \n", + "78 Greensboro Police Department Alcohol Verbal Warning \n", + "79 Greensboro Police Department Alcohol Written Warning \n", + "80 Greensboro Police Department Drugs Citation Issued \n", + "81 Greensboro Police Department Drugs No Action Taken \n", + "82 Greensboro Police Department Drugs On-View Arrest \n", + "83 Greensboro Police Department Drugs Verbal Warning \n", + "84 Greensboro Police Department Drugs Written Warning \n", + "85 Greensboro Police Department Money Citation Issued \n", + "86 Greensboro Police Department Money No Action Taken \n", + "87 Greensboro Police Department Money On-View Arrest \n", + "88 Greensboro Police Department Money Verbal Warning \n", + "89 Greensboro Police Department Money Written Warning \n", + "90 Greensboro Police Department Other Citation Issued \n", + "91 Greensboro Police Department Other No Action Taken \n", + "92 Greensboro Police Department Other On-View Arrest \n", + "93 Greensboro Police Department Other Verbal Warning \n", + "94 Greensboro Police Department Other Written Warning \n", + "95 Greensboro Police Department Weapons Citation Issued \n", + "96 Greensboro Police Department Weapons No Action Taken \n", + "97 Greensboro Police Department Weapons On-View Arrest \n", + "98 Greensboro Police Department Weapons Verbal Warning \n", + "99 Greensboro Police Department Weapons Written Warning \n", + "100 Raleigh Police Department Alcohol Citation Issued \n", + "101 Raleigh Police Department Alcohol No Action Taken \n", + "102 Raleigh Police Department Alcohol On-View Arrest \n", + "103 Raleigh Police Department Alcohol Verbal Warning \n", + "104 Raleigh Police Department Alcohol Written Warning \n", + "105 Raleigh Police Department Drugs Citation Issued \n", + "106 Raleigh Police Department Drugs No Action Taken \n", + "107 Raleigh Police Department Drugs On-View Arrest \n", + "108 Raleigh Police Department Drugs Verbal Warning \n", + "109 Raleigh Police Department Drugs Written Warning \n", + "110 Raleigh Police Department Money Citation Issued \n", + "111 Raleigh Police Department Money No Action Taken \n", + "112 Raleigh Police Department Money On-View Arrest \n", + "113 Raleigh Police Department Money Verbal Warning \n", + "114 Raleigh Police Department Money Written Warning \n", + "115 Raleigh Police Department Other Citation Issued \n", + "116 Raleigh Police Department Other No Action Taken \n", + "117 Raleigh Police Department Other On-View Arrest \n", + "118 Raleigh Police Department Other Verbal Warning \n", + "119 Raleigh Police Department Other Written Warning \n", + "120 Raleigh Police Department Weapons Citation Issued \n", + "121 Raleigh Police Department Weapons No Action Taken \n", + "122 Raleigh Police Department Weapons On-View Arrest \n", + "123 Raleigh Police Department Weapons Verbal Warning \n", + "124 Raleigh Police Department Weapons Written Warning \n", + "\n", + " all_stop_count all_search_count contraband_count \\\n", + "0 2163995 120888 1957 \n", + "1 2163995 120888 49 \n", + "2 2163995 120888 2385 \n", + "3 2163995 120888 746 \n", + "4 2163995 120888 51 \n", + "5 2163995 120888 3073 \n", + "6 2163995 120888 121 \n", + "7 2163995 120888 6406 \n", + "8 2163995 120888 575 \n", + "9 2163995 120888 67 \n", + "10 2163995 120888 194 \n", + "11 2163995 120888 22 \n", + "12 2163995 120888 2017 \n", + "13 2163995 120888 49 \n", + "14 2163995 120888 11 \n", + "15 2163995 120888 1818 \n", + "16 2163995 120888 78 \n", + "17 2163995 120888 2520 \n", + "18 2163995 120888 997 \n", + "19 2163995 120888 41 \n", + "20 2163995 120888 1188 \n", + "21 2163995 120888 74 \n", + "22 2163995 120888 4437 \n", + "23 2163995 120888 366 \n", + "24 2163995 120888 41 \n", + "25 377433 23809 209 \n", + "26 377433 23809 3 \n", + "27 377433 23809 268 \n", + "28 377433 23809 37 \n", + "29 377433 23809 9 \n", + "30 377433 23809 1876 \n", + "31 377433 23809 33 \n", + "32 377433 23809 1793 \n", + "33 377433 23809 706 \n", + "34 377433 23809 282 \n", + "35 377433 23809 95 \n", + "36 377433 23809 3 \n", + "37 377433 23809 527 \n", + "38 377433 23809 61 \n", + "39 377433 23809 58 \n", + "40 377433 23809 183 \n", + "41 377433 23809 9 \n", + "42 377433 23809 181 \n", + "43 377433 23809 38 \n", + "44 377433 23809 15 \n", + "45 377433 23809 372 \n", + "46 377433 23809 11 \n", + "47 377433 23809 675 \n", + "48 377433 23809 93 \n", + "49 377433 23809 34 \n", + "50 786646 32032 843 \n", + "51 786646 32032 5 \n", + "52 786646 32032 441 \n", + "53 786646 32032 0 \n", + "54 786646 32032 133 \n", + "55 786646 32032 3163 \n", + "56 786646 32032 39 \n", + "57 786646 32032 2277 \n", + "58 786646 32032 10 \n", + "59 786646 32032 876 \n", + "60 786646 32032 74 \n", + "61 786646 32032 3 \n", + "62 786646 32032 345 \n", + "63 786646 32032 0 \n", + "64 786646 32032 33 \n", + "65 786646 32032 295 \n", + "66 786646 32032 6 \n", + "67 786646 32032 149 \n", + "68 786646 32032 0 \n", + "69 786646 32032 87 \n", + "70 786646 32032 618 \n", + "71 786646 32032 16 \n", + "72 786646 32032 657 \n", + "73 786646 32032 5 \n", + "74 786646 32032 191 \n", + "75 703843 34935 743 \n", + "76 703843 34935 3 \n", + "77 703843 34935 619 \n", + "78 703843 34935 74 \n", + "79 703843 34935 15 \n", + "80 703843 34935 3343 \n", + "81 703843 34935 21 \n", + "82 703843 34935 3358 \n", + "83 703843 34935 441 \n", + "84 703843 34935 107 \n", + "85 703843 34935 102 \n", + "86 703843 34935 3 \n", + "87 703843 34935 542 \n", + "88 703843 34935 26 \n", + "89 703843 34935 12 \n", + "90 703843 34935 248 \n", + "91 703843 34935 3 \n", + "92 703843 34935 253 \n", + "93 703843 34935 39 \n", + "94 703843 34935 10 \n", + "95 703843 34935 626 \n", + "96 703843 34935 16 \n", + "97 703843 34935 1061 \n", + "98 703843 34935 88 \n", + "99 703843 34935 17 \n", + "100 1143117 46401 99 \n", + "101 1143117 46401 0 \n", + "102 1143117 46401 120 \n", + "103 1143117 46401 7 \n", + "104 1143117 46401 1 \n", + "105 1143117 46401 3243 \n", + "106 1143117 46401 24 \n", + "107 1143117 46401 2130 \n", + "108 1143117 46401 677 \n", + "109 1143117 46401 13 \n", + "110 1143117 46401 84 \n", + "111 1143117 46401 1 \n", + "112 1143117 46401 277 \n", + "113 1143117 46401 26 \n", + "114 1143117 46401 0 \n", + "115 1143117 46401 0 \n", + "116 1143117 46401 0 \n", + "117 1143117 46401 0 \n", + "118 1143117 46401 0 \n", + "119 1143117 46401 0 \n", + "120 1143117 46401 0 \n", + "121 1143117 46401 0 \n", + "122 1143117 46401 0 \n", + "123 1143117 46401 0 \n", + "124 1143117 46401 0 \n", + "\n", + " contraband_and_driver_arrest_count driver_contraband_arrest_rate \\\n", + "0 46 0.023505 \n", + "1 1 0.020408 \n", + "2 1182 0.495597 \n", + "3 7 0.009383 \n", + "4 0 0.000000 \n", + "5 89 0.028962 \n", + "6 0 0.000000 \n", + "7 2605 0.406650 \n", + "8 9 0.015652 \n", + "9 0 0.000000 \n", + "10 30 0.154639 \n", + "11 0 0.000000 \n", + "12 1194 0.591968 \n", + "13 7 0.142857 \n", + "14 0 0.000000 \n", + "15 74 0.040704 \n", + "16 0 0.000000 \n", + "17 1445 0.573413 \n", + "18 5 0.005015 \n", + "19 0 0.000000 \n", + "20 142 0.119529 \n", + "21 0 0.000000 \n", + "22 2911 0.656074 \n", + "23 22 0.060109 \n", + "24 0 0.000000 \n", + "25 17 0.081340 \n", + "26 0 0.000000 \n", + "27 208 0.776119 \n", + "28 0 0.000000 \n", + "29 0 0.000000 \n", + "30 167 0.089019 \n", + "31 2 0.060606 \n", + "32 1447 0.807027 \n", + "33 26 0.036827 \n", + "34 32 0.113475 \n", + "35 36 0.378947 \n", + "36 1 0.333333 \n", + "37 446 0.846300 \n", + "38 8 0.131148 \n", + "39 15 0.258621 \n", + "40 13 0.071038 \n", + "41 0 0.000000 \n", + "42 139 0.767956 \n", + "43 0 0.000000 \n", + "44 0 0.000000 \n", + "45 36 0.096774 \n", + "46 0 0.000000 \n", + "47 551 0.816296 \n", + "48 3 0.032258 \n", + "49 5 0.147059 \n", + "50 28 0.033215 \n", + "51 0 0.000000 \n", + "52 351 0.795918 \n", + "53 0 NaN \n", + "54 3 0.022556 \n", + "55 112 0.035409 \n", + "56 0 0.000000 \n", + "57 1895 0.832235 \n", + "58 1 0.100000 \n", + "59 23 0.026256 \n", + "60 11 0.148649 \n", + "61 0 0.000000 \n", + "62 313 0.907246 \n", + "63 0 NaN \n", + "64 4 0.121212 \n", + "65 7 0.023729 \n", + "66 0 0.000000 \n", + "67 123 0.825503 \n", + "68 0 NaN \n", + "69 0 0.000000 \n", + "70 23 0.037217 \n", + "71 0 0.000000 \n", + "72 539 0.820396 \n", + "73 0 0.000000 \n", + "74 6 0.031414 \n", + "75 108 0.145357 \n", + "76 0 0.000000 \n", + "77 457 0.738288 \n", + "78 1 0.013514 \n", + "79 2 0.133333 \n", + "80 563 0.168412 \n", + "81 1 0.047619 \n", + "82 2437 0.725730 \n", + "83 19 0.043084 \n", + "84 23 0.214953 \n", + "85 35 0.343137 \n", + "86 0 0.000000 \n", + "87 418 0.771218 \n", + "88 2 0.076923 \n", + "89 1 0.083333 \n", + "90 44 0.177419 \n", + "91 0 0.000000 \n", + "92 170 0.671937 \n", + "93 2 0.051282 \n", + "94 2 0.200000 \n", + "95 86 0.137380 \n", + "96 1 0.062500 \n", + "97 811 0.764373 \n", + "98 0 0.000000 \n", + "99 2 0.117647 \n", + "100 6 0.060606 \n", + "101 0 NaN \n", + "102 27 0.225000 \n", + "103 0 0.000000 \n", + "104 0 0.000000 \n", + "105 346 0.106691 \n", + "106 4 0.166667 \n", + "107 1463 0.686854 \n", + "108 108 0.159527 \n", + "109 0 0.000000 \n", + "110 28 0.333333 \n", + "111 0 0.000000 \n", + "112 186 0.671480 \n", + "113 15 0.576923 \n", + "114 0 NaN \n", + "115 0 NaN \n", + "116 0 NaN \n", + "117 0 NaN \n", + "118 0 NaN \n", + "119 0 NaN \n", + "120 0 NaN \n", + "121 0 NaN \n", + "122 0 NaN \n", + "123 0 NaN \n", + "124 0 NaN \n", + "\n", + " driver_stop_arrest_rate \n", + "0 2.125698e-05 \n", + "1 4.621083e-07 \n", + "2 5.462120e-04 \n", + "3 3.234758e-06 \n", + "4 0.000000e+00 \n", + "5 4.112764e-05 \n", + "6 0.000000e+00 \n", + "7 1.203792e-03 \n", + "8 4.158974e-06 \n", + "9 0.000000e+00 \n", + "10 1.386325e-05 \n", + "11 0.000000e+00 \n", + "12 5.517573e-04 \n", + "13 3.234758e-06 \n", + "14 0.000000e+00 \n", + "15 3.419601e-05 \n", + "16 0.000000e+00 \n", + "17 6.677465e-04 \n", + "18 2.310541e-06 \n", + "19 0.000000e+00 \n", + "20 6.561938e-05 \n", + "21 0.000000e+00 \n", + "22 1.345197e-03 \n", + "23 1.016638e-05 \n", + "24 0.000000e+00 \n", + "25 4.504111e-05 \n", + "26 0.000000e+00 \n", + "27 5.510912e-04 \n", + "28 0.000000e+00 \n", + "29 0.000000e+00 \n", + "30 4.424626e-04 \n", + "31 5.298954e-06 \n", + "32 3.833793e-03 \n", + "33 6.888640e-05 \n", + "34 8.478326e-05 \n", + "35 9.538117e-05 \n", + "36 2.649477e-06 \n", + "37 1.181667e-03 \n", + "38 2.119581e-05 \n", + "39 3.974215e-05 \n", + "40 3.444320e-05 \n", + "41 0.000000e+00 \n", + "42 3.682773e-04 \n", + "43 0.000000e+00 \n", + "44 0.000000e+00 \n", + "45 9.538117e-05 \n", + "46 0.000000e+00 \n", + "47 1.459862e-03 \n", + "48 7.948431e-06 \n", + "49 1.324738e-05 \n", + "50 3.559416e-05 \n", + "51 0.000000e+00 \n", + "52 4.461982e-04 \n", + "53 0.000000e+00 \n", + "54 3.813660e-06 \n", + "55 1.423766e-04 \n", + "56 0.000000e+00 \n", + "57 2.408962e-03 \n", + "58 1.271220e-06 \n", + "59 2.923806e-05 \n", + "60 1.398342e-05 \n", + "61 0.000000e+00 \n", + "62 3.978918e-04 \n", + "63 0.000000e+00 \n", + "64 5.084879e-06 \n", + "65 8.898539e-06 \n", + "66 0.000000e+00 \n", + "67 1.563600e-04 \n", + "68 0.000000e+00 \n", + "69 0.000000e+00 \n", + "70 2.923806e-05 \n", + "71 0.000000e+00 \n", + "72 6.851875e-04 \n", + "73 0.000000e+00 \n", + "74 7.627319e-06 \n", + "75 1.534433e-04 \n", + "76 0.000000e+00 \n", + "77 6.492925e-04 \n", + "78 1.420771e-06 \n", + "79 2.841543e-06 \n", + "80 7.998943e-04 \n", + "81 1.420771e-06 \n", + "82 3.462420e-03 \n", + "83 2.699466e-05 \n", + "84 3.267774e-05 \n", + "85 4.972700e-05 \n", + "86 0.000000e+00 \n", + "87 5.938824e-04 \n", + "88 2.841543e-06 \n", + "89 1.420771e-06 \n", + "90 6.251394e-05 \n", + "91 0.000000e+00 \n", + "92 2.415311e-04 \n", + "93 2.841543e-06 \n", + "94 2.841543e-06 \n", + "95 1.221863e-04 \n", + "96 1.420771e-06 \n", + "97 1.152246e-03 \n", + "98 0.000000e+00 \n", + "99 2.841543e-06 \n", + "100 5.248807e-06 \n", + "101 0.000000e+00 \n", + "102 2.361963e-05 \n", + "103 0.000000e+00 \n", + "104 0.000000e+00 \n", + "105 3.026812e-04 \n", + "106 3.499204e-06 \n", + "107 1.279834e-03 \n", + "108 9.447852e-05 \n", + "109 0.000000e+00 \n", + "110 2.449443e-05 \n", + "111 0.000000e+00 \n", + "112 1.627130e-04 \n", + "113 1.312202e-05 \n", + "114 0.000000e+00 \n", + "115 0.000000e+00 \n", + "116 0.000000e+00 \n", + "117 0.000000e+00 \n", + "118 0.000000e+00 \n", + "119 0.000000e+00 \n", + "120 0.000000e+00 \n", + "121 0.000000e+00 \n", + "122 0.000000e+00 \n", + "123 0.000000e+00 \n", + "124 0.000000e+00 " + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_sql(\n", + " f\"\"\"\n", + " WITH stops AS (\n", + " SELECT\n", + " agency_id\n", + " , agency_description AS agency\n", + " , count(*) as stop_count\n", + " , count(DISTINCT nc_search.search_id) AS search_count\n", + " FROM nc_stop\n", + " LEFT OUTER JOIN nc_search ON (nc_search.stop_id = nc_stop.stop_id)\n", + " WHERE nc_stop.agency_id IN ({\",\".join(map(str, agency_ids))})\n", + " GROUP BY 1, 2\n", + " )\n", + " SELECT\n", + " agency\n", + " , contraband_type\n", + " , stop_action\n", + " , stop_count AS all_stop_count\n", + " , search_count AS all_search_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true) AS contraband_count\n", + " , count(stop_id) FILTER (WHERE contraband_found = true AND driver_arrest = true) AS contraband_and_driver_arrest_count\n", + " FROM nc_contrabandsummary summary\n", + " JOIN stops ON (stops.agency_id = summary.agency_id)\n", + " WHERE summary.agency_id IN ({\",\".join(map(str, agency_ids))})\n", + " AND contraband_type is not null\n", + " GROUP BY 1, 2, 3, 4, 5\n", + " ORDER BY 1, 2, 3\n", + " \"\"\",\n", + " pg_engine,\n", + " # dtype={\"year\": \"Int64\"}\n", + ")\n", + "df[\"driver_contraband_arrest_rate\"] = df.contraband_and_driver_arrest_count / df.contraband_count\n", + "df[\"driver_stop_arrest_rate\"] = df.contraband_and_driver_arrest_count / df.all_stop_count\n", + "# df.loc['Total'] = df.sum(numeric_only=True)\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "54753817-f763-4371-8f0f-1d2afe0f0612", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + }, + "toc-autonumbering": true + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/nc/notebooks/requirements.txt b/nc/notebooks/requirements.txt index d019ad08..78aead6d 100644 --- a/nc/notebooks/requirements.txt +++ b/nc/notebooks/requirements.txt @@ -1,5 +1,5 @@ -SQLAlchemy==1.4.46 -pandas==1.5.3 +SQLAlchemy==2.0.25 +pandas==2.2.0 jupyterlab==3.5.3 jupyter-dash==0.4.2 jupyter_server>=2.0.0 From a775b80ab42c0d050c38c90ee69eb1c1e4ce41dd Mon Sep 17 00:00:00 2001 From: Aristotel Fani Date: Tue, 16 Apr 2024 12:19:32 -0400 Subject: [PATCH 03/24] Add table data for arrest graphs (#287) --- .../src/Components/Charts/Arrest/Arrests.js | 35 --- .../Arrest/Charts/CountOfStopsAndArrests.js | 25 +- .../Arrest/Charts/PercentageOfSearches.js | 25 +- .../PercentageOfSearchesForPurposeGroup.js | 76 +++--- .../PercentageOfSearchesPerStopPurpose.js | 74 +++--- .../Charts/Arrest/Charts/PercentageOfStops.js | 25 +- .../PercentageOfStopsForPurposeGroup.js | 75 +++--- .../PercentageOfStopsPerContrabandType.js | 16 +- .../Charts/PercentageOfStopsPerStopPurpose.js | 73 +++--- .../Charts/Contraband/Contraband.js | 80 +----- .../Charts/SearchRate/SearchRate.js | 43 +-- .../Components/Charts/Searches/Searches.js | 39 +-- .../Charts/TrafficStops/TrafficStops.js | 117 +-------- .../Charts/UseOfForce/UseOfForce.js | 38 +-- frontend/src/Components/Charts/chartUtils.js | 119 +++++++++ frontend/src/util/createTableData.js | 21 ++ nc/views.py | 245 +++++++++--------- 17 files changed, 464 insertions(+), 662 deletions(-) create mode 100644 frontend/src/util/createTableData.js diff --git a/frontend/src/Components/Charts/Arrest/Arrests.js b/frontend/src/Components/Charts/Arrest/Arrests.js index 1cb96b48..ad3057c0 100644 --- a/frontend/src/Components/Charts/Arrest/Arrests.js +++ b/frontend/src/Components/Charts/Arrest/Arrests.js @@ -99,38 +99,3 @@ function Arrests(props) { } export default Arrests; - -export const ARRESTS_TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', // accessor is the "key" in the data - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; diff --git a/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js b/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js index f53441b5..6564eacd 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js +++ b/frontend/src/Components/Charts/Arrest/Charts/CountOfStopsAndArrests.js @@ -9,7 +9,8 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import createTableData from '../../../../util/createTableData'; +import { RACE_TABLE_COLUMNS } from '../../chartUtils'; function CountOfStopsAndArrests(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -40,25 +41,7 @@ function CountOfStopsAndArrests(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); + const tableData = createTableData(res.data); const labels = ['Stops With Arrests', 'Stops Without Arrests']; const colors = ['#96a0fa', '#5364f4']; @@ -115,7 +98,7 @@ function CountOfStopsAndArrests(props) { agencyName={agencyName} tableData={arrestData.tableData} csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" isOpen={arrestData.isOpen} closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js index 7f35db85..28f224ce 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearches.js @@ -9,7 +9,8 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import createTableData from '../../../../util/createTableData'; +import { RACE_TABLE_COLUMNS } from '../../chartUtils'; function PercentageOfSearches(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -40,25 +41,7 @@ function PercentageOfSearches(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); + const tableData = createTableData(res.data); const colors = ['#02bcbb', '#8879fc', '#9c0f2e', '#ffe066', '#0c3a66', '#9e7b9b']; const data = { labels: ['White', 'Black', 'Hispanic', 'Asian', 'Native American', 'Other'], @@ -113,7 +96,7 @@ function PercentageOfSearches(props) { agencyName={agencyName} tableData={arrestData.tableData} csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_Percentage_Of_Searches" isOpen={arrestData.isOpen} closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js index 2c4fc577..485b6b8c 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesForPurposeGroup.js @@ -9,7 +9,9 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import createTableData from '../../../../util/createTableData'; +import DataSubsetPicker from '../../ChartSections/DataSubsetPicker/DataSubsetPicker'; +import { RACE_TABLE_COLUMNS, STOP_PURPOSE_GROUPS } from '../../chartUtils'; function PercentageOfSearchesForStopPurposeGroup(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -19,13 +21,17 @@ function PercentageOfSearchesForStopPurposeGroup(props) { const initArrestData = { labels: [], datasets: [], - isModalOpen: false, - tableData: [], - csvData: [], loading: true, }; const [arrestData, setArrestData] = useState(initArrestData); + const [arrestTableData, setArrestTableData] = useState({ + isOpen: false, + tableData: [], + csvData: [], + }); + const [selectedStopPurpose, setSelectedStopPurpose] = useState(STOP_PURPOSE_GROUPS[0]); + useEffect(() => { const params = []; if (year && year !== 'All') { @@ -40,26 +46,6 @@ function PercentageOfSearchesForStopPurposeGroup(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); - const colors = { 'Safety Violation': '#5F0F40', 'Regulatory Equipment': '#E36414', @@ -79,15 +65,30 @@ function PercentageOfSearchesForStopPurposeGroup(props) { borderWidth: 1, }, ], - isModalOpen: false, - tableData, - csvData: tableData, }; setArrestData(data); }) .catch((err) => console.log(err)); }, [year]); + useEffect(() => { + const params = []; + params.push({ + param: 'grouped_stop_purpose', + val: selectedStopPurpose, + }); + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${encodeURI(p.val)}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-searches-by-purpose-group/?modal=true&${urlParams}`; + axios.get(url).then((res) => { + const tableData = createTableData(res.data); + setArrestTableData((state) => ({ ...state, tableData, csvData: tableData })); + }); + }, [selectedStopPurpose]); + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; const subjectObserving = () => { @@ -108,7 +109,7 @@ function PercentageOfSearchesForStopPurposeGroup(props) { setArrestData((state) => ({ ...state, isOpen: true }))} + handleViewData={() => setArrestTableData((state) => ({ ...state, isOpen: true }))} />

Percentage of stops that led to an arrest for a given stop purpose group.

@@ -116,13 +117,20 @@ function PercentageOfSearchesForStopPurposeGroup(props) { tableHeader="Percentage of Searches With Arrests Per Stop Purpose Group" tableSubheader="Shows what percentage of searches led to an arrest for a given stop purpose group." agencyName={agencyName} - tableData={arrestData.tableData} - csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + tableData={arrestTableData.tableData} + csvData={arrestTableData.csvData} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" - isOpen={arrestData.isOpen} - closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} - /> + isOpen={arrestTableData.isOpen} + closeModal={() => setArrestTableData((state) => ({ ...state, isOpen: false }))} + > + setSelectedStopPurpose(stopPurpose)} + options={STOP_PURPOSE_GROUPS} + /> + diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js index 5093e025..8bf3db72 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfSearchesPerStopPurpose.js @@ -9,7 +9,9 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import createTableData from '../../../../util/createTableData'; +import DataSubsetPicker from '../../ChartSections/DataSubsetPicker/DataSubsetPicker'; +import { RACE_TABLE_COLUMNS, STOP_PURPOSE_TYPES } from '../../chartUtils'; function PercentageOfStopsForStopPurpose(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -26,6 +28,14 @@ function PercentageOfStopsForStopPurpose(props) { }; const [arrestData, setArrestData] = useState(initArrestData); + const [arrestTableData, setArrestTableData] = useState({ + isOpen: false, + tableData: [], + csvData: [], + }); + + const [selectedStopPurpose, setSelectedStopPurpose] = useState(STOP_PURPOSE_TYPES[0]); + useEffect(() => { const params = []; if (year && year !== 'All') { @@ -40,26 +50,6 @@ function PercentageOfStopsForStopPurpose(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); - const data = { labels: res.data.labels, datasets: [ @@ -74,15 +64,30 @@ function PercentageOfStopsForStopPurpose(props) { borderWidth: 1, }, ], - isModalOpen: false, - tableData, - csvData: tableData, }; setArrestData(data); }) .catch((err) => console.log(err)); }, [year]); + useEffect(() => { + const params = []; + params.push({ + param: 'stop_purpose_type', + val: selectedStopPurpose, + }); + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${encodeURI(p.val)}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-searches-per-stop-purpose/?modal=true&${urlParams}`; + axios.get(url).then((res) => { + const tableData = createTableData(res.data); + setArrestTableData((state) => ({ ...state, tableData, csvData: tableData })); + }); + }, [selectedStopPurpose]); + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; const subjectObserving = () => { @@ -103,7 +108,7 @@ function PercentageOfStopsForStopPurpose(props) { setArrestData((state) => ({ ...state, isOpen: true }))} + handleViewData={() => setArrestTableData((state) => ({ ...state, isOpen: true }))} />

Percentage of searches that led to an arrest for a given stop purpose.

@@ -111,13 +116,20 @@ function PercentageOfStopsForStopPurpose(props) { tableHeader="Percentage of Searches With Arrests Per Stop Purpose" tableSubheader="Shows what percentage of searches led to an arrest for a given stop purpose." agencyName={agencyName} - tableData={arrestData.tableData} - csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + tableData={arrestTableData.tableData} + csvData={arrestTableData.csvData} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" - isOpen={arrestData.isOpen} - closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} - /> + isOpen={arrestTableData.isOpen} + closeModal={() => setArrestTableData((state) => ({ ...state, isOpen: false }))} + > + setSelectedStopPurpose(stopPurpose)} + options={STOP_PURPOSE_TYPES} + /> + diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js index 2a6ad5ba..c273e73e 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStops.js @@ -9,7 +9,8 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import createTableData from '../../../../util/createTableData'; +import { RACE_TABLE_COLUMNS } from '../../chartUtils'; function PercentageOfStops(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -40,25 +41,7 @@ function PercentageOfStops(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); + const tableData = createTableData(res.data); const colors = ['#02bcbb', '#8879fc', '#9c0f2e', '#ffe066', '#0c3a66', '#9e7b9b']; const data = { labels: ['White', 'Black', 'Hispanic', 'Asian', 'Native American', 'Other'], @@ -113,7 +96,7 @@ function PercentageOfStops(props) { agencyName={agencyName} tableData={arrestData.tableData} csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" isOpen={arrestData.isOpen} closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js index 2f5fd55d..48f0451d 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsForPurposeGroup.js @@ -9,7 +9,9 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import DataSubsetPicker from '../../ChartSections/DataSubsetPicker/DataSubsetPicker'; +import createTableData from '../../../../util/createTableData'; +import { RACE_TABLE_COLUMNS, STOP_PURPOSE_GROUPS } from '../../chartUtils'; function PercentageOfStopsForStopPurposeGroup(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -19,12 +21,15 @@ function PercentageOfStopsForStopPurposeGroup(props) { const initArrestData = { labels: [], datasets: [], - isModalOpen: false, - tableData: [], - csvData: [], loading: true, }; const [arrestData, setArrestData] = useState(initArrestData); + const [arrestTableData, setArrestTableData] = useState({ + isOpen: false, + tableData: [], + csvData: [], + }); + const [selectedStopPurpose, setSelectedStopPurpose] = useState(STOP_PURPOSE_GROUPS[0]); useEffect(() => { const params = []; @@ -40,26 +45,6 @@ function PercentageOfStopsForStopPurposeGroup(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); - const colors = { 'Safety Violation': '#5F0F40', 'Regulatory Equipment': '#E36414', @@ -79,15 +64,30 @@ function PercentageOfStopsForStopPurposeGroup(props) { borderWidth: 1, }, ], - isModalOpen: false, - tableData, - csvData: tableData, }; setArrestData(data); }) .catch((err) => console.log(err)); }, [year]); + useEffect(() => { + const params = []; + params.push({ + param: 'grouped_stop_purpose', + val: selectedStopPurpose, + }); + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${encodeURI(p.val)}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-stops-by-purpose-group/?modal=true&${urlParams}`; + axios.get(url).then((res) => { + const tableData = createTableData(res.data); + setArrestTableData((state) => ({ ...state, tableData, csvData: tableData })); + }); + }, [selectedStopPurpose]); + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; const subjectObserving = () => { @@ -108,7 +108,7 @@ function PercentageOfStopsForStopPurposeGroup(props) { setArrestData((state) => ({ ...state, isOpen: true }))} + handleViewData={() => setArrestTableData((state) => ({ ...state, isOpen: true }))} />

Percentage of stops that led to an arrest for a given stop purpose group.

@@ -116,13 +116,20 @@ function PercentageOfStopsForStopPurposeGroup(props) { tableHeader="Percentage of Stops With Arrests Per Stop Purpose Group" tableSubheader="Shows what percentage of stops led to an arrest for a given stop purpose group." agencyName={agencyName} - tableData={arrestData.tableData} - csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + tableData={arrestTableData.tableData} + csvData={arrestTableData.csvData} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" - isOpen={arrestData.isOpen} - closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} - /> + isOpen={arrestTableData.isOpen} + closeModal={() => setArrestTableData((state) => ({ ...state, isOpen: false }))} + > + setSelectedStopPurpose(stopPurpose)} + options={STOP_PURPOSE_GROUPS} + /> + diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js index ce5a51a9..0538ee62 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerContrabandType.js @@ -9,7 +9,7 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import { CONTRABAND_TYPES_TABLE_COLUMNS } from '../../chartUtils'; function PercentageOfStopsPerContrabandType(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -50,16 +50,14 @@ function PercentageOfStopsPerContrabandType(props) { // Need to assign explicitly otherwise the download data orders columns by alphabet. tableData.unshift({ year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, + alcohol: e.alcohol, + drugs: e.drugs, + money: e.money, other: e.other, - hispanic: e.hispanic, + weapons: e.weapons, total: Object.values(dataCounts).reduce((a, b) => a + b, 0), }); }); - const colors = ['#9FD356', '#3C91E6', '#EFCEFA', '#2F4858', '#A653F4']; const data = { labels: ['Alcohol', 'Drugs', 'Money', 'Other', 'Weapons'], @@ -75,9 +73,9 @@ function PercentageOfStopsPerContrabandType(props) { borderWidth: 1, }, ], - isModalOpen: false, tableData, csvData: tableData, + isModalOpen: false, }; setArrestData(data); }) @@ -114,7 +112,7 @@ function PercentageOfStopsPerContrabandType(props) { agencyName={agencyName} tableData={arrestData.tableData} csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + columns={CONTRABAND_TYPES_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" isOpen={arrestData.isOpen} closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} diff --git a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js index 87d1e4bd..18cd37f0 100644 --- a/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js +++ b/frontend/src/Components/Charts/Arrest/Charts/PercentageOfStopsPerStopPurpose.js @@ -9,7 +9,9 @@ import axios from '../../../../Services/Axios'; import useOfficerId from '../../../../Hooks/useOfficerId'; import { ChartWrapper } from '../Arrests.styles'; import NewModal from '../../../NewCharts/NewModal'; -import { ARRESTS_TABLE_COLUMNS } from '../Arrests'; +import createTableData from '../../../../util/createTableData'; +import DataSubsetPicker from '../../ChartSections/DataSubsetPicker/DataSubsetPicker'; +import { RACE_TABLE_COLUMNS, STOP_PURPOSE_TYPES } from '../../chartUtils'; function PercentageOfStopsForStopPurpose(props) { const { agencyId, agencyName, showCompare, year } = props; @@ -26,6 +28,13 @@ function PercentageOfStopsForStopPurpose(props) { }; const [arrestData, setArrestData] = useState(initArrestData); + const [arrestTableData, setArrestTableData] = useState({ + isOpen: false, + tableData: [], + csvData: [], + }); + const [selectedStopPurpose, setSelectedStopPurpose] = useState(STOP_PURPOSE_TYPES[0]); + useEffect(() => { const params = []; if (year && year !== 'All') { @@ -40,26 +49,6 @@ function PercentageOfStopsForStopPurpose(props) { axios .get(url) .then((res) => { - const tableData = []; - const resTableData = res.data.table_data.length - ? JSON.parse(res.data.table_data) - : { data: [] }; - resTableData.data.forEach((e) => { - const dataCounts = { ...e }; - delete dataCounts.year; - // Need to assign explicitly otherwise the download data orders columns by alphabet. - tableData.unshift({ - year: e.year, - white: e.white, - black: e.black, - native_american: e.native_american, - asian: e.asian, - other: e.other, - hispanic: e.hispanic, - total: Object.values(dataCounts).reduce((a, b) => a + b, 0), - }); - }); - const data = { labels: res.data.labels, datasets: [ @@ -74,15 +63,30 @@ function PercentageOfStopsForStopPurpose(props) { borderWidth: 1, }, ], - isModalOpen: false, - tableData, - csvData: tableData, }; setArrestData(data); }) .catch((err) => console.log(err)); }, [year]); + useEffect(() => { + const params = []; + params.push({ + param: 'stop_purpose_type', + val: selectedStopPurpose, + }); + if (officerId) { + params.push({ param: 'officer', val: officerId }); + } + + const urlParams = params.map((p) => `${p.param}=${encodeURI(p.val)}`).join('&'); + const url = `/api/agency/${agencyId}/arrests-percentage-of-stops-per-stop-purpose/?modal=true&${urlParams}`; + axios.get(url).then((res) => { + const tableData = createTableData(res.data); + setArrestTableData((state) => ({ ...state, tableData, csvData: tableData })); + }); + }, [selectedStopPurpose]); + const formatTooltipValue = (ctx) => `${(ctx.raw * 100).toFixed(2)}%`; const subjectObserving = () => { @@ -103,7 +107,7 @@ function PercentageOfStopsForStopPurpose(props) { setArrestData((state) => ({ ...state, isOpen: true }))} + handleViewData={() => setArrestTableData((state) => ({ ...state, isOpen: true }))} />

Percentage of stops that led to an arrest for a given stop purpose group.

@@ -111,13 +115,20 @@ function PercentageOfStopsForStopPurpose(props) { tableHeader="Percentage of Stops With Arrests Per Stop Purpose" tableSubheader="Shows what percentage of stops led to an arrest for a given stop purpose." agencyName={agencyName} - tableData={arrestData.tableData} - csvData={arrestData.csvData} - columns={ARRESTS_TABLE_COLUMNS} + tableData={arrestTableData.tableData} + csvData={arrestTableData.csvData} + columns={RACE_TABLE_COLUMNS} tableDownloadName="Arrests_By_Percentage" - isOpen={arrestData.isOpen} - closeModal={() => setArrestData((state) => ({ ...state, isOpen: false }))} - /> + isOpen={arrestTableData.isOpen} + closeModal={() => setArrestTableData((state) => ({ ...state, isOpen: false }))} + > + setSelectedStopPurpose(stopPurpose)} + options={STOP_PURPOSE_TYPES} + /> + diff --git a/frontend/src/Components/Charts/Contraband/Contraband.js b/frontend/src/Components/Charts/Contraband/Contraband.js index 5a0d1c26..c05fe068 100644 --- a/frontend/src/Components/Charts/Contraband/Contraband.js +++ b/frontend/src/Components/Charts/Contraband/Contraband.js @@ -7,7 +7,13 @@ import ContrabandStyled, { import * as S from '../ChartSections/ChartsCommon.styled'; // Util -import { CONTRABAND_TYPES, STATIC_CONTRABAND_KEYS, YEARS_DEFAULT } from '../chartUtils'; +import { + CONTRABAND_TYPES, + CONTRABAND_TYPES_TABLE_COLUMNS, + RACE_TABLE_COLUMNS, + STATIC_CONTRABAND_KEYS, + YEARS_DEFAULT, +} from '../chartUtils'; // Hooks import useMetaTags from '../../../Hooks/useMetaTags'; @@ -580,7 +586,7 @@ function Contraband(props) { agencyName={chartState.data[AGENCY_DETAILS].name} tableData={contrabandData.tableData} csvData={contrabandData.csvData} - columns={CONTRABAND_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName='Contraband "Hit Rate"' isOpen={contrabandData.isOpen} closeModal={() => setContrabandData((state) => ({ ...state, isOpen: false }))} @@ -625,7 +631,7 @@ function Contraband(props) { agencyName={chartState.data[AGENCY_DETAILS].name} tableData={contrabandStopPurposeModalData.tableData} csvData={contrabandStopPurposeModalData.csvData} - columns={CONTRABAND_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName='Contraband "Hit Rate" Grouped By Stop Purpose' isOpen={contrabandStopPurposeModalData.isOpen} closeModal={() => @@ -725,7 +731,7 @@ function Contraband(props) { agencyName={chartState.data[AGENCY_DETAILS].name} tableData={groupedContrabandStopPurposeModalData.tableData} csvData={groupedContrabandStopPurposeModalData.csvData} - columns={CONTRABAND_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName='Contraband "Hit Rate" by Type grouped by Stop Purpose' isOpen={groupedContrabandStopPurposeModalData.isOpen} closeModal={() => @@ -851,69 +857,3 @@ function Contraband(props) { } export default Contraband; - -const CONTRABAND_TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', // accessor is the "key" in the data - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; - -const CONTRABAND_TYPES_TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', // accessor is the "key" in the data - }, - { - Header: 'Alcohol*', - accessor: 'alcohol', - }, - { - Header: 'Drugs*', - accessor: 'drugs', - }, - { - Header: 'Money*', - accessor: 'money', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Weapons*', - accessor: 'weapons', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; diff --git a/frontend/src/Components/Charts/SearchRate/SearchRate.js b/frontend/src/Components/Charts/SearchRate/SearchRate.js index 00c203e3..6cbb051a 100644 --- a/frontend/src/Components/Charts/SearchRate/SearchRate.js +++ b/frontend/src/Components/Charts/SearchRate/SearchRate.js @@ -11,7 +11,7 @@ import useMetaTags from '../../../Hooks/useMetaTags'; import useTableModal from '../../../Hooks/useTableModal'; // Constants -import { YEARS_DEFAULT } from '../chartUtils'; +import { STOP_REASON_TABLE_COLUMNS, YEARS_DEFAULT } from '../chartUtils'; // Children import { P } from '../../../styles/StyledComponents/Typography'; @@ -60,7 +60,7 @@ function SearchRate(props) { }; const handleViewData = () => { - openModal(LIKELIHOOD_OF_SEARCH, TABLE_COLUMNS); + openModal(LIKELIHOOD_OF_SEARCH, STOP_REASON_TABLE_COLUMNS); }; const formatTooltipLabel = (ctx) => ctx[0].dataset.label; @@ -150,42 +150,3 @@ function SearchRate(props) { } export default SearchRate; - -const TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', - }, - { - Header: 'Stop-reason', - accessor: 'purpose', - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; diff --git a/frontend/src/Components/Charts/Searches/Searches.js b/frontend/src/Components/Charts/Searches/Searches.js index 877bf397..b58f2f2c 100644 --- a/frontend/src/Components/Charts/Searches/Searches.js +++ b/frontend/src/Components/Charts/Searches/Searches.js @@ -3,7 +3,7 @@ import SearchesStyled from './Searches.styled'; import * as S from '../ChartSections/ChartsCommon.styled'; // Util -import { SEARCH_TYPE_DEFAULT, SEARCH_TYPES } from '../chartUtils'; +import { RACE_TABLE_COLUMNS, SEARCH_TYPE_DEFAULT, SEARCH_TYPES } from '../chartUtils'; // State import useDataset, { @@ -111,7 +111,7 @@ function Searches(props) { }; const handleViewPercentageData = () => { - openModal([STOPS, SEARCHES], PERCENTAGE_COLUMNS); + openModal([STOPS, SEARCHES], RACE_TABLE_COLUMNS); }; const handleViewCountData = () => { @@ -251,41 +251,6 @@ function Searches(props) { export default Searches; -const PERCENTAGE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; - const COUNT_COLUMNS = [ { Header: 'Year', diff --git a/frontend/src/Components/Charts/TrafficStops/TrafficStops.js b/frontend/src/Components/Charts/TrafficStops/TrafficStops.js index 69e57578..43587087 100644 --- a/frontend/src/Components/Charts/TrafficStops/TrafficStops.js +++ b/frontend/src/Components/Charts/TrafficStops/TrafficStops.js @@ -21,6 +21,8 @@ import { PURPOSE_DEFAULT, RACES, STOP_TYPES, + RACE_TABLE_COLUMNS, + STOP_REASON_TABLE_COLUMNS, } from '../chartUtils'; // State @@ -449,11 +451,11 @@ function TrafficStops(props) { const handleViewPercentageData = () => { setPurpose(PURPOSE_DEFAULT); - openModal(STOPS, STOPS_TABLE_COLUMNS); + openModal(STOPS, RACE_TABLE_COLUMNS); }; const handleViewCountData = () => { - openModal(STOPS_BY_REASON, BY_REASON_TABLE_COLUMNS); + openModal(STOPS_BY_REASON, STOP_REASON_TABLE_COLUMNS); }; const showStopPurposeModal = () => { @@ -890,7 +892,7 @@ function TrafficStops(props) { agencyName={stopsChartState.data[AGENCY_DETAILS].name} tableData={groupedStopPurposeModalData.tableData} csvData={groupedStopPurposeModalData.csvData} - columns={GROUPED_STOP_PURPOSE_TABLE_COLUMNS} + columns={RACE_TABLE_COLUMNS} tableDownloadName={`Traffic Stops By Stop Purpose and Race Count - ${groupedStopPurposeModalData.selectedPurpose}`} isOpen={groupedStopPurposeModalData.isOpen} closeModal={() => @@ -1065,80 +1067,6 @@ function TrafficStops(props) { export default TrafficStops; -const STOPS_TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; - -const BY_REASON_TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', - }, - { - Header: 'Stop-reason', - accessor: 'purpose', - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; - const STOP_PURPOSE_TABLE_COLUMNS = [ { Header: 'Year', @@ -1161,38 +1089,3 @@ const STOP_PURPOSE_TABLE_COLUMNS = [ accessor: 'total', }, ]; - -const GROUPED_STOP_PURPOSE_TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', - }, - { - Header: 'White', - accessor: 'white', - }, - { - Header: 'Black', - accessor: 'black', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Asian', - accessor: 'asian', - }, - { - Header: 'Native American', - accessor: 'native_american', - }, - { - Header: 'Other', - accessor: 'other', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; diff --git a/frontend/src/Components/Charts/UseOfForce/UseOfForce.js b/frontend/src/Components/Charts/UseOfForce/UseOfForce.js index 413cd08c..8a0f120b 100644 --- a/frontend/src/Components/Charts/UseOfForce/UseOfForce.js +++ b/frontend/src/Components/Charts/UseOfForce/UseOfForce.js @@ -9,6 +9,7 @@ import { calculatePercentage, calculateYearTotal, reduceYearsToTotal, + RACE_TABLE_COLUMNS, } from '../chartUtils'; // State @@ -118,7 +119,7 @@ function UseOfForce(props) { }; // Handle stops by percentage legend interactions const handleViewData = () => { - openModal(USE_OF_FORCE, TABLE_COLUMNS); + openModal(USE_OF_FORCE, RACE_TABLE_COLUMNS); }; const chartModalTitle = (displayYear = true) => { @@ -193,38 +194,3 @@ function UseOfForce(props) { } export default UseOfForce; - -const TABLE_COLUMNS = [ - { - Header: 'Year', - accessor: 'year', - }, - { - Header: 'White*', - accessor: 'white', - }, - { - Header: 'Black*', - accessor: 'black', - }, - { - Header: 'Native American*', - accessor: 'native_american', - }, - { - Header: 'Asian*', - accessor: 'asian', - }, - { - Header: 'Other*', - accessor: 'other', - }, - { - Header: 'Hispanic', - accessor: 'hispanic', - }, - { - Header: 'Total', - accessor: 'total', - }, -]; diff --git a/frontend/src/Components/Charts/chartUtils.js b/frontend/src/Components/Charts/chartUtils.js index a434c565..aa243e73 100644 --- a/frontend/src/Components/Charts/chartUtils.js +++ b/frontend/src/Components/Charts/chartUtils.js @@ -32,6 +32,20 @@ export const AVERAGE = { label: 'Average for all drivers', selected: true, }; +export const STOP_PURPOSE_GROUPS = ['Safety Violation', 'Regulatory and Equipment', 'Other']; + +export const STOP_PURPOSE_TYPES = [ + 'Speed Limit Violation', + 'Stop Light/Sign Violation', + 'Driving While Impaired', + 'Safe Movement Violation', + 'Vehicle Equipment Violation', + 'Vehicle Regulatory Violation', + 'Other Motor Vehicle Violation', + 'Seat Belt Violation', + 'Investigation', + 'Checkpoint', +]; export const STATIC_LEGEND_KEYS = RACES.map((r) => ({ value: r, @@ -130,3 +144,108 @@ export const reduceEthnicityByYears = (data, yearsSet, ethnicGroups = RACES) => }); return yearData; }; + +export const RACE_TABLE_COLUMNS = [ + { + Header: 'Year', + accessor: 'year', // accessor is the "key" in the data + }, + { + Header: 'White*', + accessor: 'white', + }, + { + Header: 'Black*', + accessor: 'black', + }, + { + Header: 'Native American*', + accessor: 'native_american', + }, + { + Header: 'Asian*', + accessor: 'asian', + }, + { + Header: 'Other*', + accessor: 'other', + }, + { + Header: 'Hispanic', + accessor: 'hispanic', + }, + { + Header: 'Total', + accessor: 'total', + }, +]; + +export const CONTRABAND_TYPES_TABLE_COLUMNS = [ + { + Header: 'Year', + accessor: 'year', // accessor is the "key" in the data + }, + { + Header: 'Alcohol*', + accessor: 'alcohol', + }, + { + Header: 'Drugs*', + accessor: 'drugs', + }, + { + Header: 'Money*', + accessor: 'money', + }, + { + Header: 'Other*', + accessor: 'other', + }, + { + Header: 'Weapons*', + accessor: 'weapons', + }, + { + Header: 'Total', + accessor: 'total', + }, +]; + +export const STOP_REASON_TABLE_COLUMNS = [ + { + Header: 'Year', + accessor: 'year', + }, + { + Header: 'Stop-reason', + accessor: 'purpose', + }, + { + Header: 'White*', + accessor: 'white', + }, + { + Header: 'Black*', + accessor: 'black', + }, + { + Header: 'Hispanic', + accessor: 'hispanic', + }, + { + Header: 'Asian*', + accessor: 'asian', + }, + { + Header: 'Native American*', + accessor: 'native_american', + }, + { + Header: 'Other*', + accessor: 'other', + }, + { + Header: 'Total', + accessor: 'total', + }, +]; diff --git a/frontend/src/util/createTableData.js b/frontend/src/util/createTableData.js new file mode 100644 index 00000000..0f8e2f61 --- /dev/null +++ b/frontend/src/util/createTableData.js @@ -0,0 +1,21 @@ +export default function createTableData(responseData) { + const tableData = []; + const data = responseData.table_data.length ? JSON.parse(responseData.table_data).data : []; + data.forEach((e) => { + const dataCounts = { ...e }; + delete dataCounts.year; + // Need to assign explicitly otherwise the download data orders columns by alphabet. + tableData.unshift({ + year: e.year, + white: e.white, + black: e.black, + native_american: e.native_american, + asian: e.asian, + other: e.other, + hispanic: e.hispanic, + total: Object.values(dataCounts).reduce((a, b) => a + b, 0), + }); + }); + + return tableData; +} diff --git a/nc/views.py b/nc/views.py index d353fab9..969f2fd4 100644 --- a/nc/views.py +++ b/nc/views.py @@ -113,6 +113,41 @@ def get_date_range(request): return date_precision, date_range +DEFAULT_RENAME_COLUMNS = { + "White": "white", + "Black": "black", + "Hispanic": "hispanic", + "Asian": "asian", + "Native American": "native_american", + "Other": "other", +} + +CONTRABAND_TYPE_COLS = { + "Alcohol": "alcohol", + "Drugs": "drugs", + "Money": "money", + "Other": "other", + "Weapons": "weapons", +} + + +def create_table_data_response(qs, pivot_columns=None, value_key=None, rename_columns=None): + rename_cols = rename_columns if rename_columns else DEFAULT_RENAME_COLUMNS + pivot_cols = pivot_columns if pivot_columns else ["driver_race_comb"] + table_data = [] + + if qs.count() > 0: + pivot_df = ( + pd.DataFrame(qs) + .pivot(index="year", columns=pivot_cols, values=value_key) + .fillna(value=0) + ) + + pivot_df = pd.DataFrame(pivot_df).rename(columns=rename_cols) + table_data = pivot_df.to_json(orient="table") + return table_data + + class AgencyViewSet(viewsets.ReadOnlyModelViewSet): queryset = Agency.objects.all() serializer_class = serializers.AgencySerializer @@ -802,31 +837,11 @@ def get(self, request, agency_id): ) .annotate(year=ExtractYear("date")) ) - table_data = [] - if table_data_qs.count() > 0: - pivot_df = ( - pd.DataFrame(table_data_qs) - .pivot(index="year", columns=["driver_race_comb"], values="contraband_found_count") - .fillna(value=0) - ) - - pivot_df = pd.DataFrame(pivot_df).rename( - columns={ - "White": "white", - "Black": "black", - "Hispanic": "hispanic", - "Asian": "asian", - "Native American": "native_american", - "Other": "other", - } - ) - table_data = pivot_df.to_json(orient="table") - + table_data = create_table_data_response(table_data_qs, value_key="contraband_found_count") data = { "contraband_percentages": contraband_percentages, "table_data": table_data, } - return Response(data=data, status=200) @@ -889,24 +904,12 @@ def get(self, request, agency_id): ) .annotate(year=ExtractYear("date")) ) - table_data = [] - if table_data_qs.count() > 0: - pivot_df = ( - pd.DataFrame(table_data_qs) - .pivot(index="year", columns=["contraband_type"], values="contraband_found_count") - .fillna(value=0) - ) - - pivot_df = pd.DataFrame(pivot_df).rename( - columns={ - "Alcohol": "alcohol", - "Drugs": "drugs", - "Money": "money", - "Other": "other", - "Weapons": "weapons", - } - ) - table_data = pivot_df.to_json(orient="table") + table_data = create_table_data_response( + table_data_qs, + pivot_columns=["contraband_type"], + value_key="contraband_found_count", + rename_columns=CONTRABAND_TYPE_COLS, + ) data = { "contraband_percentages": contraband_percentages, @@ -1201,29 +1204,7 @@ def get(self, request, agency_id): .order_by("year") ) - table_data = [] - if qs.count() > 0: - table_df = ( - pd.DataFrame(qs) - .pivot( - index="year", - columns=["driver_race_comb"], - values="contraband_count", - ) - .fillna(value=0) - .rename( - columns={ - "White": "white", - "Black": "black", - "Hispanic": "hispanic", - "Asian": "asian", - "Native American": "native_american", - "Other": "other", - } - ) - ) - table_data = table_df.to_json(orient="table") - + table_data = create_table_data_response(qs, value_key="contraband_count") data = {"table_data": table_data} return Response(data, status=200) @@ -1684,28 +1665,8 @@ def get(self, request, agency_id): .annotate(year=ExtractYear("date")) ) - table_data = [] - if table_data_qs.count() > 0: - pivot_df = ( - pd.DataFrame(table_data_qs) - .pivot(index="year", columns=["driver_race_comb"], values="stop_count") - .fillna(value=0) - ) - - pivot_df = pd.DataFrame(pivot_df).rename( - columns={ - "White": "white", - "Black": "black", - "Hispanic": "hispanic", - "Asian": "asian", - "Native American": "native_american", - "Other": "other", - } - ) - table_data = pivot_df.to_json(orient="table") - + table_data = create_table_data_response(table_data_qs, value_key="stop_count") data = {"arrest_percentages": percentages, "table_data": table_data} - return Response(data=data, status=200) @@ -1755,28 +1716,8 @@ def get(self, request, agency_id): ) ) - table_data = [] - if table_data_qs.count() > 0: - pivot_df = ( - pd.DataFrame(table_data_qs) - .pivot(index="year", columns=["driver_race_comb"], values="stop_count") - .fillna(value=0) - ) - - pivot_df = pd.DataFrame(pivot_df).rename( - columns={ - "White": "white", - "Black": "black", - "Hispanic": "hispanic", - "Asian": "asian", - "Native American": "native_american", - "Other": "other", - } - ) - table_data = pivot_df.to_json(orient="table") - + table_data = create_table_data_response(table_data_qs, value_key="stop_count") data = {"arrest_percentages": percentages, "table_data": table_data} - return Response(data=data, status=200) @@ -1829,28 +1770,8 @@ def get(self, request, agency_id): ) ) - table_data = [] - if table_data_qs.count() > 0: - pivot_df = ( - pd.DataFrame(table_data_qs) - .pivot(index="year", columns=["driver_race_comb"], values="stop_count") - .fillna(value=0) - ) - - pivot_df = pd.DataFrame(pivot_df).rename( - columns={ - "White": "white", - "Black": "black", - "Hispanic": "hispanic", - "Asian": "asian", - "Native American": "native_american", - "Other": "other", - } - ) - table_data = pivot_df.to_json(orient="table") - + table_data = create_table_data_response(table_data_qs, value_key="stop_count") data = {"arrest_counts": chart_data, "table_data": table_data} - return Response(data=data, status=200) @@ -1858,6 +1779,7 @@ class AgencyArrestsPercentageOfStopsByGroupPurposeView(APIView): @method_decorator(cache_page(CACHE_TIMEOUT)) def get(self, request, agency_id): year = request.GET.get("year", None) + grouped_stop_purpose = request.GET.get("grouped_stop_purpose", None) qs = StopSummary.objects.all() @@ -1883,6 +1805,16 @@ def get(self, request, agency_id): StopPurposeGroup.OTHER, ] + if "modal" in request.GET and grouped_stop_purpose: + table_data_qs = ( + qs.filter(driver_arrest=True, stop_purpose_group=grouped_stop_purpose) + .values("driver_race_comb") + .annotate(year=ExtractYear("date")) + .annotate(stop_count=Sum("count")) + ) + table_data = create_table_data_response(table_data_qs, value_key="stop_count") + return Response(data={"table_data": table_data}, status=200) + if arrests_qs.count() > 0: for stop_purpose in stop_purpose_types: group = { @@ -1902,7 +1834,6 @@ def get(self, request, agency_id): data = { "arrest_percentages": arrest_percentages, - "table_data": [], } return Response(data=data, status=200) @@ -1911,6 +1842,7 @@ class AgencyArrestsPercentageOfStopsPerStopPurposeView(APIView): @method_decorator(cache_page(CACHE_TIMEOUT)) def get(self, request, agency_id): year = request.GET.get("year", None) + stop_purpose_type = request.GET.get("stop_purpose_type", None) qs = StopSummary.objects.all() @@ -1921,6 +1853,17 @@ def get(self, request, agency_id): if officer: qs = qs.filter(officer_id=officer) + if "modal" in request.GET and stop_purpose_type: + purpose = stop_purpose_type.replace(" ", "_").replace("/", "_").upper() + table_data_qs = ( + qs.filter(driver_arrest=True, stop_purpose=StopPurpose[purpose]) + .values("driver_race_comb") + .annotate(year=ExtractYear("date")) + .annotate(stop_count=Sum("count")) + ) + table_data = create_table_data_response(table_data_qs, value_key="stop_count") + return Response(data={"table_data": table_data}, status=200) + arrests_qs = qs if year: arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) @@ -1951,7 +1894,6 @@ def get(self, request, agency_id): data = { "labels": [sp[1] for sp in stop_purpose_types], "arrest_percentages": arrest_percentages, - "table_data": [], } return Response(data=data, status=200) @@ -1961,6 +1903,7 @@ class AgencyArrestsPercentageOfSearchesByGroupPurposeView(APIView): @method_decorator(cache_page(CACHE_TIMEOUT)) def get(self, request, agency_id): year = request.GET.get("year", None) + grouped_stop_purpose = request.GET.get("grouped_stop_purpose", None) qs = StopSummary.objects.all() @@ -1988,6 +1931,20 @@ def get(self, request, agency_id): StopPurposeGroup.OTHER, ] + if "modal" in request.GET and grouped_stop_purpose: + table_data_qs = ( + qs.filter( + driver_searched=True, + driver_arrest=True, + stop_purpose_group=grouped_stop_purpose, + ) + .values("driver_race_comb") + .annotate(year=ExtractYear("date")) + .annotate(stop_count=Sum("count")) + ) + table_data = create_table_data_response(table_data_qs, value_key="stop_count") + return Response(data={"table_data": table_data}, status=200) + if arrests_qs.count() > 0: for stop_purpose in stop_purpose_types: group = { @@ -2008,7 +1965,6 @@ def get(self, request, agency_id): data = { "arrest_percentages": arrest_percentages, - "table_data": [], } return Response(data=data, status=200) @@ -2017,6 +1973,7 @@ class AgencyArrestsPercentageOfSearchesPerStopPurposeView(APIView): @method_decorator(cache_page(CACHE_TIMEOUT)) def get(self, request, agency_id): year = request.GET.get("year", None) + stop_purpose_type = request.GET.get("stop_purpose_type", None) qs = StopSummary.objects.all() @@ -2027,6 +1984,19 @@ def get(self, request, agency_id): if officer: qs = qs.filter(officer_id=officer) + if "modal" in request.GET and stop_purpose_type: + purpose = stop_purpose_type.replace(" ", "_").replace("/", "_").upper() + table_data_qs = ( + qs.filter( + driver_searched=True, driver_arrest=True, stop_purpose=StopPurpose[purpose] + ) + .values("driver_race_comb") + .annotate(year=ExtractYear("date")) + .annotate(stop_count=Sum("count")) + ) + table_data = create_table_data_response(table_data_qs, value_key="stop_count") + return Response(data={"table_data": table_data}, status=200) + arrests_qs = qs if year: arrests_qs = arrests_qs.annotate(year=ExtractYear("date")).filter(year=year) @@ -2104,9 +2074,26 @@ def get(self, request, agency_id): stop_count = filtered_df["contraband_found_count"].sum() arrest_percentages[i] = np.nan_to_num(arrest_found_count / stop_count) + table_data_qs = ( + qs.filter(driver_arrest=True) + .values("contraband_type") + .annotate( + contraband_found_count=Count( + "contraband_id", distinct=True, filter=Q(contraband_found=True) + ) + ) + .annotate(year=ExtractYear("date")) + ) + table_data = create_table_data_response( + table_data_qs, + pivot_columns=["contraband_type"], + value_key="contraband_found_count", + rename_columns=CONTRABAND_TYPE_COLS, + ) + data = { "arrest_percentages": arrest_percentages, - "table_data": [], + "table_data": table_data, } return Response(data=data, status=200) From dd66a508996b4bad3180653de3a0fa7688ea3b51 Mon Sep 17 00:00:00 2001 From: Aristotel Fani Date: Tue, 16 Apr 2024 12:26:27 -0400 Subject: [PATCH 04/24] Consolidate year dropdowns in traffic stops tab (#288) --- .../Charts/TrafficStops/TrafficStops.js | 60 +++++-------------- 1 file changed, 15 insertions(+), 45 deletions(-) diff --git a/frontend/src/Components/Charts/TrafficStops/TrafficStops.js b/frontend/src/Components/Charts/TrafficStops/TrafficStops.js index 43587087..adf74606 100644 --- a/frontend/src/Components/Charts/TrafficStops/TrafficStops.js +++ b/frontend/src/Components/Charts/TrafficStops/TrafficStops.js @@ -115,7 +115,6 @@ function TrafficStops(props) { datasets: [], loading: true, }); - const [groupedStopYear, setGroupedStopYear] = useState(YEARS_DEFAULT); const purposeGroupedPieLabels = ['Safety Violation', 'Regulatory and Equipment', 'Other']; const purposeGroupedPieColors = ['#5F0F40', '#E36414', '#0F4C5C']; @@ -216,7 +215,6 @@ function TrafficStops(props) { selectedPurpose: 'Safety Violation', purposeTypes: ['Safety Violation', 'Regulatory and Equipment', 'Other'], }); - const [yearForGroupedPieCharts, setYearForGroupedPieCharts] = useState('All'); const [checked, setChecked] = useState(false); const [trafficStopsByCountRange, setTrafficStopsByCountRange] = useState(null); @@ -366,9 +364,11 @@ function TrafficStops(props) { /* INTERACTIONS */ // Handle year dropdown state - const handleYearSelect = (y) => { + const handleYearSelect = (y, idx) => { if (y === year) return; setYear(y); + handleYearSelectForGroupedPieCharts(y, idx); + handleGroupedStopPurposeYearSelect(y, idx); }; const buildStopPurposeGroupedPieData = (ds, stopPurposeYear = null) => { @@ -407,9 +407,8 @@ function TrafficStops(props) { }; const handleGroupedStopPurposeYearSelect = (y, i) => { - if (y === groupedStopYear) return; + if (y === year) return; - setGroupedStopYear(y); if (y === YEARS_DEFAULT) { // eslint-disable-next-line no-param-reassign i = null; @@ -552,7 +551,6 @@ function TrafficStops(props) { }; const handleYearSelectForGroupedPieCharts = (selectedYear, idx) => { - setYearForGroupedPieCharts(selectedYear); // Get the reverse index of the year since it's now in descending order const idxForYear = stopsGroupedByPurposeData.labels.length - idx; updateStoppedPurposePieChart( @@ -637,9 +635,7 @@ function TrafficStops(props) { subject = `Officer ${officerId}`; } return `Traffic Stops By Stop Purpose for ${subject} ${ - groupedStopYear === YEARS_DEFAULT - ? `since ${stopsGroupedByPurposeData.labels[0]}` - : `in ${groupedStopYear}` + year === YEARS_DEFAULT ? `since ${stopsGroupedByPurposeData.labels[0]}` : `in ${year}` }`; }; @@ -649,9 +645,7 @@ function TrafficStops(props) { subject = `Officer ${officerId}`; } return `Traffic Stops By ${stopPurpose} and Race Count for ${subject} ${ - yearForGroupedPieCharts === YEARS_DEFAULT - ? `since ${stopsGroupedByPurposeData.labels[0]}` - : `in ${yearForGroupedPieCharts}` + year === YEARS_DEFAULT ? `since ${stopsGroupedByPurposeData.labels[0]}` : `in ${year}` }`; }; @@ -691,19 +685,19 @@ function TrafficStops(props) { return `Traffic Stops by Percentage for ${subject} since ${stopsByPercentageData.labels[0]}`; }; - const stopPurposeGroupedPieYears = () => { - if (stopPurposeGroupsData.labels) { - const years = [...stopPurposeGroupsData.labels].toReversed(); - return [YEARS_DEFAULT].concat(years); - } - return [YEARS_DEFAULT]; - }; - return ( {/* Traffic Stops by Percentage */} {renderMetaTags()} {renderTableModal()} +
+ +
- - - @@ -858,21 +844,13 @@ function TrafficStops(props) { tableHeader: 'Traffic Stops By Stop Purpose', tableSubheader: getPieChartModalSubHeading( 'Shows the stop purpose and race/ethnic composition of drivers stopped', - groupedStopYear + year ), agencyName: stopsChartState.data[AGENCY_DETAILS].name, chartTitle: stopPurposeGroupPieChartTitle(), }} /> - - - @@ -988,14 +966,6 @@ function TrafficStops(props) { /> - {checked && ( - - )} From 896f5d1b344c3a9e9a98613885b4c24c334083f9 Mon Sep 17 00:00:00 2001 From: Aristotel Fani Date: Tue, 16 Apr 2024 12:38:17 -0400 Subject: [PATCH 05/24] Consolidate all year dropdowns (#292) Consolidate dropdown year to just one for the entire agency site --- .../src/Components/AgencyData/AgencyData.js | 24 +++++++ .../src/Components/AgencyData/AgencyHeader.js | 11 ++++ .../src/Components/Charts/Arrest/Arrests.js | 22 +------ .../Charts/Contraband/Contraband.js | 30 +++------ .../Components/Charts/Overview/Overview.js | 26 +------- .../Charts/SearchRate/SearchRate.js | 25 +------- .../Charts/TrafficStops/TrafficStops.js | 62 ++++++------------- .../Charts/UseOfForce/UseOfForce.js | 18 +----- nc/urls.py | 5 ++ nc/views.py | 16 +++++ 10 files changed, 90 insertions(+), 149 deletions(-) diff --git a/frontend/src/Components/AgencyData/AgencyData.js b/frontend/src/Components/AgencyData/AgencyData.js index a8bdef2a..78ea5b23 100644 --- a/frontend/src/Components/AgencyData/AgencyData.js +++ b/frontend/src/Components/AgencyData/AgencyData.js @@ -15,6 +15,8 @@ import AgencyHeader from './AgencyHeader'; import Sidebar from '../Sidebar/Sidebar'; import ChartRoutes from '../Charts/ChartRoutes'; import { CompareAlertBox } from '../Elements/Alert/Alert'; +import { YEARS_DEFAULT } from '../Charts/chartUtils'; +import axios from '../../Services/Axios'; function AgencyData(props) { let { agencyId } = useParams(); @@ -27,6 +29,10 @@ function AgencyData(props) { const [chartsOpen, setChartsOpen] = useState(false); const [chartState] = useDataset(agencyId, AGENCY_DETAILS); + const [yearRange, setYearRange] = useState([YEARS_DEFAULT]); + const [year, setYear] = useState(YEARS_DEFAULT); + const [yearIdx, setYearIdx] = useState(null); + useEffect(() => { if (chartState.data[AGENCY_DETAILS]) setSidebarOpen(true); }, [chartState.data[AGENCY_DETAILS]]); @@ -39,6 +45,18 @@ function AgencyData(props) { if (chartState.data[AGENCY_DETAILS]) setChartsOpen(true); }, [chartState.data[AGENCY_DETAILS]]); + useEffect(() => { + axios.get(`/api/agency/${agencyId}/year-range/`).then((res) => { + setYearRange([YEARS_DEFAULT].concat(res.data.year_range)); + }); + }, [agencyId]); + + const handleYearSelect = (y, idx) => { + if (y === year) return; + setYear(y); + setYearIdx(idx); // Used for some pie chart graphs + }; + return ( {props.showCompare && !props.agencyId && } @@ -48,6 +66,9 @@ function AgencyData(props) { toggleShowCompare={props.toggleShowCompare} showCompareDepartments={props.showCompare} showCloseButton={!!props?.agencyId} + yearRange={yearRange} + year={year} + handleYearSelect={handleYearSelect} /> @@ -72,6 +93,9 @@ function AgencyData(props) { agencyId={agencyId} showCompare={props.showCompare} agencyName={chartState.data[AGENCY_DETAILS].name} + yearRange={yearRange} + year={year} + yearIdx={yearIdx} /> )} diff --git a/frontend/src/Components/AgencyData/AgencyHeader.js b/frontend/src/Components/AgencyData/AgencyHeader.js index 84926690..0c3cfa5d 100644 --- a/frontend/src/Components/AgencyData/AgencyHeader.js +++ b/frontend/src/Components/AgencyData/AgencyHeader.js @@ -18,6 +18,7 @@ import BackButton from '../Elements/BackButton'; import Button from '../Elements/Button'; import * as ChartHeaderStyles from '../Charts/ChartSections/ChartHeader.styled'; import CensusData from './CensusData'; +import DataSubsetPicker from '../Charts/ChartSections/DataSubsetPicker/DataSubsetPicker'; function AgencyHeader({ agencyHeaderOpen, @@ -25,6 +26,9 @@ function AgencyHeader({ toggleShowCompare, showCompareDepartments, showCloseButton, + yearRange, + year, + handleYearSelect, }) { const history = useHistory(); const { agencyId } = useParams(); @@ -92,6 +96,13 @@ function AgencyHeader({ showCompareDepartments={showCompareDepartments} /> + {!showCloseButton && (