29:null 2a:["$","title",null,{"children":"Crimes and punishment in Russia: 2009-2022 | Daniil Beilinson | Observable"}] 2f:T630,Every half of the year, Judicial Department of the Supreme Court publishes on its website tables with the summary statistics on criminal records from 2009 to the present. This information is [published](http://www.cdep.ru/index.php?id=79) in the form of dozens of illegible sheets: in order to conduct a thorough analysis a skilled professional would need days of work. A platform [Dostoevsky](https://beta.dostoevsky.io/en-GB/about) providing the same data, but cleaned from contradictions and double entries, with unified design. This notebook contains various tools for quick analysis of a small subset of data provided by the Dostoevsky project team. These tools are primarily focused on identifying unusual abnormalities in the judicial statistics. In addition, this notebook contains examples of the computational usage of judicial statistics data that can complement your research. We analysed such parameters as _the number of convicted persons_, _the number of acquitted persons_, _the use of compulsory measures of medical nature_, _the dismissal of criminal cases for lack of corpus delicti, absence of the event of the crime, non-participation in the crime_ and _the dismissal of criminal cases on other grounds_. These metrics have been analysed in relation to the predicate offence. In the raw data section, you can find the same data in relation to the additional qualification of the offence. The main data and graphs are translated to the English with the help of automated translation. Use the language switcher below if you want to see original graphs.30:T594,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const data = getData({}, ['year'], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric] })) }) return acc }, []) return Plot.plot({ caption: LABELS["summary-dynamics-abs"][`label_${language}`], marginLeft: 60, marginRight: 32, width: 800, y: { type: "sqrt", grid: true, label: LABELS["value"][`label_${language}`], }, x: { label: LABELS["year"][`label_${language}`], }, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marks: [ Plot.ruleY([1]), Plot.line(data, { x: "date", y: "value", z: "metric", stroke: "metric", curve: "catmull-rom", tip: true }), Plot.line(data, {x: "date", y: "total", interval: 'year', curve: "catmull-rom", strokeOpacity: 0.4, tip: true }), Plot.text(data, Plot.selectLast({ x: "date", y: "total", interval: 'year', text: d => LABELS["total"][`label_${language}`], textAnchor: "start", dx: 3 })) ] }) }31:T4b5,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const data = getData({}, ['year'], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric]/item.total, absValue: item[metric] })) }) return acc }, []) return Plot.plot({ caption: LABELS["summary-dynamics-share"][`label_${language}`], y: { label: LABELS["value"][`label_${language}`] + " (%)", percent: true }, x: { label: LABELS["year"][`label_${language}`], }, width: 800, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marks: [ Plot.areaY( data, Plot.stackY({ offset: "normalize", order: "metric", reverse: true, }, { x: "date", y: "value", fill: "metric", curve: "catmull-rom", tip: true }) ), Plot.ruleY([0, 1]) ] }) }32:T83c,{ const data = getData({}, ['year', `Chapter ${language}`], [anomaliesMetric], { includeCodexData: true }) const groupedData = groupByWithOptions(data, `Chapter ${language}`, { sortBy: 'year', metric: anomaliesMetric }) const metric = anomaliesOptions === 'abs' ? anomaliesMetric : anomaliesOptions const maxValue = Math.max(...groupedData.map(o => Math.abs(o[metric] || 0))) return Plot.plot({ marginLeft: 300, marginRight: 0, width: 900, height: 600, caption: LABELS[`matrix-caption-${anomaliesOptions}`][`label_${language}`], y: { label: LABELS["chapter"][`label_${language}`] }, x: { label: LABELS["year"][`label_${language}`], }, color: { scheme: anomaliesOptions !== 'abs' ? "BuRd" : "OrRd", legend: true, label: LABELS[`matrix-${anomaliesOptions}`][`label_${language}`], type: anomaliesOptions === 'diff' ? 'diverging-sqrt' : anomaliesOptions === 'ratio' ? 'log' : 'sqrt', percent: anomaliesOptions === 'ratio' }, marks: [ Plot.rect( groupedData, Plot.binX( {}, { filter: anomaliesOptions !== 'abs' ? d => d.year > 2009 : d => d, x: "date", interval: "year", y: `Chapter ${language}`, fill: d => anomaliesOptions !== 'ratio' ? d[metric] : d[metric] > 0 ? d[metric] : 'white', inset: 0.5, tip: true } ) ), Plot.text( groupedData, { filter: anomaliesOptions !== 'abs' ? d => d.year > 2009 : d => d, x: "date", interval: "year", y: `Chapter ${language}`, text: anomaliesOptions === 'ratio' ? d => d[metric]?.toLocaleString(undefined, {style: "percent"}) : metric, fill: d => Math.abs(d[metric]) > maxValue/3 ? 'white' : 'black', dx: 20 } ), Plot.axisY({textAnchor: "end", lineWidth: 25, fill: "black", dx: -5}), ] }) }33:T6c7,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const filters = {} filters[`Chapter ${language}`] = [selectedCodexChapter] const dataTotal = getData(filters, [], metrics, { sumMetrics: true }) const data = getData(filters, ['Number'], metrics, { includeCodexData: true, sumMetrics: true }) .map(item => Object.assign({}, {share: (item.total/dataTotal[0].total).toLocaleString(undefined, {style: "percent"})}, item)) return Plot.plot({ x: {label: null, axis: null}, color: {scheme: "Pastel1"}, width: 800, caption: LABELS["chapter-article-ratio"][`label_${language}`] + ` "${selectedCodexChapter}"`, marks: [ Plot.barX( data, Plot.stackX({ x: "total", fill: "Number", fillOpacity: 0.3, insetRight: 5, marginBottom: 30, channels: {name: "Name", percentage: "share" }, tip: true, sort: "total" }) ), Plot.textX( data, Plot.stackX({ x: "total", text: (d, i, a) => d.total/a.reduce((acc, i) => acc + i.total, 0) > 0.05 ? d["Number"] : '', lineWidth: 10, inset: 5, sort: "total" }) ), Plot.textX( data, Plot.stackX({ x: "total", text: (d, i, a) => { const totalSum = a.reduce((acc, i) => acc + i.total, 0) return d.total/totalSum > 0.05 ? `${d.total}\n(${(d.total/totalSum).toLocaleString(undefined, {style: "percent"})})` : '' }, inset: 5, lineAnchor: "top", dy: 20, sort: "total" }) ) ] }) }34:T611,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const filters = {} filters[`Chapter ${language}`] = [selectedCodexChapter] const data = getData(filters, ['year'], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric] })) }) return acc }, []) const maxValue = Math.max(...data.map(o => Math.abs(o.value || 0))) return Plot.plot({ marginLeft: 180, marginRight: 0, width: 800, y: { label: LABELS["metric"][`label_${language}`] }, x: { label: LABELS["year"][`label_${language}`] }, caption: LABELS["chapter-matrix-caption"][`label_${language}`] + ` "${selectedCodexChapter}"`, color: {scheme: "OrRd", legend: true, label: LABELS["chapter-matrix"][`label_${language}`], type: 'pow'}, marks: [ Plot.rect( data, Plot.binX( {fill: "sum"}, {x: "date", interval: "year", y: "metric", fill: "value", inset: 0.5, tip: true, sort: { y: "x" }} ) ), Plot.text( data, { x: "date", interval: "year", y: "metric", text: "value", fill: d => Math.abs(d.value) > maxValue/2 ? 'white' : 'black', dx: 22 } ), Plot.axisY({textAnchor: "end", lineWidth: 15, fill: "black", dx: -5}), ] }) }35:T4a6,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const filters = {} filters[`Chapter ${language}`] = [selectedCodexChapter] const data = getData(filters, ['year'], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric]/item.total })) }) return acc }, []) return Plot.plot({ marginLeft: 60, width: 800, caption: LABELS["chapter-metric-share-caption"][`label_${language}`] + ` "${selectedCodexChapter}"`, y: { label: LABELS["value"][`label_${language}`] + " (%)", percent: true, grid: true }, x: { label: LABELS["year"][`label_${language}`], }, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marks: [ Plot.ruleY([1]), Plot.line(data, { x: "date", y: "value", stroke: "metric", curve: "catmull-rom", tip: true }) ] }) }36:T4f4,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const filters = {} filters[`Chapter ${language}`] = [selectedCodexChapter] const data = getData(filters, ['year'], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric] })) }) return acc }, []) return Plot.plot({ caption: LABELS["chapter-metric-abs-caption"][`label_${language}`] + ` "${selectedCodexChapter}"`, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marginLeft: 60, width: 800, y: { grid: true, label: LABELS["decisions-taken"][`label_${language}`] }, x: { label: LABELS["year"][`label_${language}`] }, marks: [ Plot.rectY(data, {y: "value", x: "date", fill: "metric", tip: true}), Plot.text(data.filter(i => i.metric === METRICS.totalConvictedMain[`label_${language}`]), {y: "total", x: "date", text: "total", textAnchor: "middle", dy: -10, fill: "black"}), Plot.ruleY([0]) ] }) }37:T61c,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const data = getData({Number: [selectedCodexArticle]}, [PARAMETERS.article[`prop_${language}`]], metrics, { includeCodexData: true, sumMetrics: true }) return Plot.plot({ x: {label: null, axis: null}, color: {scheme: "Pastel1"}, width: 800, caption: LABELS["article-parts-ratio"][`label_${language}`] + ` "${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})"`, marks: [ Plot.barX( data, Plot.stackX({ x: "total", fill: PARAMETERS.article[`prop_${language}`], fillOpacity: 0.3, insetRight: 5, marginBottom: 30, tip: true, sort: "total" }) ), Plot.textX( data, Plot.stackX({ x: "total", text: (d, i, a) => d.total/a.reduce((acc, i) => acc + i.total, 0) > 0.1 ? d[PARAMETERS.article[`prop_${language}`]] : '', lineWidth: 10, inset: 5, sort: "total" }) ), Plot.textX( data, Plot.stackX({ x: "total", text: (d, i, a) => { const totalSum = a.reduce((acc, i) => acc + i.total, 0) return d.total/totalSum > 0.1 ? `${d.total?.toLocaleString()}\n(${(d.total/totalSum).toLocaleString(undefined, {style: "percent"})})` : '' }, inset: 5, lineAnchor: "top", dy: 20, sort: "total" }) ) ] }) }38:T47e,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const data = getData({Number: [selectedCodexArticle]}, ['year'], metrics, { includeCodexData: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric] })) }) return acc }, []) return Plot.plot({ marginLeft: 60, width: 800, caption: LABELS["article-decisions-abs"][`label_${language}`] + ` "${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})"`, y: { grid: true, type: "sqrt", label: LABELS["value"][`label_${language}`] }, x: { label: LABELS["year"][`label_${language}`], }, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marks: [ Plot.ruleY([1]), Plot.line(data, { x: "date", y: "value", z: "metric", stroke: "metric", curve: "catmull-rom", tip: true }) ] }) }39:T540,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const data = getData({Number: [selectedCodexArticle]}, ['year'], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], value: item[metric]/item.total, absValue: item[metric] })) }) return acc }, []) return Plot.plot({ y: { grid: true, percent: true, type: "sqrt", label: LABELS["value"][`label_${language}`] + " (%)" }, x: { label: LABELS["year"][`label_${language}`], }, width: 800, caption: LABELS["article-decisions-share"][`label_${language}`] + ` "${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})"`, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marks: [ Plot.areaY( data, Plot.stackY({ offset: "normalize", order: "metric", reverse: true, }, { x: "date", y: "value", fill: "metric", curve: "catmull-rom", tip: true }) ), Plot.ruleY([0, 1]) ] }) }3a:T62b,{ const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain'] const data = getData({Number: [selectedCodexArticle]}, [PARAMETERS.article[`prop_${language}`]], metrics, { includeCodexData: true, sumMetrics: true }) .reduce((acc, item) => { metrics.forEach(metric => { acc.push(Object.assign({}, item, { metric: METRICS[metric][`label_${language}`], valueShare: item[metric]/item.total, value: item[metric] })) }) return acc }, []) return Plot.plot({ caption: LABELS["article-parts"][`label_${language}`] + ` "${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})"`, marginLeft: 100, marginRight: 60, width: 800, y: { label: LABELS["article-part"][`label_${language}`], }, x: { label: LABELS["decisions-taken"][`label_${language}`] }, color: { domain: metrics.map(m => METRICS[m][`label_${language}`]), range: metrics.map(m => METRICS[m].color), legend: true }, marks: [ Plot.barX(data, { x: "value", y: PARAMETERS.article[`prop_${language}`], fill: "metric", tip: true, sort: { y: "x", reverse: true } }), Plot.axisY({textAnchor: "end", lineWidth: 20, fill: "black", dx: -5}), Plot.text(data.filter(i => i.metric === METRICS.totalConvictedMain[`label_${language}`]), { x: "total", y: PARAMETERS.article[`prop_${language}`], text: "total", textAnchor: "begin", dx: 20, fill: "black" } ) ] }) }3b:T480, ${Object.keys(selectedData[0]).map(key => htl.html``)} ${selectedData.map(item => htl.html` ${Object.keys(item).map(key => htl.html``)} `)}

${ METRICS[key] ? METRICS[key][`label_${language}`] : Object.values(PARAMETERS).reduce((acc, i) => { acc[i[`prop_${language}`]] = i[`label_${language}`] return acc }, {})[key]}
${ key === PARAMETERS.article[`prop_${language}`] && filterInputs.articles.length === 0 && settingsInputs.breakDowns.indexOf(PARAMETERS.article[`prop_${language}`]) === -1 ? 'All articles' : key === PARAMETERS.year[`prop_${language}`] && filterInputs.years.length === 0 && settingsInputs.breakDowns.indexOf(PARAMETERS.year[`prop_${language}`]) === -1 ? rawData[0][PARAMETERS.year[`prop_${language}`]] + ' - ' + rawData[rawData.length - 1][PARAMETERS.year[`prop_${language}`]] : item[key] ? item[key].toLocaleString() : '' }

${ METRICS[key] ? METRICS[key][`label_${language}`] : Object.values(PARAMETERS).reduce((acc, i) => { acc[i[`prop_${language}`]] = i[`label_${language}`] return acc }, {})[key]}

${ key === PARAMETERS.article[`prop_${language}`] && filterInputs.articles.length === 0 && settingsInputs.breakDowns.indexOf(PARAMETERS.article[`prop_${language}`]) === -1 ? 'All articles' : key === PARAMETERS.year[`prop_${language}`] && filterInputs.years.length === 0 && settingsInputs.breakDowns.indexOf(PARAMETERS.year[`prop_${language}`]) === -1 ? rawData[0][PARAMETERS.year[`prop_${language}`]] + ' - ' + rawData[rawData.length - 1][PARAMETERS.year[`prop_${language}`]] : item[key] ? item[key].toLocaleString() : '' }

3c:Tb9c,getData = (filters = {}, breakDownParameters = [], metrics = [], options = { includeCodexData: true, sumMetrics: false, noDate: false }) => { const nonMetricProps = Object.values(PARAMETERS).map(prop => prop[`prop_${language}`]) if (options.includeCodexData) nonMetricProps.push(...Object.keys(codexRaw[0])) const getArticleData = item => codex[item.articleEn.split(' ')[0]] const preprocessedData = rawData.map(item => Object.assign({}, item, getArticleData(item))) .filter(r => { const filteredProps = Object.keys(filters) let res = true filteredProps.forEach(filteredProp => { const currentValue = r[filteredProp] const filterValue = filters[filteredProp] if (filterValue.indexOf(currentValue) === -1) res = false }) return res }) .reduce((acc, r) => { const isFullBreakDown = breakDownParameters.indexOf('year') > -1 && breakDownParameters.indexOf(PARAMETERS.article[`prop_${language}`]) > -1 const item = Object.fromEntries( nonMetricProps.concat(metrics) .map(key => [key, r[key]]) ) if (breakDownParameters.length === 0) { if (!acc.noBreakdown) acc.noBreakdown = [] acc.noBreakdown.push(item) } if (breakDownParameters.length === 1) { const breakDownValue = r[breakDownParameters[0]] if (!acc[breakDownValue]) acc[breakDownValue] = [] acc[breakDownValue].push(item) } if (breakDownParameters.length > 1 && !isFullBreakDown) { const key = breakDownParameters.map(i => item[i]).join('-') if (!acc[key]) acc[key] = [] acc[key].push(item) } if (isFullBreakDown) { if (!acc.fullBreakdown) acc.fullBreakdown = [] acc.fullBreakdown.push(item) } return acc }, {}) if (preprocessedData.fullBreakdown) return preprocessedData.fullBreakdown.map(item => { metrics.forEach(metric => { item[metric] = parseInt(item[metric]) }) return item }) const aggregateRecords = records => records.reduce((acc, i, idx, arr) => { nonMetricProps.forEach(prop => { if (!acc[prop]) acc[prop] = [] acc[prop].push(i[prop]) }) metrics.forEach(metric => { if (!acc[metric]) acc[metric] = 0 if (parseInt(i[metric]) > 0) acc[metric] = parseInt(acc[metric]) + parseInt(i[metric]) }) if (arr.length - 1 === idx) { nonMetricProps.forEach(prop => { acc[prop] = [...new Set(acc[prop])].join(', ') }) } return acc }, {}) const result = preprocessedData.noBreakdown ? [aggregateRecords(preprocessedData.noBreakdown)] : Object.values(preprocessedData).map(group => aggregateRecords(group)) return result.map(item => { metrics.forEach(metric => { if (options.sumMetrics) { if (!item.total) item.total = 0 item.total = item.total + parseInt(item[metric]) } }) if (breakDownParameters.indexOf('year') > -1 && !options.noDate) item.date = new Date(item.year) return item }) }3d:T8cf,METRICS = ({ 'totalConvictedMain': { 'label_ru': 'Осуждено по основной статье', 'label_en': 'Convicted for the main offence', 'color': '#e14b31' }, 'addTotalPersons': { 'label_ru': 'Осуждено по дополнительной квалификации', 'label_en': 'Convicted under additional qualification' }, 'acquittalMain': { 'label_ru': 'Оправдано по основной статье', 'label_en': 'Acquitted for the main offence', 'color': '#b2df8a' }, 'addAcquittalPersons': { 'label_ru': 'Оправдано по дополнительной квалификации', 'label_en': 'Acquitted under additional qualification' }, 'coerciveMeasuresMain': { 'label_ru': 'Принудительные меры медицинского характера по основной статье', 'label_en': 'Coercive measures for the main offence', 'color': '#fea94a' }, 'addUnfitToPleadOffences': { 'label_ru': 'Принудительные меры медицинского характера по дополнительной квалификации', 'label_en': 'Coercive measures under additional qualification' }, 'dismissalMain': { 'label_ru': 'Прекращено дел за отсутствием состава по основной статье', 'label_en': 'Dismissed for lack of corpus delicti for the main offence', 'color': '#1f78b4' }, 'addDismissalPersons': { 'label_ru': 'Прекращено дел за отсутствием состава по дополнительной квалификации', 'label_en': 'Dismissed for lack of corpus delicti under additional qualification' }, 'dismissalOtherMain': { 'label_ru': 'Прекращено дел по иным основаниям по основной статье', 'label_en': 'Dismissed on other grounds for the main offence', 'color': '#a6cee3' }, 'addDismissalOtherPersons': { 'label_ru': 'Прекращено дел по иным основаниям по дополнительной квалификации', 'label_en': 'Dismissed on other grounds under additional qualification' } }) 3e:T1b92,LABELS = ({ 'matrix-abs': { 'label_ru': 'Количество решений', 'label_en': 'Total number of decisions' }, 'matrix-diff': { 'label_ru': 'Разница в количестве решений по сравнению с предыдущим годом', 'label_en': 'Difference in the number of decisions with the previous year' }, 'matrix-ratio': { 'label_ru': 'Отношения количества решений к предыдущему году', 'label_en': 'Ratio of the number of decisions to the previous year' }, 'matrix-caption-abs': { 'label_ru': 'Количество принятых решений сгруппированное по главам уголовного кодекса', 'label_en': 'Number of decisions grouped by chapters of the criminal code' }, 'matrix-caption-diff': { 'label_ru': 'Разница в количестве решений по сравнению с предыдущим годом сгруппированное по главам уголовного кодекса', 'label_en': 'Difference in the number of judgements compared to the previous year, grouped by chapters of the criminal code' }, 'matrix-caption-ratio': { 'label_ru': 'Отношения количества решений к предыдущему году сгруппированное по главам уголовного кодекса', 'label_en': 'Ratio of the number of judgements to the previous year, grouped by chapter of the criminal code' }, 'summary-dynamics-abs': { 'label_ru': 'Динамика изменений количества принятых решений в абсолютных значениях', 'label_en': 'Dynamics of changes in the number of decisions taken in absolute values' }, 'summary-dynamics-share': { 'label_ru': 'Динамика изменений количества принятых решений в долях от общего количества решений', 'label_en': 'Dynamics of changes in the number of adopted decisions as a share of the total number of decisions' }, 'dynamics-by-chapter': { 'label_ru': 'Динамика изменения метрики для различныв глав уголовного кодекса', 'label_en': 'Dynamics of the metric for different chapters of the criminal code' }, 'chapter-article-ratio': { 'label_ru': 'Распределение количества решений между статьями уголовного кодекса в пределах главы', 'label_en': 'Distribution of the number of decisions among the articles of the criminal code for the chapter' }, 'chapter-matrix': { 'label_ru': 'Принято решений', 'label_en': 'Decisions taken' }, 'chapter-matrix-caption': { 'label_ru': 'Динамика изменения метрик в пределах главы уголовного кодекса', 'label_en': 'Dynamics of change in metrics within a chapter of the criminal code' }, 'chapter-metric-share-caption': { 'label_ru': 'Динамика изменений долей метрик в пределах главы уголовного кодекса', 'label_en': 'Dynamics of changes in the shares of metrics within a chapter of the criminal code' }, 'chapter-metric-abs-caption': { 'label_ru': 'Динамика изменений абсолютных значений метрик в пределах главы уголовного кодекса', 'label_en': 'Dynamics of changes in the absolute values of the metrics within a chapter of the criminal code' }, 'article-parts-ratio': { 'label_ru': 'Распределение количества решений между частями статьи уголовного кодекса', 'label_en': 'Distribution of the number of decisions among the parts of the article of the criminal code' }, 'article-convicted': { 'label_ru': 'Распределение количества осужденных по годам по основной статье', 'label_en': 'Distribution of the number of convicted persons by year by main article' }, 'article-acquittal': { 'label_ru': 'Распределение количества оправданий по годам по основной статье', 'label_en': 'Distribution of the number of acquittals by year by main article' }, 'article-coercive-measures': { 'label_ru': 'Распределение количества принудительных мер медицинского характера по годам по основной статье', 'label_en': 'Distribution of the number of coercive measures applied by year by main article' }, 'article-dismissals': { 'label_ru': 'Распределение количества прекращеных дел за отсутствием состава, события преступления, непричастностью к преступлению по годам по основной статье', 'label_en': 'Distribution of the number of the dismissal of criminal cases for lack of corpus delicti, absence of the event of the crime, non-participation in the crime by year by main article' }, 'article-dismissals-other': { 'label_ru': 'Распределение количества прекращеных дел по иным основаниям по годам по основной статье', 'label_en': 'Distribution of the number of the dismissal of criminal cases on other grounds by year by main article' }, 'article-decisions-abs': { 'label_ru': 'Распределение количества решений по годам по основной статье', 'label_en': 'Distribution of the number of the decisions by year by main article' }, 'article-decisions-share': { 'label_ru': 'Распределение долей видов решений по годам по основной статье', 'label_en': 'Distribution of the shares of the decisions by year by main article' }, 'article-parts': { 'label_ru': 'Распределение решений между частями статьи', 'label_en': 'Distribution of decisions between parts of the article' }, 'total': { 'label_ru': 'Всего', 'label_en': 'Total' }, 'value': { 'label_ru': 'Значение', 'label_en': 'Value' }, 'year': { 'label_ru': 'Год', 'label_en': 'Year' }, 'metric': { 'label_ru': 'Метрика', 'label_en': 'Metric' }, 'decisions-taken': { 'label_ru': 'Принято решений', 'label_en': 'Decision taken' }, 'chapter': { 'label_ru': 'Глава УК', 'label_en': 'Chapter of the criminal code' }, 'article-part': { 'label_ru': 'Часть статьи УК', 'label_en': 'Part of the article' } })3f:[{"id":"a512da117d18e3324f2323d14b952e8a98cd39295066b6b6d439098e6c507392f65694d0543bd53b9c93cb4d5c3e60163088cbf1ad44e7d74ae6d37b3ebde64e","href":"https://static.observableusercontent.com/files/a512da117d18e3324f2323d14b952e8a98cd39295066b6b6d439098e6c507392f65694d0543bd53b9c93cb4d5c3e60163088cbf1ad44e7d74ae6d37b3ebde64e","name":"sudstat-data___2009-2022.csv","type":"text/csv","lastModified":1712227469182.961,"size":578289},{"id":"1a9151e69809a9098319a1b2f8d0991c4d60d68a353fc7055e16525b95a563e78419bd5a28dc9222cca0b75692886acb16b07fb27716c8115607e63c91edbb77","href":"https://static.observableusercontent.com/files/1a9151e69809a9098319a1b2f8d0991c4d60d68a353fc7055e16525b95a563e78419bd5a28dc9222cca0b75692886acb16b07fb27716c8115607e63c91edbb77","name":"criminal--code.csv","type":"text/csv","lastModified":1712227811222.012,"size":213084},{"id":"2ae4af490384a04eba7b3155b5dbb9ff88de6870793cfda1298c0e391cf8cfdc73ddf52b68e5483df01de1ebf7a9973a7beba21fcb6203b4bd252929748abc7c","href":"https://static.observableusercontent.com/files/2ae4af490384a04eba7b3155b5dbb9ff88de6870793cfda1298c0e391cf8cfdc73ddf52b68e5483df01de1ebf7a9973a7beba21fcb6203b4bd252929748abc7c","name":"criminal-codex.csv","type":"text/csv","lastModified":1711631928186.466,"size":144274}] 2d:{"id":"030bc95836f2eb30","slug":null,"title":"Crimes and punishment in Russia: 2009-2022","thumbnail":"42280e52a13f5938826d1bd117f6f8c8c564370c7423e011a01133897f003c91","access_level":"public","create_time":"$D2024-03-18T11:57:51.470Z","update_time":"$D2024-09-20T13:41:11.179Z","view_time":null,"first_public_time":"$D2024-04-02T12:22:35.735Z","fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"9b6646ec24dff9ba","login":"d-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/2d93226084d84c384a572996c4ef629251636290e2358a9491c05b7a329cc05b","tier":"starter_2024"},"version":1997,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"ebe552f4a6dc3f7f","login":"daniil-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/b2df9a708eacdc151433d21ffde2c2a5a7e14023c8175bb08d2f4f6aceb3b7ce","tier":null}],"members":[{"type":"individual","id":"ebe552f4a6dc3f7f","login":"daniil-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/b2df9a708eacdc151433d21ffde2c2a5a7e14023c8175bb08d2f4f6aceb3b7ce","tier":null,"role":"editor"},{"type":"team","id":"9b6646ec24dff9ba","login":"d-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/2d93226084d84c384a572996c4ef629251636290e2358a9491c05b7a329cc05b","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Crimes and punishment in Russia: 2009-2022","cells":[{"id":0,"value":"# Crimes and punishment in Russia: 2009-2022","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1647,"value":"note(md`This computational notebook explores the data of the project [Dostoevsky](https://beta.dostoevsky.io/en-GB/about), a free platform that provides instant access to the statistics on criminal cases in Russia since 2009. It is a work in progress, the first version has been presented at the joint seminar [\"Political Repression in Russia, 2012-2023](https://cercec.ehess.fr/evenement/joint-seminar-political-repression-russia-2012-2023).`) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1657,"value":"toc()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1702,"value":"# Preface","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1704,"value":"$2f","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":269,"value":"viewof language = Inputs.radio([{ label: \"English\", value: \"en\" }, { label: \"Russian\", value: \"ru\" }], { label: \"Select language\", value: \"en\", valueof: v => v.value, format: v => v.label })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":389,"value":"# General data overview","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1709,"value":"Below you will find the general summary of the data from 2009 to 2022 based on the five parameters listed above. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1484,"value":"{\n const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain']\n const data = getData({}, [], metrics, { includeCodexData: true, sumMetrics: true, debug: true })\n return renderIndicators(metrics.map(metric => ({\n value: data[0][metric]?.toLocaleString(),\n subvalue: (data[0][metric]/data[0].total).toLocaleString(undefined, {style: \"percent\", maximumFractionDigits: 2}),\n label: METRICS[metric][`label_${language}`]\n })))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":730,"value":"The following graphs show the dynamics of changes in the main metrics from year to year in absolute values and shares of the number of total decisions taken. Note that proportions of ordinate distorted in order to show the dynamics of the rare decisions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1490,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1516,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":716,"value":"The graph below shows the dynamics of the selected metric for offences grouped by chapters of the criminal code. Note that proportions of ordinate distorted in order to show the dynamics for the rarer types of offences.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":406,"value":"viewof metricsOverview = Inputs.select(new Map(Object.keys(METRICS).reduce((acc, metricId) => {\n acc.push([METRICS[metricId][`label_${language}`], metricId])\n return acc\n}, [])), {label: \"Select metric\", value: 'totalConvictedMain'})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":517,"value":"Plot.plot({\n style: \"overflow: visible;\",\n caption: LABELS[\"dynamics-by-chapter\"][`label_${language}`],\n y: {\n grid: true,\n type: \"sqrt\",\n label: METRICS[metricsOverview][`label_${language}`]\n },\n x: {\n label: LABELS[\"year\"][`label_${language}`],\n },\n width: 800,\n marks: [\n Plot.ruleY([0]),\n Plot.lineY(\n getData([], ['year', PARAMETERS.article[`prop_${language}`]], [metricsOverview], { includeCodexData: true }), \n Plot.binX(\n {y: \"sum\", filter: null}, \n {x: \"year\", interval: \"year\", y: metricsOverview, stroke: `Chapter ${language}`, inset: 0.5, tip: true, sort: { y: \"x\", reverse: true }}\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":722,"value":"This tool allows you to spot the unusual year-to-year fluctuations between the values of a selected metric for different chapters of the criminal code. Changes can be presented as absolute values (_Abs_), difference of values compared to the previous year (_Delta_), ratio of the value to the value of the previous year (_Ratio_).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1221,"value":"viewof anomaliesMetric = Inputs.select(new Map(Object.keys(METRICS).reduce((acc, metricId) => {\n acc.push([METRICS[metricId][`label_${language}`], metricId])\n return acc\n}, [])), {label: \"Select metric\", value: 'totalConvictedMain'})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1341,"value":"viewof anomaliesOptions = Inputs.radio(new Map([[\"Abs\", \"abs\"], [\"Delta\", \"diff\"], [\"Ratio\", \"ratio\"]]), {label: \"Options\", value: \"abs\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1231,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1797,"value":"The table below also helps to identify strange fluctuations in metrics. You can group data either by chapter or by the article of the criminal code. Two other inputs allows you to look only at the articles or chapters which contains more than selected amount of decisions and to compare actual value with the value in the year N-x. \nThe resulting table sorted by the absolute value of difference between years. The table also contains respected values and a ration between them.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1800,"value":"Inputs.bind(Inputs.select(new Map(Object.keys(METRICS).reduce((acc, metricId) => {\n acc.push([METRICS[metricId][`label_${language}`], metricId])\n return acc\n}, [])), {label: \"Select metric\", value: 'totalConvictedMain'}), viewof anomaliesMetric)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1237,"value":"viewof anomaliesGroupByParameter = Inputs.select(new Map(Object.keys(CODEX_PROPERTIES).filter(i => ['Number', 'Chapter'].indexOf(i) > -1).reduce((acc, prop) => {\n acc.push([CODEX_PROPERTIES[prop][`label_${language}`], prop])\n return acc\n}, [])), {label: \"Select parameter\", value: 'Chapter'})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1225,"value":"viewof minimumLevelAnomalies = Inputs.range([0, 1000], {label: \"Select only with minimum amount of decisions\", step: 1, value: 10})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1615,"value":"viewof compareWithYear = Inputs.range([1, 10], {label: \"Compare with years before\", step: 1, value: 1})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1324,"value":"{\n const groupByParameter = anomaliesGroupByParameter === 'Chapter' ? `Chapter ${language}` : 'Number'\n const data = getData({}, ['year', groupByParameter], [anomaliesMetric], { includeCodexData: true, sumMetrics: true })\n .filter(i => i.total > minimumLevelAnomalies)\n const groupedData = groupByWithOptions(data, groupByParameter, { sortBy: 'year', metric: anomaliesMetric, windowYears: compareWithYear })\n .map(i => ({ year: i.year, name: groupByParameter === 'Number' ? `${i[\"Name \" + language]} (${i.Number})` : i[groupByParameter], now: i.value, \"was\": i.prevValue, \"diff (abs)\": Math.abs(i.diff), diff: i.diff, ratio: i.ratio}))\n \n return Inputs.table(groupedData, {\n width: {\n year: 70,\n name: 500,\n total: 70\n },\n format: {\n ratio: d => htl.html`${d?.toLocaleString(undefined, {style: \"percent\"})}`\n },\n sort: \"diff (abs)\", \n reverse: true\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":528,"value":"# Overview of the data aggregated by chapters of the criminal code","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":697,"value":"In this section, you will find an overview of the data aggregated for the selected chapter of the criminal code.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1060,"value":"viewof selectedCodexChapter = Inputs.select(\n [...new Set(rawData.map(item => item[PARAMETERS.article[`prop_${language}`]]).map(item => codex[item.split(' ')[0]]?.[`Chapter ${language}`]))], {value: language === 'ru' ? \"Преступления против общественной безопасности\" : \"Crimes against public security\", label: \"Select the chapter\"}\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1116,"value":"{\n const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain']\n const filters = {}\n filters[`Chapter ${language}`] = [selectedCodexChapter]\n const data = getData(filters, [], metrics, { includeCodexData: true, sumMetrics: true, debug: true })\n return renderIndicators(metrics.map(metric => ({\n value: data[0][metric]?.toLocaleString(),\n subvalue: (data[0][metric]/data[0].total).toLocaleString(undefined, {style: \"percent\", maximumFractionDigits: 2}),\n label: METRICS[metric][`label_${language}`]\n })))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":691,"value":"The graph below shows the ratio of the number of decisions between the articles of the criminal code within the selected chapter.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1092,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":699,"value":"The three graphs below illustrate the dynamics of changes in the decisions taken in absolute numbers and shares. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1161,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1182,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":705,"value":"Number of decisions as columns (with internal proportions, either articles, either type of decisions)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1193,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":533,"value":"# Overview of the data aggregated by articles of the criminal code","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":654,"value":"In this section, you will find an overview of the data aggregated for the selected article of the criminal code.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":743,"value":"viewof selectedCodexArticle = Inputs.select(\n new Map([...new Set(rawData.map(item => item[PARAMETERS.article[`prop_${language}`]]))].filter(i => i !== '').sort((a,b) => a.localeCompare(b)).map(item => [\n codex[item.split(' ')[0]]?.[`Name ${language}`],\n codex[item.split(' ')[0]]?.Number\n ])\n), {value: \"159\", label: \"Select an article\", format: ([name, value]) => `${name} (${value})`})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":784,"value":"{\n const metrics = ['totalConvictedMain', 'acquittalMain', 'coerciveMeasuresMain', 'dismissalMain', 'dismissalOtherMain']\n const data = getData({Number: [selectedCodexArticle]}, [], metrics, { includeCodexData: true, sumMetrics: true })\n return renderIndicators(metrics.map(metric => ({\n value: data[0][metric]?.toLocaleString(),\n subvalue: (data[0][metric]/data[0].total).toLocaleString(undefined, {style: \"percent\", maximumFractionDigits: 2}),\n label: METRICS[metric][`label_${language}`]\n })))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":684,"value":"The graph below shows the ratio of the number of decisions between the parts of the selected article of the criminal code.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":796,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1904,"value":"The following five graphs show the dynamics of the main metrics aggregated for the selected criminal code article.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":856,"value":"{\n const data = getData({Number: [selectedCodexArticle]}, ['year'], ['totalConvictedMain'], { includeCodexData: true })\n return renderIndicatorGraph(data, 'totalConvictedMain', LABELS[\"article-convicted\"][`label_${language}`] + ` \"${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})\"`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":876,"value":"{\n const data = getData({Number: [selectedCodexArticle]}, ['year'], ['acquittalMain'], { includeCodexData: true })\n return renderIndicatorGraph(data, 'acquittalMain', LABELS[\"article-acquittal\"][`label_${language}`] + ` \"${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})\"`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":882,"value":"{\n const data = getData({Number: [selectedCodexArticle]}, ['year'], ['coerciveMeasuresMain'], { includeCodexData: true })\n return renderIndicatorGraph(data, 'coerciveMeasuresMain', LABELS[\"article-coercive-measures\"][`label_${language}`] + ` \"${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})\"`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":886,"value":"{\n const data = getData({Number: [selectedCodexArticle]}, ['year'], ['dismissalMain'], { includeCodexData: true })\n return renderIndicatorGraph(data, 'dismissalMain', LABELS[\"article-dismissals\"][`label_${language}`] + ` \"${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})\"`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":892,"value":"{\n const data = getData({Number: [selectedCodexArticle]}, ['year'], ['dismissalOtherMain'], { includeCodexData: true })\n return renderIndicatorGraph(data, 'dismissalOtherMain', LABELS[\"article-dismissals-other\"][`label_${language}`] + ` \"${codex[selectedCodexArticle]?.Name} (${selectedCodexArticle})\"`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1918,"value":"The graphs below show the same information together in absolute values and shares. Note that proportions of ordinate distorted in order to show the dynamics of the rare decisions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":896,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":933,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":668,"value":"In this graph you can see the distribution of decisions for the selected article disaggregated by its parts.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":962,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1936,"value":"The table below presents aggregated data for the selected article, supplemented by metrics of additional qualification of offences.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1026,"value":"\n \n \n \n ${Object.keys(METRICS).map(key => htl.html``)}\n \n \n \n ${getData({Number: [selectedCodexArticle]}, ['year'], Object.keys(METRICS)).map(item => htl.html`\n \n ${Object.keys(METRICS).map(metric => htl.html``)}\n `)}\n \n

${PARAMETERS.year[`label_${language}`]}	${\n METRICS[key] \n ? METRICS[key][`label_${language}`] \n : Object.values(PARAMETERS).reduce((acc, i) => {\n acc[i[`prop_${language}`]] = i[`label_${language}`]\n return acc\n }, {})[key]}\n
${item.year}	${\n item[metric].toLocaleString()\n }

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":19,"value":"# Raw data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1942,"value":"This section allows you to form a sample of your interest and download the data. \n \nUse the fields _Years_ and _Articles_ in order to filter the data. In the field _Metrics_ you can choose parameters we discovered above supplemented by additional qualification numbers. By default, you will get aggregated values for the whole period and for the selected items. If you wish to disaggregate data by years or/and articles, you must select the corresponding values in the field _Break down_.\n \nFinally, to download the data, press _Download CSV_ button below the table.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":228,"value":"viewof filterInputs = columns({\n years: dropdownInput({\n inputLabel: \"Years\",\n inputId: \"yearsInput\",\n placeholderText: 'Select years...',\n options: [...new Set(rawData.map(item => item[PARAMETERS.year[`prop_${language}`]]))].filter(i => i !== undefined).map(i => ({value: i, label: i})),\n selected: []\n }),\n articles: dropdownInput({\n inputLabel: \"Articles\",\n inputId: \"articlesInput\",\n placeholderText: 'Select articles...',\n options: [...new Set(rawData.map(item => item[PARAMETERS.article[`prop_${language}`]]))].filter(i => i !== undefined).sort((a,b) => a.localeCompare(b)).map(i => ({value: i, label: i})),\n selected: []\n })\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":240,"value":"viewof settingsInputs = columns({\n breakDowns: dropdownInput({\n inputLabel: \"Break down\",\n inputId: \"breakDownInput\",\n placeholderText: 'Select parameters...',\n options: Object.values(PARAMETERS).map(p => ({value: p[`prop_${language}`], label: p[`label_${language}`]})),\n selected: []\n }),\n metrics: dropdownInput({\n inputLabel: \"Metrics\",\n inputId: \"metricsInput\",\n placeholderText: 'Select metrics...',\n options: Object.keys(METRICS).reduce((acc, metricId) => {\n acc.push({ value: metricId, label: METRICS[metricId][`label_${language}`] })\n return acc\n }, []),\n selected: []\n })\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":124,"value":"$3b","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":133,"value":"DOM.download(convertDataToCSV(selectedData), \"export-sudstat\", \"Download CSV\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1938,"value":"***","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":135,"value":"selectedData = {\n const filters = {}\n if (filterInputs.years.length > 0) filters[PARAMETERS.year[`prop_${language}`]] = filterInputs.years\n if (filterInputs.articles.length > 0) filters[PARAMETERS.article[`prop_${language}`]] = filterInputs.articles\n return getData(filters, settingsInputs.breakDowns, settingsInputs.metrics, { includeCodexData: false, noDate: true })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":26,"value":"rawData = FileAttachment(\"sudstat-data___2009-2022.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":323,"value":"codexRaw = FileAttachment(\"criminal--code.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":329,"value":"codex = codexRaw.reduce((acc, item) => {\n acc[item.Number] = item\n return acc\n}, {})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1696,"value":"***","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":131,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1277,"value":"groupByWithOptions = (data, param, options = {}) => {\n if (!options.windowYears) options.windowYears = 1\n const groupedData = Object.values(\n data.reduce((acc, item) => {\n if (!acc[item[param]]) acc[item[param]] = []\n acc[item[param]].push(item)\n return acc\n }, {})\n )\n\n\n groupedData.forEach((group, i) => {\n if (options.sortBy) group.sort((b, a) => a[options.sortBy] - b[options.sortBy])\n if (options.metric) {\n groupedData[i] = group.map((item, i, arr) => {\n if (arr.length > i + options.windowYears) {\n const paramValue = item[options.metric]\n const paramValueNext = arr[i + options.windowYears][options.metric]\n const diff = paramValue - paramValueNext\n const ratio = paramValueNext > 0 ? paramValue/paramValueNext : 0\n return Object.assign({}, item, { diff, ratio, value: paramValue, prevValue: paramValueNext })\n }\n return item\n })\n }\n })\n\n return groupedData.flat()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":137,"value":"convertDataToCSV = data => {\n let parser = new json2csv.Parser()\n let csv = parser.parse(data)\n return new Blob([csv], {type: \"text/csv\"}) \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":780,"value":"renderIndicators = (indicatorsConfig, options = {}) => {\n const defaultOptions = {color: 'hsl(237deg 100% 97%)'}\n options = Object.assign({}, defaultOptions, options)\n return htl.html`\n

\n ${indicatorsConfig.map(indicatorConfig => htl.html`

${indicatorConfig.value}

${indicatorConfig.subvalue}

${indicatorConfig.label}

`)}\n

\n `\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":872,"value":"renderIndicatorGraph = (data, parameter, caption) => Plot.plot({\n caption,\n marginLeft: 0,\n marginRight: 0,\n width: 800,\n x: {\n tickFormat: \"d\",\n interval: 1,\n label: null\n },\n color: {\n scheme: \"OrRd\", type: \"ordinal\"\n },\n marks: [\n Plot.cell(data, {x: \"year\", fill: parameter}),\n Plot.text(data, {x: \"year\", text: parameter, fill: (d, i, a) => d[parameter]/Math.max(...a.map(i => i[parameter])) > 0.5 ? 'white' : 'black'})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":261,"value":"PARAMETERS = ({\n 'year': {\n 'prop_en': 'year',\n 'prop_ru': 'year',\n 'label_en': 'Year',\n 'label_ru': 'Год'\n },\n 'article': {\n 'prop_en': 'articleEn',\n 'prop_ru': 'articleRu',\n 'label_en': 'Article',\n 'label_ru': 'Статья'\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":165,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":443,"value":"CODEX_PROPERTIES = ({\n 'Name': {\n 'label_ru': 'Название статьи',\n 'label_en': 'Article Name',\n },\n 'Number': {\n 'label_ru': 'Номер статьи',\n 'label_en': 'Article Number'\n },\n 'Chapter': {\n 'label_ru': 'Глава УК',\n 'label_en': 'Chapter of Codex'\n },\n 'Section': {\n 'label_ru': 'Раздел УК',\n 'label_en': 'Section of Codex'\n }\n})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1413,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1649,"value":"import {note, try_it, details, box} from \"@observablehq/notes\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":35,"value":"import {dropdownInput, dropdownCSS} from '@tashapiro/dropdown-input'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":223,"value":"import {columns} from \"@bcardiff/observable-columns\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1653,"value":"import {toc} from \"@bryangingechen/toc\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":139,"value":"json2csv = require(\"json2csv@5.0.7/dist/json2csv.umd.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1744,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":101,"value":"htl.html`${dropdownCSS}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W3f","stdlib":"1","titling":"auto"}} 2e:"$2d:body"