{"export":{"version":"v1","entries":{"widget":{"1":{"widget":{"data":{"shared":{"sort":[],"type":"datalens","links":[],"colors":[],"labels":[],"shapes":[],"convert":false,"filters":[{"guid":"creation_dt_4enj","type":"DIMENSION","title":"creation_dt","filter":{"value":["__interval_2024-08-04T00:00:00.000Z_2024-11-23T00:00:00.000Z"],"operation":{"code":"BETWEEN"}},"calc_mode":"direct","datasetId":"4"}],"updates":[],"version":"14","segments":[],"tooltips":[],"datasetsIds":["4"],"hierarchies":[],"colorsConfig":{},"shapesConfig":{},"extraSettings":{},"visualization":{"id":"line","name":"label_visualization-line","type":"line","allowSort":true,"iconProps":{"id":"visLines","width":"24"},"allowColors":true,"allowLabels":true,"allowShapes":true,"allowFilters":true,"placeholders":[{"id":"x","type":"x","items":[{"id":"inserted-1757429627587","cast":"genericdatetime","guid":"a939feb0-8ca8-11f0-a219-ffe370dfee11","type":"DIMENSION","title":"Date scaled","valid":true,"hidden":false,"source":"","formula":"DATETRUNC([delivery_dt],[date_scale])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"genericdatetime","datasetId":"4","managed_by":"user","aggregation":"none","datasetName":"MarketPlace AI Demo","description":"","ui_settings":"","guid_formula":"DATETRUNC([delivery_dt_y2sz],[date_scale])","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"genericdatetime","aggregation_locked":true,"has_auto_aggregation":false}],"title":"section_x","capacity":1,"required":true,"settings":{"grid":"on","type":"linear","title":"off","gridStep":"auto","holidays":"off","hideLabels":"no","labelsView":"auto","titleValue":"","axisModeMap":{"a939feb0-8ca8-11f0-a219-ffe370dfee11":"continuous"},"gridStepValue":50,"axisFormatMode":"auto","axisVisibility":"show","axisLabelFormating":{},"axisLabelDateFormat":"DD.MM.YYYY"},"iconProps":{},"allowedTypes":{},"allowedDataTypes":{}},{"id":"y","type":"y","items":[{"id":"inserted-1757429619781","cast":"float","guid":"de256650-710a-11f0-a040-7f2cfa045483","type":"MEASURE","title":"GMV","valid":true,"hidden":false,"source":"","formula":"sum([amount])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"float","datasetId":"4","managed_by":"user","aggregation":"none","datasetName":"MarketPlace AI Demo","description":"","ui_settings":"","guid_formula":"sum([amount_52rb])","default_value":null,"autoaggregated":true,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"float","aggregation_locked":true,"has_auto_aggregation":true}],"title":"section_y","settings":{"grid":"on","type":"linear","nulls":"connect","scale":"auto","title":"off","gridStep":"auto","hideLabels":"no","labelsView":"auto","scaleValue":"min-max","titleValue":"","gridStepValue":50,"axisFormatMode":"auto","axisVisibility":"show","axisLabelFormating":{},"axisLabelDateFormat":"DD.MM.YYYY"},"iconProps":{},"allowedTypes":{},"allowedDataTypes":{},"allowedFinalTypes":{}},{"id":"y2","type":"y2","items":[],"title":"section_y2","settings":{"grid":"on","type":"linear","nulls":"connect","scale":"auto","title":"off","gridStep":"auto","hideLabels":"no","labelsView":"auto","scaleValue":"min-max","titleValue":"","gridStepValue":50,"axisFormatMode":"auto","axisVisibility":"show","axisLabelFormating":{},"axisLabelDateFormat":"DD.MM.YYYY"},"iconProps":{},"allowedTypes":{},"allowedDataTypes":{},"allowedFinalTypes":{}}],"allowSegments":true,"colorsCapacity":1,"shapesCapacity":1,"allowLayerFilters":false,"availableLabelModes":["absolute"]},"geopointsConfig":{},"datasetsPartialFields":[[{"guid":"78cf2b50-8ca9-11f0-a219-ffe370dfee11","title":"Orders","calc_mode":"formula"},{"guid":"374b78a0-8ca9-11f0-a219-ffe370dfee11","title":"AOV","calc_mode":"formula"},{"guid":"a939feb0-8ca8-11f0-a219-ffe370dfee11","title":"Date scaled","calc_mode":"formula"},{"guid":"date_scale","title":"date_scale","calc_mode":"parameter"},{"guid":"de256650-710a-11f0-a040-7f2cfa045483","title":"GMV","calc_mode":"formula"},{"guid":"category_level_1_n71b","title":"category_level_1","calc_mode":"direct"},{"guid":"category_level_2_exd4","title":"category_level_2","calc_mode":"direct"},{"guid":"category_level_3_50lm","title":"category_level_3","calc_mode":"direct"},{"guid":"region_delivery_efn9","title":"region_delivery","calc_mode":"direct"},{"guid":"city_delivery_ho3c","title":"city_delivery","calc_mode":"direct"},{"guid":"delivery_type_juix","title":"delivery_type","calc_mode":"direct"},{"guid":"delivery_service_blbn","title":"delivery_service","calc_mode":"direct"},{"guid":"sku_color_xokm","title":"sku_color","calc_mode":"direct"},{"guid":"user_gender_fqvv","title":"user_gender","calc_mode":"direct"},{"guid":"user_platform_rhsy","title":"user_platform","calc_mode":"direct"},{"guid":"user_id_9k0n","title":"user_id","calc_mode":"direct"},{"guid":"order_id_iejj","title":"order_id","calc_mode":"direct"},{"guid":"creation_dt_4enj","title":"creation_dt","calc_mode":"direct"},{"guid":"delivery_dt_y2sz","title":"delivery_dt","calc_mode":"direct"},{"guid":"amount_52rb","title":"amount","calc_mode":"direct"}]]}},"name":"Dynamic_line","type":"graph_wizard_node","annotation":null}},"2":{"widget":{"data":{"meta":"{\n \"links\": {}\n}","params":"module.exports = {\n backgroundColor: 'var(--g-color-base-info-light)',\n //https://storage.yandexcloud.net/skaradubpics/bi_battle_logo.svg\n companyLogo: '',\n companyLogoLink: 'https://datalens.yandex.cloud/',\n titleSize: '20',\n title: 'Поиск аналитики',\n subtitle: 'Тернистый путь к данным',\n dashOwner: 'Юра',\n dashOwnerLink: 'https://yandex.cloud/ru/docs/datalens/',\n buttonTgLink: 'https://t.me/data2viz',\n};\n","prepare":"const params = Editor.getParams();\n\nconst tgImgSrc = 'https://storage.yandexcloud.net/datalens-public-demo-assets/telegram_blue.svg';\nconst logoSrc = 'https://storage.yandexcloud.net/skaradubpics/logo.png';\nconst docsImgSrc = 'https://storage.yandexcloud.net/datalens-public-demo-assets/documentation_icon.svg';\n\nconst titleSize = params.titleSize?.[0] || '19';\n\nconst config = {\n backgroundColor: params.backgroundColor?.[0] ?? '',\n logo: params.companyLogo?.[0] || logoSrc,\n logoLink: params.companyLogoLink?.[0] || '',\n title: params.title?.[0] || '',\n titleSize: `${titleSize}px`,\n subtitle: params.subtitle?.[0] || '',\n dashOwner: params.dashOwner?.[0] || '',\n dashOwnerLink: params.dashOwnerLink?.[0] || '',\n tgImgSrc,\n docsImgSrc,\n updatedDate: '17.04',\n updatedTime: '4 hours ago',\n buttonTgLink: params.buttonTgLink?.[0] || '',\n buttonDocLink: params.buttonDocLink?.[0] || '',\n};\n\nmodule.exports = {\n render: Editor.wrapFn({\n fn: function(_dimensions, config) {\n function getIconWithLinkItem(img, link) {\n if (!img || !link) {\n return '';\n }\n return `\n
\n \n
\n `;\n }\n function getControls(controls) {\n let res = '';\n controls.forEach(item => {\n if (item.link && item.img) {\n res += getIconWithLinkItem(item.img, item.link);\n }\n });\n return res;\n }\n\n const logoBlock = `\n
\n \n
\n `;\n\n const logo = config.logoLink ? `${logoBlock}` : `${logoBlock}`;\n const dashOwner = config.dashOwnerLink ? `${config.dashOwner}` : `${config.dashOwner}`\n const subtitle = config.subtitle ? `${config.subtitle}` : '';\n\n const dashOwnerBlock = config.dashOwner ? `\n
\n Админ дашборда: \n ${dashOwner}\n
\n ` : '';\n\n const description = `\n
\n ${config.title}\n \n ${subtitle}\n ${dashOwnerBlock}\n \n
\n `;\n\n const controls = [];\n if (config.buttonTgLink) {\n controls.push({img: config.tgImgSrc, link: config.buttonTgLink});\n }\n if (config.buttonDocLink) {\n controls.push({img: config.docsImgSrc, link: config.buttonDocLink});\n }\n const iconsBlock = getControls(controls);\n\n const dateUpdate = `\n
\n
\n DATA\n
\n
\n
\n
\n ${config.updatedDate}\n Upd: ${config.updatedTime}\n
\n
\n
\n
\n `;\n\n const cellItemStyles = `\n display: flex;\n flex-direction: row;\n align-items: center;\n `;\n const content = `\n
\n
\n ${logo}\n ${description}\n
\n
\n
\n ${iconsBlock}\n
\n
\n
\n `;\n\n return Editor.generateHtml(content);\n },\n args: [config],\n libs: ['d3'],\n }),\n};\n","sources":"module.exports = {};\n","controls":"module.exports = {};\n"},"name":"finance_header","type":"advanced-chart_node","annotation":{"description":""}}},"3":{"widget":{"data":{"shared":{"sort":[],"type":"datalens","links":[],"colors":[],"labels":[],"shapes":[],"convert":false,"filters":[{"guid":"creation_dt_4enj","type":"DIMENSION","title":"creation_dt","filter":{"value":["__interval_2024-08-04T00:00:00.000Z_2024-11-23T00:00:00.000Z"],"operation":{"code":"BETWEEN"}},"calc_mode":"direct","datasetId":"4"}],"updates":[],"version":"14","segments":[],"tooltips":[],"datasetsIds":["4"],"hierarchies":[],"colorsConfig":{},"shapesConfig":{},"extraSettings":{},"visualization":{"id":"metric","name":"label_visualization-metric","type":"metric","allowSort":false,"iconProps":{"id":"visMetric","width":"24"},"allowLabels":false,"allowFilters":true,"placeholders":[{"id":"measures","type":"measures","items":[{"id":"inserted-1757429890906","cast":"float","guid":"de256650-710a-11f0-a040-7f2cfa045483","type":"MEASURE","title":"GMV","valid":true,"hidden":false,"source":"","formula":"sum([amount])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"float","datasetId":"4","formatting":{"unit":"auto","format":"number","prefix":"","postfix":"","labelMode":"absolute","precision":1,"showRankDelimiter":true},"managed_by":"user","aggregation":"none","datasetName":"MarketPlace AI Demo","description":"","ui_settings":"","guid_formula":"sum([amount_52rb])","default_value":null,"hideLabelMode":"show","autoaggregated":true,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"float","aggregation_locked":true,"has_auto_aggregation":true}],"title":"section_measure","capacity":1,"required":true,"settings":{"axisModeMap":{"de256650-710a-11f0-a040-7f2cfa045483":"discrete"}},"iconProps":{},"allowedTypes":{},"allowedDataTypes":{},"allowedFinalTypes":{}}],"allowLayerFilters":false},"geopointsConfig":{},"datasetsPartialFields":[[{"guid":"78cf2b50-8ca9-11f0-a219-ffe370dfee11","title":"Orders","calc_mode":"formula"},{"guid":"374b78a0-8ca9-11f0-a219-ffe370dfee11","title":"AOV","calc_mode":"formula"},{"guid":"a939feb0-8ca8-11f0-a219-ffe370dfee11","title":"Date scaled","calc_mode":"formula"},{"guid":"date_scale","title":"date_scale","calc_mode":"parameter"},{"guid":"de256650-710a-11f0-a040-7f2cfa045483","title":"GMV","calc_mode":"formula"},{"guid":"category_level_1_n71b","title":"category_level_1","calc_mode":"direct"},{"guid":"category_level_2_exd4","title":"category_level_2","calc_mode":"direct"},{"guid":"category_level_3_50lm","title":"category_level_3","calc_mode":"direct"},{"guid":"region_delivery_efn9","title":"region_delivery","calc_mode":"direct"},{"guid":"city_delivery_ho3c","title":"city_delivery","calc_mode":"direct"},{"guid":"delivery_type_juix","title":"delivery_type","calc_mode":"direct"},{"guid":"delivery_service_blbn","title":"delivery_service","calc_mode":"direct"},{"guid":"sku_color_xokm","title":"sku_color","calc_mode":"direct"},{"guid":"user_gender_fqvv","title":"user_gender","calc_mode":"direct"},{"guid":"user_platform_rhsy","title":"user_platform","calc_mode":"direct"},{"guid":"user_id_9k0n","title":"user_id","calc_mode":"direct"},{"guid":"order_id_iejj","title":"order_id","calc_mode":"direct"},{"guid":"creation_dt_4enj","title":"creation_dt","calc_mode":"direct"},{"guid":"delivery_dt_y2sz","title":"delivery_dt","calc_mode":"direct"},{"guid":"amount_52rb","title":"amount","calc_mode":"direct"}]]}},"name":"Indicator","type":"metric_wizard_node","annotation":null}},"5":{"widget":{"data":{"meta":"{\n \"links\": {\n \"dataset\": \"4\"\n }\n}","config":"\n\nmodule.exports = {\n title: {\n text: 'Детализация сводных данных',\n style: {\n 'text-align': 'left',\n 'font-size': '16px',\n 'font-style': 'italic',\n 'color': 'var(--g-color-text-hint)',\n 'margin-bottom': '16px',\n }\n },\n size: 'l',\n sort: 'id-rand-int',\n order: 'asc',\n};\n","params":"module.exports = {\n // разрезы к визуализации по строкам\n dimension_1:['region_delivery'],\n dimension_2:[''],\n dimension_3:[''],\n dimension_4:[''],\n dimension_5:[''],\n // разрезы к визуализации по столбцам\n dim_col1:['Date scaled'],\n // тут надо перечислить поля, которые будут участвовать в фильтрации из датасета, для этого в датасете нажмите \"показать id\" и скопируйте сюда idшники\n filter_fields_ids:['product_type_rrf6|store_name_rus_3aut|product_name_rjpb|gtin_icnr'],\n // передача массового значения из эксель, например, и подстановка в IN оператор, влияет положительно на производительность\n mass_filter_fields_ids:['gtin_icnr'],\n // Список метрик к отрисовке, для self-service анализа заводите как параметр ручного ввода на дашборд\n metrics_list:['GMV','Orders'],\n // NEW ATTRIBUTE alias_en TO WORK WITH\n metrics_defs:[`{\n \"Orders\":{\"alias_en\":\"Orders, cnt\",\"alias\":\"Заказы\",\"type\":\"abs\"},\n \"GMV\":{\"alias_en\":\"Sales, rub\",\"alias\":\"Продажи, руб\",\"type\":\"abs\",\"def\":\"Продано по централизованным ценам\"}\n }`],\n // параметр ручного ввода ввести на дашборде - он автоматически свяжется\n date_interval:['__interval_2024-08-12T00:00:00.000Z_2024-08-18T00:00:00.000Z'],\n // параметр ручного ввода ввести на дашборде - он автоматически свяжется\n date_scale:['week'],\n // поле, которое имеет формулу DATETRUNC([some_date],[date_scale]) для приведения к началу периода\n date_dimension:['Date scaled'],\n // Поле для фильтра данных в таблице, не равно полю с приведением к началу месяца, чтобы можно было оптимально выбирать данные\n filter_date_dimension:['creation_dt'],\n // сколько строк выбирать из источника LIMIT\n row_limit:['1000'],\n // какой вид таблички генерировать, в текущей версии только PoP\n table_type:['pop'],\n // список к передаче параметров в датасет\n params_to_send:['date_scale|'],\n // что показывать в отклонениях, лучше вывести как параметр на дашбдорд, значения abs, %, both\n\n //FOR THE BEAUTY\n date_format:['DD.MM'],\n heatmap:['true'],\n heatmap_color:['#BBFFAA'],\n heatmap_percentile:['50'],\n // NEW FEATURE TO WORK WITH\n lang:['ru']\n};","prepare":"// Импорт необходимых библиотек и получение параметров\nconst {dateTimeParse} = require('@gravity-ui/date-utils'); // Библиотека для работы с датами\nconst Dataset = require('libs/dataset/v2'); // Библиотека для обработки данных\nconst params = Editor.getParams(); // Получение параметров из редактора\n\nfunction createPivotTable(preparedData, rows_dims, cols_dims, metrics, params) {\n const head = []; // Массив для заголовков таблицы\n const rows = []; // Массив для строк таблицы\n \n // Получаем параметры форматирования\n const dateFormat = params.date_format && params.date_format[0] ? params.date_format[0] : \"YYYY-MM-DD\"; // Формат даты\n const metrics_defs = JSON.parse(params.metrics_defs[0]); // Определения метрик\n const useHeatmap = metrics.length === 1 && params.heatmap && params.heatmap[0] === 'true'; // Использовать тепловую карту?\n const heatmapColor = params.heatmap_color && params.heatmap_color[0] ? params.heatmap_color[0] : '#ff0000'; // Цвет тепловой карты\n const heatmapPercentile = params.heatmap_percentile && params.heatmap_percentile[0] ? \n parseInt(params.heatmap_percentile[0], 10) : 10; // Процентиль для тепловой карты\n\n\n function isDateDimension(dimensionName) {\n return dimensionName.toLowerCase().includes('дата') || \n dimensionName.toLowerCase().includes('date');\n }\n \n\n function formatDateTime(value, format) {\n if (!value) return '';\n \n try {\n const date = new Date(value);\n if (isNaN(date.getTime())) return value; // Если не удалось распарсить дату, возвращаем исходное значение\n return dateTimeParse(value).format(format); // Форматируем дату\n } catch (e) {\n return value; // В случае ошибки возвращаем исходное значение\n }\n }\n\n\n function compareDates(a, b) {\n const dateA = new Date(a);\n const dateB = new Date(b);\n \n // Если не удалось распарсить даты, сравниваем как строки\n if (isNaN(dateA.getTime()) || isNaN(dateB.getTime())) {\n return String(a).localeCompare(String(b));\n }\n \n return dateA - dateB; // Разница между датами\n }\n \n\n function getUniqueValues(data, dimension) {\n const values = new Set(); // Используем Set для хранения уникальных значений\n data.forEach(item => {\n const value = item[dimension] !== undefined ? item[dimension] : \"Undefined\"; // Если значения нет, используем \"Undefined\"\n values.add(value);\n });\n \n const uniqueValues = Array.from(values); // Преобразуем Set в массив\n \n // Сортируем по-разному в зависимости от типа измерения\n return isDateDimension(dimension) ? uniqueValues.sort(compareDates) : uniqueValues.sort();\n }\n \n\n function aggregateData() {\n const aggregated = {}; // Объект для хранения агрегированных данных\n \n preparedData.forEach(item => {\n // Создаем ключи для строк и столбцов\n const rowKey = rows_dims.map(dim => item[dim]).join('|');\n const colKey = cols_dims.map(dim => item[dim]).join('|');\n \n // Инициализируем структуру для строки, если ее еще нет\n if (!aggregated[rowKey]) {\n aggregated[rowKey] = {\n row_values: rows_dims.map(dim => item[dim]), // Значения измерений для строки\n columns: {}\n };\n }\n \n // Инициализируем структуру для столбца, если его еще нет\n if (!aggregated[rowKey].columns[colKey]) {\n aggregated[rowKey].columns[colKey] = {\n col_values: cols_dims.map(dim => item[dim]), // Значения измерений для столбца\n metrics: {}\n };\n }\n \n // Суммируем метрики для каждой комбинации строки и столбца\n metrics.forEach(metric => {\n if (!aggregated[rowKey].columns[colKey].metrics[metric]) {\n aggregated[rowKey].columns[colKey].metrics[metric] = 0;\n }\n aggregated[rowKey].columns[colKey].metrics[metric] += Number(item[metric]) || 0;\n });\n });\n \n return aggregated;\n }\n \n /**\n * Генерирует заголовки таблицы\n */\n function generateHeaders() {\n // Добавляем заголовки для измерений строк\n rows_dims.forEach((dim, index) => {\n head.push({\n id: `dim_${index}`,\n name: dim,\n type: 'text',\n css: { 'font-weight': 'bold' }, // Жирный шрифт для заголовков\n group: false,\n width: 150\n });\n });\n\n // Если нет измерений для столбцов, добавляем метрики как обычные столбцы\n if (cols_dims.length === 0) {\n metrics.forEach(metric => {\n head.push({\n id: `metric_${metric}`,\n name: metric,\n type: 'text',\n css: { 'font-weight': 'bold' },\n group: false,\n width: 120,\n hint: metrics_defs[metric] ? metrics_defs[metric].def : undefined // Добавляем подсказку, если есть\n });\n });\n return;\n }\n\n function buildColumnHeaderHierarchy() {\n const uniqueColValues = {}; // Уникальные значения для каждого измерения столбцов\n cols_dims.forEach(dim => {\n uniqueColValues[dim] = getUniqueValues(preparedData, dim);\n });\n\n\n function buildHeadersRecursive(level, path = [], headersByLevel = {}) {\n if (level >= cols_dims.length) return headersByLevel;\n\n const dim = cols_dims[level]; // Текущее измерение\n\n uniqueColValues[dim].forEach(value => {\n const currentPath = [...path, value]; // Добавляем текущее значение к пути\n const pathKey = currentPath.join('|'); // Ключ для пути\n\n if (!headersByLevel[level]) headersByLevel[level] = []; // Инициализируем массив для уровня\n\n // Проверяем, есть ли уже такой заголовок\n const existingHeader = headersByLevel[level].find(h => h.path === pathKey);\n\n if (!existingHeader) {\n let headerValue = value;\n // Форматируем дату, если нужно\n if (isDateDimension(dim)) {\n headerValue = formatDateTime(value, dateFormat);\n }\n\n // Добавляем заголовок\n headersByLevel[level].push({\n value: headerValue,\n originalValue: value,\n path: pathKey,\n parent: path.join('|')\n });\n }\n\n // Рекурсивно обрабатываем следующий уровень\n buildHeadersRecursive(level + 1, currentPath, headersByLevel);\n });\n\n return headersByLevel;\n }\n\n return buildHeadersRecursive(0);\n }\n\n // Если есть измерения для столбцов, строим иерархию заголовков\n if (cols_dims.length > 0) {\n const headerHierarchy = buildColumnHeaderHierarchy();\n const addedMetrics = new Set(); // Для отслеживания добавленных метрик\n \n\n function buildHeadersForMatrix(headerHierarchy) {\n return headerHierarchy[0].map(header => {\n\n function createSubHeaders(header, level) {\n // Если достигли последнего уровня, добавляем метрики\n if (level >= cols_dims.length) {\n return metrics.map(metric => ({\n id: `${header.path}_${metric}`,\n name: metric,\n width: 150,\n type: 'text',\n css: { 'text-align': 'center' },\n hint: addedMetrics.has(metric) ? undefined : (metrics_defs[metric] ? metrics_defs[metric].def : undefined),\n addedMetrics: addedMetrics.add(metric) // Отмечаем метрику как добавленную\n }));\n }\n\n // Ищем подзаголовки для текущего заголовка\n const children = headerHierarchy[level].filter(h => h.parent === header.path);\n\n // Если нет подзаголовков, добавляем метрики\n if (children.length === 0) {\n const localAddedMetrics = new Set();\n return metrics.map(metric => ({\n id: `${header.path}_${metric}`,\n name: metric,\n width: 120,\n type: 'text',\n css: { 'text-align': 'center' },\n hint: localAddedMetrics.has(metric) ? undefined : (metrics_defs[metric] ? metrics_defs[metric].def : undefined),\n addedMetrics: localAddedMetrics.add(metric)\n }));\n }\n\n // Рекурсивно обрабатываем подзаголовки\n return children.map(child => ({\n name: child.value,\n type: 'text',\n css: { 'font-weight': 'bold', 'text-align': 'center' },\n sub: createSubHeaders(child, level + 1)\n }));\n }\n\n // Создаем заголовок верхнего уровня с подзаголовками\n return {\n name: header.value,\n type: 'text',\n css: { 'font-weight': 'bold', 'text-align': 'center' },\n sub: createSubHeaders(header, 1)\n };\n });\n }\n\n // Добавляем заголовки для матрицы\n head.push(...buildHeadersForMatrix(headerHierarchy));\n }\n }\n \n\n function organizeRowsHierarchically(aggregatedData) {\n // Если нет измерений для строк, возвращаем пустую строку\n if (rows_dims.length === 0) {\n return [{ row_values: [], data: aggregatedData }];\n }\n \n const rowHierarchy = {}; // Иерархия строк\n \n // Создаем иерархию строк\n Object.values(aggregatedData).forEach(rowData => {\n let current = rowHierarchy;\n \n for (let i = 0; i < rows_dims.length; i++) {\n const value = rowData.row_values[i];\n \n if (i === rows_dims.length - 1) {\n // Последний уровень - добавляем данные\n if (!current[value]) {\n current[value] = { data: rowData };\n }\n } else {\n // Промежуточный уровень - добавляем дочерние элементы\n if (!current[value]) {\n current[value] = { children: {} };\n }\n current = current[value].children;\n }\n }\n });\n \n const flatRows = []; // Плоский список строк\n \n function flattenHierarchy(node, level = 0, ancestors = []) {\n let keys = Object.keys(node).filter(k => k !== 'children' && k !== 'data');\n \n // Сортируем ключи\n if (level < rows_dims.length && isDateDimension(rows_dims[level])) {\n keys = keys.sort(compareDates); // Сортировка дат\n } else {\n keys = keys.sort(); // Обычная сортировка\n }\n \n keys.forEach(value => {\n const row = node[value];\n const currentValues = [...ancestors];\n \n currentValues[level] = value; // Добавляем текущее значение\n \n if (row.data) {\n // Добавляем строку с данными\n flatRows.push({\n row_values: currentValues,\n data: row.data\n });\n }\n \n if (row.children) {\n // Рекурсивно обрабатываем дочерние элементы\n flattenHierarchy(row.children, level + 1, currentValues);\n }\n });\n }\n \n flattenHierarchy(rowHierarchy, 0, new Array(rows_dims.length).fill(null));\n return flatRows;\n }\n \n function fillRows() {\n const aggregatedData = aggregateData(); // Агрегированные данные\n const organizedRows = organizeRowsHierarchically(aggregatedData); // Организованные строки\n const colCombinations = []; // Комбинации значений столбцов\n \n // Если есть измерения для столбцов, собираем комбинации\n if (cols_dims.length > 0) {\n const colMap = new Map(); // Карта для отслеживания уникальных комбинаций\n \n preparedData.forEach(item => {\n const colValues = cols_dims.map(dim => item[dim]); // Значения для столбцов\n const colKey = colValues.join('|'); // Ключ для комбинации\n \n // Добавляем уникальные комбинации\n if (!colMap.has(colKey)) {\n colMap.set(colKey, colValues);\n colCombinations.push(colValues);\n }\n });\n \n // Сортируем комбинации по дате, если первое измерение - дата\n if (cols_dims.length > 0 && isDateDimension(cols_dims[0])) {\n colCombinations.sort((a, b) => compareDates(a[0], b[0]));\n }\n }\n \n // Собираем значения метрик для тепловой карты\n let allMetricValues = [];\n if (useHeatmap) {\n const metric = metrics[0]; // Используется только первая метрика\n \n organizedRows.forEach(rowInfo => {\n if (cols_dims.length === 0) {\n // Если нет измерений для столбцов\n if (rowInfo.data && rowInfo.data.columns[''] && \n rowInfo.data.columns[''].metrics[metric] !== undefined) {\n allMetricValues.push(rowInfo.data.columns[''].metrics[metric]);\n }\n } else {\n // Если есть измерения для столбцов\n colCombinations.forEach(colValues => {\n const colKey = colValues.join('|');\n \n if (rowInfo.data && \n rowInfo.data.columns[colKey] && \n rowInfo.data.columns[colKey].metrics[metric] !== undefined) {\n allMetricValues.push(rowInfo.data.columns[colKey].metrics[metric]);\n }\n });\n }\n });\n \n // Фильтруем нулевые значения\n allMetricValues = allMetricValues.filter(val => val !== null && val !== undefined);\n }\n \n // Вычисляем пороговые значения для тепловой карты\n let thresholdValue = null;\n let maxValue = null;\n \n if (useHeatmap && allMetricValues.length > 0) {\n const sortedValues = [...allMetricValues].sort((a, b) => a - b); // Сортируем значения\n const percentileIndex = Math.floor(sortedValues.length * (1 - heatmapPercentile / 100)); // Индекс для процентиля\n thresholdValue = sortedValues[Math.max(0, percentileIndex)]; // Пороговое значение\n maxValue = sortedValues[sortedValues.length - 1]; // Максимальное значение\n }\n \n // Заполняем строки таблицы\n organizedRows.forEach(rowInfo => {\n const cells = []; // Ячейки для строки\n \n // Добавляем значения измерений для строки\n rowInfo.row_values.forEach((value, index) => {\n const dim = rows_dims[index];\n let formattedValue = value;\n \n // Форматируем дату, если нужно\n if (isDateDimension(dim)) {\n formattedValue = formatDateTime(value, dateFormat);\n }\n \n cells.push({\n value: value, // Исходное значение\n formattedValue: formattedValue, // Отформатированное значение\n css: { 'text-align': 'left' } // Выравнивание по левому краю\n });\n });\n \n // Если нет измерений для столбцов, добавляем метрики напрямую\n if (cols_dims.length === 0) {\n metrics.forEach(metric => {\n let value = null;\n \n // Получаем значение метрики\n if (rowInfo.data) {\n const colData = rowInfo.data.columns[''];\n if (colData && colData.metrics[metric] !== undefined) {\n value = colData.metrics[metric];\n }\n }\n \n // Форматируем значение\n const metric_type = metrics_defs[metric] ? metrics_defs[metric].type : 'abs';\n const formattedValue = nFormatter(value, 1, metric_type);\n \n // Стили для ячейки\n const cellCss = { \n 'text-align': 'right' // Выравнивание по правому краю\n };\n \n // Добавляем цвет для тепловой карты, если нужно\n if (useHeatmap && value !== null && value !== undefined && value >= thresholdValue) {\n const normalizedValue = maxValue > thresholdValue \n ? (value - thresholdValue) / (maxValue - thresholdValue) // Нормализация значения\n : 1;\n \n // Вычисляем прозрачность для цвета\n let opacity = Math.round(normalizedValue * 255).toString(16).padStart(2, '0');\n opacity = opacity === '00' ? '01' : opacity; // Минимальная прозрачность\n \n cellCss['background-color'] = `${heatmapColor}${opacity}`; // Цвет фона с прозрачностью\n }\n \n // Добавляем ячейку\n cells.push({\n value: value, // Исходное значение\n formattedValue: formattedValue, // Отформатированное значение\n css: cellCss // Стили\n });\n });\n } else {\n // Если есть измерения для столбцов, добавляем метрики для каждой комбинации столбцов\n colCombinations.forEach(colValues => {\n const colKey = colValues.join('|'); // Ключ для комбинации столбцов\n \n metrics.forEach(metric => {\n let value = null;\n \n // Получаем значение метрики\n if (rowInfo.data && \n rowInfo.data.columns[colKey] && \n rowInfo.data.columns[colKey].metrics[metric] !== undefined) {\n value = rowInfo.data.columns[colKey].metrics[metric];\n }\n \n // Форматируем значение\n const metric_type = metrics_defs[metric] ? metrics_defs[metric].type : 'abs';\n const formattedValue = nFormatter(value, 1, metric_type);\n \n // Стили для ячейки\n const cellCss = { \n 'text-align': 'right' // Выравнивание по правому краю\n };\n \n // Добавляем цвет для тепловой карты, если нужно\n if (useHeatmap && value !== null && value !== undefined && value >= thresholdValue) {\n const normalizedValue = maxValue > thresholdValue \n ? (value - thresholdValue) / (maxValue - thresholdValue) // Нормализация значения\n : 1;\n \n // Вычисляем прозрачность для цвета\n let opacity = Math.round(normalizedValue * 255).toString(16).padStart(2, '0');\n opacity = opacity === '00' ? '01' : opacity; // Минимальная прозрачность\n \n cellCss['background-color'] = `${heatmapColor}${opacity}`; // Цвет фона с прозрачностью\n }\n \n // Добавляем ячейку\n cells.push({\n value: value, // Исходное значение\n formattedValue: formattedValue, // Отформатированное значение\n css: cellCss // Стили\n });\n });\n });\n }\n \n // Добавляем строку в таблицу\n rows.push({ cells });\n });\n }\n function nFormatter(num, digits = 2, type = 'abs', format = 'pretty', cutZeros = true) {\n digits = isNaN(digits) ? 2 : digits; // Проверка на корректность числа цифр\n const sign_symb = num >= 0 ? '' : '-'; // Знак числа\n \n // Таблица для сокращения больших чисел\n const lookup = [\n { value: 0, symbol: \"\"},\n { value: 1, symbol: \"\" },\n { value: 1e3, symbol: \"K\" }, // Тысячи\n { value: 1e6, symbol: \"M\" }, // Миллионы\n { value: 1e9, symbol: \"B\" }, // Миллиарды\n { value: 1e12, symbol: \"T\" }, // Триллионы\n { value: 1e15, symbol: \"P\" }, // Квадриллионы\n { value: 1e18, symbol: \"E\" } // Квинтиллионы\n ];\n\n if (type === 'abs' || type === 'val') {\n num = Math.abs(num); // Абсолютное значение\n const rx = /\\.0+$|(\\.[0-9]*[1-9])0+$/; // Регулярное выражение для обрезки нулей\n\n // Находим подходящую единицу измерения\n const item = lookup.slice().reverse().find(item => num >= item.value);\n\n if (format === 'pretty' && type !== 'val') {\n if (item ? item.value : 0 !== 0) {\n // Форматируем с единицей измерения\n const value = `${sign_symb}${item ? (num / item.value).toFixed(digits) + item.symbol : \"0\"}`;\n return cutZeros ? value.replace(rx, \"$1\") : value; // Обрезаем нули, если нужно\n } else {\n // Форматируем без единицы измерения\n const value = `${sign_symb}${item ? (num / 1).toFixed(digits) + item.symbol : \"0\"}`;\n return cutZeros ? value.replace(rx, \"$1\") : value; // Обрезаем нули, если нужно\n } \n } else {\n // Форматируем без сокращений\n return `${sign_symb}${item ? (num).toFixed(digits) : \"0\"}`;\n }\n } \n else if (type === '%') {\n num = Math.abs(num); // Абсолютное значение\n // Округляем значение с учетом процента\n const roundedNum = Math.round((num * 100 + Number.EPSILON) * Math.pow(10, digits)) / Math.pow(10, digits);\n \n return `${sign_symb}${roundedNum.toFixed(digits)}%`; // Форматируем как процент\n }\n }\n \n // Генерируем заголовки и заполняем строки\n generateHeaders();\n fillRows();\n \n // Возвращаем результат\n return { head, rows };\n}\n\n// Загружаем и обрабатываем данные\nconst loadedData = Editor.getLoadedData(); // Получаем загруженные данные\nconst preparedData = Dataset.processData(loadedData, 'dataset', Editor); // Обрабатываем данные\n\n// Получаем параметры для сводной таблицы\nconst metrics_list = params.metrics_list; // Список метрик\n// Измерения для строк (до 4 измерений, пустые отфильтрованы)\nconst dimensions_rows = [params.dimension_1[0], params.dimension_2[0], params.dimension_3[0], params.dimension_4[0],params.dimension_5[0]].filter(str => str !== '');\nconst dimensions_cols = [params.dim_col1[0]]; // Измерение для столбцов\n\n// Создаем и возвращаем сводную таблицу\nmodule.exports = createPivotTable(preparedData, dimensions_rows, dimensions_cols, metrics_list, params);\n","sources":"const {buildSource} = require('libs/dataset/v2');\nconst {dateTimeParse,dateTime,addDays, addUnits,startOf} = require('@gravity-ui/date-utils');\nconst FORMAT = 'YYYY-MM-DD'\n\n\nfunction arrayChecker(some) {\n if (Array.isArray(some)) {\n return some\n }\n else {\n return [some]\n }\n}\n\n\nfunction getDateFilters(ce_obj,params) {\n let date_interval = params.date_interval[0];\n let date_dim = params.filter_date_dimension[0];\n let scale_name = params.date_scale[0];\n let scale_dict = {'day':'D','week':'W','month':'M'};\n\n const {from:from_date,to:to_date} = ce_obj.resolveInterval(date_interval);\n let right_date = to_date;\n let left_date = from_date;\n const dateTo = dateTimeParse(right_date).add(1,scale_name).startOf(scale_dict[scale_name]).add(-1,'day').format(FORMAT);\n const dateFrom = dateTimeParse(left_date).startOf(scale_dict[scale_name]).format(FORMAT);\n\n const dateFilter = {column: date_dim,\n operation: 'BETWEEN',\n values: [dateFrom, dateTo]}\n return dateFilter;\n}\n\n\nconst params = Editor.getParams();\n// для удобства все параметры переносим в переменные без парамс\nconst date_interval = params.date_interval[0];\nconst limit = parseInt(params.row_limit[0]);\nconst metrics_list = params.metrics_list;\nconst params_to_send = params.params_to_send[0];\nconst filter_fields = params.filter_fields_ids['0'].split('|');\nconst filter_mass = params.mass_filter_fields_ids['0'].split('|');\n\n// массив для заполнения условий\nlet where = [];\n// колонки для выбора\nlet cols = [];\n// передавать параметры в датасет\nlet filled_params = []\n\n// 1) add date interval filter\nlet date_where = Editor.resolveInterval(date_interval);\nlet val = [date_where['from'],date_where['to']];\n\nlet q = getDateFilters(Editor,params);\n\nwhere.push(q)\n\nfor (const [key, value] of Object.entries(params)) {\n // добавляем все параметры из переданных и не пустых\n if (params_to_send.includes(key)) {\n filled_params.push({id:key,value:value.toString()});\n };\n\n if (filter_fields.includes(key) && value != '') {\n let val, suff;\n\n\n if (value[0] && value[0].substr(0, 2) === '__') {\n const {operation:suffx, value:vala} = Editor.resolveOperation(value);\n console.log(suffx,vala)\n val = vala;\n suff = suffx;\n\n } else {\n val = value;\n suff = 'IN';\n }\n\n\n if (Editor.resolveRelative(val) != null) {\n val = Editor.resolveRelative(val);\n }\n if (Editor.resolveInterval(value) != null) {\n val = [Editor.resolveInterval(value)['from'],Editor.resolveInterval(value)['to']];\n suff = 'BETWEEN'\n }\n\n if (filter_mass.includes(key)) {\n suff = 'IN';\n val = value[0].split(' ');\n }\n \n where.push({type:'id',column: key, operation: suff, values: arrayChecker(val)})\n }\n \n if ((key.startsWith('dimension_') || key.startsWith('dim_col')) && value[0] != '') {\n cols.push(value[0]);\n }\n\n}\n\n// добавляем колонки для выбора данных\ncols.push(...metrics_list);\n\n\nmodule.exports = {\n dataset: buildSource({\n id: Editor.getId('dataset'),\n columns: cols,\n where: where,\n parameters:filled_params,\n order:params.date_dimension[0],\n limit:limit*2,\n order_by:[{'direction':'DESC','column':metrics_list[0]}]\n })\n }\n","controls":"module.exports = {};"},"name":"0. Edit Chart with AI","type":"table_node","annotation":{"description":""}}},"6":{"widget":{"data":{"meta":"{\n \"links\": {\n \"dataset\": \"4\"\n }\n}","params":"module.exports = {\n\n // Тут надо перечислить поля, которые будут участвовать в фильтрации из датасета, для этого в датасете нажмите \"показать id\" и скопируйте их сюда\n // Следите за актуализацией id полей при их изменении в датасете!\n filter_fields_ids:['deliverytype_heh6|paymenttype_kig4|gender_ezzk|orderid_oakw'],\n // Передача массового значения из эксель, например, и подстановка в IN оператор, влияет положительно на производительность\n // Не используйте длинные значения параметров, т.к. можно выйти за лимит длины строки, поддерживаемый браузером!\n // Следите за актуализацией id полей при их изменении в датасете\n mass_filter_fields_ids:['orderid_oakw'],\n // Список метрик к отрисовке, для self-service анализа заводите как параметр ручного ввода на дашборд\n // Не используйте длинные значения параметров, т.к. можно выйти за лимит длины строки, поддерживаемый браузером!\n metrics_list:['GMV','AOV'],\n // Тут в виде JSON должны быть описаны метрики, это требуется, чтобы можно было понять, как какую метрику рисовать, в абсолютах, в процентах\n // Имейте в виду, что символы экранируются, постарайтесь избегать различных спец-символов\n // Не используйте длинные значения параметров, т.к. можно выйти за лимит длины строки, поддерживаемый браузером!\n // Следите за актуализацией id полей при их изменении в датасете\n metrics_defs:[`{\"GMV\":{\"description\":\"Gross Merchandise Volume\",\"type\":\"abs\"},\"AOV\":{\"description\":\"Average Order Value\",\"type\":\"abs\"}}`],\n // Параметр ручного ввода ввести на дашборде - он автоматически свяжется\n date_interval:['__interval_2024-08-12T00:00:00.000Z_2024-08-18T00:00:00.000Z'],\n // Параметр ручного ввода ввести на дашборде - он автоматически свяжется\n date_scale:['week'],\n // Поле, которое имеет формулу DATETRUNC([some_date],[date_scale]) для приведения к началу периода\n // Следите за актуализацией id полей при их изменении в датасете\n date_dimension:['Date scaled'],\n // Поле для фильтра данных в таблице, не равно полю с приведением к началу месяца, чтобы можно было оптимально выбирать данные\n // Следите за актуализацией id полей при их изменении в датасете\n filter_date_dimension:['creation_dt'],\n // Сколько строк выбирать из источника LIMIT\n params_to_send:['date_scale|'],\n // Что показывать в отклонениях, лучше вывести как параметр на дашбдорд, значения abs, %, both\n pop_type:['abs'],\n // С каким днем сравнивать \n day_wow:['7'],\n \n \n font_size:['14px'],\n dec_num:['1']\n};\n","prepare":"const Dataset = require('libs/dataset/v2');\n\nconst params = Editor.getParams();\nconst metrics_list = params.metrics_list;\nconst metrics_params = JSON.parse(params.metrics_defs[0]);\n\n\n// Обработка данных\nconst total_data = Dataset.getDatasetRows({datasetName: 'dataset'});\nconst dynamic_data = Dataset.getDatasetRows({datasetName: 'dataset_dynamic'});\n\nconsole.log(\n'//const total_data = ' + JSON.stringify(total_data) + ';' +\n'\\n//const dynamic_data = ' + JSON.stringify(dynamic_data)+';' +\n'\\n//nmetrics_params = ' + params.metrics_defs[0]+ ';' +\n'\\n//nmetrics_list = ' + JSON.stringify(params.metrics_list) + ';'\n)","sources":"const { buildSource } = require('libs/dataset/v2');\nconst { dateTimeParse } = require('@gravity-ui/date-utils');\nconst FORMAT = 'YYYY-MM-DD';\n\nconst params = Editor.getParams();\n\n// Для удобства все параметры переносим в переменные без params\nconst date_interval = params.date_interval[0];\nconst metrics_list = params.metrics_list;\nconst params_to_send = params.params_to_send[0];\nconst filter_fields = params.filter_fields_ids['0'].split('|');\nconst filter_mass = params.mass_filter_fields_ids['0'].split('|');\n\n/**\n * Преобразует значение в массив, если оно им не является\n * @param {*} value - Значение для проверки\n * @returns {Array} - Массив\n */\nfunction ensureArray(value) {\n return Array.isArray(value) ? value : [value];\n}\n\n/**\n * Получает фильтр дат для PoP (Period over Period) сравнения\n * @param {Object} params - Параметры\n * @returns {Object} - Объект фильтра дат\n */\nfunction getDateFilterPoP(params) {\n const date_dim = params.filter_date_dimension[0];\n const scale_name = params.date_scale[0];\n\n const {from:from_date, to: to_date } = Editor.resolveInterval(date_interval);\n const right_date = to_date;\n\n let dateFilter = {\n column: date_dim,\n operation: 'BETWEEN',\n values: [from_date, to_date],\n };\n \n\n return dateFilter;\n}\n\n\n// Массив для заполнения условий фильтрации\nconst where = [];\n// Колонки для выбора\nconst cols = [];\n// Параметры для передачи в датасет\nconst filled_params = [];\n\n// 1) Добавляем фильтр дат для PoP (Period over Period) сравнения\nwhere.push(getDateFilterPoP(params));\n\n// Обрабатываем все параметры\nfor (const [key, value] of Object.entries(params)) {\n // Добавляем все параметры из переданных и не пустых\n if (params_to_send.includes(key)) {\n filled_params.push({ id: key, value: value.toString() });\n }\n\n // Обрабатываем фильтры\n if (filter_fields.includes(key) && value !== '') {\n let val, suff;\n\n // Проверяем формат входных данных\n if (value[0] && value[0].substr(0, 2) === '__') {\n const {operation:suffx, value:vala} = Editor.resolveOperation(value);\n val = vala;\n suff = suffx;\n\n } else {\n val = value;\n suff = 'IN';\n }\n\n // Проверяем и преобразуем относительные даты\n if (Editor.resolveRelative(val) != null) {\n val = Editor.resolveRelative(val);\n }\n\n // Проверяем и преобразуем интервалы\n if (Editor.resolveInterval(value) != null) {\n val = [Editor.resolveInterval(value)['from'], Editor.resolveInterval(value)['to']];\n suff = 'BETWEEN';\n }\n\n //Проверяем фильтры с массовыми значениями\n if (filter_mass.includes(key)) {\n suff = 'IN';\n val = value[0].split(' ');\n }\n \n // Добавляем условие в массив where\n where.push({\n type: 'id',\n column: key,\n operation: suff,\n values: ensureArray(val)\n });\n }\n\n // Добавляем измерения в колонки\n if (key.startsWith('dimension_') && value[0] !== '') {\n cols.push(value[0]);\n }\n}\n\n// Добавляем метрики в колонки\ncols.push(...metrics_list);\n\n\n\n// Экспортируем настройки для buildSource\nmodule.exports = {\n dataset: buildSource({\n id: Editor.getId(\"dataset\"),\n columns: cols,\n where: where,\n parameters: filled_params,\n order: params.date_dimension[0],\n order_by: [{ 'direction': 'DESC', 'column': metrics_list[0] }],\n }),\n dataset_dynamic: buildSource({\n id: Editor.getId(\"dataset\"),\n columns: [...cols,'Date scaled'],\n where: where,\n parameters: filled_params,\n order: params.date_dimension[0],\n order_by: [{ 'direction': 'DESC', 'column': metrics_list[0] }],\n })\n};\n","controls":"module.exports = {};\n"},"name":"1. AI Chart","type":"advanced-chart_node","annotation":{"description":""}}},"9":{"widget":{"data":{"meta":"{\n \"links\": {\n \"dataset\": \"0\"\n }\n}","params":"module.exports = {\n\n};\n","prepare":"const Dataset = require('libs/dataset/v2');\n\nconst params = Editor.getParams();\n\n\n// Обработка данных\nconst full_data = Dataset.getDatasetRows({datasetName: 'dataset'});\n\n\n//const full_data = [{\"stage_id\":\"1\",\"stage_name\":\"Миссия `Мяутоматизация`: запуск котофабрики будущего\",\"start_dt\":\"2025-01-15\",\"duration\":\"180\",\"prevous_stage_id\":\"\",\"executor_login\":\"project_manager\"},{\"stage_id\":\"10\",\"stage_name\":\"Распространение механического мурчания по всему миру\",\"start_dt\":\"\",\"duration\":\"90\",\"prevous_stage_id\":\"9\",\"executor_login\":\"sales_team\"},{\"stage_id\":\"11\",\"stage_name\":\"Операция `Умная голова в песке`: создание говорящих страусов\",\"start_dt\":\"2025-03-15\",\"duration\":\"210\",\"prevous_stage_id\":\"\",\"executor_login\":\"project_manager\"},{\"stage_id\":\"12\",\"stage_name\":\"Научить ИИ прятать голову при сложных вопросах как настоящий эксперт\",\"start_dt\":\"\",\"duration\":\"60\",\"prevous_stage_id\":\"11\",\"executor_login\":\"ai_team\"},{\"stage_id\":\"13\",\"stage_name\":\"Конструирование металлоперьевых несушек смысла\",\"start_dt\":\"\",\"duration\":\"45\",\"prevous_stage_id\":\"11\",\"executor_login\":\"mechanical_engineers\"},{\"stage_id\":\"14\",\"stage_name\":\"Сборка первого страуса, который знает всё и ничего одновременно\",\"start_dt\":\"\",\"duration\":\"50\",\"prevous_stage_id\":\"12,13\",\"executor_login\":\"prototype_team\"},{\"stage_id\":\"15\",\"stage_name\":\"Вживление словарей в механические перья\",\"start_dt\":\"\",\"duration\":\"40\",\"prevous_stage_id\":\"14\",\"executor_login\":\"hardware_team\"},{\"stage_id\":\"16\",\"stage_name\":\"Обучение страуса говорить умными фразами в неподходящий момент\",\"start_dt\":\"\",\"duration\":\"35\",\"prevous_stage_id\":\"14\",\"executor_login\":\"software_team\"},{\"stage_id\":\"17\",\"stage_name\":\"Проектирование инкубатора для искусственного интеллекта\",\"start_dt\":\"\",\"duration\":\"30\",\"prevous_stage_id\":\"11\",\"executor_login\":\"planning_team\"},{\"stage_id\":\"18\",\"stage_name\":\"Монтаж гнезд для кремниевых яиц мудрости\",\"start_dt\":\"\",\"duration\":\"60\",\"prevous_stage_id\":\"15,17\",\"executor_login\":\"installation_team\"},{\"stage_id\":\"19\",\"stage_name\":\"Создание академии для птиц, которые умнее своих создателей\",\"start_dt\":\"\",\"duration\":\"40\",\"prevous_stage_id\":\"16,18\",\"executor_login\":\"training_team\"},{\"stage_id\":\"2\",\"stage_name\":\"Выяснение, сколько котиков человечеству не хватает для полного счастья\",\"start_dt\":\"\",\"duration\":\"30\",\"prevous_stage_id\":\"1\",\"executor_login\":\"marketing_team\"},{\"stage_id\":\"20\",\"stage_name\":\"Торжественный выпуск первой партии пернатых философов\",\"start_dt\":\"\",\"duration\":\"30\",\"prevous_stage_id\":\"19\",\"executor_login\":\"operations_team\"},{\"stage_id\":\"21\",\"stage_name\":\"Расселение умных страусов среди обычных людей\",\"start_dt\":\"\",\"duration\":\"45\",\"prevous_stage_id\":\"20\",\"executor_login\":\"distribution_team\"},{\"stage_id\":\"22\",\"stage_name\":\"Миссия `Вкус разочарования`: попкорн, который не оправдает никаких надежд\",\"start_dt\":\"2025-09-16\",\"duration\":\"150\",\"prevous_stage_id\":\"\",\"executor_login\":\"product_owner\"}];","sources":"const { buildSource } = require('libs/dataset/v2');\n\n// Экспортируем настройки для buildSource\nmodule.exports = {\n dataset: buildSource({\n id: Editor.getId(\"dataset\"),\n columns: [\"stage_id\",\"stage_name\",\"start_dt\",\"duration\",\"prevous_stage_id\",\"executor_login\"],\n order_by: [{ 'direction': 'ASC', 'column': 'stage_id' }],\n })\n};\n","controls":"module.exports = {};\n"},"name":"2. AI Gantt Chart","type":"advanced-chart_node","annotation":{"description":""}}},"10":{"widget":{"data":{"meta":"{\n \"links\": {\n \"dataset\": \"0\"\n }\n}","config":"module.exports = {\n\n};\n","params":"module.exports = {\n\n};\n","prepare":"const Dataset = require('libs/dataset/v2');\n\nconst params = Editor.getParams();\n\n\n// Обработка данных\nconst full_data = Dataset.getDatasetRows({datasetName: 'dataset'});\n\n\n//const full_data = [{\"stage_id\":\"1\",\"stage_name\":\"Миссия `Мяутоматизация`: запуск котофабрики будущего\",\"start_dt\":\"2025-01-15\",\"duration\":\"180\",\"prevous_stage_id\":\"\",\"executor_login\":\"project_manager\"},{\"stage_id\":\"10\",\"stage_name\":\"Распространение механического мурчания по всему миру\",\"start_dt\":\"\",\"duration\":\"90\",\"prevous_stage_id\":\"9\",\"executor_login\":\"sales_team\"},{\"stage_id\":\"11\",\"stage_name\":\"Операция `Умная голова в песке`: создание говорящих страусов\",\"start_dt\":\"2025-03-15\",\"duration\":\"210\",\"prevous_stage_id\":\"\",\"executor_login\":\"project_manager\"},{\"stage_id\":\"12\",\"stage_name\":\"Научить ИИ прятать голову при сложных вопросах как настоящий эксперт\",\"start_dt\":\"\",\"duration\":\"60\",\"prevous_stage_id\":\"11\",\"executor_login\":\"ai_team\"},{\"stage_id\":\"13\",\"stage_name\":\"Конструирование металлоперьевых несушек смысла\",\"start_dt\":\"\",\"duration\":\"45\",\"prevous_stage_id\":\"11\",\"executor_login\":\"mechanical_engineers\"},{\"stage_id\":\"14\",\"stage_name\":\"Сборка первого страуса, который знает всё и ничего одновременно\",\"start_dt\":\"\",\"duration\":\"50\",\"prevous_stage_id\":\"12,13\",\"executor_login\":\"prototype_team\"},{\"stage_id\":\"15\",\"stage_name\":\"Вживление словарей в механические перья\",\"start_dt\":\"\",\"duration\":\"40\",\"prevous_stage_id\":\"14\",\"executor_login\":\"hardware_team\"},{\"stage_id\":\"16\",\"stage_name\":\"Обучение страуса говорить умными фразами в неподходящий момент\",\"start_dt\":\"\",\"duration\":\"35\",\"prevous_stage_id\":\"14\",\"executor_login\":\"software_team\"},{\"stage_id\":\"17\",\"stage_name\":\"Проектирование инкубатора для искусственного интеллекта\",\"start_dt\":\"\",\"duration\":\"30\",\"prevous_stage_id\":\"11\",\"executor_login\":\"planning_team\"},{\"stage_id\":\"18\",\"stage_name\":\"Монтаж гнезд для кремниевых яиц мудрости\",\"start_dt\":\"\",\"duration\":\"60\",\"prevous_stage_id\":\"15,17\",\"executor_login\":\"installation_team\"},{\"stage_id\":\"19\",\"stage_name\":\"Создание академии для птиц, которые умнее своих создателей\",\"start_dt\":\"\",\"duration\":\"40\",\"prevous_stage_id\":\"16,18\",\"executor_login\":\"training_team\"},{\"stage_id\":\"2\",\"stage_name\":\"Выяснение, сколько котиков человечеству не хватает для полного счастья\",\"start_dt\":\"\",\"duration\":\"30\",\"prevous_stage_id\":\"1\",\"executor_login\":\"marketing_team\"},{\"stage_id\":\"20\",\"stage_name\":\"Торжественный выпуск первой партии пернатых философов\",\"start_dt\":\"\",\"duration\":\"30\",\"prevous_stage_id\":\"19\",\"executor_login\":\"operations_team\"},{\"stage_id\":\"21\",\"stage_name\":\"Расселение умных страусов среди обычных людей\",\"start_dt\":\"\",\"duration\":\"45\",\"prevous_stage_id\":\"20\",\"executor_login\":\"distribution_team\"},{\"stage_id\":\"22\",\"stage_name\":\"Миссия `Вкус разочарования`: попкорн, который не оправдает никаких надежд\",\"start_dt\":\"2025-09-16\",\"duration\":\"150\",\"prevous_stage_id\":\"\",\"executor_login\":\"product_owner\"}];","sources":"const { buildSource } = require('libs/dataset/v2');\n\n// Экспортируем настройки для buildSource\nmodule.exports = {\n dataset: buildSource({\n id: Editor.getId(\"dataset\"),\n columns: [\"stage_id\",\"stage_name\",\"start_dt\",\"duration\",\"prevous_stage_id\",\"executor_login\"],\n order_by: [{ 'direction': 'ASC', 'column': 'stage_id' }],\n })\n};\n","controls":"module.exports = {};"},"name":"3 AI Gantt in Table","type":"table_node","annotation":{"description":""}}}},"connection":{"8":{"connection":{"host":"rc1d-qcq36mub1a2sqn69.mdb.yandexcloud.net","name":"CH AI Editor Demo","port":8443,"secure":"on","db_name":null,"db_type":"clickhouse","password":"secure_password","readonly":2,"username":"db2_reader","description":"","workbook_id":"stwdv05018vid","cache_ttl_sec":0,"mdb_folder_id":null,"raw_sql_level":"dashsql","mdb_cluster_id":null,"data_export_forbidden":"off","connection_manager_cloud_id":null,"connection_manager_folder_id":null,"connection_manager_connection_id":null,"connection_manager_delegation_is_set":null}}},"dataset":{"0":{"dataset":{"name":"Gantt Dataset","rls2":{},"sources":[{"id":"e872e041-92f9-11f0-a18b-95ed66e718fa","title":"SQL","valid":true,"virtual":false,"managed_by":"user","parameters":{"subsql":"select * from s3('https://storage.yandexcloud.net/skaradubpics/cocktails/projects.csv')"},"raw_schema":[{"name":"stage_id","title":"stage_id","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":true,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"stage_name","title":"stage_name","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":true,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"start_dt","title":"start_dt","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":true,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"duration","title":"duration","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":true,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"prevous_stage_id","title":"prevous_stage_id","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":true,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"executor_login","title":"executor_login","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":true,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false}],"source_type":"CH_SUBSELECT","connection_id":"8","index_info_set":null,"parameter_hash":"e0ec555b9c7b9264"}],"description":"","revision_id":null,"result_schema":[{"cast":"string","guid":"stage_id_7g83","type":"DIMENSION","title":"stage_id","valid":true,"hidden":false,"source":"stage_id","formula":"","virtual":false,"avatar_id":"e872e040-92f9-11f0-a18b-95ed66e718fa","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"stage_name_4y6k","type":"DIMENSION","title":"stage_name","valid":true,"hidden":false,"source":"stage_name","formula":"","virtual":false,"avatar_id":"e872e040-92f9-11f0-a18b-95ed66e718fa","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"start_dt_9fn0","type":"DIMENSION","title":"start_dt","valid":true,"hidden":false,"source":"start_dt","formula":"","virtual":false,"avatar_id":"e872e040-92f9-11f0-a18b-95ed66e718fa","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"duration_078y","type":"DIMENSION","title":"duration","valid":true,"hidden":false,"source":"duration","formula":"","virtual":false,"avatar_id":"e872e040-92f9-11f0-a18b-95ed66e718fa","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"prevous_stage_id_3oli","type":"DIMENSION","title":"prevous_stage_id","valid":true,"hidden":false,"source":"prevous_stage_id","formula":"","virtual":false,"avatar_id":"e872e040-92f9-11f0-a18b-95ed66e718fa","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"executor_login_odi7","type":"DIMENSION","title":"executor_login","valid":true,"hidden":false,"source":"executor_login","formula":"","virtual":false,"avatar_id":"e872e040-92f9-11f0-a18b-95ed66e718fa","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false}],"source_avatars":[{"id":"e872e040-92f9-11f0-a18b-95ed66e718fa","title":"SQL","valid":true,"is_root":true,"virtual":false,"source_id":"e872e041-92f9-11f0-a18b-95ed66e718fa","managed_by":"user"}],"preview_enabled":true,"avatar_relations":[],"component_errors":{"items":[]},"template_enabled":false,"result_schema_aux":{"inter_dependencies":{"deps":[]}},"obligatory_filters":[],"data_export_forbidden":false,"load_preview_by_default":true}},"4":{"dataset":{"name":"MarketPlace AI Demo","rls2":{},"sources":[{"id":"953b7f51-6ed1-11f0-bc0b-9f4f042ada30","title":"orders_lc","valid":true,"virtual":false,"managed_by":"user","parameters":{"db_name":"db2","db_version":"25.3.6.56","table_name":"orders_lc"},"raw_schema":[{"name":"category_level_1","title":"category_level_1","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"category_level_2","title":"category_level_2","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"category_level_3","title":"category_level_3","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"region_delivery","title":"region_delivery","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"city_delivery","title":"city_delivery","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"delivery_type","title":"delivery_type","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"delivery_service","title":"delivery_service","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"sku_color","title":"sku_color","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"user_gender","title":"user_gender","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"user_platform","title":"user_platform","nullable":true,"user_type":"string","description":"","native_type":{"name":"string","nullable":false,"lowcardinality":true,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"user_id","title":"user_id","nullable":true,"user_type":"integer","description":"","native_type":{"name":"uint64","nullable":false,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"order_id","title":"order_id","nullable":true,"user_type":"integer","description":"","native_type":{"name":"uint64","nullable":false,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"creation_dt","title":"creation_dt","nullable":true,"user_type":"genericdatetime","description":"","native_type":{"name":"datetimewithtz","nullable":false,"timezone_name":"Europe/Moscow","lowcardinality":false,"explicit_timezone":false,"native_type_class_name":"clickhouse_datetimewithtz_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"delivery_dt","title":"delivery_dt","nullable":true,"user_type":"genericdatetime","description":"","native_type":{"name":"datetimewithtz","nullable":false,"timezone_name":"Europe/Moscow","lowcardinality":false,"explicit_timezone":false,"native_type_class_name":"clickhouse_datetimewithtz_native_type"},"lock_aggregation":false,"has_auto_aggregation":false},{"name":"amount","title":"amount","nullable":true,"user_type":"float","description":"","native_type":{"name":"float64","nullable":false,"lowcardinality":false,"native_type_class_name":"clickhouse_native_type"},"lock_aggregation":false,"has_auto_aggregation":false}],"source_type":"CH_TABLE","connection_id":"8","index_info_set":null,"parameter_hash":"a4368992e6943c51"}],"description":"","revision_id":null,"result_schema":[{"cast":"integer","guid":"78cf2b50-8ca9-11f0-a219-ffe370dfee11","type":"MEASURE","title":"Orders","valid":true,"hidden":false,"source":"","formula":"COUNTD_APPROX([order_id])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"integer","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"COUNTD_APPROX([order_id_iejj])","default_value":null,"autoaggregated":true,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"integer","aggregation_locked":true,"has_auto_aggregation":true},{"cast":"float","guid":"374b78a0-8ca9-11f0-a219-ffe370dfee11","type":"MEASURE","title":"AOV","valid":true,"hidden":false,"source":"","formula":"sum([amount])/COUNTD_APPROX([order_id])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"float","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"sum([amount_52rb])/COUNTD_APPROX([order_id_iejj])","default_value":null,"autoaggregated":true,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"float","aggregation_locked":true,"has_auto_aggregation":true},{"cast":"genericdatetime","guid":"a939feb0-8ca8-11f0-a219-ffe370dfee11","type":"DIMENSION","title":"Date scaled","valid":true,"hidden":false,"source":"","formula":"DATETRUNC([delivery_dt],[date_scale])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"genericdatetime","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"DATETRUNC([delivery_dt_y2sz],[date_scale])","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"genericdatetime","aggregation_locked":true,"has_auto_aggregation":false},{"cast":"string","guid":"date_scale","type":"DIMENSION","title":"date_scale","valid":true,"hidden":false,"source":"","formula":"","virtual":false,"avatar_id":null,"calc_mode":"parameter","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":"week","autoaggregated":false,"lock_aggregation":false,"template_enabled":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":true,"has_auto_aggregation":false},{"cast":"float","guid":"de256650-710a-11f0-a040-7f2cfa045483","type":"MEASURE","title":"GMV","valid":true,"hidden":false,"source":"","formula":"sum([amount])","virtual":false,"avatar_id":null,"calc_mode":"formula","data_type":"float","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"sum([amount_52rb])","default_value":null,"autoaggregated":true,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"float","aggregation_locked":true,"has_auto_aggregation":true},{"cast":"string","guid":"category_level_1_n71b","type":"DIMENSION","title":"category_level_1","valid":true,"hidden":false,"source":"category_level_1","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"category_level_2_exd4","type":"DIMENSION","title":"category_level_2","valid":true,"hidden":false,"source":"category_level_2","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"category_level_3_50lm","type":"DIMENSION","title":"category_level_3","valid":true,"hidden":false,"source":"category_level_3","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"region_delivery_efn9","type":"DIMENSION","title":"region_delivery","valid":true,"hidden":false,"source":"region_delivery","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"city_delivery_ho3c","type":"DIMENSION","title":"city_delivery","valid":true,"hidden":false,"source":"city_delivery","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"delivery_type_juix","type":"DIMENSION","title":"delivery_type","valid":true,"hidden":false,"source":"delivery_type","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"delivery_service_blbn","type":"DIMENSION","title":"delivery_service","valid":true,"hidden":false,"source":"delivery_service","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"sku_color_xokm","type":"DIMENSION","title":"sku_color","valid":true,"hidden":false,"source":"sku_color","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"user_gender_fqvv","type":"DIMENSION","title":"user_gender","valid":true,"hidden":false,"source":"user_gender","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"string","guid":"user_platform_rhsy","type":"DIMENSION","title":"user_platform","valid":true,"hidden":false,"source":"user_platform","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"string","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"string","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"integer","guid":"user_id_9k0n","type":"DIMENSION","title":"user_id","valid":true,"hidden":false,"source":"user_id","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"integer","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"integer","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"integer","guid":"order_id_iejj","type":"DIMENSION","title":"order_id","valid":true,"hidden":false,"source":"order_id","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"integer","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"integer","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"genericdatetime","guid":"creation_dt_4enj","type":"DIMENSION","title":"creation_dt","valid":true,"hidden":false,"source":"creation_dt","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"genericdatetime","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"genericdatetime","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"genericdatetime","guid":"delivery_dt_y2sz","type":"DIMENSION","title":"delivery_dt","valid":true,"hidden":false,"source":"delivery_dt","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"genericdatetime","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"genericdatetime","aggregation_locked":false,"has_auto_aggregation":false},{"cast":"float","guid":"amount_52rb","type":"DIMENSION","title":"amount","valid":true,"hidden":false,"source":"amount","formula":"","virtual":false,"avatar_id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","calc_mode":"direct","data_type":"float","managed_by":"user","aggregation":"none","description":"","ui_settings":"","guid_formula":"","default_value":null,"autoaggregated":false,"lock_aggregation":false,"value_constraint":null,"initial_data_type":"float","aggregation_locked":false,"has_auto_aggregation":false}],"source_avatars":[{"id":"953b7f50-6ed1-11f0-bc0b-9f4f042ada30","title":"db2.orders_lc","valid":true,"is_root":true,"virtual":false,"source_id":"953b7f51-6ed1-11f0-bc0b-9f4f042ada30","managed_by":"user"}],"preview_enabled":true,"avatar_relations":[],"component_errors":{"items":[]},"template_enabled":false,"result_schema_aux":{"inter_dependencies":{"deps":[{"dep_field_id":"de256650-710a-11f0-a040-7f2cfa045483","ref_field_ids":["amount_52rb"]},{"dep_field_id":"a939feb0-8ca8-11f0-a219-ffe370dfee11","ref_field_ids":["date_scale","delivery_dt_y2sz"]},{"dep_field_id":"374b78a0-8ca9-11f0-a219-ffe370dfee11","ref_field_ids":["order_id_iejj","amount_52rb"]},{"dep_field_id":"78cf2b50-8ca9-11f0-a219-ffe370dfee11","ref_field_ids":["order_id_iejj"]}]}},"obligatory_filters":[],"data_export_forbidden":false,"load_preview_by_default":true}}},"dash":{"7":{"dash":{"data":{"salt":"0.3480960843773757","tabs":[{"id":"LA","items":[{"id":"yG","data":{"tabs":[{"id":"Ez","hint":"","title":"Dynamic_line","params":{},"chartId":"1","isDefault":true,"autoHeight":false,"background":{"color":"transparent"},"enableHint":false,"description":"","enableDescription":false}],"hideTitle":true},"type":"widget","namespace":"default"},{"id":"jy","data":{"tabs":[{"id":"1J","hint":"","title":"finance_header","params":{"title":["Вайб-чартинг в DataLens Editor"]},"chartId":"2","isDefault":true,"autoHeight":false,"background":{"color":"transparent"},"enableHint":false,"description":"","enableDescription":false}],"hideTitle":true},"type":"widget","namespace":"default"},{"id":"xm","data":{"tabs":[{"id":"Gz","hint":"","title":"Indicator","params":{},"chartId":"3","isDefault":true,"autoHeight":false,"background":{"color":"transparent"},"enableHint":false,"description":"","enableDescription":false}],"hideTitle":true},"type":"widget","namespace":"default"},{"id":"0A","data":{"tabs":[{"id":"r6","hint":"","title":"AI Chart 1","params":{},"chartId":"6","isDefault":true,"autoHeight":false,"background":{"color":"transparent"},"enableHint":false,"description":"","enableDescription":false}],"hideTitle":false},"type":"widget","namespace":"default"},{"id":"98","data":{"group":[{"id":"ae","title":"Период","width":"","source":{"isRange":true,"required":false,"showHint":false,"fieldName":"date_interval","showTitle":true,"accentType":null,"elementType":"date","defaultValue":"__interval_2024-08-05T00:00:00.000Z_2024-09-09T00:00:00.000Z","titlePlacement":"left"},"defaults":{"date_interval":"__interval_2024-08-05T00:00:00.000Z_2024-09-09T00:00:00.000Z"},"namespace":"default","sourceType":"manual","placementMode":"auto"}],"autoHeight":false,"buttonApply":false,"buttonReset":false,"showGroupName":false,"updateControlsOnChange":false},"type":"group_control","namespace":"default"},{"id":"6j","data":{"text":"","autoHeight":false,"background":{"color":"","enabled":true}},"type":"text","namespace":"default"},{"id":"N9","data":{"group":[{"id":"OK","title":"Масштаб","width":"","source":{"required":false,"showHint":false,"fieldName":"date_scale","showTitle":true,"accentType":null,"elementType":"select","defaultValue":["week"],"titlePlacement":"left","acceptableValues":[{"title":"month","value":"month"},{"title":"day","value":"day"},{"title":"week","value":"week"}]},"defaults":{"date_scale":["week"]},"namespace":"default","sourceType":"manual","placementMode":"auto"}],"autoHeight":false,"buttonApply":false,"buttonReset":false,"showGroupName":false,"updateControlsOnChange":false},"type":"group_control","namespace":"default"}],"title":"Main","layout":[{"h":8,"i":"yG","w":11,"x":0,"y":9},{"h":3,"i":"jy","w":36,"x":0,"y":0},{"h":4,"i":"xm","w":11,"x":0,"y":5},{"h":12,"i":"0A","w":12,"x":11,"y":5},{"h":2,"i":"98","w":11,"x":0,"y":3},{"h":2,"i":"6j","w":17,"x":19,"y":3},{"h":2,"i":"N9","w":8,"x":11,"y":3}],"aliases":{"default":[["creation_dt_4enj","date_interval"]]},"connections":[{"to":"Ez","from":"ae","kind":"ignore"}]},{"id":"We","items":[{"id":"gM","data":{"text":"## AI Chart 2\n\n```\n# Задача\nу тебя в getCurrentCodePrompt описаны 4 массива с метриками их описанием и значениями тотал и по дням, придумай сам и напиши код, который будет показывать каждую из этих метрик в виде большого числа и детальные данные внутри красивой и понятной плитики (плитка вниз или вправо заложено в коде) числа должна быть отформатированы до 1 знака и размерности указаны 1 буквой, форматирование всех чисел сделай до передачи в render\n\nна детальных графиках должен быть тултип на точках\n\n\n# ОГРАНИЧЕНИЯ РАБОТЫ!!\n- никакие атрибуты для передачи информации кроме data-id не разрешены.\n- с датами работай как со строками, не используй библиотеки по работе с данными, просто обрезай 10 символов.\n- не забывай, клики и тултипы можно только через renderer делать\n- в значении data-id используй _ для разделителя\n- чтобы линии встраивались в график используй preserveAspectRatio=\"none\"\n```","autoHeight":false,"background":{"color":"like-chart-bg","enabled":true}},"type":"text","namespace":"default"},{"id":"o8","data":{"text":"## Что любит моделька в промпте?\n\n- Маркдаун (как средство деления задачи на блоки)\n\n- Если нужно что-то усилить - используйте bold (\\*\\*text\\*\\*)\n\n- Примеры и контр-примеры кода\n\n- Цифры, которые помогут модели лучше понять логику\n\n- Раздел с ограничениями по коду\n\n## Что делать, если не все сразу получилось?\n\n- уточнять конкретные моменты в диалоге, чтобы программа исправилась\n\n- Лучше найти все недочеты и спрашивать один раз\n\n- Много исправлений делать не надо - сохраните чарт и начните новый диалог","autoHeight":false,"background":{"color":"like-chart-bg","enabled":true}},"type":"text","namespace":"default"},{"id":"mO","data":{"text":"## AI Chart 1\n\n```\nCделай перевод заголовков метрик следующим образом:\nесли параметр params.lang[0] равен en, то в заголовок метрики брать alias_en, иначе просто alias\n\nВозврати только ту измененную функцию, которая требуется\n```","autoHeight":false,"background":{"color":"like-chart-bg","enabled":true}},"type":"text","namespace":"default"}],"title":"Prompts","layout":[{"h":16,"i":"gM","w":17,"x":0,"y":16},{"h":16,"i":"o8","w":19,"x":17,"y":0},{"h":16,"i":"mO","w":17,"x":0,"y":0}],"aliases":{},"connections":[]}],"counter":18,"settings":{"hideTabs":false,"expandTOC":false,"globalParams":{},"loadPriority":"charts","hideDashTitle":true,"silentLoading":false,"autoupdateInterval":null,"dependentSelectors":true,"loadOnlyVisibleCharts":true,"maxConcurrentRequests":null},"schemeVersion":8,"accessDescription":"","supportDescription":""},"name":"Editor AI Workshop","annotation":{"description":""}}}}}},"hash":"2bbdab9a2950be3aaaa2cc8083801d2404b705486a3fef026baf90c5a5cf600d"}