Creating a table based on a dataset

Follow this guide to build a table in Editor based on a dataset. For convenience, we will use a connection and dataset from a deployed demo workbook as the data source.

Getting started

To get started with DataLens, follow this deployment guide.

Deploy a demo workbook

  1. Save the dashboard titled DataLens Demo Dashboard from the Gallery:

    1. In Gallery, open the relevant creation card.
    2. Click Use → Download. The workbook will be downloaded as a JSON file.
    3. On the collections and workbooks page, click Create → Workbook.
    4. In the window that opens, click Select file and upload the JSON file with the demo workbook configuration. Optionally, edit the title and description and click Save.

  2. Navigate to the new workbook and, on the Datasets tab, find a dataset named 00: Sales.

  3. Copy the dataset ID by clicking → Copy ID next to it. The ID will be copied to the clipboard.

Create a chart in Editor

  1. In the workbook, click Create → Chart in Editor in the top-right corner. On the page that opens, select the Table visualization type.

  2. Link the chart with the dataset by navigating to the Meta tab and adding the connection ID to links:

    {
    "links": {
        "salesDataset": "r7h********"
	   }
}

    Where:

    • r7h********: Dataset ID you copied in the previous step.
    • salesDataset: Any alias name you assign to the dataset and use to request chart data from the source.

    Note

    You need the Meta tab to describe service information about the list of related entities. This information is used to figure out what connections and datasets the chart is related to, as well as for the related objects dialog, when copying a workbook and when publishing to Public.

  3. Get data from the data source by opening the Source tab and specifying the following:

    const {buildSource} = require('libs/dataset/v2');
module.exports = {
    'salesSourceData': buildSource({
        datasetId: Editor.getId('salesDataset'),
        columns: ['Payment type', 'Request year', 'Request month', 'Sale, ₽'],
    }),
};

    salesSourceData: Any alias name you assign to the object with requested chart data and use for access on the Prepare tab.

    The columns field value lists the fields from the dataset.

    Note

    In this example, the const {buildSource} = require('libs/dataset/v2'); service module is used for more convenient operations with datasets.

  4. Clear the contents of the Params and Config tabs: they contain a template that is not relevant to our example.

  5. On the Prepare tab, create a table:

    Note

    In this example, the const Dataset = require('libs/dataset/v2') service module is used for more convenient operations with datasets. The Dataset.getDatasetRows() method extracts data from the source specified in the datasetName parameter and provides the data in a convenient compact form.

    If you need to, you can use the Editor.getLoadedData() method to get the full data.

    const Dataset = require('libs/dataset/v2');

// Getting data from the dataset in a convenient format using the service module
// datasetName: Dataset name on the Sources tab
const data = Dataset.getDatasetRows({datasetName: 'salesSourceData'});

// Helper function to group data by a specified dataset field name 
function groupBy(arr, field) {
    return arr.reduce((acc, item) => {
        const key = item[field];
        if (!acc[key]) {
            acc[key] = [];
        }
        acc[key].push(item);
        
        return acc;
    }, {});
}

// Array containing unique values of the "Order year" field, sorted in ascending numerical order
const years = Array.from(new Set(data.map(d => String(d['Order year'])))).sort();

// Common styles for table header cells
const headStyles = {background: 'var(--g-color-base-misc-light)', verticalAlign: 'middle'};

// Table header cell configuration
const head = [
    {
        name: 'Payment type',
        formattedName: Editor.generateHtml({
            tag: 'span',
            content: [
                {tag: 'span', content: 'Payment type'},
				// tooltip for a cell header
                {
                    tag: 'dl-tooltip',
                    content: ' ℹ',
                    style: {
                        display: 'inline-block',
                        margin: '0px 0px 0px 4px',
                        'line-height': '12px',
                        'text-align': 'center',
                        width: '16px',
                        height: '16px',
                        border: '1px solid #ccc',
                        'border-radius': '50%',
                    },
                    attributes : {
                        'data-tooltip-content': {
                            tag: 'i',
                            content: 'Tooltip content',
                        },
                    },
                }
            ],
        }),
        css: headStyles,
        pinned: true,
    },
    // Creating columns based on the array of values from the "Order year" field obtained earlier
    ...years.map(year => ({
        name: year,
        css: headStyles,
    })),
    {
        name: 'Sales, all years',
        css: headStyles,
    },
];

// Helper function to render a chart line
function createChart(chartData) {
    const chartWidth = 80;
    const chartHeight = 40;

    // Calculating the minimum and maximum coordinate values
    const minX = Math.min(...chartData.map(d => d.x));
    const maxX = Math.max(...chartData.map(d => d.x));
    const minY = Math.min(...chartData.map(d => d.y));
    const maxY = Math.max(...chartData.map(d => d.y));

    // Calculating coordinates based on the chart container dimensions (chartWidth, chartHeight)
    const coords = chartData.sort((d1, d2) => d1.x - d2.x).map(d => ([
        (d.x - minX) / (maxX - minX) * chartWidth, 
        (d.y - minY) / (maxY - minY) * chartHeight,
    ]));
    // Creating a path for the SVG line using the coordinates generated above
    let d = "";
    coords.forEach((_, x) => {
        d += d === "" ? "M" : " L";
        d += `${coords[x][0]} ${coords[x][1]}`;
    });
    // Creating an SVG with var(--g-color-base-brand) for line color and thickness of 2px
    return `
        <svg width="${chartWidth}" height="${chartHeight}">
            <path 
                d="${d}" 
                style="fill: none; stroke: var(--g-color-base-brand); stroke-width: 2;"
            />
        </svg>`;
}

const rows = [];

// Helper function for number formatting
const formatSalesValue = new Intl.NumberFormat('ru-RU').format;
const postfix = ', ₽';

// Rows grouped by the "Payment type" field
const groupedData = groupBy(data, 'Payment type');
// Generating and populating table rows for each grouped payment type
Object.entries(groupedData).forEach(([key, items]) => {
    // Rows grouped by the "Order year" field
    const salesByYears = groupBy(items, 'Order year');
    // Calculating the sum for the "Sale, ₽" field across all years 
    const totalSales = items.reduce((sum, d) => sum + d['Sale, ₽'], 0);
    rows.push({
        cells: [
            {
                value: key,
            },
            // Creating columns based on previously prepared "Order year" values
            ...years.map(year => {
                const salesByYear = salesByYears[year] ?? [];
                const yearSales = salesByYear.map(d => ({
                    x: new Date(d['Order month']).getTime(), 
                    y: d['Sale, ₽'],
                }));
                const maxSales = Math.max(...salesByYear.map(d => d['Sale, ₽']));
                const minSales = Math.min(...salesByYear.map(d => d['Sale, ₽']));

                return {
                    value: maxSales, 
                    formattedValue: Editor.generateHtml(`
                        <div>
                            ${createChart(yearSales)}
                            <div style="margin-top: 8px;">Min: <b>${formatSalesValue(minSales)}${postfix}<b></div>
                            <div>Max: <b>${formatSalesValue(maxSales)}${postfix}</b></div>
                        </div>
                    `),   
                };
            }),
            {
                value: totalSales,
                formattedValue: formatSalesValue(totalSales) + postfix,
                css: {
                    verticalAlign: 'middle',
                    textAlign: 'center',
                    fontSize: '16px',
                },
            },
        ],
    });
});

module.exports = {head, rows};

  6. At the top of the chart, click Execute. The preview will show the dataset as a table with rows grouped by the Payment type field and columns grouped by the Order year field, along with a monthly sales chart:

    image.png

  7. To save the chart, click Save in the top-right corner and enter a name for the chart.

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