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  1. API reference
  2. Welcome
    1. Getting started
    2. Get Flexmonster
    3. Quick start
    4. System requirements
    5. Troubleshooting
    6. Managing license keys
    7. Migrating from WebDataRocks to Flexmonster
  3. Integration with frameworks
    1. Available tutorials
    2. Integration with Angular
    3. Integration with React
    4. Integration with Vue
    5. Other integrations
      1. Integration with Python
        1. Integration with Django
        2. Integration with Jupyter Notebook
      2. Integration with React Native
      3. Integration with Blazor
      4. Integration with AngularJS (v1.x)
      5. Integration with TypeScript
      6. Integration with R Shiny
      7. Integration with jQuery
      8. Integration with Ionic
      9. Integration with Electron.js
      10. Integration with Webpack
      11. Integration with RequireJS
  4. Connecting to Data Source
    1. Supported data sources
    2. JSON
      1. Connecting to JSON
      2. Connecting to JSON using Flexmonster Data Server
      3. Data types in JSON
    3. CSV
      1. Connecting to CSV
      2. Connecting to CSV using Flexmonster Data Server
      3. Data types in CSV
    4. Database
      1. Connecting to SQL databases
      2. Connecting to a MySQL database
      3. Connecting to a Microsoft SQL Server database
      4. Connecting to a PostgreSQL database
      5. Connecting to an Oracle database
    5. Flexmonster Data Server
      1. Introduction to Flexmonster Data Server
      2. Getting started with Flexmonster Data Server
      3. Flexmonster Admin Panel Guide
      4. Data sources guide
      5. Security and authorization guide
      6. The Data Server as a DLL
        1. Getting started with the Data Server as a DLL
        2. Referencing the Data Server as a DLL
        3. Implementing the API controller
        4. Implementing the server filter
        5. Implementing the custom parser
        6. DLL configurations reference
        7. The controller's methods for request handling
      7. The Data Server as a console application
        1. Installing the Data Server as a console application
        2. Configurations reference
        3. Data sources guide
        4. Security and authorization guide
      8. Troubleshooting the Data Server
    6. MongoDB
      1. Introduction to Flexmonster MongoDB Connector
      2. Getting started with the MongoDB Connector
      3. Embedding the MongoDB Connector into the server
      4. Configuring the MongoDB Connector
    7. Microsoft Analysis Services
      1. Connecting to Microsoft Analysis Services
      2. Getting started with Flexmonster Accelerator
      3. Referencing the Accelerator as a DLL
      4. Configuring the authentication process
      5. Configuring a secure HTTPS connection
      6. Troubleshooting
    8. Custom data source API
      1. Introduction to the custom data source API
      2. A quick overview of a sample Node.js server
      3. A quick overview of a sample .NET Core server
      4. Implement your own server
        1. Implementing the custom data source API server
        2. Implementing filters
        3. Supporting more aggregation functions
        4. Supporting multilevel hierarchies
        5. Returning data for the drill-through view
        6. Testing your custom data source API server
    9. Elasticsearch
      1. Connecting to Elasticsearch
      2. Configuring the mapping
    10. Pentaho Mondrian
      1. Connecting to Pentaho Mondrian
      2. Getting started with the Accelerator
      3. Configuring Mondrian roles
      4. Configuring username/password protection
      5. Configuring a secure HTTPS connection
      6. Troubleshooting
    11. Connecting to other data sources
  5. Accessibility
    1. Accessibility overview
    2. Keyboard navigation
  6. Configuring the component
    1. Available tutorials
    2. Getting started with the report
    3. Configure the data source
      1. Data source
      2. Mapping
    4. Define which data to show
      1. Slice
      2. Custom sorting
      3. Calculated values
    5. Manage Flexmonster’s functionality
      1. Options
      2. Configuring global options
    6. Format fields
      1. Number formatting
      2. Date and time formatting
      3. Conditional formatting
    7. Save component configs
      1. Get the report from the component
      2. Set the report for the component
      3. Share the report
      4. Export and print
  7. Charts
    1. Available tutorials
    2. Flexmonster Pivot Charts
    3. Integration with Highcharts
    4. Integration with amCharts
    5. Integration with Google Charts
    6. Integration with FusionCharts
    7. Integration with any charting library
  8. Customizing
    1. Available tutorials
    2. Customizing the Toolbar
    3. Customizing appearance
    4. Customizing the context menu
    5. Customizing the grid
    6. Customizing the pivot charts
    7. Localizing the component
  9. Security
    1. Security in Flexmonster
    2. Security aspects of connecting to an OLAP cube
      1. Ways of connecting to an OLAP cube
      2. The data transfer process
      3. Data security
      4. Data access management
  10. Updating to the latest version
    1. Updating to the latest version
    2. Release notes
    3. Migration guide from 2.8 to 2.9
    4. Migration guide from 2.7 to 2.8
    5. Migration guide from 2.6 to 2.7
    6. Migration guide from 2.5 to 2.6
    7. Migration guide from 2.4 to 2.5
    8. Migration guide from 2.3 to 2.4
    9. Migration guide from 2.2 to 2.3
  11. Flexmonster CLI Reference
    1. Overview
    2. Troubleshooting the CLI
    3. flexmonster create
    4. flexmonster add
    5. flexmonster update
    6. flexmonster version
    7. flexmonster help
  12. Documentation for older versions
Table of contents

Integration with any charting library

This tutorial will help you connect a 3rd party visualization tool to Flexmonster Pivot Table and Charts. This simple example is based on d3.js and aims to illustrate the interaction between data from Flexmonster and external visualization. Integration with any other library will have similar basic steps.

The integration is based on the getData() API call. Read about it to understand the format that the data is returned in from the component. In this article we will connect the pivot table data with the d3.js chart step by step:

Adding the basis for a new chart

  1. Add the component using data from a CSV file to your HTML page. Replace XXXX-XXXX-XXXX-XXXX-XXXX with your license key. If you don’t have a license key, contact our team and request a special trial key.
    <div id="pivotContainer">The component will appear here</div>
    <script src="https://cdn.flexmonster.com/flexmonster.js"></script>

    <script>
    var pivot = new Flexmonster({
    container: "pivotContainer",
    componentFolder: "https://cdn.flexmonster.com/",
    toolbar: true,
    report: {
    dataSource: {
    filename: "data.csv"
    },
    slice: {
    rows: [
    { uniqueName: "Country" }
    ],
    columns: [
    { uniqueName: "Business Type" },
    { uniqueName: "[Measures]" }
    ],
    measures: [
    { uniqueName: "Price" }
    ]
    }
    },
    licenseKey: "XXXX-XXXX-XXXX-XXXX-XXXX"
    });
    </script>
  2. Add a container for the chart:
    <svg id="d3Chart" width="650" height="230"></svg> 
  3. Add a reportCompleteevent handler to know when the pivot table is ready to be a data provider:
    reportcomplete: function() {
    pivot.off("reportcomplete");
    createChart();
    }
  4. Add a function to create the chart. This function uses getData(options, callbackHandler, updateHandler).
    function createChart() {
    pivot.getData(
    {
    // define your slice
    },
    drawChart,
    updateChart
    );
    }

Try it on JSFiddle.

Preparing the data and drawing the chart

The most important part of drawing a chart is preparing the data by transforming it from the format returned by the getData() API call to the format that suits the 3rd party visualization tool:

var data = prepareDataFunction(rawData);

This example shows how to define and use a function (in our example it is prepareDataFunction) to process the data. This function should prepare data appropriately for the charting library format. In this example prepareDataFunction iterates through the data array from rawData and discards a record containing the grand total because it is unnecessary for the bar chart. The function also renames rows from r0 to member and values from v0 to value. This is not required, but it makes the code more readable when referring to the data later. We have the following pivot table:

Country Total Sum of Price
Australia 1 372 281
France 1 117 794
Germany 1 070 453
Canada 1 034 112
United States 847 331
United Kingdom 779 899
Grand Total 6 221 870

The data array from rawData looks like this:

	data:[
		{
			v0:6221870
		},
		{
			r0:"Australia",
			v0:1372281
		},
		{
			r0:"France",
			v0:1117794
		},
		{
			r0:"Germany",
			v0:1070453
		},
		{
			r0:"Canada",
			v0:1034112
		},
		{
			r0:"United States",
			v0:847331
		},
		{
			r0:"United Kingdom",
			v0:779899
		}
	]

After prepareDataFunction the data will look like this:

        {
            member:"Australia",
            value:1372281
        },
        {
            member:"France",
            value:1117794
        },
        {
            member:"Germany",
            value:1070453
        },
        {
            member:"Canada",
            value:1034112
        },
        {
            member:"United States",
            value:847331
        },
        {
            member:"United Kingdom",
            value:779899
        }

The drawChart function draws a chart using the processed data. In our JSFiddle example, the logic of drawing is the same as in the d3.js example. The updateChart function works similarly but clears the SVG first.