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  1. API reference
  2. Welcome
    1. Component overview
    2. Quick start
    3. System requirements
    4. Troubleshooting
    5. Managing license keys
    6. Migrating from WebDataRocks to Flexmonster
  3. Connecting to Data Source
    1. JSON
      1. Connecting to JSON
      2. Connecting to JSON using the Data Compressor
      3. Data types in JSON
    2. CSV
      1. Connecting to CSV
      2. Connecting to CSV using the Data Compressor
      3. Data types in CSV
    3. Database
      1. Connecting to SQL databases
      2. Connecting to other databases
      3. Connecting to a database with Node.js
      4. Connecting to a database with .NET
      5. Connecting to a database with .NET Core
      6. Connecting to a database with Java
      7. Connecting to a database with PHP
    4. Microsoft Analysis Services
      1. Connecting to Microsoft Analysis Services
      2. Getting started with the Accelerator
      3. Installing the Accelerator as a Windows service
      4. Referring the Accelerator as a DLL
      5. Configuring the authentication process
      6. Configuring a secure HTTPS connection
      7. Troubleshooting
    5. 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
    6. Elasticsearch
      1. Connecting to Elasticsearch
      2. Configuring the mapping
  4. Security
    1. Security in Flexmonster
    2. Security aspects when connecting to an OLAP cube
      1. The data transfer process
      2. Data security
      3. Data access management
    3. Security aspects when connecting to a database
      1. The data transfer process
      2. Data access management
  5. Configuring report
    1. What is a report
    2. Data source
    3. Slice
    4. Options
    5. Number formatting
    6. Conditional formatting
    7. Set the report for the component
    8. Get the report from the component
    9. Date and time formatting
    10. Configuring global options
    11. Export and print
    12. Calculated values
    13. Custom sorting
  6. Integration with frameworks
    1. Available tutorials
    2. Integration with AngularJS (v1.x)
    3. Integration with Angular
    4. Integration with React
    5. Integration with Webpack
    6. Integration with ASP.NET
    7. Integration with jQuery
    8. Integration with JSP
    9. Integration with TypeScript
    10. Integration with RequireJS
    11. Integration with PhoneGap
  7. Integration with charts
    1. Integration with Highcharts
    2. Integration with Google Charts
    3. Integration with FusionCharts
    4. Integration with any charting library
  8. Customizing
    1. Customizing toolbar
    2. Customizing appearance
    3. Customizing context menu
    4. Localizing component
  9. Updating to the latest version
    1. Updating to the latest version
    2. Release notes
    3. Migration guide from 2.6 to 2.7
    4. Migration guide from 2.5 to 2.6
    5. Migration guide from 2.4 to 2.5
    6. Migration guide from 2.3 to 2.4
    7. Migration guide from 2.2 to 2.3
    8. 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 following pivot table using data from a CSV file to your HTML page.
    <div id="pivotContainer">The component will appear here</div>
    <script src="flexmonster/flexmonster.js"></script>
    
    <script>
    	var pivot = new Flexmonster({
    		container: "pivotСontainer",
    		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 reportComplete event 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). Try it in JSFiddle.
    function createChart() {
    	pivot.getData(
    		{
    			// define your slice
    		}, 
    		drawChart, 
    		updateChart 
    	);
    }
    

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.