Custom Filtering Options

This example shows how to set up a custom comparison function in SearchPanes.

Name	Position	Office	Age	Salary
Tiger Nixon	System Architect	Edinburgh	61	$320,800
Garrett Winters	Accountant	Tokyo	63	$170,750
Ashton Cox	Junior Technical Author	San Francisco	66	$86,000
Cedric Kelly	Senior Javascript Developer	Edinburgh	22	$433,060
Airi Satou	Accountant	Tokyo	33	$162,700
Brielle Williamson	Integration Specialist	New York	61	$372,000
Herrod Chandler	Sales Assistant	San Francisco	59	$137,500
Rhona Davidson	Integration Specialist	Tokyo	55	$327,900
Colleen Hurst	Javascript Developer	San Francisco	39	$205,500
Sonya Frost	Software Engineer	Edinburgh	23	$103,600
Jena Gaines	Office Manager	London	30	$90,560
Quinn Flynn	Support Lead	Edinburgh	22	$342,000
Charde Marshall	Regional Director	San Francisco	36	$470,600
Haley Kennedy	Senior Marketing Designer	London	43	$313,500
Tatyana Fitzpatrick	Regional Director	London	19	$385,750
Michael Silva	Marketing Designer	London	66	$198,500
Paul Byrd	Chief Financial Officer (CFO)	New York	64	$725,000
Gloria Little	Systems Administrator	New York	59	$237,500
Bradley Greer	Software Engineer	London	41	$132,000
Dai Rios	Personnel Lead	Edinburgh	35	$217,500
Jenette Caldwell	Development Lead	New York	30	$345,000
Yuri Berry	Chief Marketing Officer (CMO)	New York	40	$675,000
Caesar Vance	Pre-Sales Support	New York	21	$106,450
Doris Wilder	Sales Assistant	Sydney	23	$85,600
Angelica Ramos	Chief Executive Officer (CEO)	London	47	$1,200,000
Gavin Joyce	Developer	Edinburgh	42	$92,575
Jennifer Chang	Regional Director	Singapore	28	$357,650
Brenden Wagner	Software Engineer	San Francisco	28	$206,850
Fiona Green	Chief Operating Officer (COO)	San Francisco	48	$850,000
Shou Itou	Regional Marketing	Tokyo	20	$163,000
Michelle House	Integration Specialist	Sydney	37	$95,400
Suki Burks	Developer	London	53	$114,500
Prescott Bartlett	Technical Author	London	27	$145,000
Gavin Cortez	Team Leader	San Francisco	22	$235,500
Martena Mccray	Post-Sales support	Edinburgh	46	$324,050
Unity Butler	Marketing Designer	San Francisco	47	$85,675
Howard Hatfield	Office Manager	San Francisco	51	$164,500
Hope Fuentes	Secretary	San Francisco	41	$109,850
Vivian Harrell	Financial Controller	San Francisco	62	$452,500
Timothy Mooney	Office Manager	London	37	$136,200
Jackson Bradshaw	Director	New York	65	$645,750
Olivia Liang	Support Engineer	Singapore	64	$234,500
Bruno Nash	Software Engineer	London	38	$163,500
Sakura Yamamoto	Support Engineer	Tokyo	37	$139,575
Thor Walton	Developer	New York	61	$98,540
Finn Camacho	Support Engineer	San Francisco	47	$87,500
Serge Baldwin	Data Coordinator	Singapore	64	$138,575
Zenaida Frank	Software Engineer	New York	63	$125,250
Zorita Serrano	Software Engineer	San Francisco	56	$115,000
Jennifer Acosta	Junior Javascript Developer	Edinburgh	43	$75,650
Cara Stevens	Sales Assistant	New York	46	$145,600
Hermione Butler	Regional Director	London	47	$356,250
Lael Greer	Systems Administrator	London	21	$103,500
Jonas Alexander	Developer	San Francisco	30	$86,500
Shad Decker	Regional Director	Edinburgh	51	$183,000
Michael Bruce	Javascript Developer	Singapore	29	$183,000
Donna Snider	Customer Support	New York	27	$112,000
Name	Position	Office	Age	Salary

Javascript
HTML
CSS
Ajax
Server-side script
Comments

The Javascript shown below is used to initialise the table shown in this example:

var dt = $('#example').DataTable({
	columnDefs: [
		{
			orderable: false,
			render: DataTable.render.select(),
			searchPanes: {
				show: true,
				options: [
					{
						label: 'Checked',
						value: function (rowData, rowIdx) {
							return this.row(rowIdx, { selected: true }).any();
						}
					},
					{
						label: 'Un-Checked',
						value: function (rowData, rowIdx) {
							return this.row(rowIdx, { selected: true }).any() === false;
						}
					}
				]
			},
			targets: [0]
		},
		{
			searchPanes: {
				options: [
					{
						label: 'Under 20',
						value: function (rowData, rowIdx) {
							return rowData[4] < 20;
						}
					},
					{
						label: '20 to 30',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 30 && rowData[4] >= 20;
						}
					},
					{
						label: '30 to 40',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 40 && rowData[4] >= 30;
						}
					},
					{
						label: '40 to 50',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 50 && rowData[4] >= 40;
						}
					},
					{
						label: '50 to 60',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 60 && rowData[4] >= 50;
						}
					},
					{
						label: 'Over 60',
						value: function (rowData, rowIdx) {
							return rowData[4] > 60;
						}
					}
				]
			},
			targets: [4]
		},
		{
			searchPanes: {
				options: [
					{
						label: 'Not Edinburgh',
						value: function (rowData, rowIdx) {
							return rowData[3] !== 'Edinburgh';
						}
					},
					{
						label: 'Not London',
						value: function (rowData, rowIdx) {
							return rowData[3] !== 'London';
						}
					}
				],
				combiner: 'and'
			},
			targets: [3]
		}
	],
	layout: {
		top1: {
			searchPanes: {
				viewTotal: true,
				columns: [0, 3, 4]
			}
		}
	},
	select: {
		style: 'os',
		selector: 'td:first-child'
	},
	order: [[1, 'asc']]
});

dt.on('select.dt', () => {
	dt.searchPanes.rebuildPane(0, true);
});

dt.on('deselect.dt', () => {
	dt.searchPanes.rebuildPane(0, true);
});

var dt = new DataTable('#example', {
	columnDefs: [
		{
			orderable: false,
			render: DataTable.render.select(),
			searchPanes: {
				show: true,
				options: [
					{
						label: 'Checked',
						value: function (rowData, rowIdx) {
							return this.row(rowIdx, { selected: true }).any();
						}
					},
					{
						label: 'Un-Checked',
						value: function (rowData, rowIdx) {
							return this.row(rowIdx, { selected: true }).any() === false;
						}
					}
				]
			},
			targets: [0]
		},
		{
			searchPanes: {
				options: [
					{
						label: 'Under 20',
						value: function (rowData, rowIdx) {
							return rowData[4] < 20;
						}
					},
					{
						label: '20 to 30',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 30 && rowData[4] >= 20;
						}
					},
					{
						label: '30 to 40',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 40 && rowData[4] >= 30;
						}
					},
					{
						label: '40 to 50',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 50 && rowData[4] >= 40;
						}
					},
					{
						label: '50 to 60',
						value: function (rowData, rowIdx) {
							return rowData[4] <= 60 && rowData[4] >= 50;
						}
					},
					{
						label: 'Over 60',
						value: function (rowData, rowIdx) {
							return rowData[4] > 60;
						}
					}
				]
			},
			targets: [4]
		},
		{
			searchPanes: {
				options: [
					{
						label: 'Not Edinburgh',
						value: function (rowData, rowIdx) {
							return rowData[3] !== 'Edinburgh';
						}
					},
					{
						label: 'Not London',
						value: function (rowData, rowIdx) {
							return rowData[3] !== 'London';
						}
					}
				],
				combiner: 'and'
			},
			targets: [3]
		}
	],
	layout: {
		top1: {
			searchPanes: {
				viewTotal: true,
				columns: [0, 3, 4]
			}
		}
	},
	select: {
		style: 'os',
		selector: 'td:first-child'
	},
	order: [[1, 'asc']]
});

dt.on('select.dt', () => {
	dt.searchPanes.rebuildPane(0, true);
});

dt.on('deselect.dt', () => {
	dt.searchPanes.rebuildPane(0, true);
});

In addition to the above code, the following Javascript library files are loaded for use in this example:

The HTML shown below is the raw HTML table element, before it has been enhanced by DataTables:

This example uses a little bit of additional CSS beyond what is loaded from the library files (below), in order to correctly display the table. The additional CSS used is shown below:

The following CSS library files are loaded for use in this example to provide the styling of the table:

This table loads data by Ajax. The latest data that has been loaded is shown below. This data will update automatically as any additional data is loaded.

The script used to perform the server-side processing for this table is shown below. Please note that this is just an example script using PHP. Server-side processing scripts can be written in any language, using the protocol described in the DataTables documentation.

Custom Filtering Options

Other examples

Initialisation and options

Advanced initialisation

Customisation

Integration with other DataTables extensions

Creation of custom panes

Styling

Performance

DataTables