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.

      Other examples