js实现table中前端搜索(模糊查询)

时间:2023-12-28 17:32:02

项目中用到js前端搜索功能,根据 姓名或姓名 进行 搜索,实现方法如下,遍历table所有行中的某列,符合条件则置tr为display:'',不满足条件置tr为display:none。

代码如下:

    <html>
<head>
<title>s表格前端搜索</title>
<meta http-equiv="Content-Type" content="text/html;charset=GBK"/>
</head>
<body>
<h1>js表格前端搜索</h1> <label> <input type="radio" name="sex" value="男" onclick="onSearch(this.value,2)"/>男 </label>
<label><input type="radio" name="sex" value="女" onclick="onSearch(this.value,2)"/>女 </label> <table id="table1" border="1">
<thead >
<tr style="cursor: pointer;">
<td class="listHeadCell">编号</td>
<td class="listHeadCell">姓名</td>
<td class="listHeadCell">性别</td>
</tr>
</thead>
<tbody id="gridtbody">
<tr>
<td name="biaozhi">1</td>
<td>名称1</td>
<td>男</td>
</tr>
<tr>
<td name="biaozhi">2</td>
<td>名称2</td>
<td>男</td>
</tr>
<tr>
<td name="biaozhi">3</td>
<td>名称3</td>
<td>女</td>
</tr>
<tr>
<td name="biaozhi">4</td>
<td>名称4</td>
<td>男</td>
</tr>
</tbody>
</table>
<br/> <script type="text/javascript">
/**
* js 前台搜索
* @param searchContent 搜索的内容
* @col 要搜索的哪一列,这里是第一列,从0开始数起
*/
function onSearch(searchContent,col){
setTimeout(function(){//因为是即时查询,需要用setTimeout进行延迟,让值写入到input内,再读取
var storeId = document.getElementById('table1');//获取table的id标识
var rowsLength = storeId.rows.length;//表格总共有多少行 var searchCol = col;//要搜索的哪一列,这里是第一列,从0开始数起 for(var i=1;i<rowsLength;i++){//按表的行数进行循环,本例第一行是标题,所以i=1,从第二行开始筛选(从0数起) var searchText = storeId.rows[i].cells[searchCol].innerHTML;//取得table行,列的值
//alert(searchText);
if(searchText.match(searchContent) || searchText.toUpperCase().match(searchContent.toUpperCase())){//用match函数进行筛选,如果input的值,即变量 key的值为空,返回的是ture,
storeId.rows[i].style.display='';//显示行操作,
}else{
storeId.rows[i].style.display='none';//隐藏行操作
}
}
},20);//20为延时时间
}
</script>
</body>
</html>

效果图:

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" 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" 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" 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js实现table中前端搜索(模糊查询)