<!DOCTYPE html>
<html>
<head>
<style>
* {
box-sizing: border-box;
}
#myInput {
background-image: url('/css/searchicon.png');
background-position: 10px 10px;
background-repeat: no-repeat;
width: 100%;
font-size: 16px;
padding: 12px 20px 12px 40px;
border: 1px solid #ddd;
margin-bottom: 12px;
}
#myTable {
border-collapse: collapse;
width: 100%;
border: 1px solid #ddd;
font-size: 18px;
}
#myTable th, #myTable td {
text-align: left;
padding: 12px;
}
#myTable tr {
border-bottom: 1px solid #ddd;
}
#myTable tr.header, #myTable tr:hover {
background-color: #f1f1f1;
}
</style>
</head>
<body>
<h2>Number search</h2>
<input type="text" id="myInput" onkeyup="myFunction()" placeholder="Search for names.." title="Type in a name">
<table id="myTable">
<tr class="header">
<th style="width:60%;">Number</th>
<th style="width:60%;">Name</th>
<th style="width:60%;">ID</th>
</tr>
<tr>
<td>905-373-3333</td>
<td>Mike</td>
<td>4563</td>
</tr>
<tr>
<td>905-333-3333</td>
<td>adam</td>
<td>8963</td>
</tr>
<tr>
<td>416-373-3432</td>
<td>Jim</td>
<td>9363</td>
</tr>
</table>
<script>
function myFunction() {
var input, filter, table, tr, td, i, cleanedFilter;
input = document.getElementById("myInput");
filter = input.value.toUpperCase();
table = document.getElementById("myTable");
tr = table.getElementsByTagName("tr");
cleanedFilter = filter.replace("-","");
for (i = 0; i < tr.length; i++) {
td = tr[i].getElementsByTagName("td")[0];
if (td) {
cellContent = td.innerHTML.toUpperCase().replace(/-/g,"");
if (cellContent.indexOf(cleanedFilter) > -1) {
tr[i].style.display = "";
} else {
tr[i].style.display = "none";
}
}
}
}
</script>
</body>
</html>
的压缩参数。 https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_pickle.html
在pandas 0.20之前,我没有需要指定的压缩参数。
我有一个使用pandas 0.18编写的webapp并使用版本0.18中的pandas.read_pickle读取pickle文件而没有错误,我应该如何挑选文件?
到目前为止,我已尝试将压缩参数设置为无和&#39; gzip&#39;。两个都不工作。
答案 0 :(得分:2)
看起来您实际上并不需要指定。默认compression='infer'
应该有效。
但是,为什么不只是进口和使用泡菜?
这就是我一直在使用的
# import and save object as pickle
import pickle
pickle.dump(object, open('filename.pkl', 'wb'))
# and this is how to load them
loaded_object = pickle.load(open('filename.pkl', 'rb'))