我真的需要你的帮助。我一直试图转换它并寻找文档，但我想我并不确切知道我在寻找什么。
我的输入文件具有以下结构：
20010102,2301,0.95070,0.95070,0.95070,0.95070,4
20010102,2302,0.95060,0.95060,0.95050,0.95050,4
20010102,2303,0.95050,0.95070,0.95050,0.95060,4
20010102,2304,0.95060,0.95060,0.95060,0.95060,4
这是我的代码：
import numpy as np
EU = np.loadtxt('data_s.csv', delimiter=',')
sample = EU[:5]
size = len(sample)
print (sample)
输出就是：
[[ 2.00101020e+07 2.30100000e+03 9.50700000e-01 9.50700000e-01
9.50700000e-01 9.50700000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30200000e+03 9.50600000e-01 9.50600000e-01
9.50500000e-01 9.50500000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30300000e+03 9.50500000e-01 9.50700000e-01
9.50500000e-01 9.50600000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30400000e+03 9.50600000e-01 9.50600000e-01
9.50600000e-01 9.50600000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30500000e+03 9.50600000e-01 9.50600000e-01
9.50600000e-01 9.50600000e-01 4.00000000e+00]]
所以我尝试重塑它（我肯定不是我应该做的）：
sample = sample.reshape(size, 7)
print(sample)
我的输出完全相同：
[[ 2.00101020e+07 2.30100000e+03 9.50700000e-01 9.50700000e-01
9.50700000e-01 9.50700000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30200000e+03 9.50600000e-01 9.50600000e-01
9.50500000e-01 9.50500000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30300000e+03 9.50500000e-01 9.50700000e-01
9.50500000e-01 9.50600000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30400000e+03 9.50600000e-01 9.50600000e-01
9.50600000e-01 9.50600000e-01 4.00000000e+00]
[ 2.00101020e+07 2.30500000e+03 9.50600000e-01 9.50600000e-01
9.50600000e-01 9.50600000e-01 4.00000000e+00]]
我正在寻找的是这样的输出：
[[[2.00101020e+07], [2.30100000e+03], [9.50700000e-01], [9.50700000e-01],
[9.50700000e-01], [9.50700000e-01], [4.00000000e+00]],
...]
我也试过这个：
sample = EU[:5]
final = []
for line in sample:
va = []
for var in line:
var = np.array(var)
va.append(var)
final.append(va)
print(final)
，输出结果为：
[[array(20010102.0), array(2301.0), array(0.9507), array(0.9507), array(0.9507), array(0.9507), array(4.0)], [array(20010102.0), array(2302.0), array(0.9506), array(0.9506), array(0.9505), array(0.9505), array(4.0)], [array(20010102.0), array(2303.0), array(0.9505), array(0.9507), array(0.9505), array(0.9506), array(4.0)], [array(20010102.0), array(2304.0), array(0.9506), array(0.9506), array(0.9506), array(0.9506), array(4.0)], [array(20010102.0), array(2305.0), array(0.9506), array(0.9506), array(0.9506), array(0.9506), array(4.0)]]
恰好是一个列表，而不是一个数组。所以我试过这个：
final = np.array(final)
这让我回到了起点。
我正在开发一个能够接受这些输入的机器学习项目，目前它们看起来每条线都是输入，没有什么比这些值更像是一个单独的变量。
也许我在想这个错误。我尝试使用熊猫，但我意识到使用numpy并经历必须解决这个问题的痛苦比让pandas给我几千兆字节的数据几乎可以达到几百MB更好。
这可能很傻但请帮助我！我将非常感谢你的帮助！
答案 0 :(得分：0)
你试过吗
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{% block stylesheets %}
{{ parent() }}
<link type="text/css" rel="stylesheet" href="{{ asset('js/plupload/jquery-ui-1.12.1/jquery-ui.css') }}" />
<link type="text/css" rel="stylesheet" href="{{ asset('js/plupload/jquery.ui.plupload/css/jquery.ui.plupload.css') }}" media="screen" />
{% endblock %}
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<div id="box-upload">
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{% endblock %}
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multi_selection: true,
// Maximum file size
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// Specify what files to browse for
filters: [
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{title: "Zip files", extensions: "zip,7z"},
{title: "Pdf files", extensions: "pdf"},
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dragdrop: true,
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var $uploader = uploader.plupload('getUploader');
// Add Clear Button
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// Clear Button Action
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$(".plupload_filelist_content").html('');
$button.button("disable");
return true;
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// Clear Button Toggle Enabled
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if ($uploader.files.length > 0)
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else
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// Clear Button Toggle Hidden
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// Clear Button Toggle Hidden
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$uploader.splice();
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$uploader.bind('Error', function(uploader, error)
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console.error(error.message);
console.log(error.message);
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function removeErrorMessages()
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$(".ui-state-error").remove();
}
});
</script>
{% endblock %}