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Python常见问题
首先，让我为html表道歉。这是我唯一能让这张歪桌子好看的方法。你知道吗
现在，关于这个问题，我正在尝试找到将坐标数组（表中的坐标列）保存在csv文件的列中以供以后使用的最佳方法。你知道吗
目前，在使用像so:dd.read_csv()这样的dask读取CSV之后，列表是一个像so:'[[...][...]..]]'这样的字符串表示形式，我在其上使用ast.literal_eval将列表的字符串表示形式转换为一个列表，但是如果我能找到正确的方法保存数组，这是低效的。你知道吗
总之：
如何将numpy数组保存在CSV列中，以便以后以numpy数组的形式重新加载？或者如何从CSV列中提取numpy数组？你知道吗
编辑：
我使用多重处理，因此下表中的每个条目首先保存为列表列表，然后在所有迭代之后，列表转换为数据帧，并保存为CSV文件
<html xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:x="urn:schemas-microsoft-com:office:excel" xmlns="http://www.w3.org/TR/REC-html40">
<head>
<meta http-equiv=Content-Type content="text/html; charset=windows-1252">
<meta name=ProgId content=Excel.Sheet>
<meta name=Generator content="Microsoft Excel 15">
<link rel=File-List href="monte_carlo%20Jun%2013,%202019%20@%2008_files/filelist.xml">
<style id="monte_carlo Jun 13, 2019 @ 08.14__21583_Styles">
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mso-displayed-decimal-separator: "\.";
mso-displayed-thousand-separator: " ";
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mso-ignore: padding;
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font-size: 11.0pt;
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text-decoration: none;
font-family: Calibri, sans-serif;
mso-font-charset: 0;
mso-number-format: General;
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vertical-align: bottom;
mso-background-source: auto;
mso-pattern: auto;
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text-decoration: none;
font-family: Calibri, sans-serif;
mso-font-charset: 0;
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vertical-align: middle;
mso-background-source: auto;
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text-decoration: none;
font-family: Calibri, sans-serif;
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<body>
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Page wizard.-->
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<div id="monte_carlo Jun 13, 2019 @ 08.14__21583" align=center x:publishsource="Excel">
<table border=0 cellpadding=0 cellspacing=0 width=2451 style='border-collapse:
collapse;table-layout:fixed;width:1841pt'>
<col width=121 style='mso-width-source:userset;mso-width-alt:4425;width:91pt'>
<col width=94 style='mso-width-source:userset;mso-width-alt:3437;width:71pt'>
<col width=84 style='mso-width-source:userset;mso-width-alt:3072;width:63pt'>
<col width=416 style='mso-width-source:userset;mso-width-alt:15213;width:312pt'>
<col width=49 span=3 style='mso-width-source:userset;mso-width-alt:1792;
width:37pt'>
<col width=130 span=2 style='mso-width-source:userset;mso-width-alt:4754;
width:98pt'>
<col width=128 style='mso-width-source:userset;mso-width-alt:4681;width:96pt'>
<col width=171 span=2 style='mso-width-source:userset;mso-width-alt:6253;
width:128pt'>
<col width=169 style='mso-width-source:userset;mso-width-alt:6180;width:127pt'>
<col width=84 style='mso-width-source:userset;mso-width-alt:3072;width:63pt'>
<col width=606 style='mso-width-source:userset;mso-width-alt:22162;width:455pt'>
<tr height=20 style='height:15.0pt'>
<td height=20 class=xl1521583 width=121 style='height:15.0pt;width:91pt'>L-string</td>
<td class=xl1521583 width=94 style='width:71pt'>Coordinates</td>
<td class=xl1521583 width=84 style='width:63pt'>Area</td>
<td class=xl1521583 width=416 style='width:312pt'>Bounding Coordinates</td>
<td class=xl1521583 width=49 style='width:37pt'>% of F</td>
<td class=xl1521583 width=49 style='width:37pt'>% of +</td>
<td class=xl1521583 width=49 style='width:37pt'>% of -</td>
<td class=xl1521583 width=130 style='width:98pt'>Longest F sequence</td>
<td class=xl1521583 width=130 style='width:98pt'>Longest + sequence</td>
<td class=xl1521583 width=128 style='width:96pt'>Longest - sequence</td>
<td class=xl1521583 width=171 style='width:128pt'>Average chars between Fs</td>
<td class=xl1521583 width=171 style='width:128pt'>Average chars between +s</td>
<td class=xl1521583 width=169 style='width:127pt'>Average chars between -s</td>
<td class=xl1521583 width=84 style='width:63pt'>Angle</td>
<td class=xl1521583 width=606 style='width:455pt'>Rules</td>
</tr>
<tr height=120 style='height:90.0pt'>
<td height=120 class=xl6321583 style='height:90.0pt'>F---++F-F-+F-F-+</td>
<td class=xl6421583 width=94 style='width:71pt'>[[ 0. 0. 0.]<br>
<span style='mso-spacerun:yes'> </span>[ 0. 1. 0.]<br>
<span style='mso-spacerun:yes'> </span>[ 0.4 1.9 0.]<br>
<span style='mso-spacerun:yes'> </span>[-0.4 1.4 0.]<br>
<span style='mso-spacerun:yes'> </span>[ 0.03 0.6 0.]<br>
<span style='mso-spacerun:yes'> </span>[ 0.1 1.6 0.]]</td>
<td class=xl6321583>3.531154679</td>
<td class=xl6321583>(-0.4909271959019015, 0.0, 0.4226182617406995, 1.90630778703665)
</td>
<td class=xl6321583>0.3125</td>
<td class=xl6321583>0.25</td>
<td class=xl6321583>0.4375</td>
<td class=xl6321583>1</td>
<td class=xl6321583>2</td>
<td class=xl6321583>3</td>
<td class=xl6321583>2.25</td>
<td class=xl6321583>2.666666667</td>
<td class=xl6321583>1.166666667</td>
<td class=xl6321583>0.715584993</td>
<td class=xl6321583>{'X': {'options': ['---++X', 'F-F-+X'], 'probabilities': [0.24384925254542278, 0.7561507474545772]}}</td>
</tr>
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<td width=416 style='width:312pt'></td>
<td width=49 style='width:37pt'></td>
<td width=49 style='width:37pt'></td>
<td width=49 style='width:37pt'></td>
<td width=130 style='width:98pt'></td>
<td width=130 style='width:98pt'></td>
<td width=128 style='width:96pt'></td>
<td width=171 style='width:128pt'></td>
<td width=171 style='width:128pt'></td>
<td width=169 style='width:127pt'></td>
<td width=84 style='width:63pt'></td>
<td width=606 style='width:455pt'></td>
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</body>
</html>Tags： sourcestylecolaltwidthclasstdspan
我会将该列存储为一个单独的
npy文件。你知道吗我会在节省时间时使用：
然后在加载时：
由于pandas在内部对其列使用numpy ndarrays，因此可以直接保存和加载包含其他numpy数组的对象numpy arrays。你知道吗
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