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  • xml转csv
    2020-11-26 08:12:36

    #!/usr/bin/python

    #XMLtoCSV.py

    #encoding:utf-8

    import csv, os

    from xml.dom.minidom import parse

    def createCSVFile(filePrefix):

    csvFile = open(filePrefix+'.csv', 'wb')  #注意是二进制写入,否则会有多余空格

    csvWriter = csv.writer(csvFile)

    bWriteHead = False

    xmlFile = open(filePrefix+'.xml')

    domTree = parse(xmlFile)

    #print domTree

    root = domTree.documentElement

    #print dir(collection)

    for node in root.childNodes:

    if node.nodeType == node.ELEMENT_NODE:

    #print node.nodeName

    element = {}

    for key in node.attributes.keys():

    value = node.attributes.get(key).value

    element[key] = value

    if len(element) > 0:

    if bWriteHead == False:

    csvWriter.writerow(tuple(element.keys()))

    bWriteHead = True

    csvWriter.writerow(tuple(element.values()))

    else:

    print node.attributes

    csvFile.close()

    xmlFile.close()

    def main():

    for root, dirs, files in os.walk(os.getcwd()):

    print root, dirs, files

    for fname in files:

    index = fname.find('.xml')

    if index > 0:

    #print index, fname[:index]

    createCSVFile(fname[:index])

    print "Transform " + fname + " OK!"

    if __name__ == '__main__':

    main()

    input("Game Over!")

    更多相关内容
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    2015-03-28 15:06:07
    XML 转换 CSV文件,可打开查看对比xml文件
  • 在线XML转CSV工具

    2022-07-21 18:34:15
    XMLToCSVConverter可帮助你在线将XML转换为CSV。XMLToCSVConverter可帮助你在线将XML转换为CSV

    在线XML转CSV工具

    在线XML转CSV工具

    XML To CSV Converter 可帮助你在线将 XML 转换为 CSV。

    XML To CSV Converter 可帮助你在线将 XML 转换为 CSV。

    在这里插入图片描述

    https://toolgg.com/xml-to-csv.html

    展开全文
  • 专业批量XML转CSV,好用好东西大家分享。一键拖拽,很好用。
  • xml转换csv

    千次阅读 2018-06-10 22:48:56
    首先看下 .xml文件<annotation verified="no"> <folder>Pictures</folder> <filename>201092903912879</filename> <...

    首先看下  .xml文件

    <annotation verified="no">
      <folder>Pictures</folder>
      <filename>201092903912879</filename>
      <path>D:/Documents/Pictures/201092903912879.jpg</path>
      <source>
        <database>Unknown</database>
      </source>
      <size>
        <width>1366</width>
        <height>768</height>
        <depth>3</depth>
      </size>
      <segmented>0</segmented>
      <object>
        <name>dog</name>
        <pose>Unspecified</pose>
        <truncated>0</truncated>
        <Difficult>0</Difficult>
        <bndbox>
          <xmin>402</xmin>
          <ymin>103</ymin>
          <xmax>1024</xmax>
          <ymax>525</ymax>
        </bndbox>
      </object>
    </annotation>
    

    所有 xml 生成   .csv文件

    filename,width,height,class,xmin,ymin,xmax,ymax
    img1,300,300,hat,71,27,262,134
    img2,500,333,hat,244,24,346,59
    img3,500,750,hat,126,112,352,234
    

    python脚本

    '''
    只需修改三处,第一第二处改成对应的文件夹目录,
    第三处改成对应的文件名,这里是train.csv
    os.chdir('D:\\python3\\models-master\\research\\object_detection\\images\\train')
    path = 'D:\\python3\\models-master\\research\\object_detection\\images\\train'
    xml_df.to_csv('train.csv', index=None)
    '''
    import os
    import glob
    import pandas as pd
    import xml.etree.ElementTree as ET
    
    os.chdir('C:\\Users\\87703\\Desktop\\picture\\test')
    path = 'C:\\Users\\87703\\Desktop\\picture\\test'
    
    def xml_to_csv(path):
        xml_list = []
        for xml_file in glob.glob(path + '/*.xml'):
            tree = ET.parse(xml_file)
            root = tree.getroot()
            for member in root.findall('object'):
                value = (root.find('filename').text,
                         int(root.find('size')[0].text),
                         int(root.find('size')[1].text),
                         member[0].text,
                         int(member[4][0].text),
                         int(member[4][1].text),
                         int(member[4][2].text),
                         int(member[4][3].text)
                         )
                xml_list.append(value)
        column_name = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
        xml_df = pd.DataFrame(xml_list, columns=column_name)
        return xml_df
    
    
    def main():
        image_path = path
        xml_df = xml_to_csv(image_path)
        xml_df.to_csv('train.csv', index=None)
        print('Successfully converted xml to csv.')
    
    
    main()





    展开全文
  • import xml.etree.ElementTree as ELT from tqdm import tqdm ... Open xml posts dump and convert the text to a csv, tokenizing it in the process :param path: path to the xml document containing posts .
    import xml.etree.ElementTree as ELT
    from tqdm import tqdm
    
    def parse_xml_to_csv(path, save_path=None):
        """
        Open xml posts dump and convert the text to a csv, tokenizing it in the process
        :param path: path to the xml document containing posts
        :return: a dataframe of processed text
        """
    
        # Use python's standard library to parse xml file
        doc = ELT.parse(path)
        root = doc.getroot()
    
        # Each row is a question
        all_rows = [row.attrib for row in root.findall('row')]
    
        # Using tdqm to display progress since preprocessing takes time
        for item in tqdm(all_rows):
            # Decode text from HTML
            soup = BeautifulSoup(item['Body'], features='html.parser')
            item['body_text'] = soup.get_text()
    
        # Create dataframe from our list of dict
        df = pd.DataFrame.from_dict(all_rows)
        if save_path:
            df.to_csv(save_path)
        return df
        
    parse_xml_to_csv("MiniPosts.xml", "1.csv")

    '''

    MiniPosts.xml

     

    <?xml version="1.0" encoding="utf-8"?>
    <posts>
      <row Id="5" PostTypeId="1" CreationDate="2014-05-13T23:58:30.457" Score="9" ViewCount="516" Body="&lt;p&gt;I've always been interested in machine learning, but I can't figure out one thing about starting out with a simple &quot;Hello World&quot; example - how can I avoid hard-coding behavior?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;For example, if I wanted to &quot;teach&quot; a bot how to avoid randomly placed obstacles, I couldn't just use relative motion, because the obstacles move around, but I don't want to hard code, say, distance, because that ruins the whole point of machine learning.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Obviously, randomly generating code would be impractical, so how could I do this?&lt;/p&gt;&#xA;" OwnerUserId="5" LastActivityDate="2014-05-14T00:36:31.077" Title="How can I do simple machine learning without hard-coding behavior?" Tags="&lt;machine-learning&gt;" AnswerCount="1" CommentCount="1" FavoriteCount="1" ClosedDate="2014-05-14T14:40:25.950" />
      <row Id="7" PostTypeId="1" AcceptedAnswerId="10" CreationDate="2014-05-14T00:11:06.457" Score="4" ViewCount="411" Body="&lt;p&gt;As a researcher and instructor, I'm looking for open-source books (or similar materials) that provide a relatively thorough overview of data science from an applied perspective. To be clear, I'm especially interested in a thorough overview that provides material suitable for a college-level course, not particular pieces or papers.&lt;/p&gt;&#xA;" OwnerUserId="36" LastEditorUserId="97" LastEditDate="2014-05-16T13:45:00.237" LastActivityDate="2014-05-16T13:45:00.237" Title="What open-source books (or other materials) provide a relatively thorough overview of data science?" Tags="&lt;education&gt;&lt;open-source&gt;" AnswerCount="3" CommentCount="4" FavoriteCount="1" ClosedDate="2014-05-14T08:40:54.950" />
      <row Id="9" PostTypeId="2" ParentId="5" CreationDate="2014-05-14T00:36:31.077" Score="5" Body="&lt;p&gt;Not sure if this fits the scope of this SE, but here's a stab at an answer anyway.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;With all AI approaches you have to decide what it is you're modelling and what kind of uncertainty there is. Once you pick a framework that allows modelling of your situation, you then see which elements are &quot;fixed&quot; and which are flexible. For example, the model may allow you to define your own network structure (or even learn it) with certain constraints. You have to decide whether this flexibility is sufficient for your purposes. Then within a particular network structure, you can learn parameters given a specific training dataset.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;You rarely hard-code behavior in AI/ML solutions. It's all about modelling the underlying situation and accommodating different situations by tweaking elements of the model.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;In your example, perhaps you might have the robot learn how to detect obstacles (by analyzing elements in the environment), or you might have it keep track of where the obstacles were and which way they were moving.&lt;/p&gt;&#xA;" OwnerUserId="51" LastActivityDate="2014-05-14T00:36:31.077" CommentCount="0" />
      <row Id="10" PostTypeId="2" ParentId="7" CreationDate="2014-05-14T00:53:43.273" Score="12" Body="&lt;p&gt;One book that's freely available is &quot;The Elements of Statistical Learning&quot; by Hastie, Tibshirani, and Friedman (published by Springer): &lt;a href=&quot;http://statweb.stanford.edu/~tibs/ElemStatLearn/&quot;&gt;see Tibshirani's website&lt;/a&gt;.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Another fantastic source, although it isn't a book, is Andrew Ng's Machine Learning course on Coursera. This has a much more applied-focus than the above book, and Prof. Ng does a great job of explaining the thinking behind several different machine learning algorithms/situations.&lt;/p&gt;&#xA;" OwnerUserId="22" LastActivityDate="2014-05-14T00:53:43.273" CommentCount="1" />
      <row Id="14" PostTypeId="1" AcceptedAnswerId="29" CreationDate="2014-05-14T01:25:59.677" Score="23" ViewCount="1388" Body="&lt;p&gt;I am sure data science as will be discussed in this forum has several synonyms or at least related fields where large data is analyzed.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;My particular question is in regards to Data Mining.  I took a graduate class in Data Mining a few years back.  What are the differences between Data Science and Data Mining and in particular what more would I need to look at to become proficient in Data Mining?&lt;/p&gt;&#xA;" OwnerUserId="66" LastEditorUserId="322" LastEditDate="2014-06-17T16:17:20.473" LastActivityDate="2014-06-20T17:36:05.023" Title="Is Data Science the Same as Data Mining?" Tags="&lt;data-mining&gt;&lt;definitions&gt;" AnswerCount="4" CommentCount="1" FavoriteCount="5" />
      <row Id="15" PostTypeId="1" CreationDate="2014-05-14T01:41:23.110" Score="2" ViewCount="579" Body="&lt;p&gt;In which situations would one system be preferred over the other? What are the relative advantages and disadvantages of relational databases versus non-relational databases?&lt;/p&gt;&#xA;" OwnerUserId="64" LastActivityDate="2014-05-14T01:41:23.110" Title="What are the advantages and disadvantages of SQL versus NoSQL in data science?" Tags="&lt;databases&gt;" AnswerCount="0" CommentCount="1" ClosedDate="2014-05-14T07:41:49.437" />
      <row Id="16" PostTypeId="1" AcceptedAnswerId="46" CreationDate="2014-05-14T01:57:56.880" Score="18" ViewCount="336" Body="&lt;p&gt;I use &lt;a href=&quot;http://www.csie.ntu.edu.tw/~cjlin/libsvm/&quot;&gt;Libsvm&lt;/a&gt; to train data and predict classification on &lt;strong&gt;semantic analysis&lt;/strong&gt; problem. But it has a &lt;strong&gt;performance&lt;/strong&gt; issue on large-scale data, because semantic analysis concerns &lt;strong&gt;&lt;em&gt;n-dimension&lt;/em&gt;&lt;/strong&gt; problem.&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Last year, &lt;a href=&quot;http://www.csie.ntu.edu.tw/~cjlin/liblinear/&quot;&gt;Liblinear&lt;/a&gt; was release, and it can solve performance bottleneck.&#xA;But it cost too much &lt;strong&gt;memory&lt;/strong&gt;. Is &lt;strong&gt;MapReduce&lt;/strong&gt; the only way to solve semantic analysis problem on big data? Or are there any other methods that can improve memory bottleneck on &lt;strong&gt;Liblinear&lt;/strong&gt;?&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="84" LastEditDate="2014-05-17T16:24:14.523" LastActivityDate="2014-05-17T16:24:14.523" Title="Use liblinear on big data for semantic analysis" Tags="&lt;machine-learning&gt;&lt;bigdata&gt;&lt;libsvm&gt;" AnswerCount="2" CommentCount="0" />
      <row Id="17" PostTypeId="5" CreationDate="2014-05-14T02:49:14.580" Score="0" Body="&lt;p&gt;&lt;a href=&quot;http://www.csie.ntu.edu.tw/~cjlin/libsvm/&quot; rel=&quot;nofollow&quot;&gt;LIBSVM&lt;/a&gt; is a library for support vector classification (SVM) and regression.&#xA;It was created by Chih-Chung Chang and Chih-Jen Lin in 2001.&lt;/p&gt;&#xA;" OwnerUserId="63" LastEditorUserId="63" LastEditDate="2014-05-16T13:44:53.470" LastActivityDate="2014-05-16T13:44:53.470" CommentCount="0" />
      <row Id="18" PostTypeId="4" CreationDate="2014-05-14T02:49:14.580" Score="0" Body="" OwnerUserId="-1" LastEditorUserId="-1" LastEditDate="2014-05-14T02:49:14.580" LastActivityDate="2014-05-14T02:49:14.580" CommentCount="0" />
      <row Id="19" PostTypeId="1" AcceptedAnswerId="37" CreationDate="2014-05-14T03:56:20.963" Score="81" ViewCount="10681" Body="&lt;p&gt;Lots of people use the term &lt;em&gt;big data&lt;/em&gt; in a rather &lt;em&gt;commercial&lt;/em&gt; way, as a means of indicating that large datasets are involved in the computation, and therefore potential solutions must have good performance. Of course, &lt;em&gt;big data&lt;/em&gt; always carry associated terms, like scalability and efficiency, but what exactly defines a problem as a &lt;em&gt;big data&lt;/em&gt; problem?&lt;/p&gt;&#xA;&#xA;&lt;p&gt;Does the computation have to be related to some set of specific purposes, like data mining/information retrieval, or could an algorithm for general graph problems be labeled &lt;em&gt;big data&lt;/em&gt; if the dataset was &lt;em&gt;big enough&lt;/em&gt;? Also, how &lt;em&gt;big&lt;/em&gt; is &lt;em&gt;big enough&lt;/em&gt; (if this is possible to define)?&lt;/p&gt;&#xA;" OwnerUserId="84" LastEditorUserId="10119" LastEditDate="2015-06-11T20:15:28.720" LastActivityDate="2018-05-01T13:04:43.563" Title="How big is big data?" Tags="&lt;bigdata&gt;&lt;scalability&gt;&lt;efficiency&gt;&lt;performance&gt;" AnswerCount="12" CommentCount="5" FavoriteCount="23" />
    </posts>
    

    '''

     

    '''

    结果:

     

    '''

     IdPostTypeIdCreationDateScoreViewCountBodyOwnerUserIdLastActivityDateTitleTagsAnswerCountCommentCountFavoriteCountClosedDatebody_textAcceptedAnswerIdLastEditorUserIdLastEditDateParentId
    0512014-05-13T23:58:30.4579516<p>I've always been interested in machine learning, but I can't figure out one thing about starting out with a simple "Hello World" example - how can I avoid hard-coding behavior?</p>

    <p>For example, if I wanted to "teach" a bot how to avoid randomly placed obstacles, I couldn't just use relative motion, because the obstacles move around, but I don't want to hard code, say, distance, because that ruins the whole point of machine learning.</p>

    <p>Obviously, randomly generating code would be impractical, so how could I do this?</p>
    52014-05-14T00:36:31.077How can I do simple machine learning without hard-coding behavior?<machine-learning>1112014-05-14T14:40:25.950I've always been interested in machine learning, but I can't figure out one thing about starting out with a simple "Hello World" example - how can I avoid hard-coding behavior?
    For example, if I wanted to "teach" a bot how to avoid randomly placed obstacles, I couldn't just use relative motion, because the obstacles move around, but I don't want to hard code, say, distance, because that ruins the whole point of machine learning.
    Obviously, randomly generating code would be impractical, so how could I do this?
        
    展开全文
  • 软件介绍: 本程序能够直接将XML文件拖放到软件窗口中即可转换,使用非常方便,简单的一键拖拽,很好用。
  • PYTHON2.7编写的脚本,用于将testlink中导出的xml用例文件转换成csv文件; 支持testlink1.9.16
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  • xml文件转换成csv格式,好资源,好分享
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  • XmlCsvBigConvert 这是将xml大文件转换为csv文件的工具。 目标是处理大型xml文件,以将该信息建模到#BigQuery中。 模型处理工具查找重复数据集,然后使用该节点的属性。 例子: <users> <row (interative row) ...
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  • 将 Nmap XML 输出转换为 csv 文件,以及其他有用的功能。 忽略关闭的主机和未打开的端口。 用法 将 Nmap 输出转换为 csv 文件 python3 nmap_xml_parser.py -f nmap_scan.xml -csv nmap_scan.csv 向终端显示扫描信息...
  • xml2csv是用JAVA编写的小型命令行工具,可在所有支持JRE 8或更高版本的平台上使用。 示例:1.帮助java -jar xml2csv-1.0.jar --help 2.从xml中提取节点:java -jar xml2csv-1.0.jar --nodes test / cd_catalog.xml...
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    文件名cou.xml: <?xml version="1.0"?> 4 2011 59900 8 2013 77889 68 2011 13600 求助,如何将上面...
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    from xml.dom import minidom import pandas as pd def readXML(xmlfilename): xmlDoc = minidom.parse(xmlfilename) items = xmlDoc.getElementsByTagName("wfs:member") NAME=[] LNG=[] LAT=[] FROM=[] ...
  • Python把xml文件转为csv文件

    千次阅读 2020-08-11 20:18:29
    import os import glob import pandas as pd ...def xml_to_csv(path): xml_list = [] for xml_file in glob.glob(path + '/*.xml'): print(xml_file) tree = ET.parse(xml_file) root = tree.getroot()
  • 将转换的两个脚本代码拷贝到如何文件夹,红色实线标注。 新建一个文件夹(image),放入标注的图片和xml数据,其中一个文件夹放入训练集数据,另一个放入测试集数据。...cmd键入python xml_to_csv.py将csv ...

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