[数据工程]如何将xml转csv

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

 

'''

 

'''

结果:

 

'''

Id

PostTypeId

CreationDate

Score

ViewCount

Body

OwnerUserId

LastActivityDate

Title

Tags

AnswerCount

CommentCount

FavoriteCount

ClosedDate

body_text

AcceptedAnswerId

LastEditorUserId

LastEditDate

ParentId

0

5

1

2014-05-13T23:58:30.457

9

516

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? 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?

5

2014-05-14T00:36:31.077

How can I do simple machine learning without hard-coding behavior?

1

1

1

2014-05-14T14:40:25.950

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? 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?