将 XML 转换为 CSV Pandas to_csv 不是在写一些行，而是在写其他行看不出来

如何解决将 XML 转换为 CSV Pandas to_csv 不是在写一些行，而是在写其他行看不出来

我正在将 XML 转换为 CSV。

对于某些人来说，它写得很好，但对于其他人，它什么也没写。

下面是我的代码。正在写入的行是：

• 品牌
• 线
• 姓名

其他行不是。您将在 productType 中看到我进行检查并打印到控制台 retail 或 usage 并且这确实为每个项目打印到控制台。它正在工作。但是，它只是不写入数据。我完全被难住了。任何建议将不胜感激。谢谢。

代码如下：

# Importing the required libraries
import xml.etree.ElementTree as Xet
import pandas as pd
  
productColumns = ["brand","line","name","purpose","retailPrice"]
rows = []
  
# Parsing the XML file
xmlparse = Xet.parse('xmlimportdata.xml')
root = xmlparse.getroot()

products = root.findall("productTableData")

for product in products:

    # make sure a product and not a service (P vs S)
    if product.find("productType").text == "P":        

        productBrand = product.find("Make")
        if productBrand is not None:
            productBrand = productBrand.text
        else:
            productBrand = "No Data"
        
        productLine = product.find("Category")
        if productLine is not None:
            productLine = productLine.text
        else:
            productLine = "No Data"
        
        productName = product.find("Name")
        if productName is not None:
            productName = productName.text
        else:
            productName = "No Data"

        productType = product.find("usageType")
        if productType is not None:
            if productType.text == "true":
                print('usage')
                productType = "usage"
            else:
                productType = "retail"
                print('retail')
        else:
            productType = "No Data"
        
        productSize = product.find("Size")
        if productSize is not None:
            productSize = productSize.text
        else:
            productSize = "No Data"
        
        productPrice = product.find("Retail")
        if productPrice is not None:
            productPrice = productPrice.text
        else:
            productPrice = "No Data"

        productId = product.find("ID")
        if productId is not None:
            productId = productId.text
        else:
            productId = "No Data"

        rows.append({"brand": productBrand,"line": productLine,"name": productName,"type": productType,"size": productSize,"price": productPrice
                     })


# add data to pandas dataframe
df = pd.DataFrame(rows,columns=productColumns)
  
# Writing dataframe to csv
# note the columns =  This little ripper will auto sort columns for us and place in correct order
df.to_csv('Converted-Products.csv',columns = productColumns,index = False)

解决方法

更新！我找到了。 rows.append 没有附加与开始时在 productColumns 中声明的行相同的名称。一旦我让它们匹配，我们就得到了输出。

,

此转换不需要 pandas。离开大型图书馆进行数据分析。只需open一个文本文件并使用csv包来writerows。并使用定义的方法通过使用三元运算符（即,if 和 else 在同一行）。

import csv
import xml.etree.ElementTree as Xet

elementColumns = ["ID","Make","Category","Name","usageType","Size","Retail"]
productColumns = ["id","brand","line","name","purpose","size","retailPrice"]

def get_text(elem,colname):
    colElem = elem.find(colname)

    colText = colElem.text if colElem is Not None else "No Data"

    if col == "usageType" and colElem is Not None:
        colText = "usage" if colElem.text == "true" else "retail"
        
    return colText

# PARSE XML FILE
xmlparse = Xet.parse('xmlimportdata.xml')
root = xmlparse.getroot()
products = root.findall("productTableData")

# OPEN CSV FOR WRITING
with open("Output.csv","wb") as f:
    writer = csv.writer(f)

    # HEADERS
    writer.writerow(productColumns)

    # ROWS
    for product in products:
        if product.find("productType").text == "P":
            writer.writerow([
                get_text(product,col) 
                for col in elementColumns
            ])