Python——python读取xml实战，作业6（python programming）

佚名 6年前 (2019-04-18) 随笔 1504人围观抢沙发百度已收录

SRE实战互联网时代守护先锋，助力企业售后服务体系运筹帷幄！一键直达领取阿里云限量特价优惠。

cd_catalog.xml

Python——python读取xml实战，作业6（python programming）随笔第2张

<?xml version="1.0" encoding="ISO-8859-1"?>
<!-- Edited with XML Spy v2007 (http://www.altova.com) -->
<CATALOG>
    <CD>
        <TITLE>Empire Burlesque</TITLE>
        <ARTIST>Bob Dylan</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>Columbia</COMPANY>
        <PRICE>10.90</PRICE>
        <YEAR>1985</YEAR>
    </CD>
    <CD>
        <TITLE>Hide your heart</TITLE>
        <ARTIST>Bonnie Tyler</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>CBS Records</COMPANY>
        <PRICE>9.90</PRICE>
        <YEAR>1988</YEAR>
    </CD>
    <CD>
        <TITLE>Greatest Hits</TITLE>
        <ARTIST>Dolly Parton</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>RCA</COMPANY>
        <PRICE>9.90</PRICE>
        <YEAR>1982</YEAR>
    </CD>
    <CD>
        <TITLE>Still got the blues</TITLE>
        <ARTIST>Gary Moore</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Virgin records</COMPANY>
        <PRICE>10.20</PRICE>
        <YEAR>1990</YEAR>
    </CD>
    <CD>
        <TITLE>Eros</TITLE>
        <ARTIST>Eros Ramazzotti</ARTIST>
        <COUNTRY>EU</COUNTRY>
        <COMPANY>BMG</COMPANY>
        <PRICE>9.90</PRICE>
        <YEAR>1997</YEAR>
    </CD>
    <CD>
        <TITLE>One night only</TITLE>
        <ARTIST>Bee Gees</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Polydor</COMPANY>
        <PRICE>10.90</PRICE>
        <YEAR>1998</YEAR>
    </CD>
    <CD>
        <TITLE>Sylvias Mother</TITLE>
        <ARTIST>Dr.Hook</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>CBS</COMPANY>
        <PRICE>8.10</PRICE>
        <YEAR>1973</YEAR>
    </CD>
    <CD>
        <TITLE>Maggie May</TITLE>
        <ARTIST>Rod Stewart</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Pickwick</COMPANY>
        <PRICE>8.50</PRICE>
        <YEAR>1990</YEAR>
    </CD>
    <CD>
        <TITLE>Romanza</TITLE>
        <ARTIST>Andrea Bocelli</ARTIST>
        <COUNTRY>EU</COUNTRY>
        <COMPANY>Polydor</COMPANY>
        <PRICE>10.80</PRICE>
        <YEAR>1996</YEAR>
    </CD>
    <CD>
        <TITLE>When a man loves a woman</TITLE>
        <ARTIST>Percy Sledge</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>Atlantic</COMPANY>
        <PRICE>8.70</PRICE>
        <YEAR>1987</YEAR>
    </CD>
    <CD>
        <TITLE>Black angel</TITLE>
        <ARTIST>Savage Rose</ARTIST>
        <COUNTRY>EU</COUNTRY>
        <COMPANY>Mega</COMPANY>
        <PRICE>10.90</PRICE>
        <YEAR>1995</YEAR>
    </CD>
    <CD>
        <TITLE>1999 Grammy Nominees</TITLE>
        <ARTIST>Many</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>Grammy</COMPANY>
        <PRICE>10.20</PRICE>
        <YEAR>1999</YEAR>
    </CD>
    <CD>
        <TITLE>For the good times</TITLE>
        <ARTIST>Kenny Rogers</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Mucik Master</COMPANY>
        <PRICE>8.70</PRICE>
        <YEAR>1995</YEAR>
    </CD>
    <CD>
        <TITLE>Big Willie style</TITLE>
        <ARTIST>Will Smith</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>Columbia</COMPANY>
        <PRICE>9.90</PRICE>
        <YEAR>1997</YEAR>
    </CD>
    <CD>
        <TITLE>Tupelo Honey</TITLE>
        <ARTIST>Van Morrison</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Polydor</COMPANY>
        <PRICE>8.20</PRICE>
        <YEAR>1971</YEAR>
    </CD>
    <CD>
        <TITLE>The very best of</TITLE>
        <ARTIST>Cat Stevens</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Island</COMPANY>
        <PRICE>8.90</PRICE>
        <YEAR>1990</YEAR>
    </CD>
    <CD>
        <TITLE>Stop</TITLE>
        <ARTIST>Sam Brown</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>A and M</COMPANY>
        <PRICE>8.90</PRICE>
        <YEAR>1988</YEAR>
    </CD>
    <CD>
        <TITLE>Bridge of Spies</TITLE>
        <ARTIST>T'Pau</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Siren</COMPANY>
        <PRICE>7.90</PRICE>
        <YEAR>1987</YEAR>
    </CD>
    <CD>
        <TITLE>Private Dancer</TITLE>
        <ARTIST>Tina Turner</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>Capitol</COMPANY>
        <PRICE>8.90</PRICE>
        <YEAR>1983</YEAR>
    </CD>
    <CD>
        <TITLE>Midt om natten</TITLE>
        <ARTIST>Kim Larsen</ARTIST>
        <COUNTRY>EU</COUNTRY>
        <COMPANY>Medley</COMPANY>
        <PRICE>7.80</PRICE>
        <YEAR>1983</YEAR>
    </CD>
    <CD>
        <TITLE>Pavarotti Gala Concert</TITLE>
        <ARTIST>Luciano Pavarotti</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>DECCA</COMPANY>
        <PRICE>9.90</PRICE>
        <YEAR>1991</YEAR>
    </CD>
    <CD>
        <TITLE>The dock of the bay</TITLE>
        <ARTIST>Otis Redding</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>Atlantic</COMPANY>
        <PRICE>7.90</PRICE>
        <YEAR>1987</YEAR>
    </CD>
    <CD>
        <TITLE>Picture book</TITLE>
        <ARTIST>Simply Red</ARTIST>
        <COUNTRY>EU</COUNTRY>
        <COMPANY>Elektra</COMPANY>
        <PRICE>7.20</PRICE>
        <YEAR>1985</YEAR>
    </CD>
    <CD>
        <TITLE>Red</TITLE>
        <ARTIST>The Communards</ARTIST>
        <COUNTRY>UK</COUNTRY>
        <COMPANY>London</COMPANY>
        <PRICE>7.80</PRICE>
        <YEAR>1987</YEAR>
    </CD>
    <CD>
        <TITLE>Unchain my heart</TITLE>
        <ARTIST>Joe Cocker</ARTIST>
        <COUNTRY>USA</COUNTRY>
        <COMPANY>EMI</COMPANY>
        <PRICE>8.20</PRICE>
        <YEAR>1987</YEAR>
    </CD>
</CATALOG>

View Code

# -*- coding: utf-8 -*- from lxml import objectify import pandas as pd parsed = objectify.parse(open('cd_catalog.xml')) root= parsed.getroot() CDs = root.getchildren() CD0 = CDs[0] content = CD0.getchildren() for i in content: print(i.tag,":",i) #TITLE : Empire Burlesque #ARTIST : Bob Dylan #COUNTRY : USA #COMPANY : Columbia #PRICE : 10.9 #YEAR : 19855  dataframe={} for i in content: dataframe[i.tag]=[] for CD in CDs: content = CD.getchildren() for i in content: dataframe[i.tag].append(i) #转为dataframe形式 dataframe = pd.DataFrame(dataframe)