我想获取PMID,对于每个PMID,可以从作者列表中获取其他列表,对于每个PMID,我可以获取作者列表,对于所有其他PMId,我可以获取作者列表
<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE PubmedArticleSet SYSTEM "http://dtd.nlm.nih.gov/ncbi/pubmed/out/pubmed_190101.dtd">
<PubmedArticleSet>
<PubmedArticle>
<MedlineCitation Status="MEDLINE" Owner="NLM">
<PMID Version="1">2844048</PMID>
<DateCompleted>
<Year>1988</Year>
<Month>10</Month>
<Day>26</Day>
</DateCompleted>
<DateRevised>
<Year>2010</Year>
<Month>11</Month>
<Day>18</Day>
</DateRevised>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Guarner</LastName>
<ForeName>J</ForeName>
<Initials>J</Initials>
<AffiliationInfo>
<Affiliation>Department of Pathology and Laboratory Medicine, Emory University Hospital, Atlanta, Georgia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Cohen</LastName>
<ForeName>C</ForeName>
<Initials>C</Initials>
</Author>
</AuthorList>
</MedlineCitation>
由于标签的结构,我可以单独获取,但不知道如何分组。
tree = ET.parse('x.xml')
root = tree.getroot()
pid =[]
for pmid in root.iter('PMID'):
pid.append(pmid.text)
lastname=[]
for id in root.findall("./PubmedArticle/MedlineCitation/Article/AuthorList"):
for ln in id.findall("./Author/LastName"):
lastname.append(ln.text)
forename=[]
for id in root.findall("./PubmedArticle/MedlineCitation/Article/AuthorList"):
for fn in id.findall("./Author/ForeName"):
forename.append(fn.text)
initialname=[]
for id in root.findall("./PubmedArticle/MedlineCitation/Article/AuthorList"):
for i in id.findall("./Author/Initials"):
initialname.append(i.text)
预期产量
PMID AUTHORS
2844048 'Guarner J J', 'Cohen C C'
请提出解决问题的可能方法,预期输出的行数将更多,谢谢。
答案 0 :(得分:0)
XPath 1.0的数据模型在specification中定义:
3.3节点集
3.4布尔
3.5个数字
3.6字符串
节点集是适当的集:重复数据删除和无序。您需要一个sequence,即数据的有序列表(例如,节点集的有序列表)。此数据类型是XPath 2.0及更高版本的一部分。
要在XPath 1.0中将其分组为嵌入式语言,请选择“同类中的第一”,然后使用宿主语言遍历文档以获取分组的项目,即使使用其他XPath表达式也是如此。这就是在XSLT本身中完成的方式。
答案 1 :(得分:0)
虽然花了一段时间,但我想我明白了。为了使此练习有趣,我进行了一些更改。
首先,您问题中的xml代码无效; you can check it here, for example。
因此,首先我修复了xml。另外,我将其转换为PubmedArticleSet,因此它有2篇文章,第一篇文章有3位作者,第二篇文章-两位(显然是虚假信息),目的是确保代码能够全部抓住它们。为了简化起见,我删除了一些与本练习无关的信息,例如隶属关系。
这就是离开我们的地方。 首先,修改xml:
source = """
<PubmedArticleSet>
<PubmedArticle>
<MedlineCitation Status="MEDLINE" Owner="NLM">
<PMID Version="1">2844048</PMID>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Guarner</LastName>
<ForeName>J</ForeName>
<Initials>J</Initials>
</Author>
<Author ValidYN="Y">
<LastName>Cohen</LastName>
<ForeName>C</ForeName>
<Initials>C</Initials>
</Author>
<Author ValidYN="Y">
<LastName>Mushi</LastName>
<ForeName>E</ForeName>
<Initials>F</Initials>
</Author>
</AuthorList>
</MedlineCitation>
</PubmedArticle>
<PubmedArticle>
<MedlineCitation Status="MEDLINE" Owner="NLM">
<PMID Version="1">123456</PMID>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Smith</LastName>
<ForeName>C</ForeName>
<Initials>C</Initials>
</Author>
<Author ValidYN="Y">
<LastName>Jones</LastName>
<ForeName>E</ForeName>
<Initials>F</Initials>
</Author>
</AuthorList>
</MedlineCitation>
</PubmedArticle>
"""
接下来,导入需要导入的内容:
from lxml import etree
import pandas as pd
接下来,代码:
doc = etree.fromstring(source)
art_loc = '..//*/PubmedArticle' #this is the path to all the articles
#count the number of articles in the article set - that number is a float has to be converted to integer before use:
num_arts = int(doc.xpath(f'count({art_loc})')) # or could use len(doc.xpath(f'({art_loc})'))
grand_inf = [] #this list will hold the accumulated information at the end
for art in range(1,num_arts+1): #can't do range(num_arts) because of the different ways python and Pubmed count
loc_path = (f'{art_loc}[{art}]/*/') #locate the path to each article
#grab the article id:
id_path = loc_path+'PMID'
pmid = doc.xpath(id_path)[0].text
art_inf = [] #this list holds the information for each article
art_inf.append(pmid)
art_path = loc_path+'/Author' #locate the path to the author group
#determine the number of authors for this article; again, it's a float which needs to converted to integer
num_auths = int(doc.xpath(f'count({art_path})')) #again: could use len(doc.xpath(f'({art_path})'))
auth_inf = [] #this will hold the full name of each of the authors
for auth in range(1,num_auths+1):
auth_path = (f'{art_path}[{auth}]') #locate the path to each author
LastName = doc.xpath((f'{auth_path}/LastName'))[0].text
FirstName = doc.xpath((f'{auth_path}/ForeName'))[0].text
Middle = doc.xpath((f'{auth_path}/Initials'))[0].text
full_name = LastName+' '+FirstName+' '+Middle
auth_inf.append(full_name)
art_inf.append(auth_inf)
grand_inf.append(art_inf)
最后,将此信息加载到数据框中:
df=pd.DataFrame(grand_inf,columns=['PMID','Author(s)'])
df
输出:
PMID Author(s)
0 2844048 [Guarner J J, Cohen C C, Mushi E F]
1 123456 [Smith C C, Jones E F]
我们现在可以休息...