我正在尝试根据从PubMed下载的关键字数据开发研究时间表。感谢许多优秀的例子，在这个和其他网站上，我走得很远。附加代码根据输入查询下载excel文件，然后解析并将其转换为r可用数据帧。唯一的问题是元素“KeywordList”拒绝合作。注释掉后，一切都按预期运行。但是，在包含时，R会产生以下错误：
Error in FUN("pubmed_MedEng/MedEng01.xml"[[1L]], ...) :
object 'Keyword1' not found
3 FUN("pubmed_MedEng/MedEng01.xml"[[1L]], ...)
2 lapply(myxml.path, function(x) {
myxml <- xmlParse(x, useInternalNodes = TRUE)
padXML <- function(x, xstr) {
res <- xpathSApply(x, xstr, xmlValue) ...
1 pubmed_download("'medical English'", "MedEng")
我使用适当的XML开发工具生成了这个和其他XPath，所以我相当确定它们没问题。我也以同样的方式检查了XML文件。这是一个相关的片段：
<?xml version="1.0"?>
<!DOCTYPE PubmedArticleSet PUBLIC "-//NLM//DTD PubMedArticle, 1st January 2015//EN" "http://www.ncbi.nlm.nih.gov/corehtml/query/DTD/pubmed_150101.dtd">
<PubmedArticleSet>
<PubmedArticle>
<MedlineCitation Status="Publisher" Owner="NLM">
<PMID Version="1">26269536</PMID>
<DateCreated>
<Year>2015</Year>
<Month>8</Month>
<Day>13</Day>
</DateCreated>
<DateRevised>
<Year>2015</Year>
<Month>8</Month>
<Day>14</Day>
</DateRevised>
<Article PubModel="Print-Electronic">
<Journal>
<ISSN IssnType="Electronic">1527-974X</ISSN>
<JournalIssue CitedMedium="Internet">
<PubDate>
<Year>2015</Year>
<Month>Aug</Month>
<Day>11</Day>
</PubDate>
</JournalIssue>
<Title>Journal of the American Medical Informatics Association : JAMIA</Title>
<ISOAbbreviation>J Am Med Inform Assoc</ISOAbbreviation>
</Journal>
<ArticleTitle>Assessing the readability of clinicaltrials.gov.</ArticleTitle>
<Pagination>
<MedlinePgn/>
</Pagination>
<ELocationID EIdType="pii">ocv062</ELocationID>
<ELocationID EIdType="doi">10.1093/jamia/ocv062</ELocationID>
<Abstract>
<AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">ClinicalTrials.gov serves critical functions of disseminating trial information to the public and helping the trials recruit participants. This study assessed the readability of trial descriptions at ClinicalTrials.gov using multiple quantitative measures.</AbstractText>
<AbstractText Label="MATERIALS AND METHODS" NlmCategory="METHODS">The analysis included all 165 988 trials registered at ClinicalTrials.gov as of April 30, 2014. To obtain benchmarks, the authors also analyzed 2 other medical corpora: (1) all 955 Health Topics articles from MedlinePlus and (2) a random sample of 100 000 clinician notes retrieved from an electronic health records system intended for conveying internal communication among medical professionals. The authors characterized each of the corpora using 4 surface metrics, and then applied 5 different scoring algorithms to assess their readability. The authors hypothesized that clinician notes would be most difficult to read, followed by trial descriptions and MedlinePlus Health Topics articles.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Trial descriptions have the longest average sentence length (26.1 words) across all corpora; 65% of their words used are not covered by a basic medical English dictionary. In comparison, average sentence length of MedlinePlus Health Topics articles is 61% shorter, vocabulary size is 95% smaller, and dictionary coverage is 46% higher. All 5 scoring algorithms consistently rated CliniclTrials.gov trial descriptions the most difficult corpus to read, even harder than clinician notes. On average, it requires 18 years of education to properly understand these trial descriptions according to the results generated by the readability assessment algorithms.</AbstractText>
<AbstractText Label="DISCUSSION AND CONCLUSION" NlmCategory="CONCLUSIONS">Trial descriptions at CliniclTrials.gov are extremely difficult to read. Significant work is warranted to improve their readability in order to achieve CliniclTrials.gov's goal of facilitating information dissemination and subject recruitment.</AbstractText>
<CopyrightInformation>Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government employees and is in the public domain in the US.</CopyrightInformation>
</Abstract>
<AuthorList>
<Author>
<LastName>Wu</LastName>
<ForeName>Danny Ty</ForeName>
<Initials>DT</Initials>
<AffiliationInfo>
<Affiliation>School of Information, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Hanauer</LastName>
<ForeName>David A</ForeName>
<Initials>DA</Initials>
<AffiliationInfo>
<Affiliation>School of Information, University of Michigan, Ann Arbor, MI, USA Department of Pediatrics, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Mei</LastName>
<ForeName>Qiaozhu</ForeName>
<Initials>Q</Initials>
<AffiliationInfo>
<Affiliation>School of Information, University of Michigan, Ann Arbor, MI, USA Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Clark</LastName>
<ForeName>Patricia M</ForeName>
<Initials>PM</Initials>
<AffiliationInfo>
<Affiliation>School of Nursing, University of Michigan, Ann Arbor, MI, USA Center for Health Communication Research, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>An</LastName>
<ForeName>Lawrence C</ForeName>
<Initials>LC</Initials>
<AffiliationInfo>
<Affiliation>Center for Health Communication Research, University of Michigan, Ann Arbor, MI, USA Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Proulx</LastName>
<ForeName>Joshua</ForeName>
<Initials>J</Initials>
<AffiliationInfo>
<Affiliation>Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Zeng</LastName>
<ForeName>Qing T</ForeName>
<Initials>QT</Initials>
<AffiliationInfo>
<Affiliation>Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Vydiswaran</LastName>
<ForeName>Vg Vinod</ForeName>
<Initials>VV</Initials>
<AffiliationInfo>
<Affiliation>School of Information, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Collins-Thompson</LastName>
<ForeName>Kevyn</ForeName>
<Initials>K</Initials>
<AffiliationInfo>
<Affiliation>School of Information, University of Michigan, Ann Arbor, MI, USA Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author>
<LastName>Zheng</LastName>
<ForeName>Kai</ForeName>
<Initials>K</Initials>
<AffiliationInfo>
<Affiliation>School of Information, University of Michigan, Ann Arbor, MI, USA School of Public Health Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA kzheng@umich.edu.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>ENG</Language>
<PublicationTypeList>
<PublicationType UI="">JOURNAL ARTICLE</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic">
<Year>2015</Year>
<Month>8</Month>
<Day>11</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo>
<MedlineTA>J Am Med Inform Assoc</MedlineTA>
<NlmUniqueID>9430800</NlmUniqueID>
<ISSNLinking>1067-5027</ISSNLinking>
</MedlineJournalInfo>
<KeywordList Owner="NOTNLM">
<Keyword MajorTopicYN="N">CliniclTrials.gov</Keyword>
<Keyword MajorTopicYN="N">clinical trial</Keyword>
<Keyword MajorTopicYN="N">comprehension</Keyword>
<Keyword MajorTopicYN="N">electronic health records</Keyword>
<Keyword MajorTopicYN="N">natural language processing</Keyword>
<Keyword MajorTopicYN="N">readability</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData>
<History>
<PubMedPubDate PubStatus="entrez">
<Year>2015</Year>
<Month>8</Month>
<Day>14</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed">
<Year>2015</Year>
<Month>8</Month>
<Day>14</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline">
<Year>2015</Year>
<Month>8</Month>
<Day>14</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>aheadofprint</PublicationStatus>
<ArticleIdList>
<ArticleId IdType="pii">ocv062</ArticleId>
<ArticleId IdType="doi">10.1093/jamia/ocv062</ArticleId>
<ArticleId IdType="pubmed">26269536</ArticleId>
</ArticleIdList>
</PubmedData>
</PubmedArticle>
<PubmedArticle>
<MedlineCitation Owner="NLM" Status="MEDLINE">
<PMID Version="1">5819388</PMID>
<DateCreated>
<Year>1969</Year>
<Month>08</Month>
<Day>22</Day>
</DateCreated>
<DateCompleted>
<Year>1969</Year>
<Month>08</Month>
<Day>22</Day>
</DateCompleted>
<DateRevised>
<Year>2007</Year>
<Month>11</Month>
<Day>15</Day>
</DateRevised>
<Article PubModel="Print">
<Journal>
<ISSN IssnType="Print">0026-1270</ISSN>
<JournalIssue CitedMedium="Print">
<Volume>8</Volume>
<Issue>2</Issue>
<PubDate>
<Year>1969</Year>
<Month>Apr</Month>
</PubDate>
</JournalIssue>
<Title>Methods of information in medicine</Title>
<ISOAbbreviation>Methods Inf Med</ISOAbbreviation>
</Journal>
<ArticleTitle>Identification and transformation of terminal morphemes in medical English.</ArticleTitle>
<Pagination>
<MedlinePgn>84-90</MedlinePgn>
</Pagination>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Pratt</LastName>
<ForeName>A W</ForeName>
<Initials>AW</Initials>
</Author>
<Author ValidYN="Y">
<LastName>Pacak</LastName>
<ForeName>M</ForeName>
<Initials>M</Initials>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList>
<PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
</Article>
<MedlineJournalInfo>
<Country>GERMANY, WEST</Country>
<MedlineTA>Methods Inf Med</MedlineTA>
<NlmUniqueID>0210453</NlmUniqueID>
<ISSNLinking>0026-1270</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList>
<MeshHeading>
<DescriptorName MajorTopicYN="Y" UI="D000043">Abstracting and Indexing as Topic</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName MajorTopicYN="Y" UI="D003201">Computers</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName MajorTopicYN="Y" UI="D008037">Linguistics</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName MajorTopicYN="N" UI="D009316">National Institutes of Health (U.S.)</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName MajorTopicYN="N" Type="Geographic" UI="D014481">United States</DescriptorName>
</MeshHeading>
</MeshHeadingList>
</MedlineCitation>
<PubmedData>
<History>
<PubMedPubDate PubStatus="pubmed">
<Year>1969</Year>
<Month>4</Month>
<Day>1</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline">
<Year>1969</Year>
<Month>4</Month>
<Day>1</Day>
<Hour>0</Hour>
<Minute>1</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez">
<Year>1969</Year>
<Month>4</Month>
<Day>1</Day>
<Hour>0</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList>
<ArticleId IdType="pubmed">5819388</ArticleId>
<ArticleId IdType="pii">69020084</ArticleId>
</ArticleIdList>
</PubmedData>
</PubmedArticle>
</PubmedArticleSet>
这是违规部分代码（仅限）。如果此摘录有轻微的语法错误或2，请原谅我。提前感谢任何/所有建议。我希望这里的解决方案对任何其他欺负PubMed for JBosses的人都有用。
##########################
# PUBMED XML TO DATAFRAME
########################
library(XML)
library(reshape)
# initializes save path to XML files
dir <- paste0("pubmed_",input.dir)
myxml.path = file.path(dir, dir(dir, ".xml"))
## function to process xml files in the given save path
pub.data <- lapply(myxml.path, function(x){
myxml <- xmlParse(x, useInternalNodes = TRUE)
## function(s) to pad XML columns with ""
padXML <-function(x,xstr){
res<-xpathSApply(x,xstr,xmlValue)
if(length(res)==0){
out<-""
}else{
out<-res
}
out
}
# padXML <-function(x, xstr){
# res <- xpathSApply(x, xstr, xmlValue)
# ifelse(try(length(res)==0, silent=TRUE), "NA",
# ifelse(length(res)==0, "",
# ifelse(length(res)>1, paste(res, collapse=", "), res)))
# }
# padXML <-function(x, xstr){
# res <- tryCatch(xpathSApply(x, xstr, xmlValue), error=function(e) print(""))
# return(res)
# }
## Extract XML paths
PMID <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./PMID/text()')
ArticleTitle <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./Article[1]/ArticleTitle[1]/text()')
DateCreated <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./DateCreated/Year/text()')
Keyword1 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[1]/text()')
Keyword2 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[2]/text()')
Keyword3 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[3]/text()')
## builds dataframe from extracted XML paths
pub.data <- data.frame(
PMID,
DateCreated,
ArticleTitle,
Keyword1,
Keyword2,
Keyword3,
stringsAsFactors=FALSE)
})
pub.data <- merge_all(pub.data)
return(pub.data)
参考文献：
答案 0 :(得分：1)
评论太长了。 [如果人们认为这太难以回答（我倾向于认为它可能......），我会删除它。]
所以问题是拼写错误（见评论）。这只是编程实践的一个注释。排除赋值语句（尽可能多），所以：
ArticleTitle <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./Article[1]/ArticleTitle[1]/text()')
DateCreated <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./DateCreated/Year/text()')
Keyword1 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[1]/text()')
Keyword2 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[2]/text()')
Keyword3 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[3]/text()')
而不是：
ArticleTitle <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./Article[1]/ArticleTitle[1]/text()')
DateCreated <- xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./DateCreated/Year/text()')
Keyword1 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[1]/text()')
Keyword2 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[2]/text()')
Keyword3 < - xpathSApply(myxml,"//*/MedlineCitation",padXML,xstr='./KeywordList[1]/Keyword[3]/text()')
使这种类型的错误真的流行起来。