从一个可恶的当地政府网站下载了一堆数据.有77,000个项目条目看起来与以下内容完全相同,包含在纯文本文件中.我需要将这堆粪便导入R作为数据框：
Instrument: 201301240005447 Recorded: 01/24/2013 Consideration: $150,125.00 Document Type: MORTGAGES Pages: 17 Grantor: BYRES,CONNIE R / BYRES,SCOTT Grantee: MORTGAGE ELECTRONIC REGISTRATION SYSTEMS INC / QUICKEN LOANS INC Legal Description: * St:5495 MCNAMARA LN City:FLINT PrpId:1135532002 CC:11 T:8 R:7 S:35 ext:PT OF NE4 * ---------------------------------/--------------------------------- Instrument: 201301240005408 Recorded: 01/24/2013 Consideration: $65,124.00 Document Type: MORTGAGES Pages: 17 Grantor: SANNE,BETTY LOU / SANNE,KENNETH D Grantee: JPMORGAN CHASE BANK NA Legal Description: Sub:WOODCROFT NO 1 Lt:188 St:2213 RADCLIFFE AVE City:FLINT PrpId:4024106003 CC:54 * ---------------------------------/---------------------------------
有一些常用的字符向量,如“Instrument”,“Grantor”和“PrpId”.我究竟如何将其导入R？这会涉及解析或刮取某种类型吗？
不用说,我试图将此文件导入Excel但无法正常工作.我认为R会更好地工作,只需要弄清楚如何.谢谢
解决方法
我编写了一个非常通用的解析函数,可以处理@R_502_411@和字段值分隔符的任何模式,指定为参数化正则表达式.它还可以选择从字段值中删除尾随空格,并将可变参数传递给构建结果data.frame的单个data.frame()调用.
sectionedFieldLinesToFrame <- function(lines,divRE,sepRE,select,rtw=T,...) {
divLineIndexes <- grep(perl=T,lines);
## remove possible leading and trailing divs,for robustness
if (length(divLineIndexes)>0L && divLineIndexes[1L]==1L) {
leadDivCount <- match(T,c(diff(divLineIndexes)!=1L,T));
lines <- lines[-seq_len(leadDivCount)];
divLineIndexes <- divLineIndexes[-seq_len(leadDivCount)]-leadDivCount;
}; ## end if
if (length(divLineIndexes)>0L && divLineIndexes[length(divLineIndexes)]==length(lines)) {
trailDivCount <- match(T,c(rev(diff(divLineIndexes)!=1L),T));
lines <- lines[-seq(to=length(lines),len=trailDivCount)];
divLineIndexes <- divLineIndexes[-seq(to=length(divLineIndexes),len=trailDivCount)];
}; ## end if
## get fields to extract
if (missing(select)) {
allFieldLineIndexes <- grep(perl=T,lines);
fields <- unique(sub(perl=T,paste0(sepRE,'.*'),'',lines[allFieldLineIndexes]));
} else {
fields <- select;
}; ## end if
## extract each field vector and build the data.frame
do.call(data.frame,c(setNames(lapply(fields,function(field) {
fieldLineIndexes <- grep(perl=T,paste0('^\\Q',field,'\\E',sepRE),lines);
sectionIndexes <- findInterval(fieldLineIndexes,divLineIndexes); ## 0-based
values <- sub(perl=T,paste0('^.*?',lines[fieldLineIndexes]);
if (rtw) values <- sub(perl=T,'\\s+$',values);
values[match(seq(0L,length(divLineIndexes)),sectionIndexes)];
}),fields),...));
}; ## end sectionedFieldLinesToFrame()
以下是如何使用它：
fileName <- 'data.txt'; divRE <- '^-+/-+$'; sepRE <- ':\\s*'; df <- sectionedFieldLinesToFrame(readLines(fileName),stringsAsFactors=F); str(df); ## 'data.frame': 2 obs. of 8 variables: ## $Instrument : chr "201301240005447" "201301240005408" ## $Recorded : chr "01/24/2013" "01/24/2013" ## $Consideration : chr "$150,125.00" "$65,124.00" ## $Document.Type : chr "MORTGAGES" "MORTGAGES" ## $Pages : chr "17" "17" ## $Grantor : chr "BYRES,SCOTT" "SANNE,KENNETH D" ## $Grantee : chr "MORTGAGE ELECTRONIC REGISTRATION SYSTEMS INC / QUICKEN LOANS INC" "JPMORGAN CHASE BANK NA" ## $Legal.Description: chr "* St:5495 MCNAMARA LN City:FLINT PrpId:1135532002 CC:11 T:8 R:7 S:35 ext:PT OF NE4" "Sub:WOODCROFT NO 1 Lt:188 St:2213 RADCLIFFE AVE City:FLINT PrpId:4024106003 CC:54"
您还可以指定select参数以准确选择要提取的字段：
select <- c('Instrument','Pages','Grantor');
df <- sectionedFieldLinesToFrame(readLines(fileName),stringsAsFactors=F);
df;
## Instrument Pages Grantor
## 1 201301240005447 17 BYRES,SCOTT
## 2 201301240005408 17 SANNE,KENNETH D
我已经尽力使其尽可能健壮.它仔细处理可能的冗余前导和尾随@R_502_411@,并正确处理节之间不一致字段的情况.
值得强调的是最后一点.所提供的所有其他解决方案对输入数据做出了非常脆弱的假设,要么每个部分恰好有8个字段始终以相同的顺序,要么每个部分都出现每个(可能是硬编码的)字段名称.如果违反了这个假设,那些解决方案就变得毫无用处.我的函数不对字段编号,名称或一致性做出任何假设.它动态检索任何部分中存在的所有字段名称,并构建每个字段的正确向量,生成NA元素,其中字段不存在于给定部分中.
这里有些例子：
sectionedFieldLinesToFrame(character(),'^-$',':');
## data frame with 0 columns and 0 rows
sectionedFieldLinesToFrame(rep('-',2L),':');
## data frame with 0 columns and 0 rows
sectionedFieldLinesToFrame(c('A:a','-'),':');
## A
## 1 a
sectionedFieldLinesToFrame(c('A:a','-','B:b',':');
## A B
## 1 a <NA>
## 2 <NA> b
sectionedFieldLinesToFrame(c('A:a','B:c',':');
## A B
## 1 a b
## 2 <NA> c
sectionedFieldLinesToFrame(c('A:a','A:d'),':');
## A B
## 1 a b
## 2 <NA> c
## 3 d <NA>
sectionedFieldLinesToFrame(c('-','A:a','A:d','C:e',':');
## A B C
## 1 a b <NA>
## 2 <NA> c <NA>
## 3 d <NA> e
sectionedFieldLinesToFrame(c('-',':');
## A B C
## 1 a b <NA>
## 2 <NA> <NA> <NA>
## 3 <NA> c <NA>
## 4 d <NA> e
