Oze*_*uss 2 grep r string-matching data.table
DT <- data.table(num=c("20031111","1112003","23423","2222004"),y=c("2003","2003","2003","2004"))
> DT
num y
1: 20031111 2003
2: 1112003 2003
3: 23423 2003
4: 2222004 2004
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我想比较两个单元格内容,并根据布尔值执行操作.例如,如果"num"与年份匹配,则创建一个包含该值的列x.我考虑过基于grep的子集化,这是有效的,但每次都会自然检查整个列,这看起来很浪费
DT[grep(y,num)] # works with a pattern>1 warning
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我可以申请()我的方式,但也许有一个data.table方式?
谢谢
如果您对使用该stringi
软件包感到满意,这是一种利用stringi
函数向量化图形和字符串这一事实的方法:
DT[stri_detect_fixed(num, y), x := num])
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根据数据,它可能比Veerenda Gadekar发布的方法更快.
DT <- data.table(num=paste0(sample(1000), sample(2001:2010, 1000, TRUE)),
y=as.character(sample(2001:2010, 1000, TRUE)))
microbenchmark(
vg = DT[, x := grep(y, num, value=TRUE, fixed=TRUE), by = .(num, y)],
nk = DT[stri_detect_fixed(num, y), x := num]
)
#Unit: microseconds
# expr min lq mean median uq max neval
# vg 6027.674 6176.397 6513.860 6278.689 6370.789 9590.398 100
# nk 975.260 1007.591 1116.594 1047.334 1110.734 3833.051 100
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