我正在使用R连接到WRDS。现在,我想链接compustat和crsp表。在SAS中,这将使用宏和CCM链接表来实现。在R中处理这个主题的最好方法是什么?
进度更新:
我从wrds下载了crsp,compustat和ccm_link表。
sql <- "select * from CRSP.CCMXPF_LINKTABLE"
res <- dbSendQuery(wrds, sql)
ccmxpf_linktable <- fetch(res, n = -1)
ccm.dt <- data.table(ccmxpf_linktable)
rm(ccmxpf_linktable)
然后,我将建议的匹配例程从wrds事件研究sas文件转换为R:
ccm.dt[,typeflag:=linktype %in% c("LU","LC","LD","LN","LS","LX") & USEDFLAG=="1"]
setkey(ccm.dt, gvkey, typeflag)
for (i in 1:nrow(compu.dt)) {
gvkey.comp = compu.dt[i, gvkey]
endfyr.comp = compu.dt[i,endfyr]
PERMNO.val <- ccm.dt[.(gvkey.comp, TRUE),][linkdt<=endfyr.comp & endfyr.comp<=linkenddt,lpermno]
if (length(PERMNO.val)==0) PERMNO.val <- NA
suppressWarnings(compu.dt[i, "PERMNO"] <- PERMNO.val)
}
然而,这段代码的效率非常低。我从data.table开始,但并不真正理解如何应用for循环中的逻辑。我希望一些人能给我指出如何改进for循环的方法。
发布于 2016-01-17 07:15:26
在阶段中匹配字段效果更好。也许有人会觉得这很有用。当然,我们非常欢迎任何关于进一步改进的建议!
# filter on ccm.dt
ccm.dt <- ccm.dt[linktype %in% c("LU","LC","LD","LN","LS","LX") & USEDFLAG=="1"]
setkey(ccm.dt, gvkey)
setkey(compu.dt, gvkey)
compu.merged <- merge(compu.dt, ccm.dt, all.x = TRUE, allow.cartesian = TRUE)
# deal with NAs in linkenddt - set NAs to todays date, assuming they still exist.
today <- as.character(Sys.Date())
compu.merged[is.na(linkenddt), "linkenddt":=today]
# filter out date mismatches
compu <- compu.merged[linkdt <= endfyr & endfyr<=linkenddt]
https://stackoverflow.com/questions/34822178
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