针对你的需求，我们可以利用data.table的高效语法结合字符长度函数来实现。这里提供两种简洁的方法，兼顾代码简洁性和可读性：

方法一：一行式条件替换（含去空格处理） #

原数据里部分字符串带有前后空格，这些空格会干扰长度计算，所以先通过trimws()去除首尾空格，再做条件判断：

library(data.table)

# 加载你的数据集
dt <- data.table(col1 = c("PFCB ", "TEVA TEVATV ", "PLCE ", "", "Nasdaq NEI", "DE ", "SHPLN ", "", "WMT ", "ADBE ", "HPY ", "NASDAQ PRTS", "", "BEBE ", "PPC ", "Updates with additional background information", "CLWR ", "SRX ", "Nasdaq ATVI ", "QLTY ", "AMKR ", " AA ", "ED ", "", "", "SLE", "RBNF ", "FIC ", "1135 GMT ", "FROM BARRONS 111813 ", "Nasdaq DEIX ", "", "", "Updates throughout with CEO comments details on results", "Adds news on Qualcomm F5 Networks Semitool and Celadon Group updates stock prices ", "BUSINESS WIRE ", "CXW ", "HOTT ", "BAYNXE", "ICUI ", "", "TI ", "BKC ", "", "BUSINESS WIRE ", "B", "", "WBMD ", "AGIX ", "BCSI ", "ASGN ", "TUNE ", "", "AIR ", "ETRM ", "MDCO ", "DBTK ", "ROST ", "", "Nasdaq SOMX", "PRXL ", "", "SCVL ", "BUSINESS WIRE ", "", "OTC Bulletin Board SBNK ", "", "Updates to include details on planned store openings and new stock quote", "NASDAQINO ", "", "2008 GMT ", "", "ATRC ", "Updates share prices in the 14th and 15th paragraphs adds Medco statistics on Plavix in the 16th paragraph ", "", "", "NASDAQJASN ", "olivergriffindowjonescom OliGGriffin", "QCOM ", "ITW ", "NYSE LITB ", "PENN ", "BWA ", "Select Medical ", "TQNT ", "SYD ", "IM ", "YHOO ", "TOO ", "", "FO", "", "SMG ", "", "Bunge 3Q Profit Drops 86 On Charges As Revenue Rises published at 659 am EDT mischaracterized comments on the companys outlook A corrected story follows", "GSOL ", "TGT ", "URI ", "", "PX "))

# 核心处理逻辑
dt[ , col1 := ifelse(nchar(trimws(col1)) > 5, "", trimws(col1))]

方法二：分步处理（更直观的data.table风格） #

如果你偏好更清晰的分步操作，可以先统一清理空格，再通过逻辑索引精准替换目标值：

# 第一步：去除所有字符串的首尾空格
dt[ , col1 := trimws(col1)]

# 第二步：筛选出字符长度>5的行，将col1设为空字符串
dt[nchar(col1) > 5, col1 := ""]

验证结果 #

执行完代码后，用head(dt)查看前几行，完全符合你的预期：

head(dt)
#    col1
# 1: PFCB
# 2:     
# 3: PLCE
# 4:     
# 5:     
# 6:   DE

关键细节说明 #

• trimws()：必须优先处理前后空格，否则像"TEVA TEVATV "这类带尾空格的字符串，长度会被误判，导致替换逻辑出错。
• nchar()：R中计算字符长度的基础函数，直接返回字符串的字符数。
• data.table的:=赋值：这是data.table高效修改列的核心，直接在原数据集上修改，无需复制整个数据，性能远优于普通data.frame的修改方式。

内容的提问来源于stack exchange，提问作者user8959427