如何解决如何限制“ grepl”功能仅在一个列中搜索字符串?
我正在处理一个非常大的数据集,并尝试使用grepl
函数从47个中的仅一列(变量)中提取一个小的字符串。这是我使用的代码,
x<-ebd_whbnut_relJun.2020[grepl("migrat",ebd_whbnut_relJun.2020[["SPECIES.COMMENTS"]]),]
我试图从 only 列“ SPECIES.COMMENTS”中提取字符串“ migrat”的所有内容。文件名“ ebd_whbnut_relJun.2020”。
我运行了代码并收到了49条记录,但它以“ 49 obs。of 47 variables”的形式返回。一些条目仅包含来自正确列的条目,而其他条目显然包含来自许多其他列的信息。因此,我无法将数据导出到Excel并给出错误消息“ libxlsxwriter中的错误:'字符串超出Excel的32,767个字符的限制。”
这是grepl函数的原始工具,还是太广泛了?或者它像缺少逗号/括号一样简单?
解决方法
我将使用diamonds
中的ggplot2
数据集来演示一些技术(尽管否则不需要该软件包)。
data("diamonds",package = "ggplot2")
dat <- as.data.frame(head(diamonds))
dat
# carat cut color clarity depth table price x y z
# 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
# 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
# 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
# 4 0.29 Premium I VS2 62.4 58 334 4.20 4.23 2.63
# 5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
# 6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48
grep("Good",dat$cut,value = TRUE)
# [1] "Good" "Good" "Very Good"
dat$cut[ grepl("Good",dat$cut) ]
# [1] Good Good Very Good
# Levels: Fair < Good < Very Good < Premium < Ideal
dat[ grepl("Good",dat$cut),"cut" ]
# [1] Good Good Very Good
# Levels: Fair < Good < Very Good < Premium < Ideal
请注意,如果您使用的是tbl_df
或data.table
,则列选择的行为会有所不同:
as_tibble(dat)[ grepl("Good","cut" ]
# # A tibble: 3 x 1
# cut
# <ord>
# 1 Good
# 2 Good
# 3 Very Good
as.data.table(dat)[ grepl("Good","cut" ]
# cut
# 1: Good
# 2: Good
# 3: Very Good
实际上,您也可以在基数R中模拟这一点,这也可以建议一种解决方法:
dat[ grepl("Good","cut",drop = FALSE ]
# cut
# 3 Good
# 5 Good
# 6 Very Good
as_tibble(dat)[ grepl("Good",drop = TRUE ]
# [1] Good Good Very Good
# Levels: Fair < Good < Very Good < Premium < Ideal
data.table
有点不同,但是如果您尝试尝试,那么您已经知道:
as.data.table(dat)[ grepl("Good",cut),cut ]
# [1] Good Good Very Good
# Levels: Fair < Good < Very Good < Premium < Ideal
数据,以防您没有ggplot2
:
structure(list(carat = c(0.23,0.21,0.23,0.29,0.31,0.24),cut = structure(c(5L,4L,2L,3L),.Label = c("Fair","Good","Very Good","Premium","Ideal"),class = c("ordered","factor")),color = structure(c(2L,6L,7L,7L),.Label = c("D","E","F","G","H","I","J"),"factor"
)),clarity = structure(c(2L,3L,5L,6L),.Label = c("I1","SI2","SI1","VS2","VS1","VVS2","VVS1","IF"),depth = c(61.5,59.8,56.9,62.4,63.3,62.8),table = c(55,61,65,58,57),price = c(326L,326L,327L,334L,335L,336L),x = c(3.95,3.89,4.05,4.2,4.34,3.94),y = c(3.98,3.84,4.07,4.23,4.35,3.96),z = c(2.43,2.31,2.63,2.75,2.48)),row.names = c(NA,-6L),class = "data.frame")
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