我有一个如下数据集:
Country Region Molecule Item Code
IND NA PB102 FR206985511
THAI AP PB103 BA-107603 / F000113361 / 107603
LUXE NA PB105 1012701 / SGP-1012701 / F041701000
IND AP PB106 AU206985211 / CA-F206985211
THAI HP PB107 F034702000 / 1010701 / SGP-1010701
BANG NA PB108 F000007970/25781/20009021
我想基于ITEMCODE
的{{1}}列中的字符串值进行拆分,并为每个条目创建一个新行。
例如,所需的输出将是:
/
我尝试了以下代码
Country Region Molecule Item.Code
IND NA PB102 FR206985511
THAI AP PB103 BA-107603
THAI AP PB103 F000113361
THAI AP PB103 107603
LUXE NA PB105 1012701
LUXE NA PB105 SGP-1012701
LUXE NA PB105 F041701000
IND AP PB106 AU206985211
IND AP PB106 CA-F206985211
THAI HP PB107 F034702000
THAI HP PB107 1010701
THAI HP PB107 SGP-1010701
BANG NA PB108 F000007970
BANG NA PB108 25781
BANG NA PB108 20009021
但得到了错误
library(splitstackshape)
df2=concat.split.multiple(df1,"Plant.Item.Code","/", direction="long")
当我尝试"Error: memory exhausted (limit reached?)"
时,我收到以下错误消息。
strsplit()
答案 0 :(得分:16)
尝试使用cSplit
函数(因为您已经使用了@Anandas包)。请注意,它将返回data.table
对象,因此请确保已安装此软件包。您可以通过data.frame
setDF(df2)
(如果您愿意)
library(splitstackshape)
df2 <- cSplit(df1, "Item.Code", sep = "/", direction = "long")
df2
# Country Region Molecule Item.Code
# 1: IND NA PB102 FR206985511
# 2: THAI AP PB103 BA-107603
# 3: THAI AP PB103 F000113361
# 4: THAI AP PB103 107603
# 5: LUXE NA PB105 1012701
# 6: LUXE NA PB105 SGP-1012701
# 7: LUXE NA PB105 F041701000
# 8: IND AP PB106 AU206985211
# 9: IND AP PB106 CA-F206985211
# 10: THAI HP PB107 F034702000
# 11: THAI HP PB107 1010701
# 12: THAI HP PB107 SGP-1010701
# 13: BANG NA PB108 F000007970
# 14: BANG NA PB108 25781
# 15: BANG NA PB108 20009021
答案 1 :(得分:6)
基础R中的另一种方法:
as.data.frame(do.call(rbind, apply(df1, 1, function(x) {
do.call(expand.grid, strsplit(x, " */ *"))
})))
结果:
Country Region Molecule Item.Code
1 IND <NA> PB102 FR206985511
2 THAI AP PB103 BA-107603
3 THAI AP PB103 F000113361
4 THAI AP PB103 107603
5 LUXE <NA> PB105 1012701
6 LUXE <NA> PB105 SGP-1012701
7 LUXE <NA> PB105 F041701000
8 IND AP PB106 AU206985211
9 IND AP PB106 CA-F206985211
10 THAI HP PB107 F034702000
11 THAI HP PB107 1010701
12 THAI HP PB107 SGP-1010701
13 BANG <NA> PB108 F000007970
14 BANG <NA> PB108 25781
15 BANG <NA> PB108 20009021
答案 2 :(得分:2)
尝试这样的事情
d <- structure(list(Country = c("A", "B", "C"), `Item Code` = c("FR206985511",
"BA-107603/F000113361/107603", "1012701/SGP-1012701/F041701000")),
.Names = c("Country", "Item Code"), row.names = c(NA, -3L),
class = "data.frame")
d
# Country Item code
# A FR206985511
# B BA-107603/F000113361/107603
# C 1012701/SGP-1012701/F041701000
codes <- strsplit(d$"Item Code", "/")
code.lengths <- sapply(codes, length)
new.d <- d[rep(1:nrow(d), code.lengths), ]
new.d$"Item Code" <- unlist(codes)
new.d
# Country Item Code
#1 A FR206985511
#2 B BA-107603
#2.1 B F000113361
#2.2 B 107603
#3 C 1012701
#3.1 C SGP-1012701
#3.2 C F041701000
如果你想摆脱空间(你的原始数据似乎包含),你可以通过d$"Item Code" <- gsub(" ", "", d$"Item Code")