我有這個：
col1
1234HO
9535KU
4532SP
1
hello
xyz
1206
9530OK
23
8524US
我需要它是這樣的：
col1 col2 col3
1234HO 1234 HO
9535KU 9535 KU
4532SP 4532 SP
#these rows still need to be there
1206 1206 #keep in mind that I still want to keep this if there is 4 numbers
9530OK 9530 OK
8524US 8524 US
我嘗試手動洗掉它，但它有點太多的作業。我不知道如何制作一個功能，上面寫著“洗掉所有不以 4 個數字開頭的文本”。如果它們都是相同的數字，我只會知道該怎么做，但它們可以是任何數字。
uj5u.com熱心網友回復：
這是一種dplyr正則運算式級別非常低的方法。
輸入
# your df
df <- read.table(header = T, text = "
col1
1234HO
9535KU
4532SP
1
hello
xyz
1206
9530OK
23
8524US")
空行
library(dplyr)
df %>% mutate(col2 = str_extract(col1, "^[0-9]{4,}"),
col3 = str_extract(col1, "[A-Z].*$"),
col3 = replace_na(col3, ""),
across(everything(), ~ifelse(grepl("^[0-9]{4}", col1), .x, print(""))))
col1 col2 col3
1 1234HO 1234 HO
2 9535KU 9535 KU
3 4532SP 4532 SP
4
5
6
7 1206 1206
8 9530OK 9530 OK
9
10 8524US 8524 US
行為 NA
# if you want them to be filled with NA
df %>% mutate(col2 = str_extract(col1, "^[0-9]{4,}"),
col3 = str_extract(col1, "[A-Z].*$"),
across(everything(), ~ifelse(grepl("^[0-9]{4}", col1), .x, NA)))
col1 col2 col3
1 1234HO 1234 HO
2 9535KU 9535 KU
3 4532SP 4532 SP
4 <NA> <NA> <NA>
5 <NA> <NA> <NA>
6 <NA> <NA> <NA>
7 1206 1206 <NA>
8 9530OK 9530 OK
9 <NA> <NA> <NA>
10 8524US 8524 US
uj5u.com熱心網友回復：
您可以使用tidyr::separate然后filter.
library(dplyr)
library(tidyr)
dat %>%
separate(col1, into = c("num", "text"), sep = "(?<=[0-9])(?=[A-Za-z])", remove = F) %>%
filter(!grepl("[A-Za-z]", num) & nchar(num) > 3)
col1 num text
1 1234HO 1234 HO
2 9535KU 9535 KU
3 4532SP 4532 SP
4 1206 1206 <NA>
5 9530OK 9530 OK
6 8524US 8524 US
uj5u.com熱心網友回復：
另一種可能的解決方案：
library(tidyverse)
df <- data.frame(
stringsAsFactors = FALSE,
col1 = c("1234HO","9535KU",
"4532SP","1","hello","xyz","1206","9530OK","23",
"8524US")
)
df %>%
separate(col1, into=str_c("col", 2:3), sep="(?<=\\d{4})",
remove = F, fill = "right") %>% filter(!is.na(col3))
#> col1 col2 col3
#> 1 1234HO 1234 HO
#> 2 9535KU 9535 KU
#> 3 4532SP 4532 SP
#> 4 1206 1206
#> 5 9530OK 9530 OK
#> 6 8524US 8524 US
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