对 dataframe 中的列执行一系列突变

Question

I am trying to replace some text in my dataframe (a few rows given below)

> dput(Henry.longer[1:4,])
structure(list(N_l = c(4, 4, 4, 4), UG = c("100", "100", "100", 
"100"), S = c(12, 12, 12, 12), Sample = c(NA, NA, NA, NA), EQ = c("Henry", 
"Henry", "Henry", "Henry"), DF = c(0.798545454545455, 0.798545454545455, 
0.798545454545455, 0.798545454545455), meow = c("Henry.Exterior.single", 
"Multi", "Henry.Exterior.multi", "Henry.Interior.single"), Girder =     c("Henry.Exterior.single", 
"Henry.Interior.multi", "Henry.Exterior.multi", "Interior")), row.names = c(NA, 
-4L), groups = structure(list(UG = "100", S = 12, .rows = list(
1:4)), row.names = c(NA, -1L), class = c("tbl_df", "tbl", 
"data.frame"), .drop = FALSE), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"))

I try to mutate the dataframe as:

Henry.longer <- Henry.longer %>% 
  mutate(Loading = str_replace(meow, "Henry.Exterior.single", "Single")) %>%
  mutate(Loading = str_replace(meow, "Henry.Exterior.multi", "Multi")) %>%
  mutate(Loading = str_replace(meow, "Henry.Interior.single", "Single")) %>%
  mutate(Loading = str_replace(meow, "Henry.Interior.multi", "Multi")) %>%
  mutate(Girder = str_replace(meow, "Henry.Exterior.multi", "Exterior")) %>%
  mutate(Girder = str_replace(meow, "Henry.Exterior.single", "Exterior")) %>%
  mutate(Girder = str_replace(meow, "Henry.Interior.multi", "Interior")) %>%
  mutate(Girder = str_replace(meow, "Henry.Interior.single", "Interior")) %>%
  select(-meow)

But for some reason the results does not get applied to all the rows and only:

      N_l UG        S Sample EQ       DF Loading               Girder               
1     4 100      12 NA     Henry 0.799 Henry.Exterior.single Henry.Exterior.single
2     4 100      12 NA     Henry 0.799 Multi                 Henry.Interior.multi 
3     4 100      12 NA     Henry 0.799 Henry.Exterior.multi  Henry.Exterior.multi 
4     4 100      12 NA     Henry 0.799 Henry.Interior.single Interior

Answer 1

I think we can use lookup vectors for this, if it's easy or safer to use static string lookups:

tr_vec <- c(Henry.Exterior.single = "Single", Henry.Exterior.multi = "Multi", Henry.Interior.single = "Single", Henry.Interior.multi = "Multi")
tr_vec2 <- c(Henry.Exterior.multi = "Exterior", Henry.Exterior.single = "Exterior", Henry.Interior.multi = "Interior", Henry.Interior.single = "Interior")
Henry.longer %>%
  mutate(
    Loading = coalesce(tr_vec[Loading], Loading),
    Girder = coalesce(tr_vec2[Girder], Girder)
  )
# # A tibble: 4 x 8
# # Groups:   UG, S [1]
#     N_l UG        S Sample EQ       DF Loading Girder  
#   <dbl> <chr> <dbl> <lgl>  <chr> <dbl> <chr>   <chr>   
# 1     4 100      12 NA     Henry 0.799 Single  Exterior
# 2     4 100      12 NA     Henry 0.799 Multi   Interior
# 3     4 100      12 NA     Henry 0.799 Multi   Exterior
# 4     4 100      12 NA     Henry 0.799 Single  Interior

The advantage of RonakShah's regex solution is that it can very easily handle many of the types of substrings you appear to need. Regexes do carry a little risk, though, in that they may (unlikely in that answer, but) miss match.

Answer 2

Instead of using str_replace I guess it would be easier to extract what you want using regex.

library(dplyr)

Henry.longer %>%
  mutate(Loading = sub('.*\\.', '', meow), 
         Girder = sub('.*\\.(\\w+)\\..*', '\\1', meow))

where

Loading - removes everything until last dot

Girder - extracts a word between two dots.

Answer 3

Oh boy, looks like you've got some answers here already but here's a super-simple one that uses stringr::str_extract :

Henry.longer <- Henry.longer %>%
  mutate(Loading = str_extract(meow, "single|multi")) %>%
  mutate(Girder = str_extract(meow, "Interior|Exterior"))

It's worth noting that the demo data has a weird entry for meow in one column, so it didn't run perfectly on my machine: