Pattern Searching in R - r

Question

I have two data frames as below. DF1 is slighly messy (as you can see below) has multiple values from DF2 combined into one column.
DF1
SRNo. Value
1 1ABCD2EFGH3IJKL
2 1ABCD2EFGH3IJKL/7MLPO0OKMN8MNBV
3 3ABCD4EFGH5IJKL
4 3ABCD4EFGH5IJKL/1ABCD2EFGH3IJKL
5 7MLPO0OKMN8MNBV/9IUYT7HGFD3LKJH
DF2
SRNo. Value
1 1ABCD2EFGH3IJKL
2 3ABCD4EFGH5IJKL
3 6PQRS7TUVW8XYZA
4 5FGHI9XUZX1RATP
5 9AGTY6UGFW0AAUU
6 6TEYD7RARA8MHAT
7 9IUYT7HGFD3LKJH
I want to do a look up using values column in both the data set. Here is what I am trying to accomplish.
i) For rows 1 & 3 in DF1 it is a simple look up in DF2. I expect the code to return those looked up values.
ii) For row #3 in DF1, only first part of the string matches with a value in DF2. I expect the code to return only the first part.
iii) For row#4 in DF1, both the parts in the string matches with values in DF2. In this case I want the first part of the string that is matching to be retained
iv) For Row #5, the second part in the string matches with the value in DF2. I would expect the code to return the 2nd part of the string.
I have around 47000 rows in first dataset and over 300,000 in second dataset and ofcourse there are other columns in both the datasets. I have tried this in multiple ways using str_split/str_match but could not accomplish what I want to. Every suggestion is appreciated. My rest of the coding is in R.
Thank You

Answer 1

First step is to tidyr::separate() your DF1 at "/". Then I used dplyr::case_when() to see if there was a match between the first of the listed items in DF2 with %in%; if there wasn't then check against the second. I used dplyr::mutate() to append the results to DF1 under dat.
library(dplyr)
library(tidyr)
DF1 <- data.frame("SRNo." = 1:5, Value = c("1ABCD2EFGH3IJKL","1ABCD2EFGH3IJKL/7MLPO0OKMN8MNBV","3ABCD4EFGH5IJKL","3ABCD4EFGH5IJKL/1ABCD2EFGH3IJKL","7MLPO0OKMN8MNBV/9IUYT7HGFD3LKJH"), stringsAsFactors = F) %>% tbl_df()
DF2 <- data.frame("SRNo." = 1:7, Value = c("1ABCD2EFGH3IJKL","3ABCD4EFGH5IJKL","6PQRS7TUVW8XYZA","5FGHI9XUZX1RATP","9AGTY6UGFW0AAUU","6TEYD7RARA8MHAT","9IUYT7HGFD3LKJH"), stringsAsFactors = F) %>%tbl_df()
DF1 %>%
separate(Value, c("Value1", "Value2"), sep = "/") %>%
mutate(dat = case_when(
Value1 %in% DF2$Value ~ Value1,
Value2 %in% DF2$Value ~ Value2,
TRUE ~ NA_character_
))
# # A tibble: 5 x 4
# SRNo. Value1 Value2 dat
# <int> <chr> <chr> <chr>
# 1 1 1ABCD2EFGH3IJKL NA 1ABCD2EFGH3IJKL
# 2 2 1ABCD2EFGH3IJKL 7MLPO0OKMN8MNBV 1ABCD2EFGH3IJKL
# 3 3 3ABCD4EFGH5IJKL NA 3ABCD4EFGH5IJKL
# 4 4 3ABCD4EFGH5IJKL 1ABCD2EFGH3IJKL 3ABCD4EFGH5IJKL
# 5 5 7MLPO0OKMN8MNBV 9IUYT7HGFD3LKJH 9IUYT7HGFD3LKJH

Answer 2

Data.table solution
df1 <- read.table(text="SRNo. Value
1 1ABCD2EFGH3IJKL
2 1ABCD2EFGH3IJKL/7MLPO0OKMN8MNBV
3 3ABCD4EFGH5IJKL
4 3ABCD4EFGH5IJKL/1ABCD2EFGH3IJKL
5 7MLPO0OKMN8MNBV/9IUYT7HGFD3LKJH", header = T, stringsAsFactors = F)
df2 <- read.table( text = "SRNo. Value
1 1ABCD2EFGH3IJKL
2 3ABCD4EFGH5IJKL
3 6PQRS7TUVW8XYZA
4 5FGHI9XUZX1RATP
5 9AGTY6UGFW0AAUU
6 6TEYD7RARA8MHAT
7 9IUYT7HGFD3LKJH", header = T, stringsAsFactors = F )
library( data.table )
setDT(df1)[, c( "Value1", "Value2" ) := tstrsplit( Value, "/", fixed = TRUE)]
setDT(df2)
resultv1 <- df2[ df1, on = c( Value = "Value1"), nomatch = 0L ]
resultv2 <- df2[ df1, on = c( Value = "Value2"), nomatch = 0L ]
result <- rbindlist( list( resultv1, resultv2 ) )[!duplicated( i.SRNo.)]
Benchmarking it against the solution from #Paul shows similar runtimes (~2.5 miliseconds).. But data.table sometimes surprises me on larger data-sets..
If memory becomes an issue, you can do it all in one go:
rbindlist( list( setDT(df2)[ setDT(df1)[, c( "Value1", "Value2" ) := tstrsplit( Value, "/", fixed = TRUE)],
on = c( Value = "Value1"), nomatch = 0L ],
setDT(df2)[ setDT(df1)[, c( "Value1", "Value2" ) := tstrsplit( Value, "/", fixed = TRUE)],
on = c( Value = "Value2"), nomatch = 0L ] ) )[!duplicated( i.SRNo.)]