Is there a R function to strsplit specifc rows under one column based on another column?-CodePudding

I am having a data frame (for example as below:

name  student_id   age  gender
Sam   123_abc_ABC  20   F
John  234_bcd_BCD  18   M
Mark  345_cde_CDE  20   M
Ram   xyz_111_XYZ  19   M
Hari  uvw_444_UVW  23   M

Now, I need a new column as student_id_by_govt in the df. The student_id_by_govt is within the student_id but it is different for different names. For Sam, John, Mark the student_id_by_govt would be first segment of student_id (i.e., 123, 234, 345) but for Ram & Hari, the student_id_by_govt is second segment in the student_id (i.e.,111, 444).

I used the strsplit, lapply commands to get the specfic segment from the student_id but I could not able to apply that command specifically for specific rows to get the desired output mentioned above. Please let me know how to get the output as below:

name  student_id   age  gender student_id_by_govt
Sam   123_abc_ABC  20   F      123
John  234_bcd_BCD  18   M      234
Mark  345_cde_CDE  20   M      345
Ram   xyz_111_XYZ  19   M      111
Hari  uvw_444_UVW  23   M      444

CodePudding user response：

You can use regex via the function str_extract from the library stringr:

library(dplyr)
library(stringr)
library(purrr)

df <- tibble(Name = c("Sam", "John", "Mark", "Ram", "Hari"), student_id = c("123_abc_ABC", "234_bcd_BCD", "345_cde_CDE", "xyz_111_XYZ", "uvw_444_UVW")) %>%
      mutate(student_id_by_gvt = map_chr(student_id, function(x){str_extract(x, "(\\d )")}))

Here is the output:

# A tibble: 5 x 3
  Name  student_id  student_id_by_gvt
  <chr> <chr>       <chr>            
1 Sam   123_abc_ABC 123              
2 John  234_bcd_BCD 234              
3 Mark  345_cde_CDE 345              
4 Ram   xyz_111_XYZ 111              
5 Hari  uvw_444_UVW 444

I am more confortable the tidyverse package. I hope this solution will help you

CodePudding user response：

You only need str_extract:

library(tidyverse)
df %>%
  mutate(student_id_by_govt = str_extract(student_id, "\\d "))
# A tibble: 5 × 3
  Name  student_id  student_id_by_govt
  <chr> <chr>       <chr>             
1 Sam   123_abc_ABC 123               
2 John  234_bcd_BCD 234               
3 Mark  345_cde_CDE 345               
4 Ram   xyz_111_XYZ 111               
5 Hari  uvw_444_UVW 444

CodePudding user response：

Another option using parse_number to extract all numbers from a string:

df <- read.table(text="name  student_id   age  gender
Sam   123_abc_ABC  20   F
John  234_bcd_BCD  18   M
Mark  345_cde_CDE  20   M
Ram   xyz_111_XYZ  19   M
Hari  uvw_444_UVW  23   M", header = TRUE)

library(dplyr)
library(purrr)
library(stringr)
df %>%
  mutate(student_id_by_govt = readr::parse_number(as.character(student_id)))
#>   name  student_id age gender student_id_by_govt
#> 1  Sam 123_abc_ABC  20      F                123
#> 2 John 234_bcd_BCD  18      M                234
#> 3 Mark 345_cde_CDE  20      M                345
#> 4  Ram xyz_111_XYZ  19      M                111
#> 5 Hari uvw_444_UVW  23      M                444

^{Created on 2022-07-01 by the reprex package (v2.0.1)}

CodePudding user response：

I am not sure I understand what you want.

library(dplyr)
library(stringr)
library(purrr)

df <- tibble(Name = c("Sam", "John", "Mark", "Ram", "Hari"), student_id = c("123_abc_ABC", "234_596_BCD", "345_cde_CDE", "xyz_111_XYZ", "uvw_444_UVW"), Gender = c("F", "M", "M", "M", "M")) %>%
      # mutate(student_id_by_gvt = if_else(Gender == "M", str_split(student_id, "_")[[1]][1], str_split(student_id, "_")[[1]][2]))
    mutate(student_id_by_gvt = map2_chr(Gender, student_id, function(x,y){if_else(x == "M", str_split(y, "_")[[1]][1], str_split(y, "_")[[1]][2])}))

It gives the output:

 Name  student_id  Gender student_id_by_gvt
  <chr> <chr>       <chr>  <chr>            
1 Sam   123_abc_ABC F      abc              
2 John  234_596_BCD M      234              
3 Mark  345_cde_CDE M      345              
4 Ram   xyz_111_XYZ M      xyz              
5 Hari  uvw_444_UVW M      uvw

CodePudding user response：

since you changed the question in one of your follow up comments quite a bit ie to "Hi there, is there a code for getting student_id_by_govt column based on gender column? I mean for all the 'M' gender, the student_id_by_govt is first segment in the student_id (ie., 234, 345, xyz, uvw) but for 'F' gender I want the second segment of student_id (i.e., abc) as student_id_by_govt? Please note, the segments I want from student_id in my original data is not numeric." here is a simple base R solution for the case that the segments are of equal length and the positions of those segments are stable - in case the strings have differing length but have certain characters based on which you could identify the segments you could replace that substr with some regex function.

df$student_id_by_govt <- ifelse(df$gender == "M", 
                          substr(df$student_id, 1,3), substr(df$student_id, 5,7))