Create multiple new variables that are calculated from existing variables












3














I'm trying to figure out how to create multiple new variables that are calculated using variables currently in my dataset



Here's some example data



library(tidyverse)



df <- data.frame(

 a1 = rnorm(100),

 a2 = rnorm(100),

 b1 = rnorm(100),

 b2 = rnorm(100),

 c1 = rnorm(100),

 c2 = rnorm(100)

)


Essentially, I want to create a new variable for each a, b, c pair that divides a1 by a2, b1 by b2, etc. For example:



df <- df %>%

  mutate(a3 = a1/a2)


The variables in my dataset don't follow these naming conventions, so I feel like I need to assign names to vectors:



numerators <- c('a1', 'b1', 'c1')

denominators <- c('a2', 'b2', 'c2')


And then creating a new variable would follow the basic convention



mutate(newvars = numerators/denominators)


But I'm stuck as to how to actually do this. Any help would be much appreciated -- thanks!






r dplyr iteration purrr







share|improve this question



























    3














    I'm trying to figure out how to create multiple new variables that are calculated using variables currently in my dataset



    Here's some example data



    library(tidyverse)
    

    
df <- data.frame(
    
 a1 = rnorm(100),
    
 a2 = rnorm(100),
    
 b1 = rnorm(100),
    
 b2 = rnorm(100),
    
 c1 = rnorm(100),
    
 c2 = rnorm(100)
    
)


    Essentially, I want to create a new variable for each a, b, c pair that divides a1 by a2, b1 by b2, etc. For example:



    df <- df %>%
    
  mutate(a3 = a1/a2)


    The variables in my dataset don't follow these naming conventions, so I feel like I need to assign names to vectors:



    numerators <- c('a1', 'b1', 'c1')
    
denominators <- c('a2', 'b2', 'c2')


    And then creating a new variable would follow the basic convention



    mutate(newvars = numerators/denominators)


    But I'm stuck as to how to actually do this. Any help would be much appreciated -- thanks!






    r dplyr iteration purrr







    share|improve this question

























      3












      3








      3


      1





      I'm trying to figure out how to create multiple new variables that are calculated using variables currently in my dataset



      Here's some example data



      library(tidyverse)
      

      
df <- data.frame(
      
 a1 = rnorm(100),
      
 a2 = rnorm(100),
      
 b1 = rnorm(100),
      
 b2 = rnorm(100),
      
 c1 = rnorm(100),
      
 c2 = rnorm(100)
      
)


      Essentially, I want to create a new variable for each a, b, c pair that divides a1 by a2, b1 by b2, etc. For example:



      df <- df %>%
      
  mutate(a3 = a1/a2)


      The variables in my dataset don't follow these naming conventions, so I feel like I need to assign names to vectors:



      numerators <- c('a1', 'b1', 'c1')
      
denominators <- c('a2', 'b2', 'c2')


      And then creating a new variable would follow the basic convention



      mutate(newvars = numerators/denominators)


      But I'm stuck as to how to actually do this. Any help would be much appreciated -- thanks!






      r dplyr iteration purrr







      share|improve this question













      I'm trying to figure out how to create multiple new variables that are calculated using variables currently in my dataset



      Here's some example data



      library(tidyverse)
      

      
df <- data.frame(
      
 a1 = rnorm(100),
      
 a2 = rnorm(100),
      
 b1 = rnorm(100),
      
 b2 = rnorm(100),
      
 c1 = rnorm(100),
      
 c2 = rnorm(100)
      
)


      Essentially, I want to create a new variable for each a, b, c pair that divides a1 by a2, b1 by b2, etc. For example:



      df <- df %>%
      
  mutate(a3 = a1/a2)


      The variables in my dataset don't follow these naming conventions, so I feel like I need to assign names to vectors:



      numerators <- c('a1', 'b1', 'c1')
      
denominators <- c('a2', 'b2', 'c2')


      And then creating a new variable would follow the basic convention



      mutate(newvars = numerators/denominators)


      But I'm stuck as to how to actually do this. Any help would be much appreciated -- thanks!






      r dplyr iteration purrr




      r dplyr iteration purrr






      share|improve this question













      share|improve this question











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      share|improve this question










      asked Nov 14 '18 at 0:57









      Ekholme

      254




      254
























          1 Answer
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          Here is an option to split the dataset into a list of data.frame based on the column name pattern, then reduce it by dividing elementwise on each pair of columns in each of the dataset and bind with the original dataset



          library(tidyverse)
          
df %>% 
          
   split.default(sub("\d+", "", names(.))) %>% 
          
   map_df(reduce, `/`) %>% 
          
   rename_all(~paste0(., 3)) %>% 
          
   bind_cols(df, .)





          share|improve this answer





















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            1 Answer
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            active

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            active

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            active

            oldest

            votes









            1














            Here is an option to split the dataset into a list of data.frame based on the column name pattern, then reduce it by dividing elementwise on each pair of columns in each of the dataset and bind with the original dataset



            library(tidyverse)
            
df %>% 
            
   split.default(sub("\d+", "", names(.))) %>% 
            
   map_df(reduce, `/`) %>% 
            
   rename_all(~paste0(., 3)) %>% 
            
   bind_cols(df, .)





            share|improve this answer


























              1














              Here is an option to split the dataset into a list of data.frame based on the column name pattern, then reduce it by dividing elementwise on each pair of columns in each of the dataset and bind with the original dataset



              library(tidyverse)
              
df %>% 
              
   split.default(sub("\d+", "", names(.))) %>% 
              
   map_df(reduce, `/`) %>% 
              
   rename_all(~paste0(., 3)) %>% 
              
   bind_cols(df, .)





              share|improve this answer
























                1












                1








                1






                Here is an option to split the dataset into a list of data.frame based on the column name pattern, then reduce it by dividing elementwise on each pair of columns in each of the dataset and bind with the original dataset



                library(tidyverse)
                
df %>% 
                
   split.default(sub("\d+", "", names(.))) %>% 
                
   map_df(reduce, `/`) %>% 
                
   rename_all(~paste0(., 3)) %>% 
                
   bind_cols(df, .)





                share|improve this answer












                Here is an option to split the dataset into a list of data.frame based on the column name pattern, then reduce it by dividing elementwise on each pair of columns in each of the dataset and bind with the original dataset



                library(tidyverse)
                
df %>% 
                
   split.default(sub("\d+", "", names(.))) %>% 
                
   map_df(reduce, `/`) %>% 
                
   rename_all(~paste0(., 3)) %>% 
                
   bind_cols(df, .)






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 14 '18 at 4:07









                akrun

                397k13187260




                397k13187260






























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