Implement lapply in conjunction with the get() function to vectorize merge of data tables? R












2















Question: How to implement the lapply function in conjunction with the get() function to merge a list of data tables?



Objective: For each of the elements in ticker_name, merge the data table called "dt_q_'ticker_name[i]'" and that called "meta_'ticker_name[i]'" by common "id" variable: 



ticker_name <- c("CTNP", "PB", "SD", "PC", "PE", "TY", "XD") 

for (i in 1:length(ticker_name)) {



  dt <- get(paste0("dt_q_", ticker_name[i]))

  meta <- get(paste0("meta_", ticker_name[i]))

  dt <- merge(x = dt, y = meta, by= c("id"))

  head(dt)

}


My non-working attempt with lapply:



lapply(

  X = ticker_name,

  FUN = 

    merge(x = get(paste0("dt_q_", ticker_name)),

          y = get(paste0("meta_", ticker_name)), by = c("id")

             ))


The error message:



 Error in match.fun(FUN) : 

 c("'merge(x = get(paste0("dt_q_", ticker_name)),

 y = get(paste0("meta_", ' is not a function,

 character or symbol", "'    ticker_name)), by = c("id"))'

 is not a function, character or symbol")





r merge get vectorization lapply







share|improve this question





























    2















    Question: How to implement the lapply function in conjunction with the get() function to merge a list of data tables?



    Objective: For each of the elements in ticker_name, merge the data table called "dt_q_'ticker_name[i]'" and that called "meta_'ticker_name[i]'" by common "id" variable: 



    ticker_name <- c("CTNP", "PB", "SD", "PC", "PE", "TY", "XD") 
    
for (i in 1:length(ticker_name)) {
    

    
  dt <- get(paste0("dt_q_", ticker_name[i]))
    
  meta <- get(paste0("meta_", ticker_name[i]))
    
  dt <- merge(x = dt, y = meta, by= c("id"))
    
  head(dt)
    
}


    My non-working attempt with lapply:



    lapply(
    
  X = ticker_name,
    
  FUN = 
    
    merge(x = get(paste0("dt_q_", ticker_name)),
    
          y = get(paste0("meta_", ticker_name)), by = c("id")
    
             ))


    The error message:



     Error in match.fun(FUN) : 
    
 c("'merge(x = get(paste0("dt_q_", ticker_name)),
    
 y = get(paste0("meta_", ' is not a function,
    
 character or symbol", "'    ticker_name)), by = c("id"))'
    
 is not a function, character or symbol")





    r merge get vectorization lapply







    share|improve this question



























      2












      2








      2


      1






      Question: How to implement the lapply function in conjunction with the get() function to merge a list of data tables?



      Objective: For each of the elements in ticker_name, merge the data table called "dt_q_'ticker_name[i]'" and that called "meta_'ticker_name[i]'" by common "id" variable: 



      ticker_name <- c("CTNP", "PB", "SD", "PC", "PE", "TY", "XD") 
      
for (i in 1:length(ticker_name)) {
      

      
  dt <- get(paste0("dt_q_", ticker_name[i]))
      
  meta <- get(paste0("meta_", ticker_name[i]))
      
  dt <- merge(x = dt, y = meta, by= c("id"))
      
  head(dt)
      
}


      My non-working attempt with lapply:



      lapply(
      
  X = ticker_name,
      
  FUN = 
      
    merge(x = get(paste0("dt_q_", ticker_name)),
      
          y = get(paste0("meta_", ticker_name)), by = c("id")
      
             ))


      The error message:



       Error in match.fun(FUN) : 
      
 c("'merge(x = get(paste0("dt_q_", ticker_name)),
      
 y = get(paste0("meta_", ' is not a function,
      
 character or symbol", "'    ticker_name)), by = c("id"))'
      
 is not a function, character or symbol")





      r merge get vectorization lapply







      share|improve this question
















      Question: How to implement the lapply function in conjunction with the get() function to merge a list of data tables?



      Objective: For each of the elements in ticker_name, merge the data table called "dt_q_'ticker_name[i]'" and that called "meta_'ticker_name[i]'" by common "id" variable: 



      ticker_name <- c("CTNP", "PB", "SD", "PC", "PE", "TY", "XD") 
      
for (i in 1:length(ticker_name)) {
      

      
  dt <- get(paste0("dt_q_", ticker_name[i]))
      
  meta <- get(paste0("meta_", ticker_name[i]))
      
  dt <- merge(x = dt, y = meta, by= c("id"))
      
  head(dt)
      
}


      My non-working attempt with lapply:



      lapply(
      
  X = ticker_name,
      
  FUN = 
      
    merge(x = get(paste0("dt_q_", ticker_name)),
      
          y = get(paste0("meta_", ticker_name)), by = c("id")
      
             ))


      The error message:



       Error in match.fun(FUN) : 
      
 c("'merge(x = get(paste0("dt_q_", ticker_name)),
      
 y = get(paste0("meta_", ' is not a function,
      
 character or symbol", "'    ticker_name)), by = c("id"))'
      
 is not a function, character or symbol")





      r merge get vectorization lapply




      r merge get vectorization lapply






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 27 '18 at 2:28







      k1000x

















      asked Nov 26 '18 at 22:27









      k1000xk1000x

      386




      386
























          1 Answer
          1






          active

          oldest

          votes


















          2














          We can use mget to return all the objects into a list and as the corresponding data.table should be merged, use Map which can have multiple arguments



          Map(merge, mget(paste0("dt_q_", ticker_name)), 
          
    mget(paste0("meta_", ticker_name)),
          
        MoreArgs =  list(by = 'id'))



          Or using lapply, loop through the 'ticker_name' then paste the corresponding 'prefix' part, get the values of the string objects and merge



          lapply(ticker_name, function(x) merge(get(paste0("dt_q_", x)), 
          
      get(paste0("meta_", x)), by = 'id'))


          NOTE: In the OP's code, after looping through the 'ticker_name' ( or ticker_list - not clear), then it is pasteing the prefix with the whole 'ticker_name' which is not the case if we check the for loop where it is looping through the sequence of 'ticker_name'. We can also loop through the sequence



          lapply(seq_along(ticker_name), function(i) {
          
  dt <- get(paste0("dt_q_", ticker_name[i]))
          
  meta <- get(paste0("meta_", ticker_name[i]))
          
  merge(x = dt, y = meta, by= "id")
          

          
     })





          share|improve this answer





















          • 1





            Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

            – k1000x
            Nov 27 '18 at 2:27






          • 1





            @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

            – akrun
            Nov 27 '18 at 3:20











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          1 Answer
          1






          active

          oldest

          votes








          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          2














          We can use mget to return all the objects into a list and as the corresponding data.table should be merged, use Map which can have multiple arguments



          Map(merge, mget(paste0("dt_q_", ticker_name)), 
          
    mget(paste0("meta_", ticker_name)),
          
        MoreArgs =  list(by = 'id'))



          Or using lapply, loop through the 'ticker_name' then paste the corresponding 'prefix' part, get the values of the string objects and merge



          lapply(ticker_name, function(x) merge(get(paste0("dt_q_", x)), 
          
      get(paste0("meta_", x)), by = 'id'))


          NOTE: In the OP's code, after looping through the 'ticker_name' ( or ticker_list - not clear), then it is pasteing the prefix with the whole 'ticker_name' which is not the case if we check the for loop where it is looping through the sequence of 'ticker_name'. We can also loop through the sequence



          lapply(seq_along(ticker_name), function(i) {
          
  dt <- get(paste0("dt_q_", ticker_name[i]))
          
  meta <- get(paste0("meta_", ticker_name[i]))
          
  merge(x = dt, y = meta, by= "id")
          

          
     })





          share|improve this answer





















          • 1





            Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

            – k1000x
            Nov 27 '18 at 2:27






          • 1





            @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

            – akrun
            Nov 27 '18 at 3:20
















          2














          We can use mget to return all the objects into a list and as the corresponding data.table should be merged, use Map which can have multiple arguments



          Map(merge, mget(paste0("dt_q_", ticker_name)), 
          
    mget(paste0("meta_", ticker_name)),
          
        MoreArgs =  list(by = 'id'))



          Or using lapply, loop through the 'ticker_name' then paste the corresponding 'prefix' part, get the values of the string objects and merge



          lapply(ticker_name, function(x) merge(get(paste0("dt_q_", x)), 
          
      get(paste0("meta_", x)), by = 'id'))


          NOTE: In the OP's code, after looping through the 'ticker_name' ( or ticker_list - not clear), then it is pasteing the prefix with the whole 'ticker_name' which is not the case if we check the for loop where it is looping through the sequence of 'ticker_name'. We can also loop through the sequence



          lapply(seq_along(ticker_name), function(i) {
          
  dt <- get(paste0("dt_q_", ticker_name[i]))
          
  meta <- get(paste0("meta_", ticker_name[i]))
          
  merge(x = dt, y = meta, by= "id")
          

          
     })





          share|improve this answer





















          • 1





            Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

            – k1000x
            Nov 27 '18 at 2:27






          • 1





            @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

            – akrun
            Nov 27 '18 at 3:20














          2












          2








          2







          We can use mget to return all the objects into a list and as the corresponding data.table should be merged, use Map which can have multiple arguments



          Map(merge, mget(paste0("dt_q_", ticker_name)), 
          
    mget(paste0("meta_", ticker_name)),
          
        MoreArgs =  list(by = 'id'))



          Or using lapply, loop through the 'ticker_name' then paste the corresponding 'prefix' part, get the values of the string objects and merge



          lapply(ticker_name, function(x) merge(get(paste0("dt_q_", x)), 
          
      get(paste0("meta_", x)), by = 'id'))


          NOTE: In the OP's code, after looping through the 'ticker_name' ( or ticker_list - not clear), then it is pasteing the prefix with the whole 'ticker_name' which is not the case if we check the for loop where it is looping through the sequence of 'ticker_name'. We can also loop through the sequence



          lapply(seq_along(ticker_name), function(i) {
          
  dt <- get(paste0("dt_q_", ticker_name[i]))
          
  meta <- get(paste0("meta_", ticker_name[i]))
          
  merge(x = dt, y = meta, by= "id")
          

          
     })





          share|improve this answer















          We can use mget to return all the objects into a list and as the corresponding data.table should be merged, use Map which can have multiple arguments



          Map(merge, mget(paste0("dt_q_", ticker_name)), 
          
    mget(paste0("meta_", ticker_name)),
          
        MoreArgs =  list(by = 'id'))



          Or using lapply, loop through the 'ticker_name' then paste the corresponding 'prefix' part, get the values of the string objects and merge



          lapply(ticker_name, function(x) merge(get(paste0("dt_q_", x)), 
          
      get(paste0("meta_", x)), by = 'id'))


          NOTE: In the OP's code, after looping through the 'ticker_name' ( or ticker_list - not clear), then it is pasteing the prefix with the whole 'ticker_name' which is not the case if we check the for loop where it is looping through the sequence of 'ticker_name'. We can also loop through the sequence



          lapply(seq_along(ticker_name), function(i) {
          
  dt <- get(paste0("dt_q_", ticker_name[i]))
          
  meta <- get(paste0("meta_", ticker_name[i]))
          
  merge(x = dt, y = meta, by= "id")
          

          
     })






          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Nov 26 '18 at 22:44

























          answered Nov 26 '18 at 22:36









          akrunakrun

          409k13198273




          409k13198273








          • 1





            Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

            – k1000x
            Nov 27 '18 at 2:27






          • 1





            @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

            – akrun
            Nov 27 '18 at 3:20














          • 1





            Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

            – k1000x
            Nov 27 '18 at 2:27






          • 1





            @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

            – akrun
            Nov 27 '18 at 3:20








          1




          1





          Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

          – k1000x
          Nov 27 '18 at 2:27





          Three great answers. Follow-up: In the first option, why do we need to include by = 'id' in a list?

          – k1000x
          Nov 27 '18 at 2:27




          1




          1





          @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

          – akrun
          Nov 27 '18 at 3:20





          @k1000x Thank you. In Map we could have used anonymous function like Map(function(x, y) merge(x, y, by = 'id'), mget(paste0("dt_q_", ticker_name)), mget(paste0("meta_", ticker_name))). That would make it easier to understand. The compact method used in Map specifies the arguments of merge (by = 'id'). When we place it inside list, it will be a single unit that can be recycled for each element of the list (and it is the same argument for all the elements)

          – akrun
          Nov 27 '18 at 3:20




















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