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R: Merging data frames based on file name



The 2019 Stack Overflow Developer Survey Results Are InHow to join (merge) data frames (inner, outer, left, right)R - list to data frameDrop data frame columns by nameIs it possible to force Excel recognize UTF-8 CSV files automatically?Changing column names of a data frameWhy is `[` better than `subset`?data.table vs dplyr: can one do something well the other can't or does poorly?How to merge subsets of data frames from a list (i.e., merge all of the first dfs from each list component)Adding name of individual data frame to new column in merged data frameImporting and merging .csv files with loop in R



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0















My files (example as I have hundreds of these files):



France.csv
France_variables.csv
Germany.csv
Germany_variables.csv
Spain.csv
Spain_variables.csv
Portugal.csv
Portugal_variables.csv


I want to merge France with France_variables, Germany with Germany_variables etc. I know I can use rbind with the two files but I want to do this as a loop because I have lots of these to merge. I'm not sure how to do a string search and then rbind in a loop or if there is a better way of doing this.



I am new to R so any help would be much appreciated.










share|improve this question






















  • What do you mean by merge?

    – Sonny
    Mar 8 at 11:18











  • add the data in France.csv to France_variables.csv

    – user11170440
    Mar 8 at 11:20











  • Do you want different df from each country? or you want all to be merged into single df. Are the headers same or different?

    – Sonny
    Mar 8 at 11:22











  • A different df for each country

    – user11170440
    Mar 8 at 11:23











  • In terms of approach, I'd say the way to start is to figure out how to put each set into a list, e.g. list(France,csv, Germany, csv,...) and list(France_variables.csv, Germany_variables.csv,...). Then I'd use either a for loop or lapply() to merge them, where all the outputs would be in a list

    – cyun
    Mar 8 at 11:38

















0















My files (example as I have hundreds of these files):



France.csv
France_variables.csv
Germany.csv
Germany_variables.csv
Spain.csv
Spain_variables.csv
Portugal.csv
Portugal_variables.csv


I want to merge France with France_variables, Germany with Germany_variables etc. I know I can use rbind with the two files but I want to do this as a loop because I have lots of these to merge. I'm not sure how to do a string search and then rbind in a loop or if there is a better way of doing this.



I am new to R so any help would be much appreciated.










share|improve this question






















  • What do you mean by merge?

    – Sonny
    Mar 8 at 11:18











  • add the data in France.csv to France_variables.csv

    – user11170440
    Mar 8 at 11:20











  • Do you want different df from each country? or you want all to be merged into single df. Are the headers same or different?

    – Sonny
    Mar 8 at 11:22











  • A different df for each country

    – user11170440
    Mar 8 at 11:23











  • In terms of approach, I'd say the way to start is to figure out how to put each set into a list, e.g. list(France,csv, Germany, csv,...) and list(France_variables.csv, Germany_variables.csv,...). Then I'd use either a for loop or lapply() to merge them, where all the outputs would be in a list

    – cyun
    Mar 8 at 11:38













0












0








0








My files (example as I have hundreds of these files):



France.csv
France_variables.csv
Germany.csv
Germany_variables.csv
Spain.csv
Spain_variables.csv
Portugal.csv
Portugal_variables.csv


I want to merge France with France_variables, Germany with Germany_variables etc. I know I can use rbind with the two files but I want to do this as a loop because I have lots of these to merge. I'm not sure how to do a string search and then rbind in a loop or if there is a better way of doing this.



I am new to R so any help would be much appreciated.










share|improve this question














My files (example as I have hundreds of these files):



France.csv
France_variables.csv
Germany.csv
Germany_variables.csv
Spain.csv
Spain_variables.csv
Portugal.csv
Portugal_variables.csv


I want to merge France with France_variables, Germany with Germany_variables etc. I know I can use rbind with the two files but I want to do this as a loop because I have lots of these to merge. I'm not sure how to do a string search and then rbind in a loop or if there is a better way of doing this.



I am new to R so any help would be much appreciated.







r csv






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Mar 8 at 11:16









user11170440user11170440

1




1












  • What do you mean by merge?

    – Sonny
    Mar 8 at 11:18











  • add the data in France.csv to France_variables.csv

    – user11170440
    Mar 8 at 11:20











  • Do you want different df from each country? or you want all to be merged into single df. Are the headers same or different?

    – Sonny
    Mar 8 at 11:22











  • A different df for each country

    – user11170440
    Mar 8 at 11:23











  • In terms of approach, I'd say the way to start is to figure out how to put each set into a list, e.g. list(France,csv, Germany, csv,...) and list(France_variables.csv, Germany_variables.csv,...). Then I'd use either a for loop or lapply() to merge them, where all the outputs would be in a list

    – cyun
    Mar 8 at 11:38

















  • What do you mean by merge?

    – Sonny
    Mar 8 at 11:18











  • add the data in France.csv to France_variables.csv

    – user11170440
    Mar 8 at 11:20











  • Do you want different df from each country? or you want all to be merged into single df. Are the headers same or different?

    – Sonny
    Mar 8 at 11:22











  • A different df for each country

    – user11170440
    Mar 8 at 11:23











  • In terms of approach, I'd say the way to start is to figure out how to put each set into a list, e.g. list(France,csv, Germany, csv,...) and list(France_variables.csv, Germany_variables.csv,...). Then I'd use either a for loop or lapply() to merge them, where all the outputs would be in a list

    – cyun
    Mar 8 at 11:38
















What do you mean by merge?

– Sonny
Mar 8 at 11:18





What do you mean by merge?

– Sonny
Mar 8 at 11:18













add the data in France.csv to France_variables.csv

– user11170440
Mar 8 at 11:20





add the data in France.csv to France_variables.csv

– user11170440
Mar 8 at 11:20













Do you want different df from each country? or you want all to be merged into single df. Are the headers same or different?

– Sonny
Mar 8 at 11:22





Do you want different df from each country? or you want all to be merged into single df. Are the headers same or different?

– Sonny
Mar 8 at 11:22













A different df for each country

– user11170440
Mar 8 at 11:23





A different df for each country

– user11170440
Mar 8 at 11:23













In terms of approach, I'd say the way to start is to figure out how to put each set into a list, e.g. list(France,csv, Germany, csv,...) and list(France_variables.csv, Germany_variables.csv,...). Then I'd use either a for loop or lapply() to merge them, where all the outputs would be in a list

– cyun
Mar 8 at 11:38





In terms of approach, I'd say the way to start is to figure out how to put each set into a list, e.g. list(France,csv, Germany, csv,...) and list(France_variables.csv, Germany_variables.csv,...). Then I'd use either a for loop or lapply() to merge them, where all the outputs would be in a list

– cyun
Mar 8 at 11:38












2 Answers
2






active

oldest

votes


















0














You can use something like this:



library(tidyverse)
#Get Unique countries
country <- unique(gsub('\..*$|_.*', '', list.files(path = ".", pattern = "csv")))

#Loop
for (i in country)
dat <- list.files(path = ".", pattern = i) %>% map(read_csv) %>% reduce(rbind)
assign( paste("df", i, sep = "_"), dat)
rm(dat)



This will create dataframes like df_France, df_Germany , etc.






share|improve this answer

























  • Thanks I'll try this

    – user11170440
    Mar 8 at 12:06


















0














Play with the 'grepl', and see if you can get this to work......



# set the working directory (where files are saved)
setwd("C:/your_path_here/")

file_names = list.files(getwd())
file_names = file_names[grepl(".TXT",file_names)]

# print file_names vector
file_names

# see the data structure
str(file)

# run read.csv on all values of file_names
files = lapply(file_names, read.csv, header=F, stringsAsFactors = F)
files = do.call(rbind,files)

# run only on WY.TXT and NM.TXT
str(files)


# set column names
names(files) = c("col1", "col2", "col3", "col4", "col5")
str(files)


# finally...
write.table(files, "C:/your_path/mydata.txt", sep="t")
write.csv(files,"C:/your_path/mydata.csv")


http://www.rforexcelusers.com/combine-delimited-files-r/






share|improve this answer























    Your Answer






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    2 Answers
    2






    active

    oldest

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    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    0














    You can use something like this:



    library(tidyverse)
    #Get Unique countries
    country <- unique(gsub('\..*$|_.*', '', list.files(path = ".", pattern = "csv")))

    #Loop
    for (i in country)
    dat <- list.files(path = ".", pattern = i) %>% map(read_csv) %>% reduce(rbind)
    assign( paste("df", i, sep = "_"), dat)
    rm(dat)



    This will create dataframes like df_France, df_Germany , etc.






    share|improve this answer

























    • Thanks I'll try this

      – user11170440
      Mar 8 at 12:06















    0














    You can use something like this:



    library(tidyverse)
    #Get Unique countries
    country <- unique(gsub('\..*$|_.*', '', list.files(path = ".", pattern = "csv")))

    #Loop
    for (i in country)
    dat <- list.files(path = ".", pattern = i) %>% map(read_csv) %>% reduce(rbind)
    assign( paste("df", i, sep = "_"), dat)
    rm(dat)



    This will create dataframes like df_France, df_Germany , etc.






    share|improve this answer

























    • Thanks I'll try this

      – user11170440
      Mar 8 at 12:06













    0












    0








    0







    You can use something like this:



    library(tidyverse)
    #Get Unique countries
    country <- unique(gsub('\..*$|_.*', '', list.files(path = ".", pattern = "csv")))

    #Loop
    for (i in country)
    dat <- list.files(path = ".", pattern = i) %>% map(read_csv) %>% reduce(rbind)
    assign( paste("df", i, sep = "_"), dat)
    rm(dat)



    This will create dataframes like df_France, df_Germany , etc.






    share|improve this answer















    You can use something like this:



    library(tidyverse)
    #Get Unique countries
    country <- unique(gsub('\..*$|_.*', '', list.files(path = ".", pattern = "csv")))

    #Loop
    for (i in country)
    dat <- list.files(path = ".", pattern = i) %>% map(read_csv) %>% reduce(rbind)
    assign( paste("df", i, sep = "_"), dat)
    rm(dat)



    This will create dataframes like df_France, df_Germany , etc.







    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Mar 8 at 11:47

























    answered Mar 8 at 11:40









    SonnySonny

    2,0361515




    2,0361515












    • Thanks I'll try this

      – user11170440
      Mar 8 at 12:06

















    • Thanks I'll try this

      – user11170440
      Mar 8 at 12:06
















    Thanks I'll try this

    – user11170440
    Mar 8 at 12:06





    Thanks I'll try this

    – user11170440
    Mar 8 at 12:06













    0














    Play with the 'grepl', and see if you can get this to work......



    # set the working directory (where files are saved)
    setwd("C:/your_path_here/")

    file_names = list.files(getwd())
    file_names = file_names[grepl(".TXT",file_names)]

    # print file_names vector
    file_names

    # see the data structure
    str(file)

    # run read.csv on all values of file_names
    files = lapply(file_names, read.csv, header=F, stringsAsFactors = F)
    files = do.call(rbind,files)

    # run only on WY.TXT and NM.TXT
    str(files)


    # set column names
    names(files) = c("col1", "col2", "col3", "col4", "col5")
    str(files)


    # finally...
    write.table(files, "C:/your_path/mydata.txt", sep="t")
    write.csv(files,"C:/your_path/mydata.csv")


    http://www.rforexcelusers.com/combine-delimited-files-r/






    share|improve this answer



























      0














      Play with the 'grepl', and see if you can get this to work......



      # set the working directory (where files are saved)
      setwd("C:/your_path_here/")

      file_names = list.files(getwd())
      file_names = file_names[grepl(".TXT",file_names)]

      # print file_names vector
      file_names

      # see the data structure
      str(file)

      # run read.csv on all values of file_names
      files = lapply(file_names, read.csv, header=F, stringsAsFactors = F)
      files = do.call(rbind,files)

      # run only on WY.TXT and NM.TXT
      str(files)


      # set column names
      names(files) = c("col1", "col2", "col3", "col4", "col5")
      str(files)


      # finally...
      write.table(files, "C:/your_path/mydata.txt", sep="t")
      write.csv(files,"C:/your_path/mydata.csv")


      http://www.rforexcelusers.com/combine-delimited-files-r/






      share|improve this answer

























        0












        0








        0







        Play with the 'grepl', and see if you can get this to work......



        # set the working directory (where files are saved)
        setwd("C:/your_path_here/")

        file_names = list.files(getwd())
        file_names = file_names[grepl(".TXT",file_names)]

        # print file_names vector
        file_names

        # see the data structure
        str(file)

        # run read.csv on all values of file_names
        files = lapply(file_names, read.csv, header=F, stringsAsFactors = F)
        files = do.call(rbind,files)

        # run only on WY.TXT and NM.TXT
        str(files)


        # set column names
        names(files) = c("col1", "col2", "col3", "col4", "col5")
        str(files)


        # finally...
        write.table(files, "C:/your_path/mydata.txt", sep="t")
        write.csv(files,"C:/your_path/mydata.csv")


        http://www.rforexcelusers.com/combine-delimited-files-r/






        share|improve this answer













        Play with the 'grepl', and see if you can get this to work......



        # set the working directory (where files are saved)
        setwd("C:/your_path_here/")

        file_names = list.files(getwd())
        file_names = file_names[grepl(".TXT",file_names)]

        # print file_names vector
        file_names

        # see the data structure
        str(file)

        # run read.csv on all values of file_names
        files = lapply(file_names, read.csv, header=F, stringsAsFactors = F)
        files = do.call(rbind,files)

        # run only on WY.TXT and NM.TXT
        str(files)


        # set column names
        names(files) = c("col1", "col2", "col3", "col4", "col5")
        str(files)


        # finally...
        write.table(files, "C:/your_path/mydata.txt", sep="t")
        write.csv(files,"C:/your_path/mydata.csv")


        http://www.rforexcelusers.com/combine-delimited-files-r/







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Mar 12 at 21:30









        ryguy72ryguy72

        4,6611825




        4,6611825



























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